AE&M 63-1 by Sociedade Brasileira de Endocrinologia e Metabologia

ISSN 2359-4292

OFFICIAL JOURNAL OF THE BRAZILIAN SOCIETY OF ENDOCRINOLOGY AND METABOLISM Vol. 63 – No. 01 – February 2019

editorials 1

AE&M’s first issue of the year: important news!

Clinical risk predictors for differentiated thyroid cancer management: what is new?

Marcello D. Bronstein

Archives of Endocrinology

Denise Momesso

OFFICIAL JOURNAL original articles OF THE BRAZILIAN 5 Impact of the updated TNM staging criteria on prediction of persistent disease in a differentiated thyroid carcinoma cohort Carla Fernanda Nava, André B. Zanella, Rafael Selbach Scheffel, Ana Luiza Maia, Jose Miguel Dora SOCIETY OF 12 Does the Bethesda category predict aggressive features in differentiated thyroid cancer? ENDOCRINOLOGY Ana Rafaela Lopes Reis Lima, Karoline Matias Morais de Medeiros, Conceição de Maria Ribeiro Veiga Parente, Adriana de Sá Caldas, Manuel dos Santos Faria, Marcelo Magalhães, Carla Souza Pereira Sobral AND METABOLISM 16 Serum irisin and apelin levels and markers of atherosclerosis in patients with subclinical hypothyroidism

and Metabolism

Hamiyet Yilmaz Yasar, Mustafa Demirpence, Ayfer Colak, Leman Yurdakul, Merve Zeytinli, Hakan Turkon, Ferhat Ekinci, Aybike Günaslan, Erdem Yasar

22 Relationship between inflammatory markers, glycated hemoglobin and placental weight on fetal outcomes in women with gestational diabetes Fernanda Oliveira Braga, Carlos Antonio Negrato, Maria de Fátima Bevilacqua da Matta, João Régis Ivar Carneiro, Marília Brito Gomes

30 Anthropometric measurements as a potential non-invasive alternative for the diagnosis of metabolic syndrome in adolescents Silmara Salete de Barros Silva Mastroeni, Marco Fabio Mastroeni, John Paul Ekwaru, Solmaz Setayeshgar, Paul J. Veugelers, Muryel de Carvalho Gonçalves, Patrícia Helen de Carvalho Rondó

Archives of

40 Influence of obesity in pulmonary function and exercise tolerance in obese women with obstructive sleep apnea

Vivian Maria Moraes Passos, Anna Myrna Jaguaribe de Lima, Bárbara Renatha Afonso Ferreira de Barros Leite, Rodrigo Pinto Pedrosa, Isly Maria Lucena de Barros, Laura Olinda Bregieiro Fernandes Costa, Amilton da Cruz Santos, Maria do Socorro Brasileiro-Santos

47 Clinical and hormonal characteristics of patients with different types of hypophysitis: a single-center experience

Endocrinology

Narin Nasiroglu Imga, Ali Erdem Yildirim, Ozden Ozdemir Baser, Dilek Berker

53 Basal metabolic rate in Brazilian patients with type 2 diabetes: comparison between measured and estimated values Thais Steemburgo, Camila Lazzari, Juliano Boufleur Farinha, Tatiana Pedroso de Paula, Luciana Vercoza Viana, Alvaro Reischak de Oliveira, Mirela Jobim de Azevedo

62 Low levels of dehydroepiandrosterone sulfate are associated with the risk of developing cardiac autonomic dysfunction in elderly subjects

and Metabolism

Marina de Paiva Lemos, Munique Tostes Miranda, Moacir Marocolo, Elisabete Aparecida Mantovani Rodrigues de Resende, Rosângela Soares Chriguer, Carla Cristina de Sordi, Octávio Barbosa Neto

review 70 Genetic causes of isolated short stature

OFFICIAL JOURNAL OF THE BRAZILIAN SOCIETY OF ENDOCRINOLOGY AND METABOLISM

Gabriela A. Vasques, Nathalia L. M. Andrade, Alexander A. L. Jorge

case reports 79 Aggressive papillary thyroid carcinoma in a child with type 2 congenital generalized lipodystrophy Grayce Ellen da Cruz Paiva Lima, Virgínia Oliveira Fernandes, Ana Paula Dias Rangel Montenegro, Annelise Barreto de Carvalho, Lia Beatriz de Azevedo Sousa Karbage, Lindenberg Barbosa Aguiar, Mário Sérgio Rocha Macedo, Luis Alberto Albano Ferreira, Renan Magalhães Montenegro Júnior

84 Congenital hyperreninemic hypoaldosteronism due to aldosterone synthase deficiency type I in a Portuguese patient – Case report and review of literature Adriana de Sousa Lages, Beatriz Vale, Patrícia Oliveira, Rita Cardoso, Isabel Dinis, Francisco Carrilho, Alice Mirante

89 A rare mutation in hypophosphatasia: a case report of adult form and review of the literature Francisco Galeano-Valle, Jaime Vengoechea, Rodolfo J. Galindo

AND METABOLISM OFFICIAL JOURNAL OF THE BRAZILIAN SOCIETY OF ENDOCRINOLOGY AND METABOLISM

OFFICIAL JOURNAL OF THE BRAZILIAN SOCIETY OF ENDOCRINOLOGY AND METABOLISM

Financial and editorial assistant: Roselaine Monteiro roselaine@endocrino.org.br Rua Botucatu, 572 – conjunto 83 – 04023-062 – São Paulo, SP Telefax: (11) 5575-0311 / 5082-4788

Archives of Endocrinology Online submission / Electronic publishing www.aem-sbem.com • www.scielo.br/abem

and Metabolism

OFFICIAL JOURNAL OF THE BRAZILIAN SOCIETY OF ENDOCRINOLOGY AND METABOLISM

Archives of

Rua Anseriz, 27, Campo Belo 04618-050 – São Paulo, SP. Fone: 11 3093-3300 www.segmentofarma.com.br • segmentofarma@segmentofarma.com.br

Publication code: 23726.2.19

Endocrinology

and Metabolism

All adds have to comply with RDC no 96/08 Commercial advising: Estela Kater estela.kater@gmail·com

OFFICIAL JOURNAL OF THE BRAZILIAN SOCIETY OF ENDOCRINOLOGY AND METABOLISM

Indexed in Biological Abstracts, Index Medicus, Latindex, Lilacs, MedLine, SciELO, Scopus, ISI-Web of Science BRAZILIAN ARCHIVES OF ENDOCRINOLOGY AND METABOLISM Brazilian Society of Endocrinology and Metabolism – São Paulo, SP: Brazilian Society of Endocrinology and Metabolism, volume 5, 1955Six issues/year Continued from: Brazilian Archives of Endocrinology (v. 1-4), 1951-1955 ISSN 2359-4292 (online issues) 1. Endocrinology – journals 2. Metabolism – journals I. Brazilian Society of Endocrinology and Metabolism II. Brazilian Medical Association CDU 612.43 Endocrinology CDU 612.015.3 Metabolism

OFFICIAL JOURNAL OF THE BRAZILIAN SOCIETY OF ENDOCRINOLOGY AND METABOLISM

Archives of endocrinology and metabolism Official journal of SBEM – Brazilian Society of Endocrinology and Metabolism (Department of the Brazilian Medical Association), SBD – Brazilian Diabetes Society, ABESO – Brazilian Association for the Study of Obesity and Metabolic Syndrome

2019-2022 EDITOR-IN-CHIEF Marcello D. Bronstein (SP)

CO-EDITORS

REPRESENTATIVES OF COLLABORATING SOCIETIES

Laércio Joel Franco (SP)

SBD

Larissa Gomes (SP)

Luiz Alberto Andreotti Turatti (SP)

Léa Maria Zanini Maciel (SP)

ABESO

Leandro Kasuki (SP)

Archives of Endocrinology Ana Luiza Maia (RS) Beatriz D’ Agord Schaan (RS) Bruno Ferraz de Souza (SP) Erika Parente (SP) Francisco Bandeira (PE) Fernanda Vaisman (RJ) Fernando M. A. Giuffrida (BA) João Roberto Maciel Martins (SP) Melanie Rodacki (RJ) Monica R. Gadelha (RJ) Nina Rosa C. Musolino (SP) Poli Mara Spritzer (RS) Ricardo Meirelles (RJ) Rogerio Friedman (RS)

OFFICIAL JOURNALMadson Queiroz Almeida (SP) OF THE BRAZILIANManoel Ricardo Alves Martins (CE) Brazilian Editorial Commission Marcio Mancini (SP) Alexander A. L. Jorge (SP) OF SOCIETY Alexandre Hohl (SC) Margaret Cristina S. Boguszewski (PR) ENDOCRINOLOGY Ana Amélia Hoff (SP) Maria Candida B. V. Fragoso (SP) AND METABOLISM Ana Claudia Latronico (SP) Maria Izabel Chiamolera (SP) Maria Edna de Melo (SP)

and Metabolism FOUNDER Waldemar Berardinelli (RJ)

1951-1955 Waldemar Berardinelli (RJ) Thales Martins (RJ) 1957-1972 Clementino Fraga Filho (RJ) 1964-1966* Luiz Carlos Lobo (RJ)

Berenice B. Mendonça (SP)

Maria Marta Sarquis (MG) Mario Saad (SP) Mário Vaisman (RJ) Marise Lazaretti Castro (SP) Milena Caldato (PA)

Archives of

ASSOCIATE EDITORS

Bruno Halpern (SP)

Carlos Alberto Longui (SP)

César Luiz Boguszewski (PR)

Raquel Soares Jallad (SP) Rodrigo Moreira (RJ) Ruth Clapauch (RJ) Sandra R. G. Ferreira (SP)

Endocrinology

PRESIDENTS OF THE SBEM DEPARTMENTS

ADRENAL AND HYPERTENSION

Madson Queiroz de Almeida (SP) DIABETES MELLITUS

Clarisse Ponte (CE)

Delmar Muniz Lourenço Jr. (SP)

Simão A. Lottemberg (SP)

Denise Momesso (RJ)

Sonir Roberto Antonini (SP)

Eder Carlos R. Quintão (SP)

Suemi Marui (SP)

and Metabolism

Hermelinda Cordeiro Pedrosa (DF)

Edna Nakandakare (SP)

DYSLIPIDEMIA AND ATHEROSCLEROSIS

Edna T. Kimura (SP)

1969-1972* João Gabriel H. Cordeiro (RJ)

Maria Izabel Chiamolera (SP)

BASIC ENDOCRINOLOGY

Mônica de Oliveira (PE)

PEDIATRIC ENDOCRINOLOGY

1991-1994 Rui M. de Barros Maciel (SP)

BONE AND MINERAL METABOLISM

Carlos Alberto Longui (SP) Miguel Madeira (RJ))

1995-2006 Claudio Elias Kater (SP)

NEUROENDOCRINOLOGY

2007-2010 Edna T. Kimura (SP)

OBESITY

Heraldo Mendes Garmes (SP) Mario Kehdi Carra (SP) THYROID

Jose Augusto Sgarbi (SP)

Victória Borba (PR)

Elaine Maria Frade Costa (SP) Felipe Gaia (SP)

OFFICIAL JOURNAL OF THE FlavioBRAZILIAN Hojaij (SP) FEMININE ENDOCRINOLOGY AND SOCIETY OF ENDOCRINOLOGY AND METABOLISM Gil Guerra-Júnior (SP) ANDROLOGY

1983-1990 Antônio Roberto Chacra (SP)

2015-2018 Marcello D. Bronstein (SP)

Antônio Roberto Chacra (SP)

INTERNATIONAL ASSOCIATE EDITOR

Cynthia Melissa Valério (RJ)

2011-2014 Sergio Atala Dib (SP)

Andrea Glezer (SP)

Ayrton Custódio Moreira (SP)

1966-1968* Pedro Collett-Solberg (RJ)

1978-1982 Armando de Aguiar Pupo (SP)

André Fernandes Reis (SP)

Tânia S. Bachega (SP)

Shlomo Melmed (Los Angeles, EUA)

EDITORS-IN-CHIEF, EDITORIAL OFFICE*

Ana Luiza Silva Maia (RS)

International Editorial Commission Antonio C. Bianco (EUA)

Giovanna Balarini Lima (RJ)

Décio Eizirik (Bélgica)

Gisah M. do Amaral (SP)

Franco Mantero (Itália)

Hans Graf (SP)

Fernando Cassorla (Chile)

José Augusto Sgarbi (SP)

Gilberto Paz-Filho (Austrália)

José Gilberto H. Vieira (SP)

John P. Bilezikian (EUA)

Julio Z. Abucham (SP)

Ken Ho (Austrália)

SBEM – Brazilian Society of Endocrinology and Metabolism SBEM BRAZILIAN BOARD OF DIRECTORS 2019-2020 President Vice-President Executive Secretary Adjunct Executive Secretary Treasurer-General Adjunct Treasurer

Rodrigo de Oliveira Moreira César Luiz Boguszewski Neuton Dornelas Gomes Marcio Corrêa Mancini Paulo Augusto Carvalho Miranda Maria Amazonas

Rua Humaitá, 85, cj. 501 22261-000 – Rio de Janeiro, RJ Fone/Fax: (21) 2579-0312/2266-0170 www.endocrino.org.br sbem@endocrino.org.br

Scientific Departments - 2019/2020 Brazilian Society of Endocrinology and Metabolism ADRENAL AND HYPERTENSION

DIABETES MELLITUS

President Madson Queiroz de Almeida madsonalmeida@usp.br

President Hermelinda Cordeiro Pedrosa pedrosa.hc@globo.com Vice-President Rosane Kupfer Directors Erika Bezerra Parente Thaisa Dourado Guedes Trujilho Fábio Ferreira de Moura Janice Sepulveda Reis Ana Cristina Ravazzani de Almeida

Vice-President Directors

Milena Coelho Fernandes Caldato Marivânia da Costa Santos Flávia Amanda Costa Barbosa Leonardo Vieira Neto

DYSLIPIDEMIA AND ATHEROSCLEROSIS

BASIC ENDOCRINOLOGY

President Cynthia Melissa Valério cy_valerio@yahoo.com.br

President Maria Izabel Chiamolera mchiamolera@unifesp.br Vice-President Maria Tereza Nunes Directors Tania Maria Ruffoni Ortiga Bruno Ferraz de Souza Marisa Maria Dreyer Breitenbach Luciani Renata Silveira Carvalho Vania Maria Correa da Costa

Vice-President Directors

Renan Magalhães Montenegro Júnior Joaquim Custódio da Silva Júnior Marcello Casaccia Bertoluci Joana Rodrigues Dantas Pereira

Scientific Departments - 2019/2020 WOMEN ENDOCRINOLOGY AND ANDROLOGY President Mônica de Oliveira morecife@hotmail.com Vice-President Directors

Rita de Cassia Viana Vasconcellos Weiss Dolores Perovano Pardini Ruth Clapauch Larissa Garcia Gomes Marcelo Fernando Ronsoni Alexis Dourado Guedes

PEDIATRIC ENDOCRINOLOGY President Carlos Alberto Longui carloslongui@msn.com Vice-President Directors

Julienne Ângela Ramires de Carvalho Sonir Roberto Rauber Antonini Claudia Braga Monteiro Paulo César Alves da Silva

BONE AND MINERAL METABOLISM

NEUROENDOCRINOLOGY

President Vice-President Directors

President Heraldo Mendes Garmes heraldmg@uol.com.br Vice-President Manoel Ricardo Alves Martins Directors Andrea Glezer Leandro Kasuki Jomori de Pinho Mauro Ântonio Czepielewski Nina Rosa de Castro Musolino Silvia Regina Correa da Silva

Miguel Madeira migmadeira@gmail.com Francisco Alfredo Bandeira e Farias Carolina Aguiar Moreira Sérgio Setsuo Maeda Marise Lazaretti Castro Bárbara Campolina Carvalho Silva Catarina Brasil D´alva

OBESITY

THYROID

President Mario Kehdi Carra mariocarra@gmail.com Vice-President Fábio Rogério Trujilho Directors Maria Edna de Melo Rosana Bento Radominski Rodrigo Lamounier Bibiana Prada de Camargo Colenci Jacqueline Rizzolli

President José Augusto Sgarbi jose.sgarbi@gmail.com Vice-President Patricia de Fátima dos Santos Teixeira Directors Rafael Selbach Scheffel Gisah Amaral de Carvalho Danilo Glauco Pereira Villagelin Neto

Permanent Commissions - 2019/2020 Brazilian Society of Endocrinology and Metabolism STRATEGIC PLANNING FOLLOW-UP

HISTORY OF ENDOCRINOLOGY

President Alexandre Hohl alexandrehohl@uol.com.br Members Nina Rosa de Castro Musolino, Airton Golbert, Ricardo Martins da Rocha Meirelles, Ruy Lyra da Silva Filho

President Henrique de Lacerda Suplicy hsuplicy@gmail.com Members Adriana Costa e Forti, Thomaz Rodrigues Porto da Cruz

ENDOCRINOLOGY CAMPAIGNS

President

Mônica Roberto Gadelha

mgadelha@hucff.ufrj.br

Members

César Luiz Boguszewski

President Erika Bezerra Parente ebparente@gmail.com Members Alina Coutinho Rodrigues Feitosa, Carolina Ferraz da Silva, Mariana Guerra Paulino Guerra

SCIENTIFIC COMISSION President César Luiz Boguszewski clbogus@uol.com.br Indicated by the directories Sonir Roberto Rauber Antonini, Carolina Aguiar Moreira, Fernanda Vaisman, Bruno Halpern, Manoel Ricardo Alves Martins,Fábio Rogério Trujilho, Luciana Antunes de Almeida Secchi, Karen Faggioni de Marca Seidel, Fernando Gerchman, Milena Coelho Fernandes Caldato

SOCIAL COMMUNICATION President Ricardo Martins da Rocha Meirelles r.meirelles@terra.com.br Nominated by the president Alexandre Hohl ABEM Editor Marcello D. Bronstein Members Nina Rosa de Castro Musolino

INTERNATIONAL

NORMS, QUALIFICATION AND CERTIFICATION President Vivian Carole Moema Ellinger vivianellinger@gmail.com Members Ronaldo Rocha Sinay Neves, Marisa Helena César Coral, Maria Emilia Pereira de Almeida, Milena Coelho Fernandes Caldato

JOINT COMMISSION – CAAEP President Julienne Angela Ramires de Carvalho julienne@endocrinoped.com.br Members Marilia Martins Guimarães, Suzana Nesi França

RESEARCH President Members

Freddy Eliaschewitz freddy.g@uol.com.br Antônio Roberto Chacra, Luiz Augusto Tavares Russo

GUIDELINES PROJECT CONTINUOUS MEDICAL EDUCATION President João Eduardo Nunes Salles jensalles@yahoo.com.br Members César Luiz Boguszewski, Alexandre Hohl

STATUTES, RULES AND REGULATIONS President Fábio Rogério Trujilho trtruji@terra.com.br Members Alessandra Ferri Casini, Cynthia Melissa Valério, Ruy Lyra da Silva Filho, Wellington Santana da Silva Júnior

PROFESSIONAL ETHICS AND DEFENCE President Maite Trojaner Salona Chimeno etica@endocrino.org.br Vice-Inspector Itairan da Silva Terres 1ST member Diana Viegas Martins 2ND member João Modesto Filho 3RD member Luis Henrique Santos Canani 4TH member Márcio Weissheimer Lauria 5TH member Cristina Bardou Pizarro

ENDOCRINE DYSREGULATORS President Elaine Maria Frade Costa elainefradecosta@gmail.com Vice-President Maria Izabel Chiamolera Members Eveline Gadelha Pereira Fontenele, Tânia Aparecida Sanchez Bachega, Ricardo Martins da Rocha Meirelles

Coordinator Alexis Dourado Guedes dr.alexis@uol.com.br Adrenal and hypertension Madson Queiroz de Almeida Dyslipidemia and atherosclerosis Cynthia Melissa Valério Diabetes Mellitus Luiz Alberto Andreotti Turatti Basic endocrinology Maria Izabel Chiamolera Feminine and Andrology Rita de Cássia Viana Vasconcellos Weiss Pediatric Endocrinology Julienne Angela Ramires de Carvalho Bone and mineral metabolism Carolina Aguiar Moreira Neuroendocrinology Marcello D. Bronstein Obesity Maria Edna de Melo Thyroid Célia Regina Nogueira

TEMPORARY – SPORT AND EXERCISE ENDOCRINOLOGY - CTEEE President: Clayton Luiz Dornelles Macedo clayton.macedo@uol.com.br Members: Yuri Galeno Pinheiro Chaves de Freitas, Roberto Luís Zagury, Fulvio Clemo Santos Thomazelli, Felipe Henning Gaia Duarte, Ricardo de Andrade Oliveira, Andrea Messias Britto Fiorettiia

TITLE OF SPECIALIST IN ENDOCRINOLOGY AND METABOLISM President: Josivan Gomes de Lima josivanlima@gmail.com Vice-President: Márcio Corrêa Mancini Members: Marise Lazaretti Castro, Mauro Antônio Czepielewski, Milena Coelho Fernandes Caldato, Renan Magalhães Montenegro Júnior, Rogério Friedman

VALORIZATION OF NEW LEADERSHIPS President Wellington Santana da Silva Junior wellingtonsantanajr@gmail.com Members Mateus Dornelles Severo, Ricardo Mendes Martins

Brazilian Societies and Associations for Endocrinology and Metabolism

SBD – BRAZILIAN DIABETES SOCIETY SBD BRAZILIAN BOARD OF DIRECTORS (2018/2019)

President

Hermelinda Cordeiro Pedrosa

Vice-Presidents

Gustavo Caldas

Janice Sepulveda Reis

João Eduardo Nunes Salles

Rosane Kupfer

Rosângela Réa

1ST Secretary

Karla Melo

2ND Secretary

Fernanda Thomé

1ST Treasurer

Antonio Carlos Lerário

2ND Treasurer

Luiz Antônio Araújo

Supervisory Board

Silmara Leite

Regina Calsolari

Nely Calegaro

Estela Muskat Jatene

Rua Afonso Brás, 579, cj. 72/74 04511-011– São Paulo, SP Fone/Fax: (11) 3842-4931 www.diabetes.org.br

ABESO – BRAZILIAN ASSOCIATION FOR THE STUDY OF OBESITY AND METABOLIC SYNDROME ABESO BRAZILIAN BOARD OF DIRECTORS (2019-2020)

President

Mario K. Carra

Vice-President

Rodrigo Lamounier

1ST Secretary General

Jacqueline Rizzoli

2ND Secretary General

Bibiana Colenci

Treasurer

Cintia Cercato

Rua Mato Grosso, 306, cj. 1711 01239-040 – São Paulo, SP Fone: (11) 3079-2298/Fax: (11) 3079-1732 info@abeso.org.br www.abeso.org.br

editorial

AE&M’s first issue of the year: important news! Marcello D. Bronstein1

ear readers, the Archives of Endocrinology and Metabolism is entering its fourth year of activities (1), and this issue brings three important news which I would like to share with you: • First, the end of the Journal´s printed version, following the general trend to just keep the online version. This approach will make the AE&M more dynamic and agile. • Second, the disclosure of our current impact index: 2.380. This achievement probably reflects the increase of international reporting of our Journal, with the consequent increase of the number of submissions and citations. • Third, due to many commitments, Dr. Rui Maciel is leaving as an Associate Editor of the thyroid area, being replaced by Dr. Ana Luiza Maia. Additionally, Dr. Beatriz Schaan will reinforce the team of diabetes/obesity. I heartily thank Dr. Maciel for his important contribution to the AE&M and gladly welcome Drs. Maia and Schaan. As Editor-in-Chief, I would like to acknowledge and thank the devoted and essential collaboration of our Associate Editors and Reviewers, as well as the Brazilian Endocrine Society (SBEM) Board of Directors for their constant support. Last but not least, I also want to extend my special thanks to the editorial team of the AE&M.

Editor-chefe da Archives of Endocrinology and Metabolism, chefe da Unidade de Neuroendocrinologia, Serviço de Endocrinologia e Metabologia, Hospital das Clínicas, Faculdade de Medicina da Universidade de São Paulo (HCFMUSP), São Paulo, SP, Brasil 1

Correspondence to: Marcello D. Bronstein aem.editorial.office@endocrino.org.br Received on Feb/22/2019 Accepted on Feb/22/2019 DOI: 10.20945/2359-3997000000109

Disclosure: no potential conflict of interest relevant to this article was reported.

REFERENCE

1. Bronstein MD. The challenge of new directions. Arch Endocrinol Metab. 2015;59(1):1.

Arch Endocrinol Metab. 2019;63/1

editorial

Clinical risk predictors for differentiated thyroid cancer management: what is new? Denise Momesso1

Departamento de Endocrinologia, Universidade Federal do Rio de Janeiro (UFRJ). Faculdade de Medicina, Universidade Federal do Estado do Rio de Janeiro (Unirio), Rio de Janeiro, RJ, Brasil 1

Correspondence to: Denise Momesso dmomesso@terra.com.br Received on Feb/22/2019 Accepted on Feb/22/2019

DOI: 10.20945/2359-3997000000110

anagement of differentiated thyroid cancer (DTC) is highly dependent on risk stratification (1,2). An initial assessment of the risk of mortality and the risk of persistent/recurrent disease are required to guide treatment, follow-up and to set appropriate patients and physicians expectations with regard to the clinical outcomes after initial therapy. Therefore, much effort has been made for the improvement of long-term clinical risk predictors based on the information available at the time of diagnosis. In this issue of the Archives of Endocrinology and Metabolism, two very interesting papers were published concerning this subject. Nava and cols. (3) evaluated the impact of the updated American Joint Committee on Cancer; Tumor, Lymph Nodes, Metastasis (AJCC/TNM) system staging criteria on the prediction of persistent disease in DTC. The major changes from the updated TNM 8th edition were: the age cutoff used for staging was increased from 45 to 55 years of age at diagnosis; minor extrathyroidal extension detected only on histological examination was removed from the definition of T3 disease and therefore has no impact on either T category or overall stage; T3a is a new category for tumors > 4 cm confined to the thyroid gland; T3b is a new category for tumors of any size demonstrating gross extrathyroidal extension into strap muscles (sternohyoid, sternothyroid, thyrohyoid, or omohyoid muscles); level VII lymph nodes, previously classified as lateral neck lymph nodes (N1b), were reclassified as central neck lymph nodes (N1a); and the presence of distant metastases in older patients is classified as stage IVB disease rather than stage IVC disease (4). In the study of Nava and cols., the application of TNM 8th edition resulted in 37% (155/419) of DTC patientâ&#x20AC;&#x2122;s down staged and improved the prediction of poor outcomes compared to the TNM 7th edition. The re-classification for lower risk categories (stage I or stage II disease) observed in this cohort of Brazilian patients with DTC is the expected effect of the updated 8th TNM edition and allowed the appropriate classification of the majority of thyroid cancer patients as being at low risk recurrent/persistent structural disease during the follow-up. On the other hand, patients who remained classified as stage IV and III based on the 8th edition had more advanced disease and presented with higher rates of incomplete response to therapy. The TNM 8th edition had a better performance in predicting disease outcomes based on dynamic risk stratification using the response to therapy (1) than the 7th edition. Interestingly, even though the AJCC/TNM was mainly designed to predict initial estimates of disease specific mortality (1), the present study demonstrated that the 8th edition provided a satisfactory initial estimates risk of recurrent/persistent disease (3). The impact of the updated TNM staging system was more notable for older patients. The modification in the age cutoff value was based in an international multiArch Endocrinol Metab. 2019;63/1

Risk stratification for thyroid cancer

Arch Endocrinol Metab. 2019;63/1

and the American Thyroid Association (ATA) risk stratification (2) or TNM staging system considering the entire cohort. Nevertheless, most of ATA high-risk patients (54.5%) had a Bethesda V or VI result. These data suggest that the preoperative cytopathological diagnosis of Bethesda V and VI could imply not only in higher risk of malignancy (7), but also in an increased risk of DTC with aggressive features. The preoperative diagnosis of Bethesda II was observed in a higher than expected number of patients with DTC (29.4%). Fortunately, the vast majority of DTC patients that presented with Bethesda II evolved with excellent response to therapy and no evidence of disease (92.1%) (6). According to the Bethesda system the implied risk of malignancy for the diagnostic category II (benign) is of 0-3% and the recommended clinical approach is clinical and sonographic followup (7). The results of the present study suggest a very good prognosis for DTC with a Bethesda II result, what could minimize the clinical implication of the false negative result for malignancy of the cytopathology. The study of Lima and cols. (6) provides a new insight for the clinical utility of the Bethesda System, in which the preoperative cytopathology diagnosis would indicate the estimated risk of malignancy in thyroid nodules and predict the risk of aggressive features in DTC. Nevertheless, this is a small pilot study, with a retrospective design, and future studies are required to confirm these findings. The new evidence provided by these studies indicates that the long-term clinical risk prediction of DTC could be improved, based on refined findings of the preoperative cytopatholgy, histopathological data and risk stratification systems. Additionally, molecular biology will also have an important role. More studies are necessary in this field. The advances in the risk-adapted management of DTC would allow a more accurate individualized approach and better tailor treatment and follow-up strategies for patients with DTC. Disclosure: no potential conflict of interest relevant to this article was reported.

REFERENCES 1. Momesso DP, Tuttle RM. Update on differentiated thyroid cancer staging. Endocrinol Metab Clin North Am. 2014;43(2):401-21. 2. Haugen BR, Alexander EK, Bible KC, Mandel SJ, Nikiforov YE, Pacini F, et al. 2015 American Thyroid Association Management Guidelines for Adult Patients with Thyroid Nodules and

institutional validation study of 9484 patients, which included patients from Brazil (cohort from Rio de Janeiro) and demonstrated that an increase in the age cutoff from 45 to 55 years of age at diagnosis down staged 12% of patients and was associated with a 10year disease-specific survival of 98% in the down staged group (5). Similarly, the change in the age at diagnosis cutoff from 45 to 55 years was responsible for the reclassifications of 20.8% (87/419) of patients in the cohort of Navaâ&#x20AC;&#x2122;s study (3). Disease-specific survival could not be evaluated due to the low mortality rate observed during follow-up. Taken together, these findings endorse the new 8th edition of the AJCC/ TNM staging system as a better clinical risk predictor for the management of DTC. Management of DTC would be also improved with reliable clinical risk predictors available before initial surgical procedure. For this purpose, the study published in this issue by Lima and cols. (6) evaluates the Bethesda system for reporting thyroid cytopathology (7) as a predictor of aggressive features in DTC. The Bethesda system was originally designed to predict the risk of malignancy of thyroid nodules based on the cytopathological findings and to provide clinical management recommendations for each of its six diagnostic categories. The Bethesda System was revised in 2017 inspired by new data available since it was first described 2009, the use of molecular testing as an adjunct to cytopathologic examination and the reclassification of the noninvasive follicular variant of papillary thyroid carcinoma as noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) (7). The study by Lima and cols. (6) evaluated 153 patients with DTC and assessed the relationship of their preoperative fine needle aspiration diagnosis using the Bethesda system with the presence of aggressive features in histopathology, risk stratification staging systems and clinical outcomes. They found a positive relationship of Bethesda V (suspicious for malignancy) and VI (malignant) with vascular invasion and lymph node metastasis, which are associated with increased risk of recurrent/persistent disease in DTC. They also described a positive relationship of Bethesda V and VI with extrathyroidal extension, but the real impact of this finding relates do the extent of the tumor invasion to extrathyroidal structures and this was not described in the study. There was no statistically significant association between the Bethesda system categories

Risk stratification for thyroid cancer

Differentiated Thyroid Cancer: The American Thyroid Association Guidelines Task Force on Thyroid Nodules and Differentiated Thyroid Cancer. Thyroid. 2016;26(1):1-133. 3. Nava CF, Zanella AB, Scheffel RS, Maia AL, Dora JM. Impact of the updated TNM staging criteria on prediction of persistent disease in a differentiated thyroid carcinoma cohort. Arch Endocrinol Metab. 2019;63(1):5-11.

6. Lima ARLR, Medeiros KMM, Parente CMRV, Caldas AS, Faria MS, MagalhĂŁes M, et al. Does the Bethesda category predict aggressive features in differentiated thyroid cancer? Arch Endocrinol Metab. 2019;63(1):12-5. 7.

Cibas ES, Ali SZ. The 2017 Bethesda System for Reporting Thyroid Cytopathology. Thyroid. 2017;27(11):1341-6.

4. Tuttle RM, Haugen B, Perrier ND. Updated American Joint Committee on Cancer/Tumor-Node-Metastasis Staging System for Differentiated and Anaplastic Thyroid Cancer (Eighth Edition): What Changed and Why? Thyroid. 2017 Jun;27(6):751-6.

5. Nixon IJ, Wang LY, Migliacci JC, Eskander A, Campbell MJ, Aniss A, et al. An International Multi-Institutional Validation of Age 55 Years as a Cutoff for Risk Stratification in the AJCC/UICC Staging System for Well-Differentiated Thyroid Cancer. Thyroid. 2016;26(3):373-80.

Arch Endocrinol Metab. 2019;63/1

original article

Impact of the updated TNM staging criteria on prediction of persistent disease in a differentiated thyroid carcinoma cohort Carla Fernanda Nava1,2, André B. Zanella1,2, Rafael Selbach Scheffel1,2, Ana Luiza Maia1,2, Jose Miguel Dora1,2

ABSTRACT Objective: The 8th TNM system edition (TNM-8) released in 2018 presents significant changes when compared to the 7th edition (TNM-7). The aim of this study was to assess the impact of changing the TNM staging criteria on the outcomes in a Brazilian cohort of differentiated thyroid carcinoma (DTC). Subjects and methods: DTC patients, attending a tertiary, University-based hospital, were classified by TNM-7 and TNM-8. Prediction of disease outcomes status of the two systems was compared in a retrospective cohort study design. Results: Four hundred and nineteen DTC patients were evaluated, comprised by 82% (345/419) women, with mean age at diagnosis of 46.4 ± 15.6 years, 89% (372/419) papillary thyroid carcinoma, with a median tumor size of 2.3 cm (P25-P75, 1.3-3.5). One hundred and sixty patients (38%) had lymph node metastases and 47 (11%) distant metastases at diagnosis. Using the TNM-7 criteria, 236 (56%) patients were classified as Stage I, 50 (12%) as Stage II, 75 (18%) as Stage III and 58 (14%) as Stage IV. When evaluated by the TNM-8, 339 (81%) patients were classified as Stage I, 64 (15%) as Stage II, 2 (0.5%) as Stage III and 14(3%) as Stage IV. After a median followup of 4.4years (P25-P75 2.6-6.6), the rate of incomplete biochemical and/or structural response was 54% vs. 92% (P = 0.004) and incomplete structural response was 42% vs. 86% (P = 0.009) for patients classified as stage IV by TNM-7 vs TNM-8, respectively. Only 4 (1%) disease-related deaths were recorded. Conclusions: In our cohort, 37% of DTC patients were down staged with the application of TNM-8 (vs. TNM-7). Additionally, TNM-8 seems to better stratify the risk of structural incomplete response at follow-up. Arch Endocrinol Metab. 2019;63(1):5-11

Grupo de Tireoide, Serviço de Endocrinologia, Hospital de Clínicas de Porto Alegre, RS, Brasil 2 Faculdade de Medicina, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brasil 1

Correspondence to: Jose Miguel Dora Unidade de Tireoide, Serviço de Endocrinologia do Hospital de Clínicas de Porto Alegre Rua Ramiro Barcelos, 2350 90035-003 – Porto alegre, RS, Brasil jdora@hcpa.edu.br Received on Jul/29/2018 Accepted on Dec/12/2018 DOI: 10.20945/2359-3997000000097

INTRODUCTION

ifferentiated thyroid carcinoma (DTC), comprising papillary (PTC) and follicular carcinoma (FTC), accounts for the majority (> 90%) of all thyroid malignancies (1). In recent years, an increasing incidence of DTC diagnosis has been documented worldwide (2). The incremental use of imaging resources in medical practice, along with the continuous development of more sensitive techniques, led to the pandemic observation of “overdiagnosis” of DTC (2). Most of the increment in DTC diagnosis can be credited to increased detection of pre-clinical indolent tumors restricted to the thyroid gland, that present a more favorable disease profile (3,4). The current 2015 ATA Management Guidelines for Adult Patients with DTC advise that “AJCC/UICC staging is recommended for all patients with DTC, Arch Endocrinol Metab. 2019;63/1

based on its utility in predicting disease mortality, and its requirement for cancer registries” (5). In response to the change in DTC epidemiology, staging systems are being revised, to ensure a more balanced delivery of therapy for DTC, specially for those at low risk of disease-related morbidity/mortality. The 8th edition (TNM-8) of the American Joint Committee on Cancer; Tumor, Lymph Nodes, Metastasis (AJCC/TNM) system, was incorporated into the management of DTC in January of 2018 (6). The most significant changes were the age at diagnosis cut-off (from 45 to 55 years) and the redefinition of the T3b and T4a classifications. In the TNM-7, microscopic extrathyroidal extension of the tumor warranted a T3 classification. In the TNM-8, T3 is now comprised of tumors greater than 4 cm and confined to the thyroid gland (T3a) or gross extrathyroidal extension of the strap 5

Keywords Differentiated thyroid carcinoma; TNM staging; prognosis

Impact of the new DTC TNM

muscles (T3b). T4a is now defined as gross invasion of the subcutaneous tissue, larynx, trachea, esophagus or recurrent laryngeal nerve and T4b as gross invasion of the prevertebral fascia or major vessels (6,7). The update in the TNM staging criteria aims to improve prediction of disease specific and overall survival, allocating patients at risk of persistent/ recurrent disease for more advanced TNM stages, qualifying diagnostic work up and interventions at follow-up (8). In Brazil we have scarce data on the clinical impact of updating the TNM criteria. Thus, the objective of this study was to assess how changing the TNM staging criteria affects the prediction of long term outcomes in a cohort of Brazilian DTC patients in tertiary, University-based hospital.

SUBJECTS AND METHODS Patients and study design The patients included were followed in a retrospective cohort of DTC patients from the Thyroid Outpatient Clinic of the Thyroid Unit, Endocrine Division of Hospital de Clínicas de Porto Alegre (HCPA), a tertiary care, university teaching hospital in southern Brazil. From 2009 to 2015, all consecutive patients with a histological diagnosis of DTC and data available to be classified by TNM-7 and TNM-8 staging systems were included. The study was approved by the ethics committee of the institution (CAAE 68434617.5.0000.5327/GPPG 17-0482).

Treatment protocol and follow-up Our DTC treatment protocol consists of performing total thyroidectomy and administration of radioactive iodine (RAI) remnant ablation activity according to the ATA risk assessment. Decisions regarding cervical lymph node dissection were made at the discretion of the surgical team from the center where the patients underwent the first surgery. Duration of follow-up was defined as the time between the first surgery and the last medical visit to the clinic. Our ablation protocol used RAI activities prescribed at the attending physician’s discretion. The RAI was administered in a stimulated TSH condition of endogenous hypothyroidism (TSH > 30 mUI/L), after withdrawing levothyroxine (at least 3-4 weeks without thyroid hormone). A post-treatment whole body scan 6

(post-treatment WBS) was performed seven to ten days after RAI administration. In the first evaluation, the following data were recorded for each patient: demographics, tumor characteristics [e.g., histological features (papillary thyroid carcinoma or follicular thyroid carcinoma – including Hurthle cell carcinoma), extension and lymph node involvement] and treatment (e.g., surgery, RAI remnant ablation, and other interventions). Each patient was classified using the 7th and 8th editions of the TNM/AJCC staging system (I, II, III, or IV) (6,9). N0 status was defined with postoperative neck ultrasound (US) imaging or pathological examination of patients with lymph node resection. Distant metastasis (M1) was considered present when there was a lesion outside the cervical bed on imaging (CT, MRI or scintigraphy) with: histological confirmation or post-treatment WBS uptake and/or elevated Tg. The risk of persistent/ recurrent disease was assessed based on the proposed risk stratification system by the American Thyroid Association (ATA) guidelines, with patients classified into three risk groups: low, intermediate and high (5). The follow-up protocol called for an initial assessment at 3 to 6 months after the initial treatment, which included a physical examination of the neck and measurements of the serum thyroglobulin levels under TSH suppression (Tg-T4) and anti-thyroglobulin antibody (TgAb). In a second evaluation, 6 to 12 months after the initial treatment, serum thyroglobulin (Tg) under stimulated TSH condition in endogenous hypothyroidism (TSH > 30 mIU/L) (sTg) and TgAb were measured. Neck ultrasound was performed in this first year of follow-up. At this point, the patient was classified according to disease outcome to initial therapy (see below in the outcomes section). Patients classified as having an excellent response were scheduled for annual visits, during which a physical examination of the neck and measurements of Tg-T4 and TgAb were performed. Patients with indeterminate or incomplete responses were scheduled for the same examination at least twice a year. Additional imaging studies [e.g. x-ray, bone scintigraphy, computed tomography (CT), magnetic resonance (MR)] were performed, as needed, whenever the clinical or laboratory findings raised the suspicion of persistent or recurrent disease.

Outcomes In the first year of follow-up, the disease outcome of initial therapy was assessed based on the serum Tg-T4 Arch Endocrinol Metab. 2019;63/1

Impact of the new DTC TNM

Laboratory analysis Serum Tg measurements were conducted using immunoradiometric assays (from 2000 to 2002 radioimmunoassay; 2002 to 2010 electrochemiluminescence and 2010 until the present chemiluminescence) that indicated functional sensitivities of at least 0.2 ng/mL. Antithyroglobulin antibodies were measured using the passive agglutination method from 2000 to 2010 and by chemiluminescence from 2010 until the present. After each new technique had been implemented, the necessary procedures for standardization and validation were performed. TSH levels were measured by chemiluminescence assay from 2000 to 2006 (Immulite 2000 SIEMENS), electrochemiluminescence from 2006 to 2010 (Modular E Roche), chemiluminescence assay from 2010 to 2014 (Centaur XP Siemens) and electrochemiluminescence from 2014 until the present (Cobas E602 Roche). These tests were all conducted in the central laboratory of the HCPA. Arch Endocrinol Metab. 2019;63/1

Statistical analysis The clinical and laboratory data are reported as the mean ± standard deviation (SD) values or as the median and percentiles 25 and 75 (P25-75) for continuous variables, or as absolute numbers and percentages for categorical variables. Comparative analyses of frequencies were performed using Pearson Chi-Square or Fisher’s Exact Test, as appropriate. Agreement for qualitative (categorical) variables was accessed using the Cohen’s Kappa coefficient. All tests were two-tailed, and all analyses were performed using the Statistical Package for Social Science Professional software version 20.0 (IBM Corp., Armonk, NY). A two-tailed P < 0.05 was considered statistically significant.

RESULTS Patients Four hundred and nineteen DTC patients were evaluated. Clinical and oncological characteristics of these patients are described in Table 1. The mean age at diagnosis was 46.4 ± 15.6 years, 345 (82%) were women and PTC was diagnosed in 372 (89%) patients. The median tumor size was 2.3 cm (P25-75 1.3-3.5 cm). One hundred and sixty patients (38%) had lymph node metastases, and 47 (11%) patients had distant metastases. All patients underwent total thyroidectomy ± lymph node dissection and received RAI remnant ablation. The mean RAI activity was 112.3 ± 38.1 mCi.

Table 1. Characteristics of 419 patients with differentiated thyroid carcinoma Age at diagnosis (years)

46.4 ± 15.6

Female sex – n (%)

345 (82.3)

Histology – n (%) Papillary Follicular

372 (88.8) 74 (11.2)

Tumor size (cm)

2.3 (1.3-3.5)

Lymph node metastasis (N1) – n (%)

160 (38.2)

Distant metastasis – n (%)

47 (11.2)

RAI therapy – n (%)

or sTg levels, neck US,and additional imaging exams, whenever indicated. An excellent response was defined as having no clinical or imaging evidence of tumor (i.e., no imaging evidence of tumor on neck US or CT), undetectable (< 0.2 ng/mL) serum Tg-T4 levels and/or sTg levels < 1 ng/mL. Indeterminate response was defined as nonspecific findings on imaging studies, Tg-T4 detectable but < 1 ng/mL, sTg detectable but < 10 ng/mL or TgAb stable or declining in the absence of structural or functional disease. Biochemical incomplete response was defined as negative imaging and Tg-T4 ≥ 1 ng/ml or sTg levels ≥ 10 ng/mL or rising TgAb levels. Structural incomplete response was defined as structural or functional evidence of disease at any TgT4 level with or without TgAb. Patients who were diagnosed with persistent disease were evaluated for additional treatment (e.g., surgery, RAI, external-beam radiation or multi-kinase inhibitors), depending on the site involved and disease progression. All patients with biochemical incomplete and structural incomplete responses were considered to have persistent disease. Recurrence was defined as new biochemical or structural evidence of the disease detected in a patient who had been previously classified as having an excellent response. Disease specific survival (DSS) was considered the time from initial surgery to last follow-up or death related to DTC.

419 (100)

RAI activity (mCi)

112.3 ± 38.1

Follow-up (years)

4.4 (2.6-6.6)

Data are expressed as the mean ± SD, median (percentiles 25-75) or frequencies. RAI: radioactive iodine.

Impact of the new DTC TNM

TNM-7 vs. TNM-8: staging comparison Using the TNM-7 criteria, 236 (56%) patients were classified as stage I, 50 (12%) as stage II, 75 (18%) as stage III and 58 (14%) as stage IV. When evaluated by the TNM-8, 339 (81%) patients were classified as stage I, 64 (15%) as stage II, 2 (0.5%) as stage III and 14 (3%) as stage IV (Table 2). The distribution of stage frequencies from TNM-7 to TNM-8 were statistically significant (p ≤ 0.0001), and distributed as follows: 236 (100%) patients who were stage I remained the same; of the 50 previously in stage II, 36 (72%) were reclassified to stage I and only 14 (28%) maintained the classification. Of the 75 that were stage III, 49 (65%) were reclassified to stage I, 26 (35%) to stage II and none remained in this classification; of the 58 patients in stage IV, 19 (33%) were reclassified to stage I, 24 (41%) to stage II, 2 (3%) to stage III, and only 14 (24%) remained in stage IV. One hundred and fifty-five (37%) patients with DTC were downstaged with the application of TNM-8 (vs TNM-7), 87 (56%) being due to the change in the age at diagnosis cut-off from 45 to 55 years and 68 (44%) to change in T3 definition (Table 3).

TNM-7 vs. TNM-8: ATA Risk Using TNM-7, 163/233 (70%) stage I patients were classified as low risk, 63/233 (27%) as intermediate risk and 7/233 (3%) as high risk. Stage II patients were

classified as follows: 31/50 (62%) as low risk, 6/50 (12%) as intermediate risk and 13/50 (26%) as high risk. Of those in stage III, 30/75 (40%) were classified as low risk, 44/75 (59%) as intermediate risk and 1/75 (1%) as high risk. Of those in stage IV, 8/58 (14%) were stratified as low risk, 23/58 (40%) as intermediate risk and 27/58 (47%) as high risk. Applying the TNM-8, stage I patients were stratified as low risk in 212/335 (63%) cases, as intermediate risk in 113/335 (34%) and as high risk in 10/335 (3%). Those in stage II were classified as low risk in 20/65 (31%), as intermediate risk in 23/65 (35%) and as high risk in 22/65 (34%). All stage III (n = 2) and stage IV (n = 14) patients were classified as high risk (100%) (Table 4). The greater number of reclassifications in ATA low and intermediate risk patients led to a weak level of agreement between TNM-7 and TNM-8 (kappa 0.14 and 0.13, respectively; p ≤ 0.0001 for both comparisons). In ATA high-risk patients, the agreement between the two classifications was considered moderate (kappa 0.54, p ≤ 0.0001).

TNM-7 vs. TNM-8: disease outcomes Regarding disease outcomes after initial therapy, we verified an excellent response status in 47/223 (21%), 9/49 (18%), 21/71 (30%) and 6/58 (10%) for patients at stage I, II, III and IV of TNM-7, respectively. While using the TNM-8 at the same point in time, an

Table 2. Modifications of differentiated thyroid carcinoma staging from the TNM-7 to the TNM-8 system TNM-8

DTC Staging

TNM-7

I (n = 339)

II (n = 64)

III (n = 2)

IV (n = 14)

I (n = 236)

236 (100%)

0 (0%)

II (n = 50)

36 (72%)

14 (28%)

0 (0%)

III (n = 75)

49 (65%)

26 (35%)

0 (0%)

IV (n = 58)

19 (33%)

24 (41%)

2 (3%)

14 (24%)

DTC: differentiated thyroid carcinoma. Chi-square of p ≤ 0.0001 for TNM-7 vs. TNM-8.

Table 3. Comparison of Tumor classification of TNM-7 and TNM-8 systems

TNM-8

TNM-7

T1a

T1b

T3a

T3b

T4a

T4b

Total

154

111

132

T4a

T4b

Total

109

148

414

Arch Endocrinol Metab. 2019;63/1

Impact of the new DTC TNM

excellent response status was as follows: 76/322 (24%), 7/63 (11%), 0/2 (0%) and 0/14 (0%) for patients at stage I, II, III and IV, respectively. Indeterminate status was observed in 99/223 (44%), 10/49 (20%), 29/71 (41%) and 18/58 (31%) for patients at stage I, II, III and IV of TNM-7, respectively; and using the TNM-8 we found 135/322 (42%), 19/63 (30%), 1/2 (50%) and 1/14 (7%) for patients at stage I, II, III and IV, respectively. Biochemical incomplete response was the disease status in 40/223 (18%), 13/49 (27%), 11/71 (15%) and 7/58 (12%) for patients at stage I, II, III and IV of TNM-7, respectively; and while using TNM-8 62/322 (19%), 8/63 (13%), 1/2 (50%) and 0/14 (0%) for patients at stage I, II, III and IV, respectively. Structural incomplete response frequencies were 37/223 (17%), 17/49 (35%), 10/71 (14%) and 27/58 (47%) for patients at stage I, II, III and IV using TNM-7, respectively; and in 49/322 (15%), 29/63 (46%), 0/2 (0%) and 13/14 (93%) for patients at stage I, II, III and IV using TNM-8 (Table 5).

After a median follow-up of 4.4 years (P25-P75 2.6-6.6), the majority of the patients maintained the same response to therapy status or were downgraded to a more favorable status, a finding observed with both TNM staging systems (p ≤ 0.001). The rate of excellent response in stage I patients was 39% vs. 38% for TNM-7 and TNM-8; in stage II patients it was 26% vs. 17%, in stage III patients it was 36% vs 0% and in stage IV patients 14% vs. 0%. The rate of indeterminate responses was 40% vs 41% in stage I patients; 36% vs. 34% in stage II patients; 45% vs. 50% in stage III patients and 32% vs. 7% in stage IV patients. The rate of biochemical incomplete response was 13% vs. 12% in stage I patients; 14% vs. 6% in stage II patients; 3% vs. 50% in stage III patients and 12% vs. 7% in stage IV patients. The rate of structural incomplete response was 8% vs. 8% in stage I patients, 24% vs. 42% in stage II patients; 16% vs. 0% in stage III patients and 42% vs. 86% (p = 0.009) in stage IV patients for TNM-7 and TNM-8, respectively (Table 6, Figure 1). The agreement level was considered

Table 4. ATA risk according to differentiated thyroid carcinoma staging using the TNM-7 and TNM-8 systems ATA risk

TNM-7 Stage n (%) I

III

Low

163 (70)

31 (62)

Intermediate

63 (27)

6 (12)

7 (3)

13 (26)

High

TNM-8 Stage n (%) IV

III

30 (40)

8 (14)

212 (63)

20 (31)

0 (0)

44 (59)

23 (40)

113 (34)

23 (35)

0 (0)

1 (1)

27 (47)

10 (3)

22 (34)

2 (100)

14 (100)

Kappa for TNM-7 vs. TNM-8 according to ATA risk: 0.14 for low risk (p ≤ 0.0001); 0.13 for intermediate risk (p ≤ 0.0001) and 0.54 for high risk (p ≤ 0.0001).

Table 5. Disease outcomes after initial treatment according to differentiated thyroid carcinoma staging using the TNM-7 and TNM-8 systems Treatment response

TNM-7 Stage n (%) I

TNM-8 Stage n (%)

III

Structural incomplete

37 17)

17(35)

10 (14)

27 (47)

49 (15)

29 (46)

0 (0)

13 (93)

Biochemical incomplete

40 (18)

13 (27)

11 (15)

7 (12)

62 (19)

8 (13)

1 (50)

0 (0)

Indeterminate

99 (44)

10 (20)

29 (41)

18 (31)

135 (42)

19 (30)

1 (50)

1 (7)

Excellent

47 (21)

9 (18)

21 (30)

6 (10)

76 (24)

7 (11)

0 (0)

Kappa for TNM-7 vs. TNM-8 according to initial treatment response: 0.13 for excellent response (p = 0.006); 0.19 for indeterminate response (p ≤ 0.0001); 0.07 for biochemical incomplete response (p = 0.26) and 0.56 for structural incomplete response (p ≤ 0.0001).

Table 6. Disease outcomes at long-term follow-up according to differentiated thyroid carcinoma staging using the TNM-7 and TNM-8 systems TNM-7 Stage n (%)

TNM-8 Stage n (%)

III

Structural incomplete

18 (8)

12 (24)

12 (16)

24 (42)

27 (8)

27 (42)

0 (0)

12 (86)

Biochemical incomplete

29 (13)

7 (14)

2 (3)

7 (12)

39 (12)

4 (6)

1 (50)

1 (7)

Indeterminate

87 (40)

18 (36)

34 (45)

18 (32)

133 (41)

22 (34)

1 (50)

1 (7)

Excellent

86 (39)

13 (26)

27 (36)

8 (14)

123 (38)

11 (17)

0 (0)

0(0)

Kappa for TNM-7 vs. TNM-8 according to treatment response at long-term follow-up: 0.13 for excellent response (p ≤ 0.001); 0.13 for indeterminate response (p ≤ 0.001); 0.26 for biochemical incomplete response (p = 0.002) and 0.51 for structural incomplete response (p ≤ 0.0001). Arch Endocrinol Metab. 2019;63/1

Treatment response

Impact of the new DTC TNM

moderate only for patients with incomplete structural response (kappa 0.51, p â&#x2030;¤ 0.0001). Recurrence was observed only on 3/419 (0.7%) patients during follow-up period with a median time of 2.6 years. It was not possible to access the impact of the reclassification on DSS due to the low mortality rate observed in our cohort (n = 4, 1%). The four deaths occurred in TNM-7 stage IV patients (n = 4, 100%), and in TNM-8 stage II (n = 2, 50%) and stage IV (n = 2, 50%) patients. 100% 80% 60% 40% 20% 0%

II III IV TNM-7 Structural incomplete

III TNM-8 Biochemical incomplete

Figure 1. Differentiated thyroid carcinoma biochemical incomplete and structural incomplete responses to therapy at long term follow-up, according to TNM-7 and TNM-8.

DISCUSSION The classification of DTC patients using staging systems is a crucial step in the care of these patients, since it allowed the healthcare team to determine the best therapeutic and follow-up approach. This study examined the impact of updating the TNM staging system from TNM-7 to TNM-8 on the reclassification of DTC patients in a Brazilian cohort, showing that the TNM-8 reclassified 37% of patients to lower stages. We also compared the prognostic information from both systems, and observed that TNM-8 was superior in predicting disease status at follow-up. In recent years the incidence of DTC has been increasing with a more frequent diagnosis of low-risk and indolent tumors (2). These patients do not benefit from an aggressive approach, but may be exposed to the risks of overtreatment. The impact of updating the TNM-7 staging system to TNM-8 has been explored by some studies (8,10,11). In our study the majority of reclassifications occurred due to age at the diagnosis 10

cut-off change (n = 87, 56%). The change in age at the diagnosis cut-off was proposed and validated by Nixon and cols. in a multicenter study of 9,500 patients (12,13). Older patients with more advanced disease tend to have a worse prognosis and this is usually proportional to age at diagnosis. Nixon and cols. showed that increasing the age cut-off point from 45 to 55 years resulted in a better prediction of outcomes, and prevented low risk patients from being overstaged and, consequently, overtreated. The results of Kim and cols. (14) corroborate these findings, and showed that a cut-off of 55 years was better at predicting DSS. In our population age cut-off numbers were in accordance with other reports, and seem to better stratify low and high risk patients. Twenty percent of all patients in our study were downstaged because of the change in cutoff for age at diagnosis, which is in line with data from Kim and cols. (10) that found 27%, and Pontius and cols. results of 26% (SEER cohort) and 26% (NCDB cohort) (11). Using TNM-8, we observed that stage I patients are mostly classified as ATA low risk group, stage II patients are evenly distributed between low, intermediate, and high risk and patients in stages III and IV are exclusively at ATA high risk. When we compared these figures with the classification obtained using TNM-7, we noticed that patients in stage I were also mostly in the low-risk group, while patients in stage II were distributed between low and high risk, those in stage III between low and intermediate risk and those in stage IV distributed in all three groups. Taken together these findings suggest that the TNM-8 serves as a good predictor for relapses and complications related to the disease. Regarding the prediction of disease outcomes of the TNM-8, initially and after a median of 4.4 years (P25-P75 2.6-6.6) follow-up, we observed that patients with an excellent response were only those initially classified as stage I and II, those with indeterminate response were mainly patients in stage I and II, also including some stage III and IV. The groups of patients with biochemical incomplete and structural incomplete responses were comprised by patients with TNM-8 stage I to IV. It is worth mentioning that 86 to 93% of TNM-8 stage IV patients were on incomplete structural response and none of them had an excellent response. While comparing the two staging systems, TNM-8 classifies patients with a more severe disease spectrum as stages III and IV, identifying groups that benefit from a more aggressive treatment and follow-up approaches. Arch Endocrinol Metab. 2019;63/1

Impact of the new DTC TNM

Our study has some limitations. The fact that only two patients remained in stage III after reclassification to TNM-8, makes it difficult to evaluate disease outcome prediction for this subgroup. Also, all patients included in this study underwent total thyroidectomy and received radioiodine, which limits the extrapolation of our results to patients submitted to partial thyroidectomy and to those who did not receive radioiodine. Notwithstanding, one should note that our data reflect a real clinical practice scenario at a tertiary care center, where all patients have access to standardized treatment protocols. Additionally, our data comprise a considerable number of patients, and it is one of the first studies providing Brazilian information on the subject. In summary, 37% of DTC patients were downstaged with the application of TNM-8 (vs. TNM-7). The TNM-8 incorporates a large number of patients to lower stages, retaining the favorable prediction performance for stages I and II. It also selects more advanced DTC disease to stages III and IV. These findings confirm that the application of TNM-8 to our population is valid, and superior to TNM-7, regarding prediction of poor DTC outcomes. The use of TNM-8 has the potential to benefit a large number of patients, helping deliver the appropriate intensity of care according to disease prognosis. Acknowledgments: This work was a possible due to grants from CNPq, Capes, Fipe and Pronex/Fapergs. We wish to thank the anonymous reviewers that contributed to improve our work, to the surgeons of our Hospital (Dr. Alceu Migliavacca, Dr. José Ricardo Guimarães and Dr. Diego Mossmann) for surgical management of our patients and Luciana Scotti and Rosana Scalco for helping with laboratory tests. Disclosure: no potential conflict of interest relevant to this article was reported.

REFERENCES

3. Durante C, Montesano T, Torlontano M, Attard M, Monzani F, Tumino S, et al.; Group PTCS. Papillary thyroid cancer: time course of recurrences during postsurgery surveillance. J Clin Endocrinol Metab. 2013;98(2):636-42. 4. Scheffel RS, Zanella AB, Antunes D, Dora JM, Maia AL. Low Recurrence Rates in a Cohort of Differentiated Thyroid Carcinoma Patients: A Referral Center Experience. Thyroid. 2015;25(8):883-9. 5. Haugen BR, Alexander EK, Bible KC, Doherty GM, Mandel SJ, Nikiforov YE, et al. 2015 American Thyroid Association Management Guidelines for Adult Patients with Thyroid Nodules and Differentiated Thyroid Cancer: The American Thyroid Association Guidelines Task Force on Thyroid Nodules and Differentiated Thyroid Cancer. Thyroid. 2016;26(1):1-133. 6. Tuttle M, Morris LF, Haugen B, Shah J, Sosa JA, Rohren E, et al., editors. Thyroid-Differentiated and Anaplastic Carcinoma (Chapter 73) In: Amin MB, Edge S, Greene F, Byrd DR, Brookland RK, Washington MK, et al. AJCC Cancer Staging Manual. 8th ed. New York City: Springer International Publishing; 2017. 7. Tuttle RM, Haugen B, Perrier ND. Updated American Joint Committee on Cancer/Tumor-Node-Metastasis Staging System for Differentiated and Anaplastic Thyroid Cancer (Eighth Edition): What Changed and Why? Thyroid. 2017;27(6):751-6. 8. Kim TH, Kim YN, Kim HI, Park SY, Choe JH, Kim JH, et al. Prognostic value of the eighth edition AJCC TNM classification for differentiated thyroid carcinoma. Oral Oncol. 2017;71:81-6. 9. Edge S, Byrd DR, Compton CC, Fritz AG, Greene FL, Trotti A. AJCC cancer staging manual. 7th ed. New York: Springer; 2010. 10. Kim M, Kim WG, Oh HS, Park S, Kwon H, Song DE, et al. Comparison of the Seventh and Eighth Editions of the American Joint Committee on Cancer/Union for International Cancer Control Tumor-Node-Metastasis Staging System for Differentiated Thyroid Cancer. 2017;27(9):1149-55. 11. Pontius LN, Oyekunle TO, Thomas SM, Stang MT, Scheri RP, Roman SA, et al. Projecting Survival in Papillary Thyroid Cancer: A Comparison of the Seventh and Eighth Editions of the American Joint Commission on Cancer/Union for International Cancer Control Staging Systems in Two Contemporary National Patient Cohorts. Thyroid. 2017;27(11):1408-16. 12. Nixon IJ, Kuk D, Wreesmann V, Morris L, Palmer FL, Ganly I, et al. Defining a valid age cutoff in staging of well-differentiated thyroid cancer. Ann Surg Oncol. 2016;23(2):410-5. 13. Nixon IJ, Wang LY, Migliacci JC, Eskander A, Campbell MJ, Aniss A, et al. An International Multi-Institutional Validation of Age 55 Years as a Cutoff for Risk Stratification in the AJCC/UICC Staging System for Well-Differentiated Thyroid Cancer. Thyroid. 2016;26(3):373-80. 14. Kim M, Kim YN, Kim WG, Park S, Kwon H, Jeon MJ, et al. Optimal cut-off age in the TNM Staging system of differentiated thyroid cancer: is 55 years better than 45 years? Clin Endocrinol (Oxf). 2017;86(3):438-43.

1. Sherman S. Thyroid carcinoma. Lancet. 2003;361:501-11.

2. Vaccarella S, Franceschi S, Bray F, Wild CP, Plummer M, Dal Maso L. Worldwide Thyroid-Cancer Epidemic? The Increasing Impact of Overdiagnosis. N Engl J Med. 2016;375(7):614-7.

Arch Endocrinol Metab. 2019;63/1

original article

Does the Bethesda category predict aggressive features in differentiated thyroid cancer? Ana Rafaela Lopes Reis Lima¹, Karoline Matias Morais de Medeiros1, Conceição de Maria Ribeiro Veiga Parente1, Adriana de Sá Caldas1, Manuel dos Santos Faria1,2, Marcelo Magalhães1,2, Carla Souza Pereira Sobral1,2

ABSTRACT Serviço de Endocrinologia do Hospital Universitário da Universidade Federal do Maranhão (UFMA), São Luís, MA, Brasil 2 Centro de Pesquisas Clínicas, Universidade Federal do Maranhão (UFMA), São Luís, MA, Brasil 1

Correspondence to: Carla Souza Pereira Sobral Rua das Hortas 120, Centro 65020-270 – São Luís, MA, Brasil carlasouzasobral@gmail.com Received on Sept/11/2018 Accepted on Oct/30/2018 DOI: 10.20945/2359-3997000000098

Objective: To analyze the importance of preoperative cytology of thyroid nodules and its relationship with mortality risk, recurrence risk, dynamic stratification, and aggressive characteristics (vascular invasion, aggressive histology, incomplete tumor resection, extrathyroidal extension of the tumor, and presence of lymph node and distant metastases). Subjects and methods: Retrospective evaluation of 153 patients diagnosed with differentiated thyroid carcinoma (DTC) and following up at the Hospital Universitário Presidente Dutra between January 1999 and December 2016. Results: In all, 96% of the patients were female, 79.7% had papillary carcinoma and the most common fineneedle aspiration (FNA) result was Bethesda II (29.4%). The mean age was 43.11 ± 12.8 years. Overall, 85% of the patients progressed without any evidence of disease. There was a statistically significant relationship between the presurgical FNA and the presence of extrathyroidal extension, vascular invasion, and lymph node metastasis. Conclusions: The preoperative cytology of the nodule may have an impact on the follow-up of patients with DTC. Future studies in a larger population are required to confirm this finding. Arch Endocrinol Metab. 2019;63(1):12-5 Keywords Bethesda; thyroid; cancer; aggressiveness

INTRODUCTION

ifferentiated thyroid cancer (DTC) arises from a normal follicular thyroid cell and is responsible for most (> 90%) thyroid carcinomas (1). Papillary thyroid carcinoma (PTC) is the most frequent DTC (affecting 95% of all cases), followed by follicular carcinoma, Hürthle cell carcinoma, and poorly DTC (1,2). After surgical removal and histopathological confirmation of thyroid cancer, the patients are classified according to their mortality risk (MR) and recurrence risk (RR). These two classification systems help physicians evaluate the surgical result and decide about the initial treatment and follow-up of the patient (2). These systems also facilitate the communication among health care professionals. The MR is evaluated using the American Joint Committee on Cancer/International Union Against Cancer (AJCC/UICC) tumor-node-metastasis (TNM) staging system, which is based on a combination of age at diagnosis, size of the primary tumor, extrathyroidal 12

tumor extension, and the presence of lymph node and distant metastases (2,3). Since this system fails to predict the RR, we use instead the RR system, which analyzes features such as vascular invasion, aggressive histology, tumor resection, and postoperative thyroglobulin level (3-5). After the initial treatment, a dynamic stratification system is used to classify the treatment response according to clinical, biochemical, and imaging (structural and functional) data obtained during follow-up. According to this system, the patients are categorized as having an excellent response, incomplete biochemical response, indeterminate response, or incomplete structural response (2,3). These classification systems adequately define the best initial follow-up strategy for each patient (requirement of additional surgery, radioiodine therapy, and/or hormone suppressive therapy) and prevent overtreatment. However, these systems do not take into account preoperative characteristics like the cytological features of the nodule. This information Arch Endocrinol Metab. 2019;63/1

Bethesda category and aggressive thyroid cancer

SUBJECTS AND METHODS This retrospective study analyzed the records of 505 patients with DTC seen at the Hospital Universitário Presidente Dutra in São Luís (Maranhão state, Brazil), between 1999 and 2016. The cohort included adults older than 19 years with a histopathological diagnosis of thyroid cancer. All patients had preoperative FNA biopsies of the malignant nodule available for analysis and were followed up for at least 1 year with biochemical (thyroglobulin and antithyroglobulin antibody) and imaging tests (ultrasound or radioiodine whole-body scan). After exclusion of patients not meeting these criteria, the final cohort comprised 153 patients. The following information was collected from each patient: age, gender, Bethesda category of the preoperative FNA, size of the nodule, extent of surgical resection, histological variant, extrathyroidal extension, vascular invasion, margin status, presence of lymph node metastases and distant metastases, MR, RR, and the dynamic stratification on the last medical appointment. All statistical analyses were performed using GraphPad Prism 5. Continuous and categorical variables are presented as mean ± standard deviation (SD). Fisher’s exact test was used to analyze categorical variables. P values below 0.05 were considered statistically significant. The institution’s ethics committee approved the study.

results. Table 1 shows the clinical characteristics of the entire cohort. According to the TNM staging system, 90.8% (n = 139) of the patients were stage I, 3.9% (n = 6) were stage II, 4.6% (n = 7) were stage III, and 0.7% (n = 1) were stage IV. There was no relationship between the FNA result and the TNM staging system (p > 0.05). Table 2 shows the results of the RR analysis. In total, 54.5% (n = 12 out of 22) of the high-risk patients had a Bethesda V or VI FNA result, while 31.3% (n = 41 out of 131) of low- and intermediate-risk patients had such results. However, no relationship was observed between the FNA result and the RR (Table 3). We were able to identify the dynamic stratification system of 133 of the 153 patients, since 20 patients were lost to follow-up. Our data showed that 83.4% (n = 111) of the patients had an excellent response, 8.3% (n = 11) had an indeterminate response, 5.3% (n = 7) had an Table 1. Clinical characteristics of 153 patients with differentiated thyroid carcinoma Characteristics Gender Female Male Age in years (mean ± SD, range)

147 (96%) 6 (4%) 43.11 ± 12.8 (20 – 75)

Multifocality Yes

38 (24.8%)

115 (75.2%)

Histology Papillary

122 (79.7%)

Follicular

26 (17%)

Hürthle cell

5 (3.3%)

Bethesda category I

5 (3.3%)

45 (29.4%)

III

17 (11.1%)

33 (21.6%)

24 (15.7%)

29 (18.9%)

RESULTS

SD: standard deviation.

The final group comprised 153 patients with a mean age of 43.11 ± 12.8 years, of whom 96% (n = 147) were female. The most common tumor type was PTC (79.7%, n = 122) and the Bethesda II category was the most frequent FNA result (29.4%, n = 45). A total of 32.7% of the FNA samples yielded false-negative

Table 2. Recurrence risk in 153 patients with differentiated thyroid carcinoma

Arch Endocrinol Metab. 2019;63/1

Recurrence risk

Low

74 (48.4%)

Intermediary

57 (37.2%)

High

22 (14.4%)

may be important for adequate surveillance. Based on that, this study analyzed the importance of preoperative cytological analysis of thyroid nodules, obtained by ultrasound-guided fine-needle aspiration (FNA), and the relationship of preoperative cytological features of the nodule with the patients’ MR, RR, and dynamic stratification, and the tumor’s aggressive characteristics (vascular invasion, aggressive histology, incomplete tumor resection, extrathyroidal extension of the tumor, and presence of lymph node/distant metastases).

Bethesda category and aggressive thyroid cancer

incomplete biochemical response, and 3.0% (n = 4) had an incomplete structural response. Table 4 describes the relationship between the FNA results and an excellent response to treatment. Patients with a Bethesda II FNA result had better dynamic stratification classifications than patients with Bethesda III, IV, V, or VI FNA results (p < 0.05). There was no relationship between each Bethesda category and extrathyroidal extension (p > 0.05). However, when patients with a Bethesda V or VI result were analyzed as a single group, the group presented a relationship with the occurrence of extrathyroidal extension (p < 0.05). Also, patients with Bethesda V and VI results had more often vascular invasion than patients in other groups, and no relation was found between the FNA result and incomplete tumor resection (p > 0.05). Finally, there was a progressive relationship between FNA results and lymph node metastasis, with Bethesda V and VI categories showing the highest risks. Table 3. Relationship between Bethesda V or VI categories and a high recurrence risk (RR) High RR

Bethesda V or VI

Yes

12 (25.5%)

35 (74.5%)

10 (9.4%)

96 (90.6%)

p = 0.051

Table 4. Relationship between fine-needle aspiration results and dynamic classification Excellent response Yes

Bethesda V and VI

35 (74.5%)

12 (25.5%)

p > 0.05

Bethesda III and IV

37 (84.1%)

7 (15.9%)

p > 0.05

Bethesda II

35 (92.1%)

3 (7.9%)

p < 0.05

DISCUSSION In our study, the patients had a mean age at diagnosis of 43.11 Âą 12.8 years, and the cohort included women in a proportion above the one previously described in the literature (6). A possible reason for this may be the fact that women tend to seek medical care more frequently than men. As a result, men with DTC may be underdiagnosed or diagnosed at more advanced stages. 14

According to the histopathological DTC subtype, our cohort showed a distribution similar to that in previous studies, namely, PTC 79.7% versus 85%, respectively, and FTC 17% versus 12%, respectively (4). At diagnosis, most of our patients (90.8%) were categorized as stage I, and only one patient was categorized as stage IV. This information is aligned with results from other studies in the literature (6) and shows that in most of our patients, the disease was identified at initial stages. We found no relationship between the FNA result and the TNM staging system (p > 0.05). The clinical course of malignant thyroid tumors varies widely. Most patients with DTC have a good prognosis when treated properly, and the mortality rates in these cases are similar to those in the general population (2). However, the percentage of patients who present recurrence is not negligible, while some fail to respond to conventional therapies and may even die of the disease. The TNM staging system is used to determine the disease-related mortality rate (7). When we analyzed the relationship between the FNA results and the RRs, we observed that 54.5% of the high-risk patients had a Bethesda V or VI FNA result; however, this association was not statistically significant. VanderLaan and cols., in a study with 474 patients with preoperative FNA and diagnosed with PTC, observed that more patients with a Bethesda VI FNA result had a high RR (p < 0.05) (8). We also observed an excellent response to treatment during follow-up in 74.5%, 84.1%, and 92.1% of the Bethesda V/VI, III/IV, and II patients, respectively. In fact, the Bethesda II group had a better dynamic staging (p < 0.05). This suggests that this group may receive a less aggressive treatment. Our data also showed a positive relationship between Bethesda V and VI and extrathyroidal extension (p < 0.05), vascular invasion (p < 0.05), and lymph node metastasis (p < 0.05). On the other hand, there was no relationship between the Bethesda I, II, III, and IV categories and extrathyroidal extension and vascular invasion. Moreover, there was no relationship between the FNA result and incomplete tumor resection. Liu and cols. analyzed 1,291 patients with PTC and described a progressive relationship between Bethesda III, IV, V, and VI FNA results and extrathyroidal extension, lymph node metastases, and incomplete tumor resection. The authors observed no relationship between these Bethesda categories with vascular invasion (9). VanderLaan and cols. also observed a higher Arch Endocrinol Metab. 2019;63/1

Bethesda category and aggressive thyroid cancer

incidence of lymph node metastases, vascular invasion, and extrathyroidal extension in Bethesda VI patients (8). In a study including 360 patients with DTC, Kleiman and cols. found a strong relationship between the Bethesda V and VI categories with extrathyroidal extension and lymph node metastases (10). Our data suggest that patients with a Bethesda V or VI FNA result may have more aggressive features related to a poor prognosis and, consequently, may receive a more aggressive treatment. Therefore, along with surgery, FNA results may help the treatment of patients with PTC. Our study has some limitations. Among all patients with DTC included in the cohort, the Bethesda II was the most frequent category found in preoperative FNAs (29.4%). This is not aligned with the estimated MR in this Bethesda category (2) and may have influenced some of the results. Unfortunately, we were unable to identify other preoperative factors, such as suspicious ultrasound features, because several patients only started following up with our group after surgery. In conclusion, the FNA results of thyroid nodules are helpful in guiding the initial treatment and may influence the follow-up of patients with DTC. Bethesda II patients show a better dynamic stratification, while Bethesda V or VI patients have an increased risk of extrathyroidal extension, vascular invasion, and lymph node metastasis. More studies are important to analyze how the FNA result impacts the treatment and follow-up of DTC.

REFERENCES 1.

Lamartina L, Grani G, Durante C, Borget I, Filetti S, Schlumberger M. Follow-up of differentiated thyroid cancer – what should (and what should not) be done. Nat Rev Endocrinol. 2018;14(9):538-51.

2. Haugen BR, Alexander EK, Bible KC, Doherty GM, Mandel SJ, Nikiforov YE, et al. 2015 American Thyroid Association Management Guidelines for Adult Patients with Thyroid Nodules and Differentiated Thyroid Cancer: The American Thyroid Association Guidelines Task Force on Thyroid Nodules and Differentiated Thyroid Cancer. Thyroid. 2016;26(1):1-133. 3. Tuttle RM, Leboeuf R. Follow up approaches in thyroid cancer: a risk adapted paradigm. Endocrinol Metab Clin North Am. 2008;37(2):419-35. 4. Coeli CM, Brito AS, Barbosa FS, Ribeiro MG, Sieiro APAV, Vaisman M. Incidência e mortalidade por câncer de tireóide no Brasil. Arq Bras Endocrinol Metab. 2005;49(4):503-9. 5.

Hegedüs L. The thyroid nodule. N Engl J Med. 2004;351(17):1764-71.

6. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2016. CA Cancer J Clin. 2016;66(1):7-30. 7.

Rosário PW, Ward LS, Carvalho GA, Graf H, Maciel RMB, Maciel LMZ, et al. Nódulo tireoidiano e câncer diferenciado de tireoide: atualização do consenso brasileiro. Arq Bras Endocrinol Metab. 2013;57(4):240-64.

8. VanderLaan PA, Marqusee E, Krane JF. Features Associated with Locoregional Spread of Papillary Carcinoma Correlate with Diagnostic Category in The Bethesda System for Reporting Thyroid Cytopathology. Cancer Cytopathol. 2012;120(4):245-53. 9. Liu X, Medici M, Kwong N, Angell TE, Marqusee E, Kim MI, et al. Bethesda categorization of thyroid nodule cytology and prediction of thyroid cancer type and prognosis. Thyroid. 2016;26(2):256-61. 10. Kleiman DA, Beninato T, Soni A, Shou Y, Zarnegar R, Fahey TJ. Does Bethesda category predict aggressive features in malignant thyroid nodules? Ann Surg Oncol. 2013;20(11):3484-90.

Disclosure: no potential conflict of interest relevant to this article was reported.

Arch Endocrinol Metab. 2019;63/1

original article

Serum irisin and apelin levels and markers of atherosclerosis in patients with subclinical hypothyroidism Department of Endocrinology, Tepecik Research and Training Hospital, Izmir, Turkey 2 Department of Biochemistry, Tepecik Research and Training Hospital, Izmir, Turkey 3 Department of Radiology, Tepecik Research and Training Hospital, Izmir, Turkey 4 Department of Biochemistry, Canakkale Onsekiz Mart University, Canakkale, Turkey 5 Department of Internal Medicine, Hatay State Hospital, Hatay, Turkey 6 Department of Anesthesiology and Algology, Ataturk Research and Training Hospital, Izmir, Turkey 1

Correspondence to: Hamiyet Yılmaz Yasar Tepecik Research and Training Hospital, Department of Endocrinology, Guney district, Street number: 1140/1 no: 1 35110 – Izmir, Turkey drhamiyetyilmaz@yahoo.com Received on Feb/2/2018 Accepted on July/4/2018 DOI: 10.20945/2359-3997000000106

Hamiyet Yilmaz Yasar1, Mustafa Demirpence1, Ayfer Colak2, Leman Yurdakul3, Merve Zeytinli2, Hakan Turkon4, Ferhat Ekinci5, Aybike Günaslan2, Erdem Yasar6

ABSTRACT Objective: In this study, we aimed to evaluate serum irisin and apelin levels in patients with subclinical hypothyroidism (SCH) when they were subclinical hypothyroid and become euthyroid after levothyroxine therapy and association of these adipokines with markers of atherosclerosis such as serum homocysteine levels and carotid intima-media thickness (IMT). Subjects and methods: The study included 160 patients with newly diagnosed subclinical hypothyroidism due to Hashimoto’s thyroiditis and 86 euthyroid healty subjects. Serum glucose and lipid profile, insulin, HOMA, TSH, free T3, free T4, anti-thyroperoxidase and anti-thyroglobulin antibodies, homocysteine, apelin and irisin levels were measured in all study subjects. Thyroid and carotid ultrasound examinations were performed. The subclinical hypothyroid group was reevaluated after 12-weeks of levothyroxine therapy when they became euthyroid. Results: Clinical characteristics of the patient and control group were similar. Glucose, insulin and HOMA levels, lipid parameters and free T3 were similar between the two groups.. Serum homocystein was higher and apelin was lower in patients with SCH, but irisin levels were similar between the two groups. While thyroid volume was lower, carotid IMT was significantly greater in patients with SCH (pCarotidIMT:0,01). After 12-weeks of levothyroxine therapy, all the studied parameters remained unchanged except, serum freeT4, TSH, homocystein and apelin. While homocystein decreased (p: 0,001), apelin increased significantly (p = 0,049). In multivariate analysis, low apelin levels significantly contributed to carotid IMT (p = 0,041). Conclusions: ApelinAPJ system may play a role in vascular and cardiac dysfunction in patients with SCH and treatment of this condition may improve the risk of cardiovascular disease. Arch Endocrinol Metab. 2019;63(1):16-21 Keywords

Subcinical hypothyroidism; irisin, apelin; atherosclerosis; carotid intima-media thickness

INTRODUCTION

ubclinical hypothyroidism (SCH) is defined by elevated serum levels of TSH, with normal levels of free T3 and T4. SCH prevalence ranges between 4% and 10% in the general population and between 7% and 26 % in the older population. About 2-5% of patients with SCH progress to overt hypothyroidism annually (1). Hypothyroidism and by extension SCH is associated with a significant decrease in insulin sensitivity and metabolic syndrome (2). SCH was also shown to be positively associated with coronary heart disease (CHD) events and mortality in a meta-analysis of the most relevant prospective studies (3,4). Irisin, the most recently identified adipomyokine, is the extracellular cleaved product of fibronectin type III domain-containing 5 (FDNC5) and is regulated by peroxisome proliferator-activated receptor gamma (PPARγ) coactivator-1 alpha (PGC1α) (5). Studies have shown that FDNC5/irisin overexpression induces 16

browning and enhances thermogenesis in white adipose tissue, contributing to improvements in glucose homeostasis and insulin resistance (5). FDNC5, which is the precursor of irisin was shown to be present in many tissues, including the thyroid tissue (5-7). Irisin was evaluated in a variety of conditions such as type II diabetes mellitus, metabolic syndrome, insulin resistance, obesity, chronic renal disease, anorexia nervosa and hypothyroidism (8). It was also reported to be associated with increased cardiometabolic risk and suggested that it might be implicated in proinflammatory and atherogenic pathways (9). Apelin is an endogenous ligand of the G-protein coupled angiotensin-like 1 (APJ) receptor and adipose tissue is the most important source. APJ is expressed by the heart, lung, kidney, liver, adipose tissue, gastrointestinal tract, brain, adrenal glands, endothelium and plasma cells (10,11). Apelin was studied in diabetes, insulin resistance and hypertension Arch Endocrinol Metab. 2019;63/1

Adipokines in subclinical hypothyroidism

SUBJECTS AND METHODS Patients and study design The study was a single-center, prospective, case-control study including patients with SCH. A total of 160 patients attending to our outpatient Endocrinology Clinic of Tepecik Research and Training Hospital with newly diagnosed SCH due to Hashimoto’s thyroiditis (age range, 20-72 years) were recruited between August 2014 and June 2015. The patients had not had yet levothyroxine treatment. The control group included 86 euthyroid healthy subjects (age range, 22-55 years) attending to our family practice outpatient clinic just for check-up. All subclinical hypothyroid subjects had autoimmune thyroiditis (Hashimto’s thyroiditis) and anti-TPO antibody was positive in all of them. The exclusion criteria included; diabetes mellitus (fasting glucose > 126 mg/dL on 2 separate occasions), hypertension (present or past antihypertensive drug use or detection of systolic pressure > 140 mmHg and/or diastolic pressure > 90 mmHg), dyslipidemia (plasma LDL-cholesterol levels > 130 mg/dL, triglyceride levels > 150 mg/dL), acute and chronic renal disease, coronary artery disease, peripheral artery disease, neurological disease or any other chronic disease or malignancy. None of the study subjects were smokers or drank alcohol. The study was approved by the medical ethics committee of the Tepecik Research and Training Hospital and all participants provided written informed consent. Arch Endocrinol Metab. 2019;63/1

All of the study subjects underwent physical examination, laboratory assessment and thyroid and carotid artery ultrasound examination. Physical examination included measurement of blood pressure and waist circumference as well as calculation of body mass index (BMI). Blood pressure was measured with the person in a seated position after a 5 minute rest with an Omron M3 HEM-7131 electronic, auscultatory blood pressure reading machine. The first reading was discarded, and the mean of the next three consecutive readings was used. Waist circumference was measured on bare skin between the tenth rib and the iliac crest in centimeters. BMI was calculated by the ratio between weight and height squared in kg/m2. The subclinical hypothyroid group was reevaluated by physical examination, laboratory assessment and carotid artery ultrasound examination after 12 weeks of levothyroxine replacement therapy when they became euthyroid. Levothyroxine replacement was started with a dose of 25 µg/day and TSH was measured every 4 weeks for dose adjustment. Euthyroid state was achieved with a mean levothyroxine dose of 73.33 ± 21.70 µg/day at 12th week.

Laboratory assessments After an overnight fast of 12 hours, venous blood was collected from the antecubital vein. Glucose concentrations were measured by a hexokinase method with the Olympus AU-2700 analyzer. Triglycerides, total cholesterol and HDL-cholesterol were measured by an enzymatic method with an Olympus AU-2700 analyzer using reagents from Olympus Diagnostics (Gmbh, Hamburg, Germany). LDL-cholesterol was calculated by the Friedewald’s equation method. Insulin, free T3 (normal range: 2.5-4.4 pg/mL), free T4 (normal range: 0.54-1.24 ng/dL), TSH (normal range: 0.34-5.6 uIU/mL), anti-TPO (normal range: 0-10 IU/mL) and anti-Tg (normal range:0-50 IU/mL) levels were measured by chemiluminescent method using an Immulite 2000 otoanalyzer (Immulite XPi, Siemens, Germany). Homeostasis model assessment (HOMA) was used as a measure of insulin sensitivity using the following equation = fasting insulin (mU/L) X glucose (mmol/L)/22.5. Insulin resistance is defined as having a HOMA value > 2.7 as suggested by Matthews and cols. (16). Serum homocysteine levels were measured by high-performance liquid chromatography (Shimadzu 17

and it was reported to be negatively associated with hypertensive heart disease (12,13). It was also shown to protect against ischaemia-reperfusion injury. Irisin was previously studied in patients with SCH (14,15), but only Stratigou and cols. evaluated serum irisin levels after being euthyroid with levothyroxine treatment (15). Apelin was studied in patients with SCH (10,13), however it was also not evaluated after becoming euthyroid. Therefore in this study, we aimed to investigate serum irisin and apelin levels – which were reported to be associated with increased cardiometabolic risk – in patients with SCH and the effect of levothyroxine therapy on these adipokines. We also aimed to investigate the correlation of these adipokines with surrogate markers of atherosclerosis such as serum homocysteine levels and carotid intimamedia thickness (IMT).

Adipokines in subclinical hypothyroidism

LC20A, Shimadzu Corp, Kyoto, Japan) based on fluorometric detection. Serum irisin and apelin concentrations were measured with an enzyme-linked immunosorbent assay (ELISA) kit according to the manufacturer’s directions (Apelin; Catalog No.: 20112-2015, Irisin; Catalog No: 201-12-5328), Sunred biological technology, Shanghai, China. The intra-assay and inter-assay coefficients of variations were < 10% and < 12% for apelin and irisin, respectively.

Ultrasonography of the thyroid gland and carotid arteries The thyroid and carotid ultrasound examinations were performed by a radiologist experienced in ultrasonography with a linear probe 8-13 MHz (Toshiba Aplio 300, Tokyo, Japan). Thyroid volume was calculated by the elliptical shape volume formula (0.479 X length X width X height) for each lobe (17). Carotid IMT measurements were obtained within a region free of plaque, on the far wall of the distal CCA, 2 cm proximal to the carotid bulb and on the end diastolic phase (18). In a longitudinal view of the CCA where a clearly identified double-line pattern was observed, a 10 mm length of a straight CCA far wall segment was chosen. The mean IMT was calculated by ultrasound as the mean of the computer-based lines in the selected region.

Statistical analysis Results are expressed as means ± SD. The patient and control groups were compared by using Student-t test. The Chi-Square test was used for nominal variables. Bazal and post-treatment values of the study group were compared by using paired samples t-test. Correlation between MPV and other parameters were assessed by Pearson’s correlation analysis. Multiple regression analysis was used to identify the independent predictors that have an effect on carotid IMT. P < 0.05 was considered statistically significant. Statistical analysis was performed with SPSS 20 statistical software.

RESULTS Clinical characteristics of the patient and control groups are described in Table 1. No significant differences were observed between the 2 groups according to age, gender, BMI, waist circumference and blood pressure values. 18

Table 1. Clinical characteristics of the study population

Age Gender (M/F)

Group with SCH n: 160

Control group n: 86

P value

39.58 ± 14.87

40.40 ± 10.06

0.808

26/134

18/68

0.171

BMI (kg/m )

30.22 ± 5.71

29.60 ± 6.12

0.705

Waist circumference (cm)

93.40 ± 12.13

89.47 ± 14.16

0.294

Systolic blood pressure (mmHg)

119 ± 15.8

123.6 ± 12.8

> 0.05

Diastolic blood pressure (mmHg)

84 ± 12.7

82.8 ± 8.6

> 0.05

Fasting blood glucose, insulin levels, HOMA values, lipid parameters and free T3 were similar between the 2 groups (Table 2). As expected, free T4 levels were lower and TSH, anti-TPO levels and anti-Tg levels were significantly higher (pfT4 = 0.025, pTSH < 0.001, p-anti-TPO = 0.003 and p-anti-Tg = 0.004) in the subclinical hypothyroid group (Table 2). Table 2. Laboratory parameters and carotid artery Doppler ultrasound assessment of the study population

Glucose (mg/dL) Insulin ( µU/mL)

Group with SCH (n: 160)

Control group (n: 86)

P value

92.80 ± 10.91

93.76 ± 6.83

0.704

11.00 ± 5.99

9.11 ± 4.23

0.074

Total cholesterol (mg/dL)

204.07 ± 38.00 203.08 ± 43.32

0.931

LDL-cholesterol (mg/dL)

124.88 ± 28.37 123.41 ± 32.18

0.865

HDL-cholesterol (mg/dL)

48.78 ± 14.19

53.34 ± 14.86

0.269

Triglyceride (mg/dL)

142.89 ± 90.59 137.34 ± 89.65

0.543

fT3 (pg/mL)

3.20 ± 0.41

3.35 ± 0.38

0.201

fT4 (ng/mL)

1.06 ± 0.23

1.19 ± 0.16

0.025

TSH (uIU/mL)

7.71 ± 4.08

1.82 ± 0.82

0.001

Anti-TPO (IU/mL)

142.93 ± 99.6

7.23 ± 2.93

0.003

Anti-thyroglobulin (IU/mL)

184.25 ± 49.54

44.24 ± 28.66

0.004

Thyroid volume (mL)

10.13 ± 3.39

12.29 ± 4.28

0.040

Homocystein (mMol/L)

59.32 ± 18.54

8.59 ± 4.01

0.001

Irisin (ng/mL)

23.04 ± 25.72

22.21 ± 24.34

0.801

Apelin (ng/mL)

44.55 ± 31.84

74.94 ± 63.06

0.034

0.55 ± 0.13

0.43 ± 0.19

0.008

Carotid IMT (mm)

Serum homocysteine levels were significantly higher in patients with SCH with respect to the control group (phomocysteine = 0.001). Despite similar irisin levels, apelin levels were significantly lower in patients with SCH (papelin = 0.034). Although thyroid volume was significantly lower, carotid IMT was significantly greater in patients with SCH (p thyroid volume = 0.04, p carotid IMT = 0.008). Arch Endocrinol Metab. 2019;63/1

Adipokines in subclinical hypothyroidism

Group with SCH Group with SCH (n: 160) (n: 160) after Basal LT4 treatment 30.24 ± 5.57

29.72 ± 5.78

0.114

Waist circumference (cm)

91.68 ± 12.13

90.13 ± 12.67

0.216

Glucose (mg/dL)

92.80 ± 10.91

94.43 ± 9.48

0.273

Insulin (µU/mL)

11.00 ± 5.99

14.39 ± 8.23

0.188

Total cholesterol (mg/dL)

214.07 ± 38.00

205.85 ± 36.52

0.269

LDL-cholesterol (mg/dL)

134.88 ± 28.37

130.11 ± 30.22

0.606

HDL-cholesterol (mg/dL)

48.78 ± 14.19

46.25 ± 13.99

0.084

Triglyceride (mg/dL)

152.89 ± 90.59 158.107 ± 92.00

0.759

fT3 (pg/mL)

3.20 ± 0.41

3.16 ± 0.37

0.234

fT4 (ng/mL)

1.06 ± 0.23

1.27 ± 0.49

0.022

TSH (uIU/mL)

7.71 ± 4.08

3.51 ± 1.91

0.001

Anti-TPO (IU/mL)

142.93 ± 99.6

147.66 ± 98.14

0.154

Anti-thyroglobulin (IU/mL)

184.25 ± 49.54

143.04 ± 59.68

0.190

Homocystein (mMol/L)

59.53 ± 26.28

8.59 ± 4.01

0.001

Irisin (ng/mL)

23.04 ± 25.72

23.20 ± 24.63

0.821

Apelin (ng/mL)

44.55 ± 31.84

72.91 ± 81.67

0.035

0.55 ± 0.13

0.44 ± 0.17

0.030

Correlation analyses between irisin, apelin, homocysteine, carotid IMT and all the other parameters studied were conducted. Irisin was negatively correlated with age (r = -0.271, p = 0.040) and apelin (r = -0.547, p = 0.001) was positively correlated with carotid IMT (r = 0.614, p = 0.001). Apelin level was negatively Arch Endocrinol Metab. 2019;63/1

300.00

200.00

100.00

.00 .00 .20 .40 .60 .80 CIMT

r = -0.335, p = 0.041

P values

BMI (kg/m2)

Carotid IMT (mm)

400.00

Figure 1. Correlation analysis between apelin levels and CIMT.

DISCUSSION The association of SCH with all components of metabolic syndrome and risk of cardiovascular disease have been well-studied (2-4). However the data are limited about the level of adipokines such as irisin and apelin – whose metabolic and cardiovascular effects were supposed to be similar to the effects of hypothyroidism – in patients with SCH. Therefore, in this study we investigated serum irisin and apelin levels and known cardiovascular risk factors such as serum homocysteine levels and carotid IMT, in patients with SCH. We also re-evaluated all of these parameters after 12-weeks of levothyroxine therapy when euthyroidism was achieved. SCH has been associated with functional cardiac abnormalities, vascular abnormalities, (eg increased vascular resistance, arterial stiffness and endothelial dysfunction), and atherosclerosis (19). Several cohort studies have analyzed the association between SCH and CHD. Although in the Whickham survey, CHD events were increased in individuals with SCH, in another survey including 3,233 individuals no significant difference was 19

Table 3. Basal and 12th week clinical and laboratory evaluation of patients with SCH

correlated with age (r = -0.328, p = 0.012) and carotid IMT (r = -0,611, p = 0.001), in addition to irisin. No correlation was observed between homocysteine level and other parameters. Multiple regression analysis revealed that although low apelin level significantly contributed to carotid IMT (p = 0,041) (Figure 1), high serum irisin level did not significantly affect carotid IMT (p = 0.096).

Apelin

The subclinical hypothyroid group was reevaluated with the same laboratory parameters after 12 weeks of levothyroxine replacement therapy when they became euthyroid. The basal and post-treatment data are reported in Table 3. Basal and post-treatment BMI and waist circumference measurements were similar. No significant differences were observed between basal and post-treatment serum glucose, insulin and HOMA values and lipid parameters. As expected, serum freeT4 levels were increased and TSH levels were decreased significantly (pfT4 = 0.022), Ptsh = 0.001). Serum homocysteine levels were decreased significantly from 59.53 ± 26.28 to 8.59 ± 4.01 after 12 weeks of levothyroxine treatment (p = 0.001). Although serum irisin levels remained similar, apelin levels were significantly increased from 44.55 ± 31.84 to 72.91 ± 81.67 (p = 0.035). In addition, carotid IMT decreased significantly after treatment (p carotid IMT = 0.030).

Adipokines in subclinical hypothyroidism

observed in the prevalence of CHD between SCH patients and euthyroid controls (20,21). Likewise surrogate indexes of atherosclerosis such as serum homocysteine levels and carotid IMT have been well studied in SCH and after restoration of the euthyroid state, but the results are contradictory (22-25). Similar to some of the previous reports, we observed hyperhomocysteinemia (24,25) and significantly increased carotid IMT in subclinical hypothyroid patients (24). Also, in our study we observed significantly decreased homocysteine values with the restoration of euthyroid state after 12-weeks of levothyroxine treatment similar to Sengül and cols. (25). Yet it was reported as unchanged in other studies (23). Irisin has a role in the browning of subcutaneous adipocytes via elevation of uncoupling protein-1 (UCP-1)and it has been shown to increase energy expenditure. Although there are conflicting results about irisin levels in type II diabetes, a meta-analysis showed that irisin levels were decreased in type II diabetes and they were found to be increased in insulin resistance and metabolic syndrome (26). Irisin was previously studied in hypothyroid patients. Ates and cols. reported increased irisin levels in hypothyroid patients and suggested that increased TSH levels might cause increased irisin levels. It was proposed that increased TSH might lead to increased adipogenesis and hormones such as leptin, ghrelin and irisin could be synthesized to keep the fat distribution in balance in the increased white adipose tissue (6). Zybek-Kocik and cols. found decreased irisin levels in long-standing hypothyroidism and suggested that it might result from muscle damage due to prolonged myopathy and leakage of irisin from damaged muscle cells (7). Only two studies evaluated circulating irisin levels in SCH: Although irisin levels were similar between euthyroid and subclinical hypothyroid patients in one study (14), it was reported to be increased in the other study (15). Stratigou and cols. suggested that irisin might represent an adipo-myokine counterbalancing the deterioration of lipid metabolism and insulin sensitivity in SCH as well as reflecting a protective compensatory mechanism against oxidative muscle and thyroid cell stress (15). In our study irisin levels in subclinical hypothyroid patients were similar to healthy controls. This may be because in Stratigou’s study insulin and lipid levels were significantly higher in patients with SCH compared to the control group. In our study, these parameters were similar between the patient and control group. Also, Stratigou and cols, observed no change in serum irisin 20

levels after 6 months of levothyroxine treatment with restoration of euthyroidism. It was suggested that this might be attributed to 1) the small number of treated patients, 2) the short follow-up period, and 3) the variation of irisin not depending solely on TSH levels. Likewise, we found similar irisin levels after treatment. Apelin, an adipocytokine is a constituent of adipose tissue and is secreted by adipocytes that are stimulated by insulin. It is also an endogenous peptide that is a ligand for the APJ receptor and produced by endothelial cells in many parts of the body and the sites of receptor expression are linked to the different functions of apelin (13). It is a powerful inotrope and peripheral vasodilator and may be involved in fluid homeostasis, by its antidiuretic effect (27). Apelin levels were found to be increased in type II diabetes and hyperinsulinemia-dependent obesity and decreased in hypertension and hypertensive heart disease (10). In addition a more recent study suggested that the apelin-APJ system might protect the myocardium from ischemia reperfusion injury by its actions on the reperfusion injury salvage kinase pathway (13). A small amount of evidence shows that the apelin-APJ system may be involved in modulating endothelial oxidative stress and the formation of coronary atherosclerotic plaques (27,28). Two studies have evaluated apelin levels in patients with SCH. In both studies no significant difference was observed in serum apelin levels between patients with SCH and healthy control subjects (10,13). The authors explained that these results were because, BMI was similar in both groups. In contrast to these findings, we observed significantly lower serum apelin levels in patients with SCH. Being different from these studies, we also evaluated apelin levels after becoming euthyroid with levothyroxine treatment in patients with SCH and we found a significant increase in serum apelin levels. This may be explained by SCH possibly being associated with increased risk of atherosclerosis (3-5) and treating SCH might lead to improvement in the atherosclerosis risk as suggested by changes in established markers of atherosclerosis such as homocysteine levels and carotid IMT. In the present study, we also investigated serum homocysteine levels and carotid IMT in patients with SCH and the association of serum irisin and apelin levels with these markers of atherosclerosis. We found significant association of low apelin levels with carotid IMT. To our knowledge, this is the first study that has evaluated serum irisin and apelin levels in patients with Arch Endocrinol Metab. 2019;63/1

Adipokines in subclinical hypothyroidism

Disclosure: no potential conflict of interest relevant to this article was reported.

REFERENCES 1. Canaris GJ, Manowitz NR, Mayor G, Ridgway EC. The Colorado thyroid disease prevalence study. Arch Intern Med. 2000;160(4):526-34. 2. Maratou E, Hadjidakis DJ, Kollias A, Tsegka K, Peppa M, Alevizaki M, et al. Studies of insulin resistance in patients with clinical and subclinical hypothyroidism. Eur J Endocrinol. 2009;160(5):785-90. 3. Ochs N, Auer R, Bauer DC, Nanchen D, Gussekloo J, Cornuz J, et al. Meta-analysis: subclinical thyroid dysfunction and the risk for coronary heart disease and mortality. Ann Intern Med. 2008;148(11):832-45. 4. Rodondi N, den Elzen WP, Bauer DC, Cappola AR, Razvi S, Walsh JP, et al.; Thyroid Studies Collaboration. Subclinical hypothyroidism and the risk of coronary heart disease and mortality. JAMA. 2010;304(12):1365-74. 5. Moreno-Navarrete JM, Ortega F, Serrano M, Guerra E, Pardo G, Tinahones F, et al, Irisin is expressed and produced by human muscle and adipose tissue in association with obesity and insulin resistance. J Clin Endocrinol Metab. 2013;98(4):E769-78. 6. Ateş İ, Altay M, Topçuoğlu C, Yılmaz FM. Circulating levels of irisin is elevated in hypothyroidism, a case-control study. Arch Endocrinol Metab. 2016;60(2):95-100. 7. Zybek-Kocik A, Sawicka-Gutaj N, Wrotkowska E, Sowiński J, Ruchała M. Time-dependent irisin concentration changes in patients affected by overt hypothyroidism. Endokrynol Pol. 2016;67(5):476-80. 8. Moreno M, Moreno-Navarrete JM, Serrano M, Ortega F, Delgado E, Sanchez-Ragnarsson C, et al. Circulating irisin levels are positively associated with metabolic risk factors in sedentary subjects. PLoS One. 2015;10(4):e0124100. 9. Panagiotou G, Mu L, Na B, Mukamal KJ, Mantzoros CS. Circulating irisin, omentin-1, and lipoprotein subparticles in adults at higher cardiovascular risk. Metabolism. 2014;63(10):1265-71. 10. Gürel A, Doğantekin A, Özkan Y, Aydın S. Serum apelin levels in patients with thyroid dysfunction. Int J Clin Exp Med. 2015;8(9):16394-8. 11. Szokodi I, Tavi P, Földes G, Voutilainen-Myllylä S, Ilves M, Tokola H, et al. Apelin, the novel endogenous ligand of the orphan receptor APJ, regulates cardiac contractility. Circ Res. 2002;91(5):434-40. 12. Akcılar R, Yümün G, Bayat Z, Donbaloğlu O, Erselcan K, Ece E. APJ receptor A445C gene polymorphism in Turkish patients with coronary artery disease. Int J Clin Exp Med. 2015;8(10):18793-9. Arch Endocrinol Metab. 2019;63/1

13. Akhondali Z, Badavi M, Dianat M, Faraji F. Co-administration of Apelin and T4 protects inotropic and chronotropic changes occurring in hypothyroid rats. Arq Bras Cardiol. 2015;105(3): 235-40. 14. Panagiotou G, Pazaitou-Panayiotou K, Paschou SA, Komninou D, Kalogeris N, Vryonidou A, et al. Changes in thyroid hormone levels within the normal and/or subclinical hyper- or hypothyroid range do not affect circulating ırisin levels in humans. 45. Thyroid. 2016;26(8):1039-45. 15. Stratigou T, Dalamaga M, Antonakos G, Marinou I, Vogiatzakis E, Christodoulatos GS, et al. Hyperirisinemia is independently associated with subclinical hypothyroidism: correlations with cardiometabolic biomarkers and risk factors. Endocrine. 2018;61(1):83-93. 16. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28(7):412-9. 17. Brunn J, Block U, Ruf G, Bos I, Kunze WP, Scriba PC. [Volumetric analysis of thyroid lobes by real-time ultrasound (author’s transl)]. Dtsch Med Wochenschr. 1981;106(41):1338-40. 18. Touboul PJ, Hennerici MG, Meairs S, Adams H, Amarenco P, Bornstein N, et al. Mannheim carotid intima-media thickness and plaque consensus (2004-2006-2011). An update on behalf of the advisory board of the 3rd, 4th and 5th watching the risk symposia, at the 13th, 15th and 20th European Stroke Conferences, Mannheim, Germany, 2004, Brussels, Belgium, 2006, and Hamburg, Germany, 2011. Cerebrovasc Dis. 2012;34(4):290-6. 19. Taddei S, Caraccio N, Virdis A, Dardano A, Versari D, Ghiadoni L, et al. Impaired endothelium-dependent vasodilatation in subclinical hypothyroidism: beneficial effect of levothyroxine therapy. J Clin Endocrinol Metab. 2003;88(8):3731-7. 20. Razvi S, Weaver JU, Vanderpump MP, Pearce SH. The incidence of ischemic heart disease and mortality in people with subclinical hypothyroidism: reanalysis of the Whickham Survey cohort. J Clin Endocrinol Metab. 2010;95(4):1734-40. 21. Cappola AR, Fried LP, Arnold AM, Danese MD, Kuller LH, Burke GL, et al. Thyroid status, cardiovascular risk, and mortality in older adults. JAMA. 2006;295(9):1033-41. 22. Cakal B, Cakal E, Demirbaş B, Ozkaya M, Karaahmetoğlu S, Serter R, et al. Homocysteine and fibrinogen changes with L-thyroxine in subclinical hypothyroid patients. J Korean Med Sci. 2007;22(3):431-5. 23. Turhan S, Sezer S, Erden G, Guctekin A, Ucar F, Ginis Z, et al. Plasma homocysteine concentrations and serum lipid profile as atherosclerotic risk factors in subclinical hypothyroidism. Ann Saudi Med. 2008;28(2):96-101. 24. Adrees M, Gibney J, El-Saeity N, Boran G. Effects of 18 months of L-T4 replacement in women with subclinical hypothyroidism. Clin Endocrinol (Oxf). 2009;71(2):298-303. 25. Sengül E, Cetinarslan B, Tarkun I, Cantürk Z, Türemen E. Homocysteine concentrations in subclinical hypothyroidism. Endocr Res. 2004;30(3):351-9. 26. Qiu S, Cai X,Yin H, Zügel M, Sun Z, Steinacker JM, et al. Association between circulating irisin and insulin resistance in non-diabetic adults: a meta-analysis. Metabolism. 2016;65(6):825-34. 27. Chandrasekaran B, Dar O, McDonagh T. The role of apelin in cardiovascular function and heart failure. Eur J Heart Fail. 2008;10(8):725-32. 28. Kadoglou NP, Lampropoulos S, Kapelouzou A, Gkontopoulos A, Theofilogiannakos EK, Fotiadis G, et al. Serum levels of apelin and ghrelin in patients with acute coronary syndromes and established coronary artery disease – KOZANI STUDY. Transl Res. 2010;155(5):238-46.

SCH when they were subclinical hypothyroid and had become euthyroid after levothyroxine replacement therapy. Nevertheless, our study has some limitations: the studied groups were small and the percentage of male participants was low. In conclusion, the apelin-APJ system may play a role in vascular and cardiac dysfunction described in patients with SCH and treatment of this condition may decrease the risk of cardiovascular disease. However, further studies should be carried out to evaluate the effect of the apelin-APJ system and thyroid hormone replacement in preventing cardiovascular events and mortality.

original article

Relationship between inflammatory markers, glycated hemoglobin and placental weight on fetal outcomes in women with gestational diabetes Fernanda Oliveira Braga1, Carlos Antonio Negrato2, Maria de Fátima Bevilacqua da Matta1, João Régis Ivar Carneiro3, Marília Brito Gomes1

ABSTRACT Unidade de Diabetes, Universidade do Estado do Rio de Janeiro (UERJ), Rio de Janeiro, RJ, Brasil 2 Associação dos Diabéticos de Bauru, Bauru, SP, Brasil 3 Departamento de Nutrologia, Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, RJ, Brasil 1

Correspondence to: Carlos Antonio Negrato Associação dos Diabéticos de Bauru Rua Saint Martin, 27-07 17012-433 – Bauru, SP, Brasil carlosnegrato@uol.com.br Received on Dec/12/2017 Accepted on Nov/14/2018 DOI: 10.20945/2359-3997000000099

Objective: The aim of this study was to evaluate the relationship between inflammatory cytokines, placental weight, glycated hemoglobin and adverse perinatal outcomes (APOs) in women with gestational diabetes mellitus (GDM). Subjects and methods: This was a prospective, longitudinal and observational study conducted from April 2004 to November 2005 in Bauru, Brazil. Included patients had singleton pregnancies and performed a 100 g OGTT and had the levels of C-reactive protein (CRP), interleukin (IL)-6, TNF alfa and glycated hemoglobin (HbA1c) determined at 24-28th gestation weeks. Results: A total of 176 patients were included, of whom 78 had the diagnosis of GDM (44.3%). Multivariate analysis demonstrated that HbA1c, age, body mass index (BMI) and previous history of GDM were independent predictors for GDM diagnosis. ROC curve indicated that HbA1C levels ≥ 5.1% at 24-28 weeks gestation were associated with GDM. No difference was found in IL-6, tumor necrosis factor alpha (TNF-alpha) and CRP serum levels in women with and without GDM. Multivariate analysis showed that placental weight was significantly associated with APOs (p < 0.005), with a cut-off value of 610 grams as demonstrated by the ROC curve. Conclusion: Placental weight ≥ 610 grams and HbA1C ≥ 5.1% were found to be associated with APOs and GDM, respectively, and their evaluation should be part of prenatal care routine. Arch Endocrinol Metab. 2019;63(1):22-9 Keywords Gestational diabetes; inflammation; cytokines; placenta; macrosomia; preterm birth

INTRODUCTION

estational diabetes mellitus (GDM) is the most common metabolic disorder found during gestation and is defined as hyperglycemia of variable severity with onset or first recognition during pregnancy that does not clearly characterize any type of preexisting diabetes (1). In Brazil, a study conducted in the 90’s called Brazilian Gestational Diabetes Study Group has found that approximately 7.6% of pregnancies were complicated by GDM (2). In 2010, the International Association of Diabetes and Pregnancy Study Groups has proposed new diagnostic criteria for the diagnosis of GDM with lower cutoff values, which lead to higher diagnostic rates (3). If these criteria were to be used in the population that was evaluated in the Brazilian Gestational Diabetes Study Group, the prevalence of GDM would be 18% instead of 7.6% as previously found (4). This finding shows that the prevalence of GDM varies widely depending on the diagnostic criteria that are used (5). 22

GDM is a heterogeneous disorder, resulting from an interaction between genetic and environmental risk factors. Currently, one of the most important risk factors for the development of GDM is the increasing prevalence of overweight/obesity which is present in up to 60.0% of women on reproductive age in the USA and some other developed countries (5). GDM is associated with a constellation of alterations such as impaired insulin secretion, hyperinsulinemia, insulin resistance, obesity, dyslipidemia and hypertension (6), that are related to an increased risk of adverse perinatal outcomes (APOs) such as large for gestational age babies (LGA), overweight (ponderal index) and low Apgar scores (< 7) (7). In general, specific risks of poorly controlled diabetes in pregnancy, that can be evaluated by HbA1c levels, include spontaneous abortion, fetal malformations, preeclampsia, intrauterine fetal demise, macrosomia, neonatal hypoglycemia and neonatal hyperbilirubinemia. Diabetes in pregnancy may increase Arch Endocrinol Metab. 2019;63/1

the risk of obesity and type 2 diabetes in the offspring later in life (8). Placenta is a maternal-fetal organ that separates the maternal and fetal circulations and plays a central metabolic role in pregnancy, mainly in fetal development (9). Several complications found in pregnancy such as GDM, preeclampsia, intrauterine growth restriction, prematurity and low birth weight are linked to angiogenic placental processes that are related to low and high placental weight (10). The human placenta expresses several cytokines including tumor necrosis factor-alpha (TNF-alpha), resistin, C-reactive protein (CRP), interleukin 6 (IL-6) and leptin which are also produced by adipose cells. Cytokines are produced by three different placental cell types: Hofbauer cells, trophoblast cells and vascular endothelium cells. Leptin and IL-6 are released into the fetal and maternal systemic circulation; they can exert endocrine actions by acting at remote sites from their original production site. In contrast, TNF-alpha is poorly released from placenta and hence is more likely to exert paracrine effects. In GDM, the overexpression of placental TNFalpha is associated with increased fetal adiposity (11). The aim of this study was to evaluate the relationship between inflammatory markers, placental weight, glycated hemoglobin and APOs in women with GDM.

SUBJECTS AND METHODS This was a prospective, longitudinal and observational study conducted between April 2004 and November 2005 in Bauru, a Southeastern Brazilian city. The methodology has been described previously (7). All patients received free health-care from the Brazilian National Health Care System (BNHCS). One hundred and eighty women with singleton pregnancies were invited to participate. In the 3rd trimester (24-28th weeks of gestation) a 100g OGTT was performed; the cutoff values for the OGTT were those proposed by Carpenter & Coustan (12). After performing the test, patients were classified as having GDM if they presented at least two altered values in the curve or controls if they had a normal test (CG). This study was approved by the ethics committee of Botucatu’s School of Medicine – São Paulo State University (Unesp), Brazil. Written informed consent was obtained from all patients. The following maternal variables were accessed using a questionnaire during a clinical visit: age, parity, Arch Endocrinol Metab. 2019;63/1

ethnicity, years of school attendance, family income (Brazilian minimum wage), weight and length at birth, pre-pregnancy body mass index (BMI), family’s history of diabetes, hypertension, obesity and dyslipidemia. At the screening, weight, height, legs length, blood pressure, waist circumference (at the point of minimal abdominal girth) and hip circumference (at the point of maximum extension of the buttocks) were measured. BMI was calculated dividing weight in kilograms by the square of the height in meters. A prepregnancy BMI ≥ 30 kg/m2 was defined as obesity. When a systolic blood pressure > 140 mmHg or a diastolic blood pressure > 90 mmHg was found on at least two occasions, at least six hours apart, the diagnosis of hypertension was made. The waist-to-hip ratio was calculated dividing waist by hip circumferences. At the time the OGTT was made, blood samples were collected to determine fasting levels of glucose, HbA1C, total cholesterol, HDL, LDL, VLDL cholesterol and triglycerides. Sera samples were stored at -80oC. Glucose oxidase method (Glucose–analyzer II Beckman, Fullerton, CA, USA) was used to determine blood glucose levels. Triglycerides, cholesterol and its fractions (LDL, VLDL, HDL) were measured by enzymatic colorimetric assays. High performance liquid column method (HPLC) was used to determine HbA1C values (Dia-Stat analyzer, Bio-Rad Laboratories, Hercules, CA, USA reference values: 4.0-6.3%). The following biochemical parameters were measured: CRP by turbidimetric method (A25 BioSystems and CRP kit BioSystems, with a reference value of < 0.3 mg/dl and an intra-assay and interassay coefficient of variation of 1.8% and 3.6%, respectively); IL-6 and TNF-alpha dosages by the MAGPIX (Luminex), multiplex immunoassay (xMAP Technology) with the Human Adipokine Magnetic Bead Panel 2 kit with coefficients of variation for TNFalpha (intra-assay of 3.0% and inter-assay of 19.0%) and for IL-6 (intra-assay of 2.0% and inter- assay of 10.0%). The following fetal data were collected: birth weight, length, ponderal index, gender, gestational age at delivery, Apgar scores at 1, 2 and 5 minutes, APOs and congenital malformations. Preterm was present when gestational age was < 37 weeks. The need for a baby to be admitted into an intensive care unit (ICU) was defined by the presence of any acute morbidity. The presence of malformations, respiratory distress syndrome, icterus, infections, LGA, macrosomia, neonatal hypoglycemia and the need to be admitted into an ICU, were considered as APOs. 23

Placental weight and adverse fetal outcomes in gestational diabetes

Ponderal index was determined by the ratio between 100 times the weight and the cube of the length in cm. Lubchenco’s classification was used to determine the relationship between newborns’ weight to gestational age (13). Placental weight was obtained immediately after delivery, in the same balance used to evaluate the newborn’s weight. Weight was measured in kilograms (kg), grams (g) and in subsequent scales of up to 0.05 kg.

error (SE), odds ratio (OR) and 95% confidence interval (95% CI). The ROC (receiver operator characteristic) curve was constructed from these analyzes. Analyses were performed using SAS® System, version 6.11 (SAS Institute, Inc., Cary, North Carolina). A two-sided p value less than 0.05 was considered significant.

RESULTS

Statistical analysis

Demographic, clinical and laboratory data according to the presence or absence of GDM

Data are presented as means (±SD) or median (minimum-maximum) for continuous variables and numbers (relative frequencies) for discrete variables. Comparisons between independent continuous variables were performed using Mann-Whitney test. Chi-Square (χ2) or Fisher tests were used for comparisons between discrete variables. Spearman coefficient of correlation (rho) was performed between clinical and laboratory maternal and fetal data. Multivariate stepwise forward logistic regression was performed to identify independent demographic and clinical predictors of GDM (yes or no) and for the presence or absence of APOs (LGA, macrosomia, preterm birth, and need for ICU admission). In all models the following parameters were described: coefficient (B), standard

A total of 176 patients were included in the study of whom 78 (44.3%) had the diagnosis of GDM. Four patients were excluded: two were HIV positive and in two blood samples were not adequately stored. Patients in the GDM group were older, mostly Caucasians n = 51 (65.4%), had less years of school attendance and lower income. They were also shorter and had shorter legs’ length than the CG. They were heavier and presented higher blood pressure levels (both diastolic and systolic). Pregnant women with GDM had a higher frequency of previous history of GDM, higher levels of fasting glucose and HbA1c. These data are described in Tables 1-3.

Table 1. Clinical, demography and laboratory data of the population according to OGTT

Variable

GDM

Normal OGTT IQR

p valuea

Median

IQR

Median

Age (years)

31.0

29.0-37.0

27.5

24-32

Education level (years)

11.0

8.0-12.3

12.0

10.0-15.0

0.004

Family income (Brazilian minimum wage)

2.65

1.67-7.9

6.0

3.0-12.0

0.0001

Height (m)

1.61

1.58-1.67

1.65

1.59-1.7

0.010

Legs length (cm)

73.3

71.0-76.1

75.0

72.5-78.6

0.011

Legs/height ratio (%)

45.6

44.5-46.4

45.8

45.0- 46.7

0.089

Weight (kg)

70.0

62.0-87.5

64.0

57.8-72.0

0.0009

Body Mass Index (kg/m2)

27.8

23.6-32.1

22.8

20.9-27.3

< 0.0001

Systolic blood pressure (mmHg)

120

110-120

110

100-120

0.0001

Diastolic blood pressure (mmHg)

70-80

< 0.0001

Fasting glycemia (mg/dL)

90.5

82.6-103.3

74.0

67.0-79.0

< 0.0001

HbA1c (%)

5.68

5.09-6.10

4.8

4.41-5.20

< 0.0001

Total cholesterol (mg/dL)

209.0

191.0-238.0

230.0

206.0-261.0

0.001

LDL cholesterol (mg/dL)

112.0

89.0-141.0

127.0

110.0-153.0

0.008

HDL cholesterol (mg/dL)

56.3

47.6-66.9

64.0

54.3-76.7

0.002

VLDL cholesterol (mg/dL)

37.0

27.4-44.9

37.0

25.6-48.0

0.90

Triglycerides (mg/dL)

185.0

132.0-227.0

185.0

128.0-240.0

0.78

IL-6 (pg/mL)

0.175

0.120-0.298

0.155

0.100-0.325

0.77

CRP (mg/dL)

0.585

0.335-1.123

0.530

0.250-0.883

0.40

TNF alpha (pg/mL)

0.230

0.130-0.330

0.200

0,130-0.310

0.76

< 0.0001

IQR: interquartile range; GDM: gestational diabetes mellitus; OGTT: oral glucose tolerance test; CRP: C-reactive protein; TNF alpha: tumor necrosis factor alpha; TSH: thyroid-stimulating hormone. a

Mann-Whitney test.

Arch Endocrinol Metab. 2019;63/1

Placental weight and adverse fetal outcomes in gestational diabetes

Multivariate Analysis according to the presence or absence of GDM Multivariate logistic analysis performed with 160 observations (missing data of 16 patients for HbA1c) showed that HbA1c [OR 4.92; (95% CI 2.51-9.65); B 1.5931; SE 0.3438, p < 0.0001], age [OR 1.14; (95% CI 1.06-1.23); B 0.1341; SE 0.0368, p = 0.0002], BMI [OR 1.09; (95% CI 1.02-1.17); B 0.0880; SE 0.0351, p = 0.012] and previous history of GDM [OR 3.73; (95% CI 1.01-13.8); B 1.3162; SE 0.6669, p = 0.048] were independent predictors of GDM. Figure 1

illustrates the ROC curve of HbA1c for GDM. An area under the curve (AUC) of 0.79 [95% CI (0.72-0.86)] p < 0.0001) was observed. The cut-off value according to the ROC curve for GDM was HbA1c ≥ 5.1%, with a sensitivity of 70.8% and a specificity of 71.6%.

Clinical and laboratory data, including inflammatory markers and multivariate analysis according to the presence or absence of APOs There was no significant difference between the two groups in the levels of the evaluated cytokines, in APOs

Table 2. Previous clinical and obstetric history of the population according to OGTT Category

GDM

Normal OGTT

P value

Polycystic ovary syndrome

Yes No

21 57

26.9 73.1

39 59

39.8 60.2

0.073

Acanthosis

Yes No

50 28

64.1 35.9

27 71

27.6 72.4

< 0.0001

Smoking

Yes No

6 72

7.7 92.3

7 91

7.1 92.9

0.15

GDM

Yes No

13 65

16.7 83.3

6 92

6.1 93.9

0.025

Abortion

Yes No

21 57

26.9 73.1

25 73

25.5 74.5

0.83

Stillbirth

Yes No

3 75

3.8 96.2

2 96

2.0 98.0

0.39

Babies’ mal formation

Yes No

5 73

6.4 93.6

3 95

3.1 97.0

0.24

Polyhydramnios

Yes No

26 52

33.3 66.7

30 68

30.6 69.4

0.70

Multiple pregnancy

Yes No

0 78

0.0 100.0

4 94

4.1 95.9

0.094

Respiratory distress syndrome

Yes No

5 73

6.4 93.6

1 97

1.0 99.0

0.061

Preterm birth

Yes No

13 65

16.7 83.3

10 88

10.2 89.8

0.21

Neonatal hypoglycemia

Yes No

0 78

0.0 100.0

0 98

0.0 100.0

Icterus

Yes No

7 71

9.0 91.0

5 93

5.1 94.9

0.31

< 2,500g newborn

Yes No

6 72

7.7 92.3

7 91

7.1 92.9

0.89

> 4,000g newborn

Yes No

9 69

11.5 88.5

11 87

11.2 88.8

0.95

Pregnancy induced hypertension

Yes No

12 66

15.4 84.6

11 87

11.2 88.8

0.42

Newborn death

Yes No

3 75

3.8 96.2

0 98

0.0 100.0

0.085

Familial DM

Yes No

65 13

83.3 16.7

72 26

73.5 26.5

0.12

Variable

OGTT: oral glucose tolerance test; GDM: gestational diabetes mellitus; DM: diabetes mellitus. χ2 test or Fisher test.

Arch Endocrinol Metab. 2019;63/1

Placental weight and adverse fetal outcomes in gestational diabetes

and in placental weight (Tables 1 and 3). We observed a correlation between levels of TNF-alpha, maternal BMI and CRP with placental weight (rho = 0.188; p = 0.021, r = 0.186; p = 0.022, r = 0.176; p = 0.031, respectively). A correlation between CRP and HbA1c levels (rho = 0.167, p = 0.035), in the total sample was also noted. An association between blood glucose [93.2 (76.0-115.4) vs. 79.0 (71.0-88.3) mg/dl; p < 0.003] and CRP [0.86 (0.68-1.36) mg/dl; p < 0.01] levels with prematurity was found. A correlation between CRP and HbA1c levels (rho = 0.167, p = 0.035) in the total sample was also observed.

Multivariate logistic analyses were performed with 150 observations (loss of placental weight records n = 26) with APOs’ as dependent variable. The only significant independent variable was placental weight with an [OR 0.0014; (95% CI 1.001-1.007; B 1.004; SE 0.0040, p = 0.005]. Figure 2 illustrates the ROC curve of placental weight for the presence or absence of APOs. An AUC of 0.65 with a 95% CI of 0.55 to 0.75, (p = 0.003) was observed. The cut-off point according to the ROC curve was placental weight ≥ 610 grams, with a sensitivity of 63.0% and a specificity of 64.4%.

Table 3. Fetal demographic data according to OGTT GDM

Variable

Normal OGTT

p valuea

Median

IQR

Median

IQR

Newborn weight (grams)

3,195

2935-3555

3,275

2,993-3,564

0.36

Length (cm)

48.0

46.5-49.0

48.5

47.0-50.0

0.18

Head circumference (cm)

35.0

33.5-35.0

35.0

34.0-36.0

0.24

Thoracic circumference (cm)

33.0

32.0-34.0

33.2

32.0-34.0

0.96

Waist circumference (cm)

32.0

30.0-33.0

32.0

30.0-33.0

0.72

Apgar T1 score

8-9

0.68

Apgar T2 score

9-10

0.92

Apgar T5 score

10-10

0.52

Placental weight (grams)

600

500-684

580

518-713

0.65

IQR: interquartile range; GDM: gestational diabetes mellitus; OGTT: oral glucose tolerance test. a Mann-Whitney test.

1.0

0.8

0.6

0.6 Sensitivity

Sensitivity

1.0

0.4

0.4 AUC = 0,79 CI 95%: 0,72-0,86 p < 0.0001

0.2

0.0

0.0 0.0

0.2

0.4

0.6

Specificity

Figure 1. ROC curve for HbA1c as a predictor for GDM.

AUC = 0,65 CI 95%: 0,55-0,75 p = 0,003

0.8

1.0

0.0

0.2

0.4

0.6

0.8

1.0

Specificity

Figure 2. Receiver Operator Characteristics (ROC) curve for placental weight as a predictor of fetal adverse outcomes. Arch Endocrinol Metab. 2019;63/1

DISCUSSION No difference was found in serum levels of IL-6, TNF-alpha, CRP and placental weight in women with GDM compared to those from the CG, between 2428 gestation weeks. We found that values of HbA1C ≥ 5.1% at 24 to 28 weeks of gestation could be associated with GDM, however with high sensitivity and low specificity. A placental weight ≥ 610 grams was also found to be associated with the presence of APOs. Our prevalence of GDM was higher than the prevalence found in the Brazilian Study on Gestational Diabetes (BSGD) in the 1990s, which was 7.6% (2). This may be justified by the fact that our study was performed at a secondary level medical care service, focused on diabetes in pregnancy, and also by the increasing prevalence of overweight and obesity in Brazil in recent years. In 1999, around the time this study begun, the estimated prevalence of obesity in the Brazilian general population was of 32.0% (14) and has been steadily increasing ever since, reaching 53.8% in 2016 (15). It is possible that if these data were to be collected nowadays, the rates of GDM would be even greater. In our study, pregnant women with GDM were older, shorter, heavier, with higher blood pressure levels and shorter legs (16,17) as expected, since all these characteristics are risk factors for the development of GDM (18). Multivariate analysis for the prediction of GDM demonstrated that HbA1c, age, BMI and previous history of GDM were independently associated with GDM. The ROC curve indicated that values of HbA1C ≥ 5.1% at 24 to 28 gestation weeks are associated with GDM. Universal screening for diabetes in pregnancy is recommended by the International Association of the Diabetes and Pregnancy Study Groups (IADPSG) (3), the American Diabetes Association (ADA) (1) the World Health Organization (WHO) (19) and more recently by the Brazilian Diabetes Association (BDS), Brazilian Federation of Gynecologists and Obstetricians (Febrasgo), Pan American Health Organization (PAHO) and the Brazilian Ministry of Health at the first antenatal visit (20). However what should be the most appropriate test and glucose levels thresholds are still debated in many regions and countries around the world (21,22). This screening should be done with a fasting glycemia and a 75g OGTT at the first antenatal visit or at 24-28 gestation weeks, respectively (20). Arch Endocrinol Metab. 2019;63/1

The OGTT is time consuming, poorly tolerated by pregnant women, needs a previous patient preparation and presents issues with preanalytical stability and reproducibility (21,22). HbA1c, the most used measurement of chronic glycemia outside of pregnancy is easier to perform, does not need a previous patient preparation and is much less time consuming than the OGTT. However, the evaluation of HbA1c has its limitations such as: conditions that promote a reduction in the real value of HbA1c due to the reduction in the number of red blood cells, hemoglobin levels and hematocrit, conditions that increase the real value of HbA1c (21) and the period of pregnancy in which it is performed, being lower in the first trimester and around 0.5% lower at the 14th week (22). However it is important to emphasize that the accuracy of HbA1c as a screening tool in pregnancy has been studied in recent decades and the results are inconsistent (22-29). Thus, it would be necessary to establish reference values according to different ethnic populations before recommending the universal use of HbA1c for the screening of GDM (28). Khalafallah and cols. (21) aiming to compare HbA1c levels with glucose values on the 75g OGTT for the screening and diagnosis of GDM, found a HbA1c cut-off point of 5.4% associated with GDM, with a negative predictive value of 91.0% and a specificity of 95.0%. Similar results were also obtained when a cut-off point of HbA1c > 5.1% was used, with a sensitivity of 55% and a specificity of 80.0%, which was also the cut-off point we found (21). In our study, the cutoff point of HbA1c > 5.1% had higher sensitivity (70.9%) and lower specificity (71.6%) than this study. Studies with small number of patients revealed an increase in inflammatory markers such as TNF-alpha (30) and CRP (31) in women with GDM which was not found in our study, maybe because the prevalence of obesity was small among those patients. In a study conducted in Austria, evaluating women with and without GDM an increase in CRP levels in pregnant women with GDM was found only at 37th-38th weeks gestation but not at 24th-28th weeks (32), the time frame we conducted our study. Cytokine levels fluctuate during the gestational trimesters, being the first and third trimesters characterized by a pro-inflammatory state and the second trimester by an anti-inflammatory state. There was a correlation between TNF-alpha values, maternal BMI and CRP levels with placental weight 27

Placental weight and adverse fetal outcomes in gestational diabetes

in our study. This correlation, although weak (rho < 0.30), can point to a relationship between BMI with TNF-alpha and CRP that can generate damage to the placenta due to their inflammatory actions independent of glycemic levels. Retnakaran and cols. (31) performed a study with 180 healthy pregnant women who underwent an OGTT at the end of the 2nd and beginning of the 3rd trimester and found higher CRP levels in patients with normal OGTT and overweight and a correlation between CRP and prepregnancy BMI. In our study, placental weight was an independent predictor for the presence of any of the following APOs (LGA, macrosomia, preterm birth and need for neonatal ICU admission) with a cut-off point of ≥ 610g. Studies performed with pregnant women having GDM indicate that they could have greater placental weight in relation to pregnant women having GDM (33,34), which we did not find in our study. In a study performed in Tanzania (35), in Sub-Saharan Africa, with 6,579 pregnant women, younger and with lower BMI than those patients enrolled in our study, low placental weight was associated with an increased risk of APOs. Possibly, a poorer nutritional status and the presence of infectious diseases in that population could have contributed for these results. Disruptions in placental growth can have long-term consequences on perinatal and childhood health and have been associated with adverse obstetric outcomes (intrauterine growth restriction and preeclampsia, maternal disease), perinatal mortality and morbidity, as well as impairment in childhood growth and development (10,35). A Romanian study (33), with pregnant women between 24-28 weeks of gestation showed that the placentas of six out of 13 GDM patients presented micro and macroscopic alterations. Macroscopically, the most frequent pathological changes found were larger placental size, volume and weight. It was also observed that, in the total sample, the presence of preterm birth was related to higher levels of fasting glycemia and CRP. The Camden Study conducted in USA, including 520 pregnant women with normal OGTT, showed that during pregnancy, higher levels of CRP were related to APOs, such as prematurity, only in lean women (BMI < 25) (36). Some limitations of this study must be addressed such as the small number of patients and also the pregestational weight that was self-reported by the patients, which could generate some “bias”. We also correlated the presence of one or more APOs among 28

those that were evaluated, with placental weight; therefore, we do not know which outcome had the greatest statistical strength this correlation. In conclusion, in our study, some predictors of GDM are modifiable such as high BMIs and HbA1c levels. HbA1c values ≥ 5.1% at 24-28 weeks gestation were found to be associated with GDM, but we cannot hypothesize that this test could be used as a tool for GDM screening or diagnosis, because in our study, the sensitivity and specificity were low. A placental weight ≥ 610 grams was found to be associated with APOs, and consequently its weight should be monitored through ultrasound evaluation during the whole pregnancy as part of prenatal care routine to stratify risks for APOs. Further prospective studies with larger number of participants are necessary to confirm if this placental cutoff weight is associated to APOs for all pregnant women or just for those with GDM. Acknowledgements: we thank all members of our work teams in our units that enabled us to dedicate ourselves to this research. Funding source: this research was supported by “Fundação do Amparo à Pesquisa do Estado do Rio de Janeiro” (Faperj). Disclosure: no potential conflict of interest relevant to this article was reported.

REFERENCES 1. American Diabetes Association. Classification and Diagnosis of Diabetes. Standards of medical Care in Diabetes – 2017. Diabetes Care. 2017;40(Suppl 1):S18. 2. Schmidt MI, Matos MC, Reichelt AJ, Forti AC, de Lima L, Duncan BB. Prevalence of gestational diabetes mellitus – do the new WHO criteria make a difference? Brazilian Gestational Diabetes Study Group. Diabet Med. 2000;17(5):376-80. 3. International Association of Diabetes and Pregnancy Study Groups Consensus Panel; Metzger BE, Gabbe SG, Persson B, Buchanan TA, Catalano PA, Damm P, et al. International Association of Diabetes and Pregnancy Study Groups recommendations on the diagnosis and classification of hyperglycemia in pregnancy. Diabetes Care. 2010;33(3):676-82. 4. Trujillo J, Vigo A, Duncan BB, Falavigna M, Wendland EM, Campos MA, et al. Impact of the International Association of Diabetes and Pregnancy Study Groups criteria for gestational diabetes. Diabetes Res Clin Pract. 2015;108(2):288-95. 5. Koivusalo SB, Rönö K, Klemetti MM, Roine RP, Lindström J, Erkkola M, et al. Gestational Diabetes Mellitus Can Be Prevented by Lifestyle Intervention: The Finnish Gestational Diabetes Prevention Study (RADIEL): A Randomized Controlled Trial. Diabetes Care. 2016;39(1):24-30. 6. Clark CM Jr, Qiu C, Amerman B, Porter B, Fineberg N, Aldasouqi S, et al. Gestational diabetes: should it be added to the syndrome of insulin resistance? Diabetes Care. 1997;20(5):867-71. 7. Negrato CA, Jovanovic L, Tambascia MA, Calderon Ide M, Geloneze B, Dias A, et al. Mild gestational hyperglycaemia as a risk Arch Endocrinol Metab. 2019;63/1

Placental weight and adverse fetal outcomes in gestational diabetes

factor for metabolic syndrome in pregnancy and adverse prenatal outcomes. Diabetes Metab Res Rev. 2008;24:324-30.

ing diabetes and identifies women at increased risk of adverse pregnancy outcomes. Diabetes Care. 2014;37(11):2953-9.

8. American Diabetes Association. Management of diabetes in pregnancy. Sec.12. In Standards of Medical Care in Diabetes-2016. Diabetes Care. 2016;39(Suppl 1):S94-8.

23. Agarwal MM, Hughes PF, Punnose J, Ezimokhai M,Thomas L. Gestational diabetes screening of a multiethnic, high-risk population using glycated proteins. Diabetes Res Clin Pract. 2001;51(1):67-73.

24. Agarwal MM, Dhatt GS, Punnose J, Koster G. Gestational diabetes: a reappraisal of HBA1c as a screening test. Acta Obstet Gynecol Scand. 2005;84(12):1159-63.

Rudge MV, Lima CP, Damasceno DC, Sinzato YK, Napoli G, Rudge CV, et al. Histopathological placental lesions in mild gestational hyperglycemic and diabetic women. Diabetol Metab Syndr. 2011;10;3(1):19.

10. McNamara H, Hutcheon JA, Platt RW, Benjamin A, Kramer MS. Risk factors for high and low placental weight. Paediatr Perinat Epidemiol. 2014;28(2):97-105.

25. Pollak A, Brehm R, Havelec L, Lubec G, Malamitsi-Puchner A, Simbrunner G, et al. Total glycosylated hemoglobin in mothers of large-for-gestational-age infants: a postpartum test for undetected maternal diabetes? Biol Neonate. 1981;40(3-4):129-35.

11. Desoye G, Hauguel-de Mouzon S. The human placenta in gestational diabetes mellitus. The insulin and cytokine network. Diabetes Care. 2007;30 Suppl 2:S120-6.

26. Griffiths RJ, Vinall PS, Stickland MH, Wales JK. Haemoglobin A1c levels in normal and diabetic pregnancies. Eur J Obstet Gynecol Reprod Biol. 1987;24(3):195-200.

12. Carpenter MW, Coustan DR. Criteria for screening tests for gestational diabetes. Am J Obstet Gynecol. 1982;144(7):768-73.

27. Moses RG. HbA1c and the diagnosis of gestational diabetes mellitus – a test whose time has not yet come. Diabetes Res Clin Pract. 2012;98:3-4.

13. Lubchenco LO, Hansman C, Boyd E. Intrauterine growth in length and head circumference as estimated from live births at gestational ages from 26 to 42 weeks. Pediatrics. 1966;37(3): 403-8. 14. Sociedade Brasileira de Cardiologia. Exercício anti-sedentarismo/ obesidade. 1999. Available at: http://www.cardiol.br/exerc.htm. Acessed in: 13 Feb 2017].

28. Lippi G, Targher G. Glycated hemoglobin (HbA1c): old dogmas, a new perspective? Clin Chem Lab Med. 2010;48(5):609-14.

15. Vigitel .2016. Available at: https://www.endocrino.org.br/media/ uploads/PDFs/vigitel/pdf. Acessed in: 23 Apr 2017).

29. Netto AP. Grupo Interdisciplinar de Padronização da Hemoglobina Glicada in Atualização sobre Hemoglobina Glicada para avaliação do controle glicêmico e para o diagnóstico do Diabetes Mellitus: aspectos clínicos e laboratoriais. J Bras Patol Med Lab. 2009;45(1):31-48.

16. Moses RG, Mackay MT. Gestational Diabetes: is there a relationship between leg length and glucose tolerance? Diabetes Care. 2004;27(5):1033-5.

30. Winkler G, Cseh K, Baranyi E, Melczer Z, Speer G, Hajós P, et al. Tumor necrosis factor system in insulin resistance in gestational diabetes. Diabetes Res Clin Pract. 2002;56(2):93-9.

17. Ma RM, Lao TT, Ma CL, Liao SJ, Lu YF, Du MY, et al. Relationship between leg length and gestational diabetes mellitus in Chinese pregnant women. Diabetes Care. 2007;30(11):2960-1.

31. Retnakaran R, Hanley AJ, Raif N, Connelly PW, Sermer M, Zinman B. C-Reactive Protein and Gestational Diabetes: The Central Role of Maternal Obesity. J Clin Endocrinol Metab. 2003;88(8):3507-12.

18. Ben-Haroush A, Yogev Y, Hod M. Epidemiology of gestational diabetes mellitus and its association with type 2 diabetes. Diabet Med. 2004;21(2):103-13.

32. Leipold H1, Worda C, Gruber CJ, Prikoszovich T, Wagner O, Kautzky-Willer A. Gestational diabetes mellitus is associated with increased C-reactive protein concentrations in the third but not second trimester. Eur J Clin Invest. 2005;35(12):752-7.

19. World Health Organization. Diagnostic criteria and classification of hyperglycaemia first detected in pregnancy. 2013. Available at: http://www.who.int/diabetes/publications/Hyperglycaemia_In_ Pregnancy/en/. Accessed 23 May 2016. 20. Organização Pan-Americana de Saúde. Ministério da Saúde. Federação Brasileira das Associações de Ginecologia e Obstetrícia. Sociedade Brasileira de diabetes. Rastreamento e diagnóstico de diabetes mellitus gestacional no Brasil. Brasília, DF: OPAS; 2016. 21. Khalafallah A, Phuah E, Al-Barazan AM, Nikakis I, Radford A, Clarkson W, et al. Glycosylated haemoglobin for screening and diagnosis of gestational diabetes mellitus. BMJ Open. 2016;6(4):e011059.

34. Taricco, E, Radaelli, T, Nobile de Santis, MS, Cetin, I. Foetal and placental weights in relation to maternal characteristics in Gestational Diabetes. Placenta. 2003;24(4):343-7. 35. McDonald CR, Darling AM, Liu E, Tran V, Cabrera A, Aboud S, et al. Angiogenic proteins, placental weight and perinatal outcomes among pregnant women in Tanzania. PLoS One. 2016;9;11(12):e0167716. 36. Scholl TO, Chen X, Goldberg GS, Khusial R, Stein P. Maternal Diet, C-Reactive Protein, and the Outcome of Pregnancy. J Am Coll Nutr. 2011;30(4):233-40.

22. Hughes RC, Moore MP, Gullam JE, Mohamed K, Rowan J. An early pregnancy HbA1c ≥5.9% (41 mmol/mol) is optimal for detect-

33. Edu A, Teodorescu C, Dobjanschi CG, Socol ZZ, Teodorescu V, Matei A, et al. Placenta changes in pregnancy with gestational diabetes. Rom J Morphol Embryol. 2016;57(2):507-12.

Arch Endocrinol Metab. 2019;63/1

original article

Anthropometric measurements as a potential non-invasive alternative for the diagnosis of metabolic syndrome in adolescents Departamento de Educação Física, Universidade da Região de Joinville (Univille), Joinville, SC, Brasil 2 Population Health Intervention Research Unit, School of Public Health, University of Alberta, Edmonton, Alberta, Canada 3 Programa de Pós-Graduação em Saúde e Meio Ambiente, Universidade da Região de Joinville (Univille), Joinville, SC, Brasil 4 Departamento de Ciências Biológicas, Universidade da Região de Joinville (Univille), Joinville, SC, Brasil 5 Departamento de Nutrição, Faculdade de Saúde Pública, Universidade de São Paulo (FSPUSP), São Paulo, SP, Brasil 1

Correspondence to: Marco Fabio Mastroeni Programa de Pós-Graduação em Saúde e Meio Ambiente, Universidade da Região de Joinville Rua Paulo Malschitzki, 10 89219-710 – Joinville, SC, Brasil marco.mastroeni@univille.br Received on Dec/19/2017 Accepted on Nov/14/2018 DOI: 10.20945/2359-3997000000100

Silmara Salete de Barros Silva Mastroeni1,2, Marco Fabio Mastroeni2,3, John Paul Ekwaru2, Solmaz Setayeshgar2, Paul J. Veugelers2, Muryel de Carvalho Gonçalves4, Patrícia Helen de Carvalho Rondó5

ABSTRACT Objective: To identify which anthropometric measurement would be the best predictor of metabolic syndrome (MetS) in Brazilian adolescents. Subjects and methods: Cross-sectional study conducted on 222 adolescents (15-17 years) from a city in southern Brazil. Anthropometric, physical activity, blood pressure and biochemical parameters were investigated. MetS criteria were transformed into a continuous variable (MetS score). Linear regression analyses were performed to assess the associations of BMI, hip circumference, neck circumference (NC), triceps skinfold, subscapular skinfold and body fat percentage with MetS score. ROC curves were constructed to determine the cutoff for each anthropometric measurement. Results: The prevalence of MetS was 7.2%. Each anthropometric measurement was significantly (p < 0.001) associated with MetS score. After adjusting for potential confounding variables (age, sex, physical activity, and maternal education), the standardized coefficients of NC and body fat percentage appeared to have the strongest association (beta = 0.69 standard deviation) with MetS score. The regression of BMI provided the best model fit (adjusted R2 = 0.31). BMI predicted MetS with high sensitivity (100.0%) and specificity (86.4%). Conclusions: Our results suggest that BMI and NC are effective screening tools for MetS in adolescents. The early diagnosis of MetS combined with targeted lifestyle interventions in adolescence may help reduce the burden of cardiovascular diseases and diabetes in adulthood. Arch Endocrinol Metab. 2019;63(1):30-9 Keywords Adolescents; metabolic syndrome; anthropometric measurements; neck circumference; ROC curve

INTRODUCTION

he prevalence of overweight and of its comorbidities have increased in adolescents and have reached epidemic proportions in both developed and developing countries (1). The increase in the prevalence of overweight is higher in developing than in developed countries, with reported increases of 65% and 48% between 1990 and 2010, respectively (1). In 2015, 23.7% of 13-17-year-old Brazilian adolescents were overweight (including obese) and 7.8% were obese (2). The rise in the prevalence of childhood overweight will result in significant health problems and financial burdens in the future, therefore warranting comprehensive prevention efforts (3). One of the consequences of being obese or overweight is the risk of developing metabolic 30

syndrome (MetS) (4), a complex condition of multiple, interrelated risk factors for cardiovascular diseases (CVDs) and diabetes (5). These risk factors include elevated fasting glucose and triglyceride levels, high blood pressure, low high-density lipoprotein cholesterol (HDL-c) levels, and central adiposity (5). According to the International Diabetes Federation (IDF), MetS is defined as the presence of elevated waist circumference plus two of the following four criteria: high blood pressure, elevated triglyceride and fasting plasma glucose levels, and decreased HDL-c levels (6). The prevalence of MetS is increasing worldwide due to the rise in obesity and poor lifestyle (5). Excess body weight is the primary cause of MetS due to the increase in insulin production, as well as the likelihood of developing insulin resistance, a central pathophysiological factor in Arch Endocrinol Metab. 2019;63/1

Anthropometric measurements and metabolic syndrome in adolescents

Arch Endocrinol Metab. 2019;63/1

subscapular skinfold and body fat percentage (BF%)) in the same population for the identification of MetS in Brazilian healthy adolescents. Since the diagnosis of MetS is invasive, expensive, and labor intensive on the part of health professionals, noninvasive and low-cost methods are needed, particularly in low-resource settings. The aim of this study was to evaluate BMI, hip circumference, NC, triceps skinfold, subscapular skinfold and BF% as potential alternatives for the diagnosis of MetS in adolescents.

SUBJECTS AND METHODS Subjects and study design This was a cross-sectional study conducted in two phases on 15- to 17-year-old high school students from Joinville, a city of about 500,000 inhabitants, Santa Catarina, Brazil. Details of the recruitment process have been described previously (32). In the first phase, 2,195 students completed a short survey on socioeconomic and demographic characteristics. An informed consent form was handed out to obtain agreement for participation from their parents/ guardians and 1,104 (50.3%) students returned the signed consent form (32). All of the 1,104 students were invited to participate in the second phase. They were contacted by phone and by a personal visit in the residence and were informed about the day and place of data collection. At the end of the study, 222 students participated in the data collection (32). Assessments in this phase included anthropometric measurements (weight, height, waist and hip circumferences, NC, triceps and subscapular skinfold thickness, and BF%), physical activity, biochemical analyses, and blood pressure measurement. Blood samples were drawn from each participant to assess the levels of fasting insulin, fasting glucose, total cholesterol, low-density lipoprotein cholesterol (LDL-c), HDL-c, and triglycerides. The study was carried out in accordance with the Declaration of Helsinki and the Research Ethics Committee of the University of Joinville Region approved this study (Approval No. 005/2007).

Data collection The anthropometric measurements were made in the morning after an overnight fast, with the subjects 31

the development of MetS (7,8). Insulin resistance has multiple metabolic effects in the organism, including the increased synthesis of very-low-density lipoprotein cholesterol and cholesterol, resistance to the action of insulin on lipoprotein lipase in peripheral tissues, degradation of HDL-c, enhanced sympathetic activity, and increased formation of plaque which is associated with high blood pressure (8,9). Another important point regarding the adipose tissue is the production of leptin, adiponectin, and resistin, as well as interleukin-6, tumor necrosis factor-alpha and plasminogen activator inhibitor-1 (8,9). All these cytokines are involved in the inflammatory process (8,9), indicating that the pathological consequences of excess body fat involve different tissues and organs (8,9). In the last decade, MetS has been identified in younger populations (4,10-12). This is particularly concerning given the potential earlier manifestations of MetS outcomes, such as type 2 diabetes and CVDs (4,13). The early identification of MetS would permit early preventive actions (14) designed to reduce the burden of type 2 diabetes and CVDs later in life (15). However, there is no universal or uniform definition of MetS in younger populations (12). Since the prevalence of MetS in children and adolescents shows significant disparities among studies and the use of multiple logistic regression analysis provided controversial results, some authors (12) suggested the use of a continuous variable of MetS (MetS score) to overcome these limitations (12). In recent years, several authors have suggested the use of neck circumference (NC) to identify MetS in adult populations (16-24). Other studies proposed the use of NC (25-27), BMI (15,25,28-30), waist circumference (11,12,15,26,29), waist-hip ratio (25), waist-height ratio (29), wrist circumference (26), skinfold thickness (31), conicity index (29), and fat and lean body mass index (BMI) (30) to predict MetS in adolescents. More recently, a national study assessed the prevalence of MetS and its components in a large sample of Brazilian adolescents (The ERICA Study) (11). Another national study the authors evaluated the validity of continuous metabolic syndrome score for predicting MetS and to determine the cutoff values in a representative sample of Iranian children and adolescents (The CASPIAN-V Study) (12). However, to the best of our knowledge, no study simultaneously compared six different anthropometric measurements (BMI, hip circumference, NC, triceps skinfold,

Anthropometric measurements and metabolic syndrome in adolescents

wearing light clothing and no shoes. The adolescents were weighed on a Filizola® digital scale (Curitiba, PR, Brazil; capacity of 180 kg) to the nearest 0.1 kg. Height was measured with a Cardiomed® stadiometer (Curitiba, PR, Brazil; 200 cm) to the nearest 0.1 cm. Waist circumference was measured midway between the lowest rib and the top of the iliac crest during the mid-expiratory phase. Hip circumference was measured with the tape at the widest portion of the buttocks. Neck circumference was measured horizontally above the cricothyroid cartilage with the tape not compressing the skin (33). All circumferences were measured with a flexible tape (Cardiomed®; 150 cm) to the nearest 0.1 cm. A Cescorf® skinfold caliper (Porto Alegre, RS, Brazil) was used to measure triceps and subscapular skinfold thickness at a pressure of 10 g/mm2 over the contact surface area to the nearest 0.1 mm. Triceps skinfold thickness was measured on the back of the arm and at a point midway between the acromion and olecranon process. With the arm hanging loosely, subscapular skinfold thickness was measured 2 cm below the inferior angle of the right scapula. All anthropometric variables were measured three times and the arithmetic mean of these measurements was used as the final result. Body mass was evaluated by calculating the BMI [weight (kg)/height (m2)] following the classification of the World Health Organization for the calculation of BMI according to age and sex (34). Body fat percentage was obtained by foot-to-foot bioelectrical impedance analysis using a BIA 310e® Bioimpedance Analyzer (Biodynamics Corporation, Shoreline, WA, USA). The diastolic (DBP) and systolic blood pressure (SBP) was measured using the HDI/Pulse WaveTM CR-2000 Research Cardiovascular Profiling System (Hypertension Diagnostic, Inc., Eagan, MN, USA), with the adolescent lying on a gurney after a 10-min resting period. Information about maternal education and physical activity was collected by interview. Physical activity was classified using the International Physical Activity Questionnaire (IPAQ) (35).

Biochemical analysis Approximately 15 ml of venous blood was drawn from the antecubital vein of each subject. All blood samples were collected in the morning after an overnight fast. Within 30 min, the remaining blood serum was separated by centrifugation at 3,500 rpm for 10 min at 32

4 °C, immediately aliquoted, and frozen at -70 °C until the time of analysis. Fasting glucose, LDL-c, and HDL-c were analyzed by colorimetric enzymatic methods on the Bayer ADVIA 1650 automated analyzer using the GLUO, D-LDL and D-HDL kits, respectively (Siemens Diagnostics®, Tarrytown, NY, USA). Total cholesterol and triglycerides were measured with the Bayer ADVIA Centaur automated analyzer using the Cholesterol and Triglycerides Liquiform kits, respectively (Labtest Diagnostica®, Vista Alegre, MG, Brazil). Insulin was assayed by a chemoluminescence method on the Bayer ADVIA Centaur automated analyzer with IRI Bayer ADVIA kit, analytical sensitivity of 0.5 μIU/ ml (Siemens Diagnostics®). The homeostatic model assessment for insulin resistance (HOMA-IR) index was calculated using the equation [HOMA-IR = fasting insulin [(μIU/ml) × fasting glucose (mmol/l)/22.5]. All measurements were performed in a laboratory accredited by the Brazilian Society of Clinical Analysis.

Definition of metabolic syndrome and metabolic syndrome score MetS was defined using age- and sex-specific cutoff points for each component, according to Jollife and Janssen (6). Each MetS component growth curve was linked to the corresponding Adult Treatment Panel and the IDF cut point (6) In the present study, MetS was defined according to the IDF criteria as increased waist circumference and two of the following four criteria: elevated blood pressure, triglyceride and fasting plasma glucose or decreased HDL-c (6). For the purpose of the present study, a MetS score was created using the sex- and age- specific Z-score cutoff points for the following variables: waist circumference, SBP, DBP, triglycerides, HDL-c, and HOMA-IR according to Eisenmann (36). The MetS score was chosen due to the lack of a standard definition of MetS for children or adolescents and because its prevalence in the population is still low (36). Since HDL-c concentration is inversely related to metabolic risk, the values of this variable were multiplied by -1. A higher score indicates a less favorable MetS profile (36).

Statistical analysis The Statistical Package for the Social Sciences (SPSS), version 22.0, was used for statistical analysis. Central tendency and absolute and relative frequencies were estimated as descriptive statistics. Continuous variables Arch Endocrinol Metab. 2019;63/1

are reported as median and interquartile range. The chi-square test was used to compare the prevalence of categorical variables according to the presence of MetS. The Mann-Whitney U test was applied to compare the medians of general characteristics according to the presence of MetS. Spearman correlation coefficients were calculated to evaluate the association of the anthropometric parameters with MetS score, MetS components and HOMA-IR. Multiple linear regression analysis was applied to analyze the relationship between the anthropometric parameters and MetS score. Since the anthropometric parameters showed skewed distributions, they were log-transformed. Multivariable linear regression models were developed adjusting for age, sex, physical activity and maternal education. The standardized regression coefficients from these models were used to compare the relative effects of the anthropometric measurements on MetS score, regardless of the anthropometric measurement units. We also carried out analyses to determine cutoff values of BMI, hip circumference, NC, triceps and subscapular skinfolds, and BF% to predict MetS. These cutoffs were determined by constructing receiver operating characteristic (ROC) curves for girls and boys separately. The area under the curve (AUC) was used as a measure of the diagnostic power of the test, considering the anthropometric measurements investigated. The greater the AUC, the greater the discriminatory power of the anthropometric measurement. Subsequently, the sensitivity (proportion of individuals with a diagnosis of MetS who were identified as having MetS by the anthropometric measure) and specificity (proportion of individuals without MetS who were identified as not having MetS by the anthropometric measure) were determined. The outcome, MetS score, was analyzed separately for each anthropometric parameter (BMI, hip circumference, NC, triceps and subscapular skinfolds, and BF%). Statistical significance was defined as p < 0.05.

RESULTS All analyses were conducted in the second phase of the study (n = 222), corresponding to individuals who returned the consent form of the first phase (n = 1,104). The Mann-Whitney U test showed no significant difference in maternal education or BMI (p = 0.204 and p = 0.252, respectively) between adolescents enrolled in the first and second phases. Excess body weight Arch Endocrinol Metab. 2019;63/1

(overweight and obesity) was observed in 20.3% of the participants and 7.2% had MetS. Table 1 shows the general characteristics of the adolescents according to the presence of MetS. All anthropometric and metabolic parameters were significantly (p < 0.05) higher in adolescents with MetS, except for HDL-c. No significant differences in age, sex, maternal education or physical activity were observed between adolescents with and without MetS (Table 1). The Spearman correlation coefficients of all anthropometric parameters were positively correlated (p < 0.001) with MetS score and HOMA-IR. The correlation coefficients of MetS score (rho = 0.46), triglycerides (rho = 0.21), waist circumference (rho = 0.81) and HOMA-IR (rho = 0.39) with BMI were higher when compared to the other anthropometric parameters (hip circumference, NC, triceps and subscapular skinfolds, and BF%). However, SBP (rho = 0.41) and HDL-c (rho = -0.39) showed a higher correlation with NC than with BMI, hip circumference, triceps and subscapular skinfolds, or BF%. The results of linear regression analysis are summarized in Table 2. All anthropometric variables were significantly (p < 0.001) associated with MetS score in both unadjusted and adjusted analysis. After adjusting each model for potential confounding variables (age, sex, physical activity, and maternal education), the standardized coefficients of log transformed values of NC and BF% indicated similar associations with MetS score. For each standard deviation (SD) increase in log NC or in log BF%, the MetS score increased by 0.69 SD. The proportion of variance explained (adjusted R2) was higher for the regression analysis that included BMI when compared to any of the other anthropometric measurements (Table 2), i.e., BMI, age, sex, physical activity, and maternal education together explained 31% of the variation in MetS score. Table 3 and Figure 1 show the AUC for the anthropometric variables associated with metabolic syndrome according to sex. Higher AUC values were observed for boys (95.4% to 100.0%) when compared to girls (87.4% to 94.1%) and all differences in AUC were statistically significant (p < 0.001). Hip circumference and BMI showed the highest AUC for boys and girls, respectively. The optimal cutoffs, sensitivity and specificity of the anthropometric variables related to increased MetS risk are shown in Table 4. Except for triceps skinfold and BF%, the other cutoffs were higher in boys than in girls. High sensitivity (100.0%) and specificity (> 70.0%) were 33

Anthropometric measurements and metabolic syndrome in adolescents

Table 1. Socio-demographic and biochemical characteristics of Brazilian adolescents according to the presence of metabolic syndrome Metabolic syndrome* (n = 222)

Variable

Absent (n = 206)

Present (n = 16)

16.0 (1.0)

0.699†

125 (60.7%)

10 (62.5%)

0.889‡

Maternal education (years)

8.0 (6.0)

7.0 (7.0)

0.302†

Physical activity (min/week)

2,160.0 (3,441.5)

2,641.0 (3,771.8)

0.647†

BMI (kg/m )

21.0 (3.6)

30.2 (8.3)

< 0.001†

Waist circumference (cm)

69.7 (8.7)

93.6 (18.3)

< 0.001†

Hip circumference (cm)

94.6 (8.2)

112.0 (15.0)

< 0.001†

Neck circumference (cm)

32.5 (5.0)

36.1 (5.7)

< 0.001†

Triceps skinfold (mm)

13.1 (10.1)

30.2 (9.2)

< 0.001†

Subscapular skinfold (mm)

11.3 (6.7)

33.7 (15.8)

< 0.001†

Body fat percentage (%)

18.0 (12.7)

27.7 (5.9)

< 0.001†

Systolic blood pressure (mmHg)

116.0 (13.0)

124.5 (14.0)

0.002

Diastolic blood pressure (mmHg)

61.0 (8.0)

66.0 (13.0)

0.001

HDL-c (mg/dL)

62.0 (15.3)

54.5 (17.5)

0.080

Triglycerides (mg/dl)

82.0 (40.3)

107.0 (62.3)

0.011

Fasting glucose (mg/dl)

102.0 (13.0)

106.5 (9.3)

0.008

Insulin (mIU/l)

9.1 (6.8)

16.6 (18.0)

< 0.001†

HOMA-IR

2.3 (1.8)

4.5 (5.5)

< 0.001†

Age (years) Girls (%)

BMI: body mass index; HDL-c: high-density lipoprotein cholesterol; HOMA-IR: homeostasis model assessment-insulin resistance. *

Values were expressed as the median (interquartile range).

†

Mann-Whitney U test.

‡

Chi-square test.

Table 2. Association between log transformed values of the anthropometric measurements and metabolic syndrome score among Brazilian adolescents Standardized coefficient*

95% CI

Adjusted R2†

BMI

0.57

0.06

0.45-0.69

< 0.001

0.32

Hip circumference

0.52

0.06

0.40-0.64

< 0.001

0.27

Neck circumference

0.35

0.06

0.23-0.47

< 0.001

0.12

Triceps skinfold

0.40

0.06

0.28-0.52

< 0.001

0.15

Subscapular skinfold

0.51

0.06

0.39-0.63

< 0.001

0.25

Body fat percentage

0.33

0.07

0.18-0.46

< 0.001

0.10

BMI

0.57

0.06

0.45-0.69

< 0.001

0.31

Hip circumference

0.51

0.06

0.39-0.63

< 0.001

0.25

Neck circumference

0.69

0.09

0.51-0.87

< 0.001

0.22

Triceps skinfold

0.56

0.08

0.40-0.72

< 0.001

0.21

Subscapular skinfold

0.53

0.06

0.41-0.65

< 0.001

0.26

Body fat percentage

0.69

0.09

0.51-0.87

< 0.001

0.21

Unadjusted analysis

Adjusted analysis

‡

BMI: body mass index; SE: standard error of the mean; CI: confidence interval. *

Standardized regression coefficients to compare the relative effects of the anthropometric measurements on MetS score, regardless of the anthropometric measurement unit.

Adjusted R2: proportion of variance explained including anthropometric measurement and confounders (age, sex, physical activity, and maternal education) as independent variables, and MetS score as the dependent variable. †

‡

Each model was adjusted for age, sex, physical activity, and maternal education.

Arch Endocrinol Metab. 2019;63/1

Anthropometric measurements and metabolic syndrome in adolescents

Table 3. Area under the curve of the anthropometric measurements in the assessment of metabolic syndrome among Brazilian adolescents Boys (n = 87)

Girls (n = 135)

Both (n = 222)

AUC (95% CI)

99.5 (98.3-100.0)

94.1 (89.8-98.4)

96.2 (93.5-98.9)

100.0 (100.0-100.0)

91.3 (85.2-97.5)

95.0 (91.2-98.7)

Variable BMI (kg/m ) 2

Hip circumference (cm) Neck circumference (cm)

95.4 (88.4-100.0)

93.8 (89.1-98.5)

82.8 (73.6-92.0)

Triceps skinfold (mm)

99.6 (98.5-100.0)

90.4 (80.8-100.0)

94.3 (89.6-99.0)

Subscapular skinfold (mm)

99.2 (97.3-100.0)

90.5 (82.3-98.7)

94.8 (90.5-99.1)

Body fat percentage (%)

99.2 (97.3-100.0)

87.4 (79.4-95.4)

89.2 (82.7-95.7)

1.0

0.8

0.6

0.4

a) Girls Source of the curve Body mass index Hip circumference Neck circumference Triceps skinfold Subscapular skinfold Body fat percentage Reference line

0.2

0.0

Sensitivity

BMI: body mass index; AUC: area under the curve; CI: confidence interval.

0.0

0.2

0.4 0.6 1 - Specificity

0.4

b) Boys Source of the curve Body mass index Hip circumference Neck circumference Triceps skinfold Subscapular skinfold Body fat percentage Reference line

0.2

0.8

1.0

0.0

0.2

0.4 0.6 1 - Specificity

0.8

1.0

0.8

0.4

c) Girls and boys Source of the curve Body mass index Hip circumference Neck circumference Triceps skinfold Subscapular skinfold Body fat percentage Rererence line

0.2

0.0

0.2

0.4 0.6 1 - Specificity

0.8

1.0

Figure 1. Receiver operating characteristics (ROC) curves for the prediction of metabolic syndrome using anthropometric measurements in adolescents. a) Girls. b) Boys. c) Girls and boys. Arch Endocrinol Metab. 2019;63/1

Sensitivity

0.6

Anthropometric measurements and metabolic syndrome in adolescents

Table 4. Optimal cutoff, sensitivity and specificity of the anthropometric measurements for metabolic syndrome among Brazilian adolescents according to sex Boys (n = 87) Variable

Cutoff

Girls (n = 135)

Sensitivity (95% CI)

Specificity (95% CI)

Cutoff

Both (n = 222)

Sensitivity (95% CI)

Specificity (95% CI)

Cutoff

Sensitivity (95% CI)

Specificity (95% CI)

BMI (kg/m2)

27.2

100.0 (61.0-100.0)

97.5 (91.4-99.3)

24.0

100.0 (72.3-100.0)

84.8 (77.5-90.0)

24.1

100.0 (80.6-100.0)

86.4 (81.1-90.4)

HC (cm)

106.9

100.0 (61.0-100.0)

100.0 (95.5-100.0)

99.4

100.0 (72.3-100.0)

75.0 (67.0-82.0)

99.5

100.0 (80.6-100.0)

77.7 (71.5-82.8)

NC (cm)

36.4

100.0 (61.0-100.0)

76.5 (66.3-84.4)

32.7

100.0 (72.3-100.0)

83.1 (75.5-88.7)

32.7

100.0 (80.6-100.0)

51.5 (44.4-58.0)

TS (mm)

20.8

100.0 (61.0-100.0)

97.5 (91.4-99.3)

25.0

90.0 (59.6-98.2)

88.7 (82.1-93.2)

21.0

93.8 (71.7-98.9)

83.8 (78.4-88.4)

SS (mm)

22.9

100.0 (61.0-100.0)

95.0 (88.0-98.1)

18.2

90.0 (59.6-98.2)

79.0 (71.3-85.4)

18.2

93.8 (71.7-98.9)

82.8 (77.3-87.5)

BF (%)

18.0

100.0 (61.0-100.0)

95.0 (88.0-98.1)

24.2

100.0 (72.3-100.0)

70.2 (63.6-79.1)

23.6

100.0 (80.6-100.0)

80.4 (74.5-85.3)

BMI: body mass index; HC: hip circumference; NC: neck circumference; TS: triceps skinfold; SS: subscapular skinfold; BF: body fat percentage; CI: confidence interval.

found for almost all anthropometric measurements in both sexes. Hip circumference (100.0% sensitivity and specificity) and BMI (100.0% sensitivity and 84.8% specificity) were the best predictors of MetS in boys and girls, respectively. BMI was also the best predictor of MetS when boys and girls were combined (100.0% sensitivity and 86.4% specificity).

DISCUSSION In this study, we observed that BMI, hip circumference, NC, triceps skinfold, subscapular skinfold and BF% were associated with MetS score. Although BMI was the strongest predictor of MetS, all other anthropometric measurements showed good or high sensitivity and specificity to identify MetS in boys and girls. Additionally, for screening purposes and clinical practice, we tried to determine the cutoff values of the six anthropometric measurements related to increased MetS risk. Our results suggest that BMI and NC are effective screening tools for MetS in adolescents. The prevalence of MetS observed in this study (7.2%) was higher than that reported in other studies involving Brazilian adolescents (2.6%) (11), Iranian children and adolescents (5.0%) (12), Algerian adolescents (0-4.0%) (25), Greek adolescents (3.0%) (37), young Thai adults (5.9%) (38), and Korean adolescents (2.0%) (39). On the other hand, the prevalence was lower than that reported for adolescents in Brazil (12.8%) (14), and in Puerto Rico (16.8%) (40). Our study confirmed previous evidence (4,11) of a higher prevalence of MetS 36

in overweight (33.0%) compared to normal weight adolescents (0.6%). The worldwide prevalence of MetS among adolescents is on average 10.0%, ranging from 2.0% among normal weight adolescents to 32.0% among obese individuals (4). The wide variability in MetS prevalence among studies is partly due to the use of different criteria to define MetS. The use of different criteria to identify MetS and the lack of a universal definition for adolescents make it difficult to interpret and compare the results (41,42). Few studies conducted on adolescents (38,41) have associated body composition, measured by dualenergy X-ray absorptiometry (DXA), with MetS. Some authors have indicated BMI as the best anthropometric parameter to detect MetS in children and adolescents (15,30), in agreement with our results. We also showed that NC and BF% are strong predictors of MetS, corroborating the results of other authors (26). Although NC has been suggested to identify overweight in children (43-45) and adolescents (45,46) or to predict CVDs and MetS in the adult population (1621,24), this parameter was recently investigated as an anthropometric parameter to predict MetS in apparently healthy adolescents (22,26,27). Since NC is a low-cost, time-saving, noninvasive, quick and easy-to-use measure (18,43,47,48), it might be used to screen individuals with MetS in epidemiological studies (20). Because of the limitations of BF% assessment (overnight fast necessary, not applicable in women during the menstrual cycle or in individuals performing moderate to vigorous physical activity before measurement, and ethnic variation) (49), Arch Endocrinol Metab. 2019;63/1

Anthropometric measurements and metabolic syndrome in adolescents

Arch Endocrinol Metab. 2019;63/1

in the same population of adolescents. This approach is important for clinical practice since it permits better comparison of different anthropometric indicators to diagnose MetS and to identify the best parameter to be used. Finally, this study has some limitations. First, its cross-sectional design does not allow conclusions about causality. Second, the lack of an international consensus classification of MetS in adolescents restricts the comparison of results between studies. Third, the small number of participants with MetS may limit the generalizability of our findings. Lastly, the MetS score derived in this study cannot be compared to other studies since it is sample specific. In conclusion, all anthropometric measurements were associated with MetS score, with BMI showing the strongest relationship. However, in situations in which the measurement of height and weight is not possible, NC might be an interesting surrogate measurement because it can be obtained only with a tape measure at no cost. Health professionals should be made aware of this important tool for predicting MetS, even in apparently healthy adolescents. Since risk factors for MetS progress from childhood into adulthood, early lifestyle interventions are important to reverse the rising trend of noncommunicable diseases in adolescents. This approach may help decrease or prevent the onset of CVD and type 2 diabetes in adulthood, thus reducing the economic burden for the public health system. Acknowledgements: We thank the Gimenes Laboratory of Joinville for processing the biochemical data and the Secretary of Education for the city of Joinville, Santa Catarina, for allowing us access to the students. This study was funded by grants from the Research and Innovation Support Foundation of the State of Santa Catarina (FAPESC), Brazil (Grant 14029/2007-5) and the University of Joinville Region (Univille), Brazil (Grant 1750/2006). S. Mastroeni was the recipient of a postdoctoral fellowship from the Population Health Intervention Research Unit (PHIRU), School of Public Health, University of Alberta, Canada. M. Mastroeni was the recipient of a research grant from the National Council for Scientific and Technological Development (CNPq), Brazil (Grant 249048/2013-2), and of a postdoctoral fellowship from PHIRU. Finally, we thank Kerstin Markendorf for the English revision. Disclosure: no potential conflict of interest relevant to this article was reported.

REFERENCES 1. de Onis M, Blossner M, Borghi E. Global prevalence and trends of overweight and obesity among preschool children. Am J Clin Nutr. 2010;92(5):1257-64.

NC might be a more convenient option to detect MetS in adolescents. Compared to the other anthropometric measurements investigated in the present study, NC showed strong correlations with SBP and HDL-c, both MetS components. These results are consistent with other authors who also observed a strong relationship between SBP and NC in a study conducted in Lithuania on 1,947 adolescents aged 12-15 years (50). Although BMI was the stronger predictor and showed higher accuracy in identifying MetS, the use of NC has advantages. For example, NC eliminates the need for a scale, stadiometer and undressing the subject, thus reducing the time necessary for evaluation and permitting to increase the number of subjects to be investigated (43). Given its good sensitivity and specificity, NC may be used for screening purposes, especially among people living in remote areas and in low-resource settings or when it is difficult to obtain weight and height (43). Furthermore, NC 1) is a proxy of upper BF distribution (47,48), which is strongly associated with the risk of CVDs and diabetes; 2) is not affected by postprandial abdominal distensions, avoiding false results (16,19,47); 3) is more acceptable among overweight and obese people (19,47), and 4) can be used both in research and in clinical settings to identify the risk of MetS in adolescents. The use of sex- and age-specific criteria to identify adolescents with MetS was a strength of this study (6). Additionally, the use of a continuous variable (MetS score) instead of a categorical variable (MetS: yes or no) to detect MetS in adolescents has been recommended (12,36,41,42), especially due to the limitation of logistic regression in studies involving a small number of individuals with MetS (12). The prevalence of MetS in adolescents is low. In this respect, considering the outcome as a continuous variable increases the statistical power of the test (36,42) and avoids the loss of information that occurs when continuous variables are reclassified into categorical variables (41). For clinical purposes, since there are no accepted criteria for the definition of MetS in children and adolescents and because of the growing prevalence of MetS in this population, the use of a continuous variable to detect MetS seems to be an effective strategy to prevent the progression of MetS and associated pathologies in young people. Another important strength of this study was the simultaneous association of multiple anthropometric measurements, including BMI, hip circumference, NC, triceps and subscapular skinfolds and BF%, with MetS

Anthropometric measurements and metabolic syndrome in adolescents

2. Brasil. Pesquisa nacional de saúde do escolar: 2015. Instituto Brasileiro de Geografia e Estatística - IBGE, Coordenação de População e Indicadores Sociais. Rio de Janeiro: IBGE; 2016. p. 132. 3. Krebs NF, Jacobson MS. Prevention of pediatric overweight and obesity. Pediatrics. 2003;112(2):424-30. 4. Tailor AM, Peeters PH, Norat T, Vineis P, Romaguera D. An update on the prevalence of the metabolic syndrome in children and adolescents. Int J Pediatr Obes. 2010;5(3):202-13. 5. Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation. 2009;120(16):1640-5. 6. Jolliffe CJ, Janssen I. Development of age-specific adolescent metabolic syndrome criteria that are linked to the Adult Treatment Panel III and International Diabetes Federation criteria. J Am Coll Cardiol. 2007;49(8):891-8. 7.

Vikram NK, Pandey RM, Misra A, Goel K, Gupta N. Factor analysis of the metabolic syndrome components in urban Asian Indian adolescents. Asia Pac J Clin Nutr. 2009;18(2):293-300.

8. Daniels SR, Arnett DK, Eckel RH, Gidding SS, Hayman LL, Kumanyika S, et al. Overweight in children and adolescents: pathophysiology, consequences, prevention, and treatment. Circulation. 2005;111(15):1999-2012. 9. Bastien M, Poirier P, Lemieux I, Despres JP. Overview of epidemiology and contribution of obesity to cardiovascular disease. Prog Cardiovasc Dis. 2014;56(4):369-81. 10. Friend A, Craig L, Turner S. The prevalence of metabolic syndrome in children: a systematic review of the literature. Metab Syndr Relat Disord. 2013;11(2):71-80. 11. Kuschnir MC, Bloch KV, Szklo M, Klein CH, Barufaldi LA, Abreu GA, et al. ERICA: prevalence of metabolic syndrome in Brazilian adolescents. Rev Saúde Pública. 2016;50 Suppl 1:11s. 12. Heshmat R, Heidari M, Ejtahed HS, Motlagh ME, Mahdavi-Gorab A, Ziaodini H, et al. Validity of a continuous metabolic syndrome score as an index for modeling metabolic syndrome in children and adolescents: the CASPIAN-V study. Diabetol Metab Syndr. 2017;9:89. 13. Tavares Giannini D, Caetano Kuschnir MC, Szklo M. Metabolic syndrome in overweight and obese adolescents: a comparison of two different diagnostic criteria. Ann Nutr Metab. 2014;64(1):71-9. 14. Dias Pitangueira JC, Rodrigues Silva L, Portela de Santana ML, Monteiro da Silva Mda C, de Farias Costa PR, D’Almeida V, et al. Metabolic syndrome and associated factors in children and adolescents of a Brazilian municipality. Nutr Hosp. 2014;29(4):865-72. 15. Wicklow BA, Becker A, Chateau D, Palmer K, Kozyrskij A, Sellers EA. Comparison of anthropometric measurements in children to predict metabolic syndrome in adolescence: analysis of prospective cohort data. Int J Obes (Lond). 2015;39(7):1070-8.

16. Arnold TJ, Schweitzer A, Hoffman HJ, Onyewu C, Hurtado ME, Hoffman EP, et al. Neck and waist circumference biomarkers of cardiovascular risk in a cohort of predominantly African-American college students: a preliminary study. J Acad Nutr Diet. 2014;114(1):107-16. 17. Hoebel S, Malan L, de Ridder JH. Determining cut-off values for neck circumference as a measure of the metabolic syndrome amongst a South African cohort: the SABPA study. Endocrine. 2012;42(2):335-42. 18. Kumar NV, Ismail MH, P M, M G, Tripathy M. Neck circumference and cardio-metabolic syndrome. J Clin Diagn Res. 2014;8(7):MC23-5.

19. Pereira DC, Araujo MF, Freitas RW, Teixeira CR, Zanetti ML, Damasceno MM. Neck circumference as a potential marker of metabolic syndrome among college students. Rev Lat Am Enfermagem. 2014;22(6):973-9. 20. Preis SR, Massaro JM, Hoffmann U, D’Agostino RB Sr, Levy D, Robins SJ, et al. Neck circumference as a novel measure of cardiometabolic risk: the Framingham Heart study. J Clin Endocrinol Metab. 2010;95(8):3701-10. 21. Zhou JY, Ge H, Zhu MF, Wang LJ, Chen L, Tan YZ, et al. Neck circumference as an independent predictive contributor to cardiometabolic syndrome. Cardiovasc Diabetol. 2013;12:76. 22. Silva CC, Zambon MP, Vasques AC, Rodrigues AM, Camilo DF, Antonio MA, et al. Neck circumference as a new anthropometric indicator for prediction of insulin resistance and components of metabolic syndrome in adolescents: Brazilian Metabolic Syndrome Study. Rev Paul Pediatr. 2014;32(2):221-9. 23. Kroll C, Mastroeni SSBS, Czarnobay SA, Ekwaru JP, Veugelers PJ, Mastroeni MF. The accuracy of neck circumference for assessing overweight and obesity: a systematic review and meta-analysis. Ann Hum Biol. 2017;44(8):667-77. 24. Limpawattana P, Manjavong M, Sopapong R. Can neck circumference predict metabolic syndrome? An experience from a university community. Endocr Pract. 2016;22(1):8-15. 25. Benmohammed K, Valensi P, Benlatreche M, Nguyen MT, Benmohammed F, Paries J, et al. Anthropometric markers for detection of the metabolic syndrome in adolescents. Diabetes Metab. 2015;41(2):138-44. 26. Kelishadi R, Heidari-Beni M, Qorbani M, Motamed-Gorji N, Motlagh ME, Ziaodini H, et al. Association between neck and wrist circumferences and cardiometabolic risk in children and adolescents: The CASPIAN-V study. Nutrition. 2017;43-44:32-8. 27. Gomez-Arbelaez D, Camacho PA, Cohen DD, Saavedra-Cortes S, Lopez-Lopez C, Lopez-Jaramillo P. Neck circumference as a predictor of metabolic syndrome, insulin resistance and low-grade systemic inflammation in children: the ACFIES study. BMC Pediatr. 2016;16:31. 28. Oliveira RG, Guedes DP. Performance of different diagnostic criteria of overweight and obesity as predictors of metabolic syndrome in adolescents. J Pediatr. 2017;93(5):525-31. 29. Oliveira RG, Guedes DP. Performance of anthropometric indicators as predictors of metabolic syndrome in Brazilian adolescents. BMC Pediatr. 2018;18(1):33. 30. Weber DR, Leonard MB, Shults J, Zemel BS. A comparison of fat and lean body mass index to BMI for the identification of metabolic syndrome in children and adolescents. J Clin Endocrinol Metab. 2014;99(9):3208-16. 31. Agredo-Zuniga RA, Aguilar-de Plata C, Suarez-Ortegon MF. Waist: height ratio, waist circumference and metabolic syndrome abnormalities in Colombian schooled adolescents: a multivariate analysis considering located adiposity. Br J Nutr. 2015;114(5):700-5. 32. Mastroeni SSBS, Mastroeni MF, Gonçalves MC, Debortoli G, Silva NN, Bernal RT, et al. Cardiometabolic risk markers of normal weight and excess body weight in Brazilian adolescents. Appl Physiol Nutr Metab. 2016;41(6):659-65. 33. Laakso M, Matilainen V, Keinanen-Kiukaanniemi S. Association of neck circumference with insulin resistance-related factors. Int J Obes Relat Metab Disord. 2002;26(6):873-5. 34. de Onis M, Onyango AW, Borghi E, Siyam A, Nishida C, Siekmann J. Development of a WHO growth reference for school-aged children and adolescents. Bull World Health Organ. 2007;85(9):660-7. 35. Craig CL, Marshall AL, Sjostrom M, Bauman AE, Booth ML, Ainsworth BE, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003;35(8):1381-95. Arch Endocrinol Metab. 2019;63/1

Anthropometric measurements and metabolic syndrome in adolescents

36. Eisenmann JC. On the use of a continuous metabolic syndrome score in pediatric research. Cardiovasc Diabetol. 2008;7:17. 37. Hatzis CM, Papandreou C, Sifaki-Pistolla D, Jildeh C, Kafatos AG. The metabolic syndrome among preschool and school age children and adolescents in Crete in the first decade of the 21st century. Hormones (Athens). 2014;13(4):588-90. 38. Namwongprom S, Rerkasem K, Wongthanee A, Pruenglampoo S, Mangklabruks A. Relationship between body composition parameters and metabolic syndrome in young Thai adults. J Clin Res Pediatr Endocrinol. 2014;6(4):227-32. 39. Song S, Young Paik H, Song WO, Song Y. Metabolic syndrome risk factors are associated with white rice intake in Korean adolescent girls and boys. Br J Nutr. 2015;113(3):479-87. 40. Perez CM, Ortiz AP, Fuentes-Mattei E, Velazquez-Torres G, Santiago D, Giovannetti K, et al. High prevalence of cardiometabolic risk factors in Hispanic adolescents: correlations with adipocytokines and markers of inflammation. J Immigr Minor Health. 2014;16(5):865-73. 41. He F, Rodriguez-Colon S, Fernandez-Mendoza J, Vgontzas AN, Bixler EO, Berg A, et al. Abdominal obesity and metabolic syndrome burden in adolescents – Penn State Children Cohort study. J Clin Densitom. 2015;18(1):30-6.

44. Nafiu OO, Burke C, Lee J, Voepel-Lewis T, Malviya S, Tremper KK. Neck circumference as a screening measure for identifying children with high body mass index. Pediatrics. 2010;126(2):e306-10. 45. Castro-Pinero J, Delgado-Alfonso A, Gracia-Marco L, GomezMartinez S, Esteban-Cornejo I, Veiga OL, et al. Neck circumference and clustered cardiovascular risk factors in children and adolescents: cross-sectional study. BMJ Open. 2017;7(9):e016048. 46. Ferretti RL, Cintra IP, Passos MA, Ferrari GL, Fisberg M. Elevated neck circumference and associated factors in adolescents. BMC Public Health. 2015;15:208. 47. Androutsos O, Grammatikaki E, Moschonis G, Roma-Giannikou E, Chrousos GP, Manios Y, et al. Neck circumference: a useful screening tool of cardiovascular risk in children. Pediatr Obes. 2012;7(3):187-95. 48. Kurtoglu S, Hatipoglu N, Mazicioglu MM, Kondolot M. Neck circumference as a novel parameter to determine metabolic risk factors in obese children. Eur J Clin Invest. 2012;42(6):623-30. 49. Dehghan M, Merchant AT. Is bioelectrical impedance accurate for use in large epidemiological studies? Nutr J. 2008;7:26. 50. Kuciene R, Dulskiene V, Medzioniene J. Association of neck circumference and high blood pressure in children and adolescents: a case-control study. BMC Pediatr. 2015;15:127.

42. Rodriguez-Colon SM, He F, Bixler EO, Fernandez-Mendoza J, Vgontzas AN, Calhoun S, et al. Metabolic syndrome burden in apparently healthy adolescents is adversely associated with cardiac autonomic modulation – Penn State Children Cohort. Metabolism. 2015;64(5):626-32.

43. Santos D, Contarato AAPF, Kroll C, Bertoli M, Czarnobay SA, Figueirêdo KBW, et al. Neck circumference as a complementary measure to identify excess body weight in children aged 13-24 months. Rev Bras Saúde Matern Infant. 2015;15(3):301-7.

Arch Endocrinol Metab. 2019;63/1

original article

Centro Integrado de Saúde Amaury de Medeiros, Universidade de Pernambuco (UPE), Recife, PE, Brasil 2 Departamento de Morfologia e Fisiologia Animal, Universidade Federal Rural de Pernambuco (UFRPE), Recife, PE, Brasil 3 Laboratório do Sono e Coração, Pronto-Socorro Cardiológico de Pernambuco (PROCAPE), Recife, PE, Brasil 4 Departamento de Cardiologia, Pronto-Socorro Cardiológico de Pernambuco (PROCAPE), Recife, PE, Brasil 5 Departamento de Ginecologia e Obstetrícia, Universidade de Pernambuco (UPE), Recife, PE, Brasil 6 Departamento de Educação Física, Universidade Federal da Paraíba (UFPB), João Pessoa, PB, Brasil 1

Correspondence to: Anna Myrna Jaguaribe de Lima Universidade Federal Rural de Pernambuco Departamento de Morfologia e Fisiologia Animal Rua Dom Manoel de Medeiros, s/n, Dois Irmãos 52171-900 – Recife, PE, Brasil annamyrna@uol.com.br Received on April/25/2017 Accepted on Nov/24/2018 DOI: 10.20945/2359-3997000000101

Influence of obesity in pulmonary function and exercise tolerance in obese women with obstructive sleep apnea Vivian Maria Moraes Passos1, Anna Myrna Jaguaribe de Lima2, Bárbara Renatha Afonso Ferreira de Barros Leite1, Rodrigo Pinto Pedrosa3, Isly Maria Lucena de Barros4, Laura Olinda Bregieiro Fernandes Costa5, Amilton da Cruz Santos6, Maria do Socorro Brasileiro-Santos6

ABSTRACT Objective: To evaluate the influence of obesity on pulmonary function and exercise tolerance in women with obstructive sleep apnea (OSA). Subjects and methods: A descriptive analytic crosssectional study was carried out. Thirty-nine (39) sedentary climacteric women, aged 45 to 60 years, were evaluated and submitted to polysomnography. The participants were divided into 4 groups: a) ‘eutrophic non-OSA’ (n = 13); b) ‘eutrophic OSA’ (n = 5); c) ‘obese non-OSA’ (n = 6); d) ‘obese OSA’ (n = 15). All subjects underwent clinical and anthropometric evaluation, followed by pulmonary function tests and 6-minute walk test (6MWT). Results: There was a significant difference in the predicted percentage values of FEV1/FVC when comparing ‘eutrophic OSA’ and ‘obese OSA’ (97.6% ± 6.1% vs. 105.7% ± 5.7%, respectively; p = 0.025). The other spirometric variables did not show any differences between the studied groups. There was no significant difference in the maximum distance walked when the ‘eutrophic non-OSA’, ‘eutrophic OSA’, ‘obese non-OSA’ and ‘obese OSA’ groups were compared. Conclusion: Considering the results of this study, OSA itself did not influence pulmonary function or functional capacity parameters compared to eutrophic women. However, not only isolated obesity but also obesity associated with OSA can negatively impact sleep quality and lung function. Arch Endocrinol Metab. 2019;63(1):40-6 Keywords Obesity; obstructive sleep apnea; lung function; exercise tolerance

INTRODUCTION

bstructive sleep apnea (OSA) is a respiratory disorder characterized by repeated and cyclic episodes of total collapse of the upper airway during sleep. These events may result in oxygen desaturation, high blood levels of carbon dioxide and microarousals (1,2). Recent studies have estimated that nearly 4% of men and 2% of women in the world, aged between 30 to 60 years, suffer from OSA (3). Tufik and cols. (4) showed that in São Paulo, Brazil’s most populous city, approximately 32% of the population present risk factors for any degree of OSA severity, and its prevalence increases with age for men and women, although it is higher in males. 40

There is also a high prevalence of OSA in obese individuals, mainly due to fat accumulation in the neck region, morphological modification of upper airways and lung volume reduction (2,3,5). Women of working/reproductive age tend to have less OSA than men, possibly as a result of protective action of progesterone over the pharyngeal dilator muscles. Leptin levels seem to have an influence on ventilatory control, promoting better responses to hypoxia and hypercapnia (6). In contrast, post-menopausal women have higher prevalence and severity of OSA caused by the loss of hormonal protection (3,6,7). Regarding the deleterious effects of obesity on pulmonary function, reduced forced expiratory Arch Endocrinol Metab. 2019;63/1

volume in the first second (FEV1) is observed, as well as reduced forced vital capacity (FVC) and their relation, lower strength and endurance of the respiratory muscles (5,8). In obese women, there is a reduction in the respiratory function, with lower vital capacity (VC) and diminished maximum voluntary ventilation (MVV) (9). To our knowledge, this is the first paper that has studied exercise tolerance in obese women with OSA. Therefore, the aim of this study was to evaluate the influence of obesity on pulmonary function, cardiorespiratory fitness and sleep quality in women with obstructive sleep apnea.

SUBJECTS AND METHODS This is a cross-sectional descriptive study, approved by the Ethics and Research Committee of the Universidade Federal de Pernambuco. The participants were selected through the medical records of the patients admitted to the Heart and Sleep Laboratory – PROCAPE, based on their previous polysomnography exam. Polysomnography was performed in the same laboratory, where all patients were monitored overnight using an Embletta-type handheld portable respirator (Embla, Embletta® Gold, USA) (10). This test aimed to identify the Apnea-Hypopnea Index (AHI), which is defined by the mean number of apnea and hypopnea events per hour, in order to confirm diagnosis and to measure OSA severity according to definitions of the American Academy of Sleep Medicine (11): i) absence of OSA < 5 events/ hour); ii) mild OSA (5 < AHI < 15 events/hour); iii) moderate OSA (15 < AHI < 30 events/hour); iv) severe OSA (AHI > 30 events/hour). Women who were submitted to a polysomnography, aged between 45 and 60 years, eutrophic and grade I and II obese (12) were included in the study. Overweight and morbidly obese women, as well as smokers or people who had quit smoking for at least one year were excluded from the study. Participants receiving hormone replacement therapy or with respiratory disorders besides OSA, subjects who could not comprehend the verbal commands during evaluation or showed discomfort during the exams were excluded. Each participant provided written informed consent to participate. Sample size calculation was performed using the GPower® software, version 3.1.6 (Kiel University, Arch Endocrinol Metab. 2019;63/1

Germany), using a probabilistic error of 0.05, effect size of 0.25, and 80% statistical power as parameters, so that the minimum sample was determined as a total of 20 subjects (n = 5 in each group). Pittsburgh Sleep Quality Index. The Pittsburgh sleep quality index (PSQI), validated for Brazilian population (13), is a self-reported measure of sleep quality and queries about sleep-related variables over the previous month. The global score varies from 0 to 21, and higher results indicate poor sleep quality. Physical Activity Questionnaire. The physical activity questionnaire (14), validated for the Brazilian population and remained from the original International Physical Activity Questionnaire (IPAQ), is also a selfreport questionnaire to detect the level physical fitness. Lung Function Evaluation. During spirometric tests (Spirobank G® USB (MIR, Rome, Italy), the patients remained seated, back steady and performed the forced vital capacity (FVC) and maximum voluntary ventilation (MVV) maneuvers. In every test, the maneuvers should conform with the criteria of the American Thoracic Society (ATS) (15). The resulting measurements of all tested maneuvers were FVC, FEV1, FEV1/FVC ratio, forced expiratory flow between 25 and 75% (FEF25%-75%), peak expiratory flow (PEF) and the MVV. All the results were expressed as an absolute value and percentage of the predicted numbers (16). Cardiorespiratory Fitness Evaluation. Six-minute walk test (6MWT), a submaximal effort test, was performed according to ATS (17) rules. Parameters such as saturation of peripheral oxygen (SpO2), heart rate (HR), respiratory rate (RR), systolic and diastolic blood pressure (SBP and DBP) and rate of perceived exertion were measured before and after the 6MWT, as recommended. Statistical Analysis. Statistical analysis was performed using the Statistical Package for the Social SciencesSPSS 15.0 (Statsofat Inc., Chicago, IL, USA, 2006). The Kolmogorov-Smirnov test evaluated normality of the data. ANOVA repeated measures was used to compare means within and between groups and posthoc analysis was evaluated by Bonferroni test. Fischer’s exact test verified differences between categorical variables. The results are presented as mean ± standard deviation. A p-value < 0.05 was considered statistically relevant for all analyses. 41

Exercise tolerance in obese women with OSA

RESULTS Out of the 265 medical records evaluated in the Heart and Sleep Laboratory – PROCAPE, 178 provided information that did not match the inclusion criteria. From the 87 patients remaining, 21 were excluded because they did not fill the eligibility criteria when contacted and 66 were considered eligible. Then, 19 subjects refused to participate, and another 8 started to participate in the study but were unable to perform the necessary tests, comprising a total sample loss of 226 subjects. The final sample consisted of 39 women, aged between 45 to 60 years, divided into the groups 1) ‘eutrophic non-OSA’ (n = 13), 2) ‘eutrophic OSA’ (n = 5), 3) ‘obese non-OSA’ (n = 6) and 4) ‘obese OSA’ (n = 15). In the ‘eutrophic OSA’ group, the prevalence of mild and moderate apnea was 80% and 20%, respectively. In the ‘obese OSA’ group, the results were 40% for mild OSA, 47% for moderate OSA and 13% for severe OSA. Anthropometric measures are presented in Table 1. When comparing the eutrophic group with the obese group, regardless of OSA, a significant difference related to weight, body mass index (BMI), neck circumference and waist-hip ratio (WHR) were observed. Likewise, when comparing OSA and nonOSA groups, regardless of obesity, different AHI results were detected, as expected. When comparing

the ‘eutrophic OSA’ group and the ‘obese OSA’ group, the latter had significantly higher AHI levels (8.94 vs. 17.98; p = 0.032) (Table 1). Sleep quality assessed with PQSI did not differ between eutrophic groups (OSA or non-OSA) (9.80 ± 6.63 and 9.08 ± 3.04; p = 0.617). The ‘eutrophic OSA’ group had higher PQSI results than the ‘obese OSA’ (9.08 ± 3.04 vs. 6.17 ± 2.48, p = 0.01), as well as comparing the ‘eutrophic OSA’ and ‘obese non-OSA’ (9.80 ± 3.04 vs. 6.17 ± 2.48; p = 0.04). In comparing the obese OSA and non-OSA, there were also different results (9.73 ± 3.53 vs. 6.17 ± 2.48, respectively; p = 0.035) (Table 1). Groups were paired in percentage of non-smokers/ex-smokers, presence of dyslipidemia and diabetes mellitus (DM). However, the presence of systemic arterial hypertension (SAH) was more expressive in the ‘obese OSA’ group (Table 2). Physical fitness obtained through IPAQ did not show differences between groups (p = 0.621) (Table 2). There was only a significant difference in the predicted percentage values of FEV1/FVC when we compared eutrophic and obese OSA groups (97.60% ± 6.07% vs. 105.73% ± 5.73%, respectively; p = 0.025) (Table 3). The other spirometric variables did not show any differences between the studied groups. There was no significant difference in the maximum distance walked comparing the groups (Table 3).

Table 1. Sample characteristics, anthropometric information, apnea classification (AHI) and sleep quality (PSQI) Groups Eutrophic non-OSA (n = 13)

Eutrophic OSA (n = 5)

Obese non-OSA (n = 6)

Obese OSA (n = 15)

Mean ± SD

Age (years)

52.5 ± 4.2

50.0 ± 12.1

50.0 ± 1.4

53.1 ± 6.22f

Weight (kg)

54.2 ± 6.18

53.5 ± 10.8

84.2 ± 10.72b.d

85.5 ± 10.02c.e

Height (m)

1.54 ± 0.05

1.55 ± 0.09

1.6 ± 0.07

1.6 ± 0.08e

BMI (kg/m2)

22.8 ± 2.0

22.1 ± 2.4

33.8 ± 3.09b.d

34.0 ± 1.79c.e

Neck Circumference (cm)

32.0 ± 1.8

33.1 ± 0.9

37.2 ± 1.3

36.9 ± 2.59c.e

Waist (cm)

82.6 ± 7.9

78.4 ± 8.1

103.2 ± 8.8b.d

105.5 ± 6.83c.e

Hip (cm)

94.4 ± 5.6

94.3 ± 10.3

111.7 ± 6.5

114.2 ± 5.58c.e

WHR

0.88 ± 0.08

0.83 ± 0.05

0.92 ± 0.04d

0.93 ± 0.06e

AHI (events/hour)

1.8 ± 1.5

8.9 ± 2.9

2.3 ± 1.7

18.0 ± 10.7c.e.f

PSQI

9.1 ± 3.0

9.8 ± 3.6

6.2 ± 2.5b,d

9.7 ± 3.5f

Variables

b.d

BMI: body mass index; WHR: waist hip ratio; AHI: apnea hypopnea index; PSQI: Pittsburgh sleep quality index. a p < 0.05 Eutrophic non-OSA x Eutrophic OSA; b p < 0.05 Eutrophic non-OSA x Obese non-OSA; c p < 0.05 Eutrophic non-OSA x Obese OSA; d p < 0.05 Eutrophic OSA x Obese non-OSA; e p < 0.05 Eutrophic OSA x Obese OSA; f p < 0.05 Obese non-OSA x Obese OSA.

Arch Endocrinol Metab. 2019;63/1

Exercise tolerance in obese women with OSA

Table 2. Sample characterization, tobacco smoking, comorbidities and physical activity level Groups Eutrophic non-OSA

Eutrophic OSA

Obese non-OSA

Obese OSA

n (%)

Non-smoker

10 (76.9)

5 (100.0)

4 (66.7)

10 (66.7)

Ex-smoker

3 (23.1)

0 (0.0)

2 (33.3)

5 (33.3)

Variables

p-value*

Smoking 0.585

SAH Yes

7 (53.8)

0 (0.0)

4 (66.7)

12 (80.0)

6 (46.2)

5 (100.0)

2 (33.3)

3 (20.0)

Yes

4 (30.8)

2 (40.0)

1 (16.7)

4 (26.7)

9 (69.2)

3 (60.0)

5 (83.3)

11 (73.3)

Yes

1 (7.7)

0 (0.0)

1 (16.7)

4 (26.7)

12 (92.3)

5 (100.0)

5 (83.3)

11 (73.3)

273,0 ± 198,5

283,8 ± 148,1

256,9 ± 101,6

273,0 ± 198,5

0.016

Dyslipidemia 0.879

DM 0.532

IPAQ MET (min/week)

0.621

SAH: systemic arterial hypertension; DM: diabetes mellitus; IPAQ: international physical activity questionnaire. (*) Fisher’s Exact Test.

Table 3. Pulmonary function test results and maximum distance walked in the 6MWT Groups Variables

FVC (l) predicted FVC% FEV1 (l)

Eutrophic Non-OSA (n = 13)

Eutrophic OSA (n = 5)

Obese non-OSA (n = 6)

Obese OSA (n = 15)

Mean ± SD

2.55 ± 0.45

3.05 ± 0.74

2.65 ± 0.64

2.60 ± 0.48

89.92 ± 16.44

102.00 ± 19.42

87.33 ± 19.65

86.47 ± 11.49

2.16 ± 0.36

2.43 ± 0.60

2.26 ± 0.42

2.22 ± 0.40

94.69 ± 16.36

98.60 ± 18.26

91.00 ± 15.28

92.60 ± 16.86

FEV1/FVC

84.92 ± 4.26

79.84 ± 6.16

86.38 ± 8.44

85.52 ± 4.87

predicted FEV1/FVC%

104.00 ± 5.52

97.60 ± 6.07

105.67 ± 9.61

105.73 ± 5.73e

predicted FEV1%

PEF (l/s) predicted PEF% FEF25-75% (l/s) predicted FEF% MVV (l/min)

4.00 ± 0.90

3.91 ± 0.61

3.79 ± 0.43

4.33 ± 0.93

59.31 ± 13.33

56.80 ± 7.22

54.17 ± 4.88

62.13 ± 13.16

2.53 ± 0.41

2.47 ± 0.70

2.72 ± 0.46

2.82 ± 0.69

108.92 ± 19.94

99.20 ± 23.57

111.00 ± 17.74

119.07 ± 33.74

82.74 ± 9.97

82.24 ± 12.68

90.87 ± 11.98

89.49 ± 19.18

predicted MVV%

75.69 ± 9.24

72.80 ± 8.96

75.67 ± 9.29

77.07 ± 15.81

Distance walked (m)

470.77 ± 8.22

462.72 ± 39.38

434.97 ± 51.32

453.11 ± 87.04

DISCUSSION OSA did not seem to affect the pulmonary function of eutrophic and obese individuals in the present study, but in the latter group it caused poor sleep quality. On the other hand, the presence of obesity proved Arch Endocrinol Metab. 2019;63/1

to be a condition that not only negatively interferes in sleep quality of subjects with or without OSA, but also in certain pulmonary function variables. However, exercise tolerance was not modified by any of these disorders in the evaluated population. 43

FEV1: forced expiratory volume in the first second; FVC: forced vital capacity; PFE: peak expiratory flow; FEV1/FVC: ratio of FEV1 to FVC; MVV: maximal voluntary ventilation. e p < 0.05 Eutrophic OSA x Obese OSA.

Exercise tolerance in obese women with OSA

Regarding sleep quality, the PQSI had better results in the ‘eutrophic non-OSA’ when compared to the ‘obese non-OSA’, but there was no difference between the obese with OSA group. When validating the PQSI for the Brazilian population, Bertolazi and cols. (13) identified the results of this test from 2.5 ± 2.0 in control individuals to 8.1 ± 4.0 in subjects with OSA. In our sample, non-OSA participants showed different outcomes, suggesting that not only OSA but also other factors related to sleep may have interfered in the results. In the groups with OSA, the results followed the ones observed in PSQI validation (13). Among obese individuals, the PQSI showed differences when compared to OSA or non-OSA subjects, pointing out that the presence of the disease decreases sleep quality, at least in these individuals. In fact, other studies using the Epworth sleepiness scale (ESS) showed that obese people with OSA have bad sleep quality when compared to control groups (18,19). Regarding pulmonary function and OSA, it is very clear that there is a complex interaction between structure and function. Previous studies have shown a relation between OSA and reduced pulmonary volume such as residual volume, and a decline of expiratory reserve volume and vital capacity, with a reduction of airway patency which increases the possibility of collapse, thus leading to emergence or aggravation of OSA. However, these primary variables are not the purpose of our study. Our results revealed that the main spirometric variables were not influenced by OSA when eutrophic or obese groups with or without the disorder were compared, as previously observed (20). Regarding FEV1 and FVC, the negative relationship between obesity and pulmonary function has already been demonstrated (21,22). Previous studies have also shown that there is reduction in these parameters and the predicted percentage in individuals with severe OSA (23). There were no differences in these two variables in the present study. It is possible that higher BMI as well as higher degrees of OSA may have interfered in the final results of those studies (22,23), which limits comparisons with our data. There were differences in the FEV1/FVC ratio in our study in terms of the predicted percentage between ‘eutrophic OSA’ and ‘obese OSA’, contradicting the results of other studies (21-23) which found that the quotient does not show a difference between eutrophic or obese groups with OSA or nonOSA due to simultaneous and proportional reduction 44

of FEV1 and FVC. It is assumed that the severity of the OSA, initially different, may have affected some level of obstruction in the participants, promoting such results. Regarding respiratory muscle resistance, Costa and cols. (9) showed that the MCC is reduced as the BMI increases. In the same way, Chien and cols. (23) observed a decrease of MVV in individuals with OSA. Their results are not compatible to our research, since our results did not show a difference between the studied groups. It is assumed that our MVV results were not influenced by OSA, or that the obese individuals may have received non-specific and indirect muscle training caused by the adipose tissue on the respiratory muscles, showing no differences in comparison to the eutrophic group. Data for FEF25-75% were similar in all the groups, corroborating the results of previous authors in which these variables do not change when comparing obese individuals with healthy control individuals (8,22). These answers explain the lower influence of obesity on expiratory volumes and confirm the restrictive character of it. However, there is evidence that this variable may decrease significantly, as long as there is a high BMI and presence of OSA (24). With regards to cardiorespiratory fitness, our results did not show any difference in the maximum distance walked during 6MWT in any of the groups, assuming that there would be no interference from obesity or OSA in this parameter. When the eutrophic and obese groups were compared, there were no significant changes in the maximum distance walked due to the obesity factor. The results contradict studies performed with obese and eutrophic subjects, which showed that the latter walked a greater distance, and that the difference among women was bigger (25). These authors confirmed a negative and discrete relationship between obesity (and its severity levels) and the distance walked in the 6MWT. Nevertheless, in comparing eutrophic and obese without OSA, Alameri and cols. (26) did not detect any differences in the distance walked, which supports the results of our research. Regarding the effects of OSA on cardiorespiratory fitness, just one previous study compared eutrophic individuals with or without OSA (27), and no difference was observed regarding VO2Max, respiratory exchange ratio (RER) or anaerobic threshold (AT) between the groups, which suggests no or little influence of the OSA on the functional capacity. Other results reinforce the low influence that this respiratory disorder has on exercise tolerance, as there Arch Endocrinol Metab. 2019;63/1

Exercise tolerance in obese women with OSA

Arch Endocrinol Metab. 2019;63/1

and psychological factors. Moreover, a maximum effort test could generate more reliable answers about the exercise tolerance for the studied population. Considering the results of this study, OSA itself did not influence pulmonary function and functional capacity parameters when obese and non-obese women were compared, but this disorder improved poor sleep quality in obese subjects. However, not only isolated obesity but also obesity associated with OSA can negatively impact sleep quality and lung function. It is suggested that studies with a larger sample size with different grades of OSA and obesity, along with pulmonary strength tests and maximal cardiopulmonary exercise test and associations between lung function and anthropometric and polysomnographic variables should be considered to obtain more reliable answers about pulmonary function and exercise tolerance in obese women with OSA. Acknowledgments: the authors would like to thank Coordenação de Aperfeiçoamento de Pessoal do Nível Superior (CAPES) and PROCAPE for their assistance. Disclosure: no potential conflict of interest relevant to this article was reported.

REFERENCES 1. Caples SM, Gami AS, Somers VK. Obstructive sleep apnea. Ann Intern Med 2005;142:187-97. 2. Daltro CHC, Fontes FHO, Santos-Jesus R, Gregorio PB, Araújo LMB. Síndrome da apnéia e hipopnéia obstrutiva do sono: associação com obesidade, gênero e idade. Arq Bras Endocrinol Metab 2006;50(1):74-81. 3. Bixler E, Vgontzas A, Lin H, Ten Have T, Rein J, Vela-Bueno A, et al. Prevalence of sleep-disordered breathing in women. Am J Respir Crit Care Med. 2001;163(3 Pt 1):608-13. 4. Tufik S, Santos-Silva R, Taddei JA, Bittencourt LRA. Obstructive sleep apnea syndrome in the São Paulo Sleep Study. Sleep Med. 2010;11(5):441-6. 5. Togeiro SMGP, Fontes FH. Hipoventilação relacionada ao sono. J Bras Pneumol. 2010;36(supl.2):S1-S61. 6. Kapsimalis F, Kryger MH. Gender and obstructive sleep apnea syndrome, part 2: mechanisms. Sleep. 2002;25(5):499-506. 7. Verdaguer M, Levrat V, Lamour C, Paquereau J, Neau J. Pathologie pulmonaire au féminin: le SAOS de la femme, une entité particulière? Rev Mal Respir. 2011;1279-88. 8. Sarikaya S, Cimen, OB, Gokcay Y, Erdem R. Pulmonary function tests, respiratory muscle strength, and endurance of persons with obesity. Endocrinologist. 2003;13:136-41. 9. Costa D, Barbalho MC, Miguel GPS, Forti EMP, Azevedo JLMC. The impact of obesity on pulmonary function in adult women. Clinics. 2008;63(6):719-24. 10. Ng SS, Chan TO, To KW, Ngai J, Tung A, Ko FW, et al. Validation of Embletta portable diagnostic system for identifying patients with suspected obstructive sleep apnoea syndrome (OSAS). Respirology. 2010;15(2):336-42. 11. American Academy of Sleep Medicine. Sleep-related breathing disorders in adults: recommendations for syndrome definition

was no difference in variables such as VO2, RER and work rate by comparing groups with or without OSA or obese subjects separated by the level of OSA (28). Many previous studies have shown an association between OSA and reduced cardiorespiratory fitness. Some indicate that patients suffering with OSA have reduced functional capacity, since they observed lower VO2peak, VO2Max and AT values compared to the predicted values or in comparison to healthy individuals (29,30). In a gender comparison study, Cintra and cols. (31) showed that women with OSA in the climacteric period submitted to maximum effort test had lower oxygen consumption (VO2), reduced maximum heart rate (HRmax) and lower pressure levels than the ones found in men, which suggest that women with OSA have peculiarities during and after aerobic exercise. Pływaczewski and cols. (19) also suggest that patients with severe OSA show exercise intolerance and point to the female gender, the presence of SAH, high BMI and low FVC as increased factors. Vanhecke and cols. (18) not only observed a reduction of VO2max in morbidly obese individuals with OSA when compared to individuals who do not suffer from the disorder, but also an inverse relation between this variable and AHI, even if the ventilatory equivalents remain similar between the groups. Regarding the 6MWT, it was already seen that the distance walked was much higher in eutrophic with no OSA than in obese with OSA (26). It is important to note that the level of apnea was severe (average AHI of 66 events/hour) (26) for these authors, as well as the obesity level (average BMI of 50 kg/m2) (18), which may have boosted the outcomes. The present study has some limitations. The low number of patients may have interfered in the results and some of the tested groups may have been even more negatively affected by this factor. The performance of this study was limited to one research center, what makes the data less extrapolated and compromises the generalization of the results. The results for pulmonary function could have been supplemented by evaluation of respiratory muscle strength, without which it is not possible to know if there is a muscular condition affecting the functional matter. Regarding the submaximal functional capacity, one of the limitations was the fact that other factors that contribute to exercise tolerance were not investigated, such as peripheral muscular condition, heart function

Exercise tolerance in obese women with OSA

and measurement techniques in clinical research. The Report of an American Academy of Sleep Medicine Task Force. Sleep. 1999;22:667-89. 12. World Health Organization (WHO). Physical status: the use and interpretation of anthropometry. Geneva, Technical Report Series 854, 1995. 13. Bertolazi AN, Fagondes SC, Hoff LS, Dartora EG, Miozzo ICDS, de Barba ME, et al. Validation of the Brazilian Portuguese version of the Pittsburgh Sleep Quality Index. Sleep Med. 2011;12(1):70-5. 14. Matsudo S, Araújo T, Matsudo V, Andrade D, Andrade E, Oliveira LC, et al. Questionário Internacional de Atividade Física (IPAQ): Estudo de validade e reprodutibilidade no Brasil. Rev Bras Ativ Fis Saúde. 2001;6(2):5-18. 15. Miller MR, Hanskinson J, Brusasco F, Burgos R, Casaburi A, Coates R, et al.; ATS/ERS Task Force. Standardisation of spirometry. Eur Respir J. 2005;26(2):319-38. 16. Pereira CA, Sato T, Rodrigues SC. Novos valores de referência para espirometria forçada em brasileiros adultos de raça branca. J Bras Pneumol. 2007;33(4):397-406. 17. ATS Committee on Proficiency Standards for Clinical Pulmonary Function Laboratories. ATS statement: guidelines for the sixminute walk test. Am J Respir Crit Care Med. 2002;166(1):111-7. 18. VanheckeTE, Franklin BA, Zalesin KC, Sangal B, DeJong AT, Agraw lV, et al. Cardiorespiratory fitness and obstructive sleep apnea syndrome in morbidly obese patients. Chest. 2008;134(3):539-45. 19. Pływaczewski R, Stokłosa A, Bielen8 P, Bednarek M, Czerniawska J, Jonczak L, et al. [Six-minute walk test in obstructive sleep apnoea]. Pneumonol Alergol Pol. 2008;76(2):75-82.

20. Sharma B, Feinsilver S, Owens, RL, Malhotra A, McSharry D, Karbowitz S. Obstructive Airway Disease and Obstructive Sleep Apnea: Effect of Pulmonary Function. Lung. 2011;189(1):37-41. 21. Salome CM, King GG, Berend N. Physiology of obesity and effects on lung function. J Appl Physiol. 2010;108:206-11.

22. Melo SMD, Melo VA, Menezes Filho RS, Santos FA. Effects of progressive increase in body weight on lung function in six groups of body mass index. Rev Assoc Med Bras. 2011;57(5):499505. 23. Chien MY, Wu YT, Lee PL, Chang, YJ, Yang PC. Inspiratory muscle dysfunction in patients with severe obstructive sleep apnoea. Eur Respir J. 2010;35:373-80. 24. Zerah-Lancner F, Lofaso F, Coste A, Ricolfi F, Goldenberg F, Harf A. Pulmonary function in obese snorers with or without sleep apnea syndrome. Am J Respir Crit Care Med. 1997;156:522-7. 25. Gontijo PL, Lima TP, Costa TR, Reis EP, Cardoso FPF, Cavalcanti Neto FF. Correlação da espirometria com o teste de caminhada de seis minutos em eutróficos e obesos. Rev Assoc Med Bras. 2011;57(4):387-93. 26. Alameri H, Al-Kabab, BaHammam A. Submaximal exercise in patients with severe obstructive sleep apnea. Sleep Breath. 2010;14:145-51. 27. Rizzi CF, Cintra F, Risso T, Pulz C, Tufik S, de Paola A, et al. Exercise Capacity and Obstructive Sleep Apnea in Lean Subjects. Chest. 2010;137:109-14. 28. Kaleth AS, Chittenden TW, Hawkins BJ, Hargens TA, Guill SG, Zedalis D, et al. Unique cardiopulmonary exercise test responses in overweight middle-aged adults with obstructive sleep apnea. Sleep Med. 2007;8(2):160-8. 29. Nanas S, Sakellariou D, Kapsimalakou S, Dimopoulos S, Tassiou A, Tasoulis A, et al. Heart Rate Recovery and Oxygen Kinetics After Exercise in Obstructive Sleep Apnea Syndrome. Clin Cardiol. 2010;33(1):46-51. 30. Öztürk L, Metin G, Çuhadaroglu Ç, Utkusavas A, Tutluoglu B. Cardiopulmonary responses to exercise in moderate-to-severe obstructive sleep apnea. Tuberk Toraks. 2005;53(1):10-8. 31. Cintra F, Poyares D, Rizzi CF, Risso TT, Skomro R, Montuori E, et al. Cardiorespiratory response to exercise in men and women with obstructive sleep apnea. Sleep Med. 2009;10(3):368-73.

Arch Endocrinol Metab. 2019;63/1

original article

Clinical and hormonal characteristics of patients with different types of hypophysitis: a single-center experience Narin Nasiroglu Imga1, Ali Erdem Yildirim2, Ozden Ozdemir Baser1, Dilek Berker1

ABSTRACT Objective: The inflammation of the pituitary gland is known as hypophysitis. It is a rare disease accounting for approximately 0.24%-0.88% of all pituitary diseases. The natural course of hypophysitis is variable. Main forms are histologically classified as lymphocytic, granulomatous, IgG4 related and xanthomatous. We aim to present our patients with hypophysitis and compare clinical, laboratory and radiological features. Subjects and methods: We retrospectively reviewed our database of 1.293 patients diagnosed with pituitary diseases between 2010 and 2017. Twelve patients with hypophysitis were identified. Demographical data, clinical features, endocrinological dysfunction, imaging findings, treatment courses and follow-up periods were evaluated. Results: The frequency of hypophysitis was found 0.93% in all cases of the pituitary disease.Twelve patients (nine females and three males), ages between 17-61 years, were evaluated.The characteristic features of our patients tended to be predominantly female and young. Diagnosis of hypophysitis was made after pituitary biopsy in four patients, and in eight patients after pituitary operation due to adenoma. Headache (67%) and visual problems (33%) were the most frequent nonendocrine symptoms. Anterior pituitary hormone deficiencies (63.7%) and/or diabetes insipidus (17%) were seen among patients. According to histopathological forms, four had lymphocytic, seven had granulomatous and one had xanthogranulomatous types. Contrast enhancement heterogeneous and thickened pituitary stalk were the most common radiological alterations. Conclusion: Hypophysitis should be considered in the differential diagnosis of sellar masses. It can mimic pituitary adenomas in radiological and endocrinological aspects. The different patterns of pituitary hormone deficiencies may be seen in the course of the disease. Arch Endocrinol Metab. 2019;63(1):47-52

Saglik Bilimleri University, Ankara Numune Education and Research Hospital Department of Endocrinology and Metabolism, Ankara, Turkey 2 Saglik Bilimleri University, Ankara Numune Education and Research Hospital Department of Neurosurgery, Ankara, Turkey 1

Correspondence to: Narin Nasiroglu Imga Ankara Numune Education and Research Hospital Department of Endocrinology 06100 â&#x20AC;&#x201C; Ankara, Turkey xnarinx@yahoo.com Received on May/16/2017 Accepted on Oct/5/2018 DOI: 10.20945/2359-3997000000102:

Keywords Primary hypophysitis; secondary hypophysitis; hypopituitarism; diabetes insipidus

ocal or diffuse inflammation and cellular infiltration of the pituitary gland is known as hypophysitis. It is a significant condition, which can mimic the other sellar lesions and result in the destruction of pituitary gland cells. It may also result in isolated anterior and posterior pituitary hormone deficiency or panhypopituitarism (1). Hypophysitis is an uncommon disease accounting for approximately 0.24%-0.88% of all pituitary diseases, with a reported annual incidence rate of one case per 9 million (2-4). Based on histological appearance and pathophysiological mechanism, the inflammation of the pituitary gland is categorized as primary and secondary hypophysitis. Secondary hypophysitis can be originated from neighboring tissue lesions or multisystemic inflammatory diseases (5,6). Primary hypophysitis is classified as lymphocytic (autoimmune), granulomatous, xanthomatous, IgG4-related and lymphoplasmacytic. Arch Endocrinol Metab. 2019;63/1

It also has mixed forms called lymphogranulomatous and xanthogranulomatous hypophysitis. Xanthomatous hypophysitis is characterized by infiltration of foamy histiocytes in the anterior pituitary gland. Causes and natural courses of secondary hypophysitis are variable. According to the anatomical location, hypophysitis lesions are classified into adenohypophysitis, infundibuloneurohypophysitis or panhypophysitis (7). In this study, we aim to present clinical features, neurologic and endocrinologic data, and treatment courses of twelve patients with hypophysitis that followed up in a single-center.

SUBJECTS AND METHODS We retrospectively reviewed our database of 1.293 patients diagnosed with a pituitary mass disease followed at Ankara Numune Education and Research Hospital 47

INTRODUCTION

Clinical characteristics of hypophysitis

Department of Endocrinology between 2010 and 2017. Out of 1.293 patients, 12 patients who had histological confirmation of hypophysitis were included to the study. Demographical and laboratory data, clinical features, endocrinological dysfunction, magnetic resonance imaging (MRI) findings of the pituitary gland, treatment courses and follow-up period were all evaluated. All patients had initial and control MRI images taken of their pituitary gland. Pituitary gland volume was measured by the volume = 1/2 x length x width x height formula, as described in a previous study (8). All patients underwent transsphenoidal microscopic surgery (TSS). After TSS, all specimens were exposed to hematoxylin and eosin (H&E) staining and immunohistochemical staining. After that, according to underlying disease, they were divided into primary or secondary hypophysitis. By the anatomical location, the cases were classified into adenohypophysitis, infundibuloneurohypophysitis or panhypophysitis. Pretreatment and post-treatment plasma concentrations of hormones related to the pituitary gland, such as ACTH, basal cortisol, thyrotropin stimulating hormone (TSH), free T4, free T3, growth hormone (GH), IGF-1, prolactin, folliclestimulating hormone (FSH), luteinizing hormone (LH) and estradiol or total and free testosterone levels, were evaluated. In addition, the function of the posterior pituitary gland was evaluated with clinical symptoms according to plasma and urinary osmolality and plasma sodium levels. The laboratory analyses of all these cases were evaluated. Growth hormone deficiency (GHD) was diagnosed by the insulin tolerance test (ITT) or glucagon test. In patients with clear-cut characteristics of GHD and three other documented pituitary hormone deficits the diagnosis of GHD was made without biochemical testing. Steroid replacement therapy was given to patients with adrenal insufficiency. Adrenal insufficiency diagnosed if a morning cortisol level < 3 μg/dL and a

level > 15 μg/dL likely excluded an adrenal insufficiency diagnosis. In case of cortisol levels between 3-15 μg/dL adrenal insufficiency was assessed using ITT or standarddose ACTH stimulation tests. Peak cortisol levels > 18.1 μ/dL at 30 or 60 minutes excluded adrenal insufficiency. Central hypothyroidism diagnosis confirmed by free T4 level below the laboratory reference range in concurrence with a low, normal, or mildly elevated TSH (9). For the follow-up in the first year, the patients were evaluated every six months after the surgery, followed by every year. The local ethical committee of Ankara Numune Education and Research Hospital approved the study.

RESULTS The frequency of hypophysitis was found 0.9% among our 1.293 cases with pituitary disease. The follow-up time ranged from 6 to 98 months (median: 28 months). Demographical characteristics of 12 cases and pituitary gland volume at the presentation and control are summarized in Table 1. Twelve patients (nine females and three males) with ages ranged between 17 and 61 years (mean age: 44) were evaluated. At the time of diagnosis female patients were not pregnant or in the puerperium period. The mean age at presentation was between fourth and fifth decades in lymphocytic and granulomatous hypophysitis; on the other hand, a case of xanthogranulomatous hypophysitis was younger (27 years). The features suggesting hypophysitis on the MRI scans were: diffuse symmetric enlargement of the pituitary gland, a thickened stalk, expansion of sella turcica and homogeneous or heterogeneous pituitary gland. Mean pituitary gland volume at presentation was found to be 6,115 ± 8,873 mm3. However, in the follow-up period, the mean pituitary gland volume was decreased to 1,009 ± 2,225 mm3. No other major changes were observed radiological image pattern.

Table 1. Demographical data of patients according to those subgrouped with histological diagnosis Mean age, y

Gender Female Male BMI

All

LyHy (n = 4)

GrHy (n = 7)

XantgrHy (n = 1)

44 (17-61)

40 (17-55)

48 (28-61)

9 (75%) 3 (25%)

3 (75%) 1 (%25)

6 (%86) 1 (%14)

1 (100%)

26.8 ± 2.6

26.2 ± 2.4

26.9 ± 2.9

29.1

Pituitary gland volume baseline (mm3)

6,115 ± 8,873

8,169 ± 7,717

5,564 ± 10,403

1,755

Pituitary gland volume after follow-up (mm3)

1,009 ± 2,225

4,415 ± 3,867

174 ± 315

40.5

LyHy: lymphocytic hypophysitis; GrHy: granulomatous hypophysitis; XantgrHy: xanthogranulomatous hypophysitis BMI: body mass index. Values are expressed as mean (range), median or number (%).

Arch Endocrinol Metab. 2019;63/1

Clinical characteristics of hypophysitis

Pituitary surgery was performed for histological diagnosis and to improve the compressive neuropathy symptoms in big-sized pituitary gland and mimicking adenoma cases. In cases of a small-sized pituitary gland, surgery was performed only for histological diagnosis. In four patients diagnosis was made through pituitary biopsy, while in eight patients after pituitary operation. All the patients underwent TSS, and histopathological diagnosis was made through H&E staining and immunohistochemical staining. According to the histopathological features, three types of the hypophysitis were detected: lymphocytic (n = 4), granulomatous (n = 7) and xanthogranulomatous (n = 1). The clinical characteristics, radiological and endocrinologic findings of patients according to histological diagnosis of hypophysitis was given in Table 2. Symptoms were found non-specific, but the most predominant non-endocrine symptoms were headache (67%) and visual field defects (33%), followed by secondary amenorrhea and impotence. The duration of symptoms varied from a few days to over five years. Pituitary gland swelling (33%), compression of the optic chiasm (33%) thickened pituitary stalk (41%) and heterogeneous contrast enhancement (58%) were identified in patients. Endocrinological evaluation was performed in all cases. Pituitary gland dysfunction was seen in variable degrees. Panhypopituitarism was seen

in 50% of the cases and 25% had one or more isolated hormone deficiencies. The most isolated pituitary dysfunctions were suppressed gonadal axis, followed by suppression of pituitary-thyroid axis (75%). Diabetes insipidus (DI) was identified in 17% of patients. At the time of the diagnosis, seven patients received steroid therapy (58%) and nine patients received levothyroxine therapy (75%). Four cases with primary hypophysitis were treated with high doses of glucocorticoids (1g/ day methylprednisolone for three days), followed by tapering gradually (10 mg/day). Complete recovery was observed in one patient (25%). During the follow-up period, six patients remained to receive steroid therapy, seven on levothyroxine therapy and nine on hypogonadotropic hypogonadism therapy. Radiological features of all cases at presentation were evaluated according to MRI focused on the sellar area (Table 3). Heterogeneous contrast enhancement and increased infundibulum thickening were found in 50% of lymphocytic cases and in 57% of granulomatous hypophysitis cases. Cavernous sinus invasion and optic tract compression were found in one case of lymphocytic and one case of granulomatous hypophysitis. Etiology of the hypophysitis including autoimmune diseases and antibodies were investigated in all patients. All the lymphocytic cases were found idiopathic. Granulomatous hypophysitis cases were

Table 2. The clinical characteristics, radiological and endocrinologic findings of patients according to histological diagnosis of hypophysitis Symptoms and clinical signs

All (n = 12)

LyHy (n = 4)

GrHy (n = 7)

XantgrHy (n = 1)

Headache

8 (67%)

2 (50%)

5 (71%)

1 (100%)

Weight gain

2 (16%)

1 (25%)

1 (14%)

Nausea, vomiting

3 (25%)

1 (25%)

2 (29%)

Visual defects

4 (33%)

2 (50%)

2 (29%)

Amenorrhea/impotence

5 (41%)

1 (25%)

3 (43%)

1 (100%)

Pituitary gland swelling

4 (33%)

2 (50%)

2 (29%)

Compression of the optic chiasm

4 (33%)

1 (25%)

3 (43%)

Thickened pituitary stalk

5 (41%)

2 (50%)

3 (43%)

Contrast enhancement heterogeneous

7 (58%)

2 (50%)

4 (57%)

1 (100%)

Diabetes insipidus

2 (17%)

1 (25%)

1 (14%)

Hypogonadism

9 (75%)

3 (75%)

6 (86%)

GH deficiency

6 (50%)

2 (50%)

4 (57%)

Hypothyroidism

9 (75%)

4 (100%)

5 (71%)

Adrenal insufficiency

7 (58%)

4 (57%)

Hyperprolactinemia

1 (8%)

1 (14%)

Initial radiological signs

1 (25%)

Initial endocrinological disturbance

LyHy: lymphocytic hypophysitis; GrHy: granulomatous hypophysitis; XantgrHy: xanthogranulomatous hypophysitis; GH: growth hormone. Arch Endocrinol Metab. 2019;63/1

Clinical characteristics of hypophysitis

evaluated; three patients had secondary granulomatous hypophysitis and four patients were idiopathic. All three cases of secondary hypophysitis were diagnosed with tuberculosis hypophysitis and the diagnosis of pituitary tuberculosis was made through a positive tuberculin skin test and response of an interferon-gamma release by QuantiFERON TB- Gold test. These patients received antituberculous therapy. In the follow-up period, no recurrence of hypophysitis was observed in patients. The visual functions were improved in patients who had optic tract compression. Contrarily, the hormonal deficiencies were not improved and were aggravated after the diagnosis in some patients.

the entire pituitary gland (panhypophysitis) (13). Infundibuloneurohypophysitis is related to the etiological diagnosis of anterior hypopituitarism, particularly GH deficit, and secondary hypogonadism and DI (14). In other studies, it was reported that primary hypophysitis was usually seen in the anterior lobe of hypophysitis (15), and symptoms due to anterior pituitary hormone deficiency were the highest (16). This anterior pituitary deficiency was most common in our study group. Most of our patients had adenohypophysitis involvement, and DI was seen in 16% of the patients. These patients had panhypophysitis and infundibuloneurohypophysitis. In the literature, it was reported that infundibuloneurohypophysitis is a cause of central DI (17,18). Primary hypophysitis is commonly idiopathic, but in some cases it is related to other autoimmune diseases, such as autoimmune polyglandular syndrome (APS), Hashimoto thyroiditis, Graves’ disease, type 1 diabetes mellitus, systemic lupus erythematosus and Sjögren’s syndrome. Secondary hypophysitis causes are variable and consist of local pituitary lesions (adenomas, craniopharyngiomas, Rathke’s cleft cysts, germinomas and meningiomas), systemic inflammatory diseases (sarcoidosis, granulomatosis with polyangiitis, vasculitis), infectious diseases (tuberculosis, syphilis, aspergillosis, coccidioidomycosis), infiltrative diseases (hemochromatosis, amyloidosis, Langerhans cell histiocytosis) and secondary to treatment (anti-CTLA-4 monoclonal antibodies, interferon-alfa), but the source is frequently unknown. Lymphocytic hypophysitis is

DISCUSSION The natural course of hypophysitis is variable, ranging from spontaneous recovery to death. The prevalence and incidence of hypophysitis are not known with accuracy. In previous studies, the frequency of hypophysitis tends to be more in females (10,11). Our study confirmed the male/female ratio of 1:3 with the dominance of females reported in recent studies. The hormonal and clinical manifestations of hypophysitis are variable for all types. The signs and symptoms are related to anterior or posterior pituitary hormone deficiency and compression of sella. It is estimated that the immune system affects the anterior lobe, posterior lobe or both and caused hormone deficiency (12). According to clinical and neuroradiological findings, hypophysitis can involve the anterior pituitary gland, infundibulum, posterior lobe (infundibuloneurohypophysitis) or

Table 3. The clinicopathological characteristics and radiological features of the patients included in this study Gland volume (cm3)

Enhancement

Infundibulum Thickening

4,872

Homo

Yes

19,656

Homo

Yes

17, F

5,148

Hetero

40, M

3,000

Hetero

1,200

Homo

28,910

Homo

Yes

61, F

1,568

Homo

Yes

Granulomatous

48, F

495

Hetero

Granulomatous

48, F

750

Hetero

Granulomatous

51, F

1,073

Hetero

Yes

Granulomatous

28, M

4,959

Hetero

Yes

Xhanthogranulomatous

27, M

1,755

Hetero

Yes

Case nº

Diagnosis

Age, Gender

Size (mm)

Lymphocytic

31, F

Lymphocytic

55, F

Lymphocytic

Granulomatous

39, F

Granulomatous

37, F

Granulomatous

8 9 10 11 12

Cavernous sinus invasion

Optic tract compression

F: female; M: male.

Arch Endocrinol Metab. 2019;63/1

initially characterized by lymphocytic infiltration and expansion of the pituitary gland, and followed by destruction of the pituitary cells (12). Granulomatous hypophysitis is characterized by infiltration by histiocytes and giant cells. Xanthomatous hypophysitis is a very uncommon form of hypophysitis, and histologically it is characterized by infiltration of foamy histiocytes in the pituitary gland (19). Lymphocytic hypophysitis is the most common subtype of hypophysitis (7), but the granulomatous type was the most common type seen among our patients. In our patients, 67% had granulomatous hypophysitis and 33% had lymphocytic hypophysitis. Based on the histopathologic features IgG4 related hypophysitis is a rare type of hypophysitis, but IgG4 positivity was not found in our patients. The courses of primary and secondary hypophysitis are variable and unpredictable (20). Naturally, in the pituitary gland, inflammation primarily occurs and then is followed by edematous and an enlarged gland, and then the secondary mass effects are developed. The mechanism is due to the destruction of pituicytes, and the parenchyma is replaced by fibrosis. This results in pituitary atrophy and leads to hypopituitarism. The disease course may be rapidly destructive and aggressive (21). In some cases in the literature, the partial or full recovery resolution of pituitary functions has been recognized (22,23). In our study, full recovery was seen in only one case. Partial recovery of pituitary function was seen in 17% of patients, and 50% of patients remained unchanged in pituitary functions during follow-up. Long-term follow-up is essential for possible hypopituitarism due to development of empty sella. In the management of hypophysitis, a symptomatic treatment approach is usually needed. Symptomatic treatment can both minimize the size of the pituitary mass and replace the defective endocrine function. Observation with replacement for deficient pituitary hormones, TSS, radiotherapy, medical treatment with immunosuppressant drugs such as glucocorticoids, azathioprine, methotrexate or cyclosporine A are treatment options to reduce the mass effect. Owing to the lymphocytolytic features, the glucocorticoids are efficient for reducing the volume of the pituitary mass and the thickened stalk (24,25). Therewithal, the treatment of secondary hypophysitis must be focused for the etiology of underlying disease and simultaneous missing hormone replacement. In addition, providing the histological diagnosis surgery can achieve sellar mass decompression and resolve the symptoms of mass Arch Endocrinol Metab. 2019;63/1

effect. In our patients, of all who underwent surgical treatment, three of five patients who had lymphocytic hypophysitis who received high dose glucocorticoid treatment, and three of seven patients who had granulomatous hypophysitis who had treatment of underlying disease showed significant mass reduction. Complete recovery without any hormone replacement was observed in one patient. We consider that the diffuse lymphocytic and granulomatous infiltration leads to cell destruction in the pituitary gland and resulted in irreversible pituitary hormone dysfunction. As seen in our patients, the individuals who had hypopituitarism usually did not benefit from surgical decompression and high dose glucocorticoid treatment. After the fibrous stage of hypophysitis, the responsiveness of glucocorticoid therapy is decreased. Surgical treatment is generally appropriate for achieving decompression of pituitary masses, however, it infrequently improved hormone deficiency. It is suggested that surgery should generally be performed in the presence of critical and progressive deficits of visual fields and in patients who are unresponsive to medical treatment. Surgery also has some complications, such as bleeding, cerebrospinal fluid leaks and DI (26). Consequently, in the treatment of hypophysitis in the absence of symptoms related to mass effect, the replacement of missing hormones must be performed. After that, hypophysitis should be distinguished as primary or secondary. If the diagnosis of primary hypophysitis is made, high dose glucocorticoid therapy should be given, for the secondary hypophysitis appropriate management of underlying disease still remains incontrovertible. Pituitary tuberculosis is a rare cause of a secondary hypophysitis. All our three cases of secondary hypophysitis were diagnosed with tuberculosis hypophysitis, without the systemic manifestations of tuberculosis infection. The histological studies showed chronic inflammatory lesions of granulomatous type in different phases, leading to different degrees of destruction and necrosis of the pituitary gland with giant cells. The diagnosis of pituitary tuberculosis was made through a positive response of an interferongamma release by QuantiFERON TB- Gold test and positive tuberculin skin test. A confirmation by acid fast Bacilli, and chain polymerase reaction for detection of mycobacterial DNA, and Ziehl-Neelsen staining tests of pituitary biopsy were found negative. Patients received antituberculous therapy at least one year. In 51

Clinical characteristics of hypophysitis

the follow-up period, no recurrence of hypophysitis was observed in patients. The limitation of our study is the lack of serum anti-pituitary auto-antibodies (APA) and serum antihypothalamus auto-antibodies (AHA) because these tests have not been routinely available in our laboratory. It was suggested that high positivity of APA and AHA has the potential to be helpful in the diagnosis of hypophysitis (27) but autoantigens are poorly defined (28). In conclusion, hypophysitis should be kept in mind in patients with hormone deficiencies and sellar masses. It can mimic pituitary adenomas in radiological and endocrinological aspects. The different patterns of anterior pituitary hormone deficiencies and diabetes insipidus may be seen in the course of disease. The deficit of the anterior pituitary hormones was seen most commonly in our cases of hypophysitis. In the absence of surgical decompression, the first-line therapy must be the replacement of missing hormones. Surgical treatment should be done to reduce the size of the mass and degree of compressive neuropathy, such as ophthalmoplegia and visual field defects. The goal of the medical treatment is consistent with high dose glucocorticoids for primary hypophysitis, and for secondary hypophysitis is underlying disease. Due to possible development of empty sella long-term, followup is necessary in all hypophysitis cases. Funding: nothing to declare. Disclosure: no potential conflict of interest relevant to this article was reported.

REFERENCES 1. Thodou E, Asa SL, Kontogeorgos G, Kovacs K, Horvath E, Ezzat S. Clinical case seminar: lymphocytic hypophysitis: clinicopathological findings. J Clin Endocrinol Metab. 1995;80(8):2302-11. 2. Caturegli P, Iwama S. From Japan with love: another tessera in the hypophysitis mosaic. J Clin Endocrinol Metab. 2013;98(5):1865-8. 3. Falorni A, Minarelli V, Bartoloni E, Alunno A, Gerli R. Diagnosis and classification of autoimmune hypophysitis. Autoimmun Rev. 2014;13(4-5):412-6.

4. Buxton N, Robertson I. Lymphocytic and granulocytic hypophysitis: a single centre experience. Br J Neurosurg. 2001;15(3):242-5. 5. Sautner D, Saeger W, Lüdecke DK, Jansen V, Puchner MJ. Hypophysitis in surgical and autoptical specimens. Acta Neuropathol. 1995;90(6):637-44. 6. Allix I, Rohmer V. Hypophysitis in 2014. Ann Endocrinol (Paris). 2015;76(5):585-94. 7. Caturegli P, Newschaffer C, Olivi A, Pomper MG, Burger PC, Rose NR. Autoimmune hypophysitis. Endocr Rev. 2005;26(5):599-614. 8. Lurie SN, Doraiswamy PM, Husain MM, Boyko OB, Ellinwood EH Jr, Figiel GS, et al. In vivo assessment of pituitary gland volume

with magnetic resonance imaging: the effect of age. J Clin Endocrinol Metab. 1990;71(2):505-8. 9. Fleseriu M, Hashim IA, Karavitaki N, Melmed S, Murad MH, Salvatori R, et al. Hormonal replacement in hypopituitarism in adults: an endocrine society clinical practice guideline. J Clin Endocrinol Metab. 2016;101(11):3888-921. 10. Honegger J, Fahlbusch R, Bornemann A, Hensen J, Buchfelder M, Müller M, et al. Lymphocytic and granulomatous hypophysitis: experience with nine cases. Neurosurgery. 1997;40(4):713-22. 11. Imber BS, Lee HS, Kunwar S, Blevins LS, Aghi MK. Hypophysitis: a single-center case series. Pituitary. 2015;18(5):630-41. 12. Rivera A. Lymphocytic hypophysitis: disease spectrum and approach to diagnosis and therapy. Pituitary. 2006;9(1):35-45. 13. Flanagan DE, Ibrahim AE, Ellison DW, Armitage M, Gawne-Cain M, Lees PD. Inflammatory hypophysitis – the spectrum of disease. Acta Neurochir (Wien). 2002;144(1):47-56. 14. Chiloiro S, Tartaglione T, Angelini F, Bianchi A, Arena V, Giampietro A, et al. An overview of diagnosis of primary autoimmune hypophysitis in a prospective single-center experience. Neuroendocrinology. 2017;104(3):280-90. 15. Tashiro T, Sano T, Xu B, Wakatsuki S, Kagawa N, Nishioka H, et al. Spectrum of different types of hypophysitis: a clinicopathologic study of hypophysitis in 31 cases. Endocr Pathol. 2002;13(3):183-95. 16. Cheung CC, Ezzat S, Smyth HS, Asa SL. The spectrum and significance of primary hypophysitis. J Clin Endocrinol Metab. 2001;86(3):1048-53. 17. Ahmed SR, Aiello DP, Page R, Hopper K, Towfighi J, Santen RJ. Necrotizing infundibulo-hypophysitis: a unique syndrome of diabetes insipidus and hypopituitarism. J Clin Endocrinol Metab. 1993;76(6):1499-504. 18. Imura H, Nakao K, Shimatsu A, Ogawa Y, Sando T, Fujisawa I, et al. Lymphocytic infundibuloneurohypophysitis as a cause of central diabetes insipidus. N Engl J Med. 1993;329(10):683-9. 19. Cosman F, Post KD, Holub DA, Wardlaw SL. Lymphocytic hypophysitis. Report of 3 new cases and review of the literature. Medicine (Baltimore). 1989;68(4):240-56. 20. Gutenberg A, Hans V, Puchner MJ, Kreutzer J, Brück W, Caturegli P, et al. Primary hypophysitis: clinical-pathological correlations. Eur J Endocrinol. 2006;155(1):101-7. 21. Tanaka S, Tatsumi KI, Kimura M, Takano T, Murakami Y, Takao T, et al. Detection of autoantibodies against the pituitary-specific proteins in patients with lymphocytic hypophysitis. Eur J Endocrinol. 2002;147(6):767-75. 22. Castle D, de Villiers JC, Melvill R. Lymphocytic adenohypophysitis. Report of a case with demonstration of spontaneous tumour regression and a review of the literature. Br J Neurosurg. 1988;2(3):401-5. 23. McGrail KM, Beyerl BD, Black PM, Klibanski A, Zervas NT. Lymphocytic adenohypophysitis of pregnancy with complete recovery. Neurosurgery. 1987;20(5):791-3. 24. Yamagami K, Yoshioka K, Sakai H, Fukumoto M, Yamakita T, Hosoi M, et al. Treatment of lymphocytic hypophysitis by high-dose methylprednisolone pulse therapy. Intern Med. 2003;42(2):168-73. 25. Kristof RA, Van Roost D, Klingmüller D, Springerb W, Schramm J. Lymphocytic hypophysitis: non-invasive diagnosis and treatment by high dose methylprednisolone pulse therapy? J Neurol Neurosurg Psychiatry. 1999;67(3):398-402. 26. Ciric I, Ragin A, Baumgartner C, Pierce D. Complications of transsphenoidal surgery: results of a national survey, review of the literature, and personal experience. Neurosurgery. 1997;40(2):225-36. 27. Kleinschmidt-DeMasters BK, Lopes MB. Update on hypophysitis and TTF‐1 expressing sellar region masses. Brain Pathol. 2013;23(5):495-514. 28. Lupi I, Broman KW, Tzou SC, Gutenberg A, Martino E, Caturegli P. Novel autoantigens in autoimmune hypophysitis. Clin Endocrinol (Oxf). 2008;69(2):269-78. Arch Endocrinol Metab. 2019;63/1

original article

Basal metabolic rate in Brazilian patients with type 2 diabetes: comparison between measured and estimated values Thais Steemburgo1,2,3, Camila Lazzari2, Juliano Boufleur Farinha4, Tatiana Pedroso de Paula3, Luciana Vercoza Viana3, Alvaro Reischak de Oliveira4, Mirela Jobim de Azevedo3

ABSTRACT Objectives: The aims of this study are to investigate which of the seven selected predictive equation for estimating basal metabolic rate (BMR) is the best alternative to indirect calorimetry (IC) and to evaluate the dietary energy intake in patients with type 2 diabetes. Subjects and methods: Twentyone patients with type 2 diabetes participated in this diagnostic test study. Clinical and laboratorial variables were evaluated as well as body composition by absorptiometry dual X-ray emission (DXA) and BMR measured by IC and estimated by prediction equations. Dietary intake was evaluated by a quantitative food frequency questionnaire. Data were analyzed using Bland–Altman plots, paired t-tests, and Pearson’s correlation coefficients. Results: Patients were 62 (48-70) years old, have had diabetes for 8 (2-36) yeas, and 52.4% were females. The mean body composition comprised a fat-free mass of 49.8 ± 9.4 kg and a fat mass of 28.3 ± 7.2 kg. The energy intake was 2134.3 ± 730.2 kcal/day and the BMR by IC was 1745 ± 315 kcal/day. There was a wide variation in the accuracy of BMR values predicted by equations when compared to IC BMR measurement. Harris-Benedict, Oxford, FAO/WHO/ UNO equations produced the smallest differences to IC, with a general bias of < 8%. The FAO/WHO/ UNO equation provided the best BMR prediction in comparison to measured BMR. Conclusion: In patients with type 2 diabetes, the equation of the FAO/WHO/UNO was the one closest to the BMR values as measured by IC. Arch Endocrinol Metab. 2019;63(1):53-61

INTRODUCTION

ype 2 diabetes is the most common form of the diabetes mellitus (DM), usually occurs in adult life, and is associated with obesity in about 80% of cases. The primary strategy for treating obese patients with type 2 diabetes is the loss of body mass through changes in lifestyle, which has been associated with improvement in glycemic control (1). Among these interventions, an appropriate dietary prescription with the goal of reducing body weight, taking into account each patient’s daily energy needs, is essential. The main energy requirement component is the total energy expenditure (TEE), and calculating the TEE requires knowledge of the basal metabolic rate (BMR) (2). The most accurate procedure for measuring BMR is indirect calorimetry (IC), which is considered the Arch Endocrinol Metab. 2019;63/1

Correspondence to: Thais Steemburgo Programa de Pós-Graduação em Alimentação, Nutrição e Saúde, Universidade Federal do Rio Grande do Sul (UFRGS) Rua Ramiro Barcelos, 2400, 2º andar 90035-003 – Porto Alegre, RS, Brasil tsteemburgo@gmail.com Received on Jan/23/2018 Accepted on Dec/12/2018 DOI: 10.20945/2359-3997000000103

reference method. However, its use is limited due to equipment costs, the need for qualified and trained personnel, and time constraints. In clinical practice, several predictive equations have been developed as alternative methods for estimating BMR (3-6). The variability of BMR may depend on several factors, such as sex, ethnicity, age, physical activity, genetic factors, the presence of diabetes or obesity, body composition, and caloric intake (7). Several studies have evaluated BMR using prediction equations in different populations (8-10) and specific ethnic groups, as demonstrated in the US and Dutch (11), Belgian (12), Pima Indians (13), Caucasians (14) and Asian populations (15-18) In nondiabetic individuals, different studies have demonstrated that the equations described by Harris53

Keywords Indirect calorimetry; basal metabolic rate; energy metabolism; type 2 diabetes

Programa de Pós-Graduação em Alimentação, Nutrição e Saúde, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brasil 2 Departamento de Nutrição, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brasil 3 Divisão de Endocrinologia, Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brasil 4 Escola de Educação Física, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brasil 1

Basal metabolic rate in type 2 diabetes

Benedict (3), Schofield (4), Mifflin-St. Jeor (5), and the FAO/WHO/UNO (6) can overestimate or underestimate the BMR value as compared with IC. A cross-sectional study in Brazilian eutrophic and obese men showed a variation between the prediction equations as compared to IC (8). The equation that was closest to the BMR was the one proposed by Mifflin-St. Jeor, with a difference of -9.1% in obese subjects and of 0.9% in eutrophic subjects (8). In 40 obese Brazilian women, the equations of Harris and Benedict and the FAO/WHO/UNO that use weight and height in their formulas were the only ones that did not present statistically significant differences when compared to IC (9). Finally, in another study conducted in 86 Spanish obese women also submitted to a dietary intervention, the most accurate formula for estimating BMR was the Mifflin-St. Jeor equation and the smallest bias was demonstrated by Owen’s equation using IC as the reference method (10). In patients with type 2 diabetes data on BMR prediction equations have been previously described (13,14,16-22), however, in Brazilian diabetic patients it was scarcely investigated (19). Indeed, one study that included only Brazilian obese women with type 2 diabetes, the equation of Mifflin-St. Jeor underestimated BMR in -2.6% and the FAO/WHO/UNO equation overestimated BMR in 10.6% as compared with IC (19). Two other studies proposed formulas for predicting BMR in diabetic patients, irrespective of sex (20,21). In a cross-sectional study conducted in 65 patients with type 2 diabetes, the inclusion of fasting blood glucose as a variable in a BMR predictive formula improved its predictability for real BMR by > 3% (20). Hyperglycemia, defined as fasting blood glucose > 180 mg/dL, increased the BMR by up to 8% (20). A retrospective analysis of severely obese patients was performed to compare the BMR of patients with and without diabetes (21). Obese Japanese patients with diabetes had a higher BMR than nondiabetic patients (18) and the presence of diabetes should be included as a variable in their proposed BMR predictive equation (21). In fact, the association of poor glycemic control with a high BMR, as evaluated by high A1c values, has already been demonstrated (22). In addition, the reduction of BMR has been negatively associated with both endogenous and exogenous insulin values, as demonstrated in a study conducted in 58 patients with type 2 diabetes (23). Given that most predictive equations overestimate BMR in obese subjects, that the majority of patients 54

with diabetes are obese or overweight, and that hyperglycemia has been associated with an increase in BMR, it is important to evaluate the best prediction equations for calculating BMR in order to recommend an adequate dietary intervention for diabetic patients. In addition, studies in Brazilian diabetics are scarce, the aim of the present study was to evaluate which predictive BMR equation was the best alternative to IC in Brazilian patients with type 2 diabetes.

SUBJECTS AND METHODS Study design and patients This diagnostic study test was conducted in 21 patients with type 2 diabetes, defined as patients over 30 years of age at onset of diabetes, with no previous episode of ketoacidosis or documented ketonuria, and treatment with insulin only after 5 years of diagnosis. Patients attending the outpatient clinic of the Endocrine Division of the Hospital de Clínicas de Porto Alegre, Brazil were selected on the basis of the following criteria: did not receive dietary counseling from a registered dietitian during the previous 6 months, age < 80 years, serum creatinine < 2 mg/dL, normal liver and thyroid function tests, and absence of renal disease, cardiac failure, or any acute or consumptive disease. The study protocol was approved by the Ethics Commission of Hospital de Clínicas de Porto Alegre (number 15.0625) and all subjects signed a written consent form.

Clinical evaluation Patients were classified as current smokers or not. Physical activity status, according to activities during a typical day and based on the short version of the International Physical Questionnaire (IPAQ) (24) adapted to local habits (25), was classified into three levels: (1) low, (2) moderate, and (3) high. Blood pressure was measured twice to the nearest 2 mmHg, after a 10 minutes rest, using an Omron HEM-705CP digital sphygmomanometer (Omron Healthcare, Inc., Bamockburn, IL, USA). Hypertension was defined as blood pressure ≥ 140/90 mmHg measured on two occasions or the use of antihypertensive drugs (26). The body weight and height of patients (without shoes and coats) were obtained using a calibrated and anthropometric scale (Filizola®). Measurements were recorded to the nearest 100g for weight and to the Arch Endocrinol Metab. 2019;63/1

Basal metabolic rate in type 2 diabetes

Dietary assessment The usual diet was evaluated by the quantitative food frequency questionnaire (FFQ) previously validated for patients with diabetes which details 80 items divided into 10 food groups (27).

Laboratory measurements Blood samples were obtained after a 12-hour fasting. Plasma glucose level was determined by a glucose oxidase method, the A1c test by ion exchange highperformance liquid chromatography (Merck-Hitachi L-9100 glycated hemoglobin analyzer, reference range 4.7%-6.0%; Merck Diagnostica, Darmstadt, Germany), serum cholesterol and triglycerides by enzymatic colorimetric methods (Merck; Boeringher Mannheim, Buenos Aires, Argentina), and high-density lipoprotein (HDL) cholesterol by a homogeneous direct method (autoanalyzer, ADVIA 1650). Low-density lipoprotein (LDL) cholesterol was calculated using the Friedewald formula: LDL cholesterol = total cholesterol – HDL cholesterol – triglycerides/5.

Basal metabolic rate measurement The measurement of BMR was performed by IC. The IC protocol consisted of 10 min of rest on a gurney in dorsal decubitus, followed by 30 minutes of collection of exhaled gases using the canopy dilution technique and a coupled collection device. An open circuit calorimeter (QUARK RMR, Cosmed, Rome, Italy) was used for determining VO2 (oxygen consumption) and VCO2 (carbon dioxide production). To calibrate the equipment, the volume of the turbine flowmeter was first calibrated electronically by the system, followed by calibration of the collector plates using a known gas concentration. This process was repeated for each test to standardize the measurement. The first 10 min of gas collection were excluded from the analysis; thus, VO2 and VCO2 (L/min) obtained during the final 20 min of each collection (mean value of the period) were used Arch Endocrinol Metab. 2019;63/1

for the calculation of BMR. The equation proposed by Weir (28) was used to obtain values in kcal/min, which does not require the use of protein metabolism by incorporating a correction factor: [(3.9 x VO2) + (1.1 x VCO2)]. The result in kcal/min was multiplied by 1,440 min to obtain the value for 24 hours. The subjects were asked not to perform any type of physical activity of moderate or high intensity during the 24 hours preceding the test, and not to consume alcohol or caffeine. The smoking patients were instructed not to smoke 12 hours before the day of BMR measurement. Additionally, the subjects were instructed to fast for 12 hours prior to the test, with only the ad libitum intake of water being permitted, and to have a good night’s sleep of at least 8 hours. Finally, all subjects came to the test site using a motor vehicle to avoid energy expenditure before the determination of BMR. All tests were performed between 07:00 and 08:00 in a temperature-controlled (20 ºC to 25 ºC) and soundcontrolled room under low luminosity. All medications in use were maintained during the study period and patients received their usual medication after the IC.

Selection of equations for estimating basal metabolic rate (BMR) Predictive equations for estimating BMR were selected by searching previous publications on this subject (8-21). To be included, the equations had to have been developed for adults, men, and women, and based on body weight, height, age, sex, and/or fat mass (FM). Equations derived only for specific ethnic groups or for subjects with BMI ≥ 40 kg/m2 were not included. In accordance with these criteria, we included a total of seven BMR equations (Supplement 1).

Statistical analyses The sample size calculation was based on a study conducted in obese and normal-weight subjects that evaluated the accuracy of predictive BMR equations for estimating energy expenditure as compared to IC (8). Assuming an alpha error of 5% and a power of 80%, a total of 21 patients with type 2 diabetes could be included. The BMR was estimated by seven prediction equations commonly used according to sex and age: Harris-Benedict (5), Schofield (6), Mifflin-St. Jeor (7), FAO/WHO/UNO (8), Gougeon (20), Bernstein (29), and Oxford (30). We also evaluated the estimated caloric intake (27) versus measured 55

nearest 0.1 cm for height. Body mass index (BMI) was calculated as weight in kilograms divided by the square of the height in meters. Body composition was assessed by dual-energy X-ray absorptiometry (Healthcare® GE Medical Systems) for determining fat mass (kg) and fat-free mass (FFM) (kg). The procedure was performed in a specialized clinic by an imaging specialist.

Basal metabolic rate in type 2 diabetes

BMR. The Shapiro-Wilk normality test was used to determine the distribution of the variables. The bias was calculated as follows: estimated BMR – measured BMR. For each prediction equation the percentage of deviation of estimated BMR from measured BMR was calculated: [(estimated BMR − measured BMR) / measured BMR] × 100. Estimated and measured BMR was compared by paired Student’s t-test. The agreement between estimated and measured BMR was graphically examined by plotting the differences between the predicted and the measured BMR against their mean values, with 95% limits of agreement (mean difference ± 1.96 standard deviation of the difference) (31). Pearson’s correlation coefficient was used to assess the correlation between estimated and measured BMR. Results are expressed as means and standard deviations, or medians (P25-P75). Data were analyzed using SPSS version 21.0, and Bland and Altman plot values were analyzed by the R Project for Statistical

Computing software (version 3.3.3). A p value of < 0.05 was considered significant.

RESULTS Twenty-one patients with type 2 diabetes were evaluated [62 (48-70) years of age; 28.6% were older than 65 years old, 8 (2-36) years of diabetes duration and 52.4% of women]. Most patients in the study were sedentary (66.7%), and 90.5% were overweight/obese. The mean body composition comprised 49.8 ± 9.4 kg of fat-free mass and 28.3 ± 7.2 kg of fat mass. The mean total energy intake was 2134.3 ± 730.2 kcal/day. Also, the presence of hypertension was observed in all patients (100%). The lipid profile was within normal limits; however, the glycemic control expressed by fasting glucose and A1c test showed altered levels, as expected in diabetic patients. With regard to drug treatment, all patients used oral antihyperglycemic agents (100%)

Supplement 1. Selected equations for estimating basal metabolic rate (BMR) Reference Harris-Benedict (3) Men Women Schofield (4) Men age < 60 years Men age > 60 years Women age < 60 years Women age > 60 years

Number of subjects

Sample characteristics

Weight/BMI

66 + [13.8 x W (kg)] + [5.0 x Ht (cm)] – [6.8 x (A)] 655 [9.5 x W (kg)] + [1.9 x Ht (cm)] – [4.7 x (A)]

Healthy adults

[0.048 x W (kg) + 3.653] x 239 [0.049 x W (kg) + 2.459] x 239 [0.034 x W (kg) + 3.538] x 239 [0.028 x W (kg) + 2.755] x 239

Mifflin-St. Jeor (5) Men Women

[W (kg) x 10] + [Ht (cm) x 6.25] – [(A) x 5] + 5 [W (kg) x 10] + [Ht (cm) x 6.25] – [(A) x 5] + 5 -166

251 men 247 women

FAO/WHO/UNO (6) Men age < 60 years Men age > 60 years Women < 60 years Women > 60 years

11.6 x W (kg) + 879 13.5 x W (kg) + 487 8.7 x W (kg) + 829 10.5 x W (kg) + 596

7173 men/women

Healthy adults

375 + (85 × W) – (48 × FM) + (63 × FPG)

25 men 40 women

Patients with type 2 diabetes

Bernstein (29) Men

(11.0 x W) + (10.2 x Ht) – (5.8 x A) – 1,032

48 men

Obese

(7.48 x W) + (0.42 x Ht) - (3.0 x A) + 844

154 women

Oxford (30) Men 30-60 years Men > 60 years Women 30-60 years Women > 60 years

14.2 x weight + 593 13.5 x weight + 514 9.74 x weight + 694 10.1 x weight + 569

800 men 5,000 women

Gougeon and cols. (20) Men and women

BMR predictive equations

Healthy adults

100 ± 3 kg 37 ± 1 kg/m²

BMI: body mass index; W: weight; A: age; Ht: height; FM: fat mass; FPG: fasting plasma glucose (mM)*. * Unit of measure described in the original article of the equation (20).

Arch Endocrinol Metab. 2019;63/1

Basal metabolic rate in type 2 diabetes

and antihypertensive agents (100%), and 38.1% (n = 8) used lipid-lowering agents. The characteristics of the sample are described in Table 1. Table 2 shows mean and standard deviation values of measured BMR and estimated BMR with selected predictive equations, bias (percentage deviation) and 95% limits of agreement. The variables assumed a normal distribution according to the Shapiro-Wilk test (data not shown). The mean of the BMR (kcal/day) verified by IC was statistically different by 1,745 ± 315 kcal/day kcal/day from the BMR values (kcal/day) estimated by the prediction equations. According to the percentage, the prediction equation that underestimated the measured BMR the most were those of Bernstein (-20.1%), followed by Mifflin-St Jeor (-13.6%) and Schofield (-11.7%). Also, the equations that in lower values underestimated the measured BMR were the Harris-Benedict (-7.8%) equation when using weight and height together and the Oxford equation (-7.6%) when using only weight. The value of overestimation (8.7%) observed corresponded to the equation reported by Gougeon and cols. (20) when including FM and fasting plasma glucose (FPG). The equation that most

closely estimated the BMR measured was that of the FAO/WHO/UNO (-5.6%), which also uses only the weight in its formula. When we evaluated energy intake by FFQ vs. the BMR by CI, was observed a difference of approximately 400 kcal/day (2134.3 ± 730.2 vs. 1745 ± 315 kcal/day, respectively), which corresponds to an overestimation of 23%. The Bland and Altman plots for the difference between predicted and measured BMR against the mean obtained equations are reported in Figure 1. The graphs demonstrating the agreement between the values of measured and estimated BMR suggest a poor correlation between the two methods, with wide limits of agreement. However, strong positive correlations were observed (p < 0.001) between methods. The correlation shows the association between dependent and independent variables, and BMR was significantly positively correlated (p < 0.01) with fat-free mass (FFM) (r = 0.859), BMI (r = 0.593), sex (r = 0.281), and age (r = 0.509). There were no significant correlations between BMR fat mass, FPG or between BMR and A1 test.

Table 1. Characteristics of patients with type 2 diabetes

There is little research that compares the BMR measured by IC with that estimated by prediction equations in patients with type 2 diabetes. Our study shows a wide range of differences between predicted and measured BMR. The Harris-Benedict (when using weight and height together), and the Oxford and FAO/WHO/ UNO equations (when using only weight), showed mean differences between measurements and predicted BMR < 8%. These results suggest that these three equations are the most suitable equations to estimate BMR in patients with diabetes. However, the equation that presented lower values of bias (-98.2 kcal) and difference (-5.6%) compared to BMR measured by IC was that described by FAO/WHO/UNO. This finding is in agreement with a previous study conducted in women with obesity, but without diabetes, which also demonstrated an underestimation of the formulas proposed by the FAO/WHO/UNO and HarrisBenedict (9). In obese women and men with diabetes, these equations showed an overestimation compared to BMR measured by IC (19,20). Validation studies show that the FAO weight and height equation is the most accurate (32), which is in agreement with our results. An explanation for this could be that this equation derived from a similar ethnic population as found in

Age (years) Duration of diabetes (years)

n (21) 62 (48-70) 8 (2-36)

Sex (female)

11 (52.4%)

Psysical activity – level 1 (sedentarism) (%)

14 (66.7%)

Weight (kg)

85.2 ± 18.0

Height (cm)

168.3 ± 10.2

BMI (kg/m²)

29.4 (20.2-37.4)

Fat-free mass (kg) Fat mass (kg) Total energy intake (kcal/day) Hypertension (%)

49.8 ± 9.4 28.3 ± 7.2 2134.3 ± 730.2 21 (100%)

Fasting plasma glucose (mg/dL)

155.6 ± 58.4

A1C test (%)

7.6 (6.1-10.0)

Total cholesterol (mg/dL) LDL cholesterol (mg/dL) HDL cholesterol (mg/dl) Triglycerides (mg/dL) Medications Oral antihyperglycemic Antihypertensive agents Hypolipidemic agents

166.4 ± 36.1 88.7 ± 32.8 47.2 ± 14.2 145 (49-342) 21 (100%) 21 (100%) 8 (38.1%)

Data are presented as median (25th-75th), percentage (%) or mean ± standard deviation. BMI: body mass index; A1C: glycated hemoglobin; HDL: high-density lipoprotein; LDL: lowdensity lipoprotein. Arch Endocrinol Metab. 2019;63/1

Variable

DISCUSSION

Basal metabolic rate in type 2 diabetes

Brazil, which is mainly composed of a population of European descendants, especially Italians. The Harris-Benedict equation is one of the most commonly used equations in clinical practice and, as it is the oldest, has undergone the most extensive validation (3). A Belgian study which validated BMR equations in 536 women with a wide variety of body weight (18.550 kg/m2) showed that the Harris-Benedict equation and the Mifflin-St. Jeor equation are a reliable tools to predict BMR (12). The Mifflin-St. Jeor equation was developed with a large sample of obese subjects. Several studies proposed this equation as the most valid to estimate BMR in overweight and obese subjects aged 1969 years (78% accurate predictions) (10,12). In our study, the Mifflin-St. Jeor equation presented a bias of -236 kcal, underestimating by -13.6% the value of the BMR measured. In the same way, we observed that

the equations proposed by Schofield and Bernstein presented high values of -193.1 and -368.6 kcal, underestimating the BMR value measured by IC by -11.7% and 20.1%, respectively. Although the Bland and Altman plots revealed a poor agreement between the equations and the IC, it is important to emphasize the correlations found between the methods. However, the correlation indicates only how the two methods interact linearly by not correctly expressing the agreement between them. The findings of this study are clinically relevant and suggest that the best equation for estimating BMR in patients with type 2 diabetes is the one that considers the current weight. We observed a positive correlation of the BMR with BMI (r = 0.593, p = 0.005). This result is in agreement with the study conducted in Brazilian obese women with type 2 diabetes (19). These outcomes corroborate the importance of

Table 2. Evaluation of measured and estimated BMR in patients with type 2 diabetes Variable

Mean

Measured BMR by IC (kcal/day)

1745

315

Harris-Benedict (5)

1607.8

340.0

Bias (kcal/day)

-137.4

95% Limits of Agreement1

p value

Estimated BMR (kcal/day) 2

Percentage %

Schofield (6) Bias (kcal/day) Percentage %3 2

Mifflin-St.Jeor (7) Bias (kcal/day) Percentage %3 2

-7.8 1552.2

387.2

-193.1 -11.7 1508.4

319.0

-236.9 -13.6

Gougeon (20)

1593.55

285.4

-368.6 -21.1

Oxford (30) Bias2 (kcal/day) Percentage %3

1615.1 -130.2 -7.5

0.012† (-416.1; 219.8)

151.8 8.7

Bias2 (kcal/day) Percentage %3

< 0.001† (-540.0; 66.2)

331.1

1376.7

< 0.001† (-534.0; 147.8)

1647.1 -98.2 -5.6

Bernstein (29)

(-486.0; 211.1)

FAO/WHO/UNO (8) Bias2 (kcal/day) Percentage %3 Bias2 (kcal/day) Percentage %3

0.002†

< 0.001† (-206.5; 510.0)

224.3

(-801.2; 64.0)

353.6

< 0.001†

0.002† (-459.5; 199.2)

Paired Student’s t-test: to compared estimated and measured BMR Mean difference ± 1.96 SD of the difference. 2 Estimated − measured (kcal in 24h. 3 Difference/measured) × 100 (%). BMR: basal metabolic rate; IC: indirect calorimetry; SD: standard deviation. † 1

Arch Endocrinol Metab. 2019;63/1

Basal metabolic rate in type 2 diabetes

r = 0.855; p < 0.001

Mean of BMR Harris-Benedict and BMR measured (kcal/day).

BMR Bernstein - BMR measured (kcal/day) BMRBernstein Bernstein- -BMR BMRmeasured measured(kcal/day) (kcal/day) BMR

BMR Schofield - BMR measured (kcal/day)

r = 0.897; p < 0.001

Mean of BMR Gougeon and BMR measured (kcal/day) Mean of BMR Gougeon and BMR measured (kcal/day) Mean of BMR Gougeon and BMR measured (kcal/day)

r = 0.713; p < 0.001 r = 0.713; p < 0.001 r = 0.713; p < 0.001

Mean of BMR Bernstein and BMR measured (kcal/day). Mean of BMR Bernstein and BMR measured (kcal/day). Mean of BMR Bernstein and BMR measured (kcal/day).

Mean of BMR Mifflin-St. Jeor and BMR measured (kcal/day).

r = 0.880; p < 0.001 r = 0.880; p < 0.001 r = 0.880; p < 0.001

Mean of BMR Oxford and BMR measured (kcal/day). Mean of BMR Oxford and BMR measured (kcal/day). Mean of BMR Oxford and BMR measured (kcal/day).

r = 0.875; p < 0.001

Mean of BMR FAO/WHO/UNU and BMR measured (kcal/day)

Arch Endocrinol Metab. 2019;63/1

Figure 1. Bland and Altman plots comparing indirect calorimetry (IC) and the following prediction equations for basal metabolic rate (BMR) in patients with type 2 diabetes: A) Harris-Benedict (5); B) Schofield (6); C) Mifflin-St. Jeor (7); D) FAO/WHO/UNO (8); E) Gougeon and cols. (20); F) Bernstein (31), and G) Oxford (30). 59

r = 0.881; p < 0.001

BMR FAO/WHO/UNU - BMR measured (kcal/day)

r = 0.875; p < 0.001 r = 0.875; p < 0.001 r = 0.875; p < 0.001

Mean of BMR Schofield and BMR measured (kcal/day).

BMR Mifflin-St. Jeor - BMR measured kcal/day)

BMR Gougeon - BMR measured (kcal/day) BMRGougeon Gougeon- -BMR BMRmeasured measured(kcal/day) (kcal/day) BMR

BMR Oxford - BMR measured (kcal/day) BMROxford Oxford- -BMR BMRmeasured measured(kcal/day) (kcal/day) BMR

BMR Harris-Benedict - BMR measured (kcal/day)

Basal metabolic rate in type 2 diabetes

using the weight as an independent variable in the prediction equations to correctly estimate the BMR of patients with diabetes, since the equations selected in this study included weight as independent variable (3-6,20,29,30). It is important to more accurately estimate the BMR of patients with type 2 diabetes with overweight and obesity to promote specific and individualized dietary management for these patients. There is scarce scientific evidence indicating how the presence of diabetes may influence basal metabolism. However, some authors have confirmed higher BMR values in subjects with type 2 diabetes compared with controls without the disease (18,20,29,30). Another factor to consider is the association between diabetes and excessive body weight, since obese people have both increased FM and FFM fat mass and fat-free mass, which contributes to the increase in BMR (33). In patients with type 2 diabetes evaluated in this study, we observed a strong correlation of BMR measured with FFM (r = 0.859; p < 0.001). No correlation was found between BMR and FM. In agreement with other studies, we noted that the inclusion of body composition (FM and/or FFM) into the equations did not improve the accuracy of BMR prediction (10-12). This is a relevant finding because equations based on anthropometric parameters (weight and height) are more feasible in clinical practice than are body composition-based equations. Gougeon and cols. (20) evaluated the BMR of women with type 2 diabetes, proposing an equation to predict the BMR that tested plasma glucose, and FM as some of its independent variables, which justifies a better fit in the model equation. However, when we evaluated, the specific equation for patients with type 2 diabetes, described by Gougeon, using FM and fasting glycemia, it showed an 8.7% overestimation of the measured BMR. In our study, we observed an overestimation of 23% of calorie consumption, which corresponds to around 400 kcal/day. These results suggest that in this group, patients consumed more calories than is actually required for their basal metabolism, and this explains the difficulty of weight loss in patients with obesity and diabetes. Moreover, regardless of the formula used, actual intake is higher than measured intake and estimations. The difference between the equations (-368.6 to -98.2 kcal/day) shows that with the diet prescription, any of the equations would lead to an adequate weight loss. 60

Our findings indicate that in the absence of a gold standard method the best equation for estimating BMR in patients with type 2 diabetes is the equation reported by the FAO/WHO/UNO. This equation presented a smaller value of bias, around -5.6%, and for clinical practice this corresponds to 100 kcal/day less when we apply the formula in this group of patients. It is important to remember that this same group overestimated their calorie intake by 400 kcal/day. The present study is limited in particular by the small sample size and it is also possible to observe a different BMR behavior with regard to sex in the distribution of our group of diabetic patients in the Bland and Altman plots. In fact, sex is a variable that appear to influence BMR. The decreased BMR with increasing age, specifically in women, may also be a result of changes in body composition caused by menopause (34). Also, from the age of 20, women present a reduction of BMR by about 2% per decade, and the decrease of the FFM directly influences this decline (35,36). Thus, for a better evaluation in the comparison of the real BMR and the BMR calculated by prediction equations, we suggest the importance of a study conducted in patients with type 2 diabetes using a larger sample in order to evaluate the difference between the sex with their inherent characteristics. In conclusion, this study showed that there is a great variation in the accuracy of BMR prediction equations. The accuracy of BMR prediction equations should be adequate to promote the efficacy of dietary counseling and treatment of diabetes. The findings showed that among the selected prediction equations, the BMR estimated by the FAO/WHO/UNO equation was the closest to the measured BMR as assessed by the percentage deviation. Funding: This work was supported by the FIPE – Fundo de Incentivo à Pesquisa do Hospital de Clínicas de Porto Alegre (15.0625). Acknowledgments: The authors thank the volunteers and investigating staff. In particular our thanks go to the School of Physical Education of Universidade Federal do Rio Grande do Sul, which made possible the evaluation of BMR by IC. Professor Susi Alves Camey, our thanks for the help in the improvement of statistical analysis of the data this study. Finally, we dedicate this work to our dear Professor Mirela Jobim de Azevedo (in memory) for all the teachings in the research. Our thanks and gratitude for your presence in our lives. Disclosure: no potential conflict of interest relevant to this article was reported. Arch Endocrinol Metab. 2019;63/1

Basal metabolic rate in type 2 diabetes

1. ADA – American Diabetes Association. Standards of medical care in diabetes: lifestyle management. Diabetes Care. 2018;41 Suppl 1:S38-S50.

19. de Figueiredo Ferreira M, Detrano F, Coelho GM, Barros ME, Serrão Lanzillotti R, Firmino Nogueira Neto J, et al. Body composition and basal metabolic rate in women with type 2 diabetes mellitus. J Nutr Metab. 2014;2014:574057.

17. Ikeda K, Fujimoto S, Goto M, Yamada C, Hamasaki A, Megumi I, et al. A new equation to estimate basal energy expenditure of patients with diabetes. Clin Nutr. 2013;32(5):777-82.

20. Gougeon R, Lamarche M, Yale JF, Venuta T. The prediction of resting energy expenditure in type 2 diabetes mellitus is improved by factoring for glycemia. Int J Obes Relat Metab Disord. 2002;26(12):1547-52. 21. Huang KC, Kornas N, Steinbeck, Loughnan, Caterson ID. Resting metabolic rate in severely obese diabetic and nondiabetic subjects. Obes Res. 2004;12(5):840-5. 22. Alawad AO. Merghani TH. Mansour AB. Resting metabolic rate in obese diabetic and obese non-diabetic subjects and its relation to glycaemic control. BMC Research Notes. 2013;6(382):1-5. 23. Ikeda K, Fujimoto S, Goto M, Yamada C, Hamasaki A, Shide K, et al. Impact of endogenous and exogenous insulin on basal energy expenditure in patients with type 2 diabetes under standard treatment. Am J Clin Nutr. 2011;94(6):1513-8. 24. International Physical Activity Questionnaire (IPAQ). Available from: http://www.ipaq.ki.se/ipaq.htm. Accessed on: Nov 20, 2016. 25. Hallal PC, Matsudo SM, Matsudo VKR, Araújo TL, Andrade DR, Bertoldi AD. Physical activity in adults from two Brazilian areas: similarities and differences. Cad Saúde Pública. 2005;21(2):573-80. 26. James PA, Oparil S, Carter BL, Cushman WC, Dennison-Himmelfarb C, Handler J, et al. 2014 evidence-based guideline for the management of high blood pressure in adults: report from the Panel Members Appointed to the Eighth Joint National Committee (JNC 8). JAMA. 2014;311(5):507-20. 27. Sarmento RA, Antonio JP, Riboldi BP, Montenegro KR, Friedman R, Azevedo MJ, et al. Reproducibility and validity of a quantitative food frequency questionnaire designed for patients with type 2 diabetes from Southern of Brazil. Public Health Nutr. 2013:10:1-9. 28. Weir JB. New methods for calculating metabolic rate with special reference to protein metabolism. J Physiol. 1949;109(1-2):1-9. 29. Bernstein RS, Thornton JC, Yang MU, Wang J, Redmond AM, Pierson RN Jr, et al. Prediction of the resting metabolic rate in obese patients. Am J Clin Nutr. 1983;37(4):595-602. 30. Cole TJ, Henry CJ. The Oxford Brookes basal metabolic rate database-a reanalysis. Public Health Nutr. 2005;8(7A):1202-12. 31. Bland J, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986;327(8476):307-10. 32. Frankenfield D, Roth-Yousey L, Compher C. Comparison of predictive equations for resting metabolic rate in healthy nonobese and obese adults: a systematic review. J Am Diet Assoc. 2005;105(5):775-89. 33. Sun MX, Zhao S, Mao H, Wang ZJ, Zhang XY, Yi L. Increased BMR in overweight and obese patients with type 2 diabetes may result from an increased fat-free mass. J Huazhong Univ Sci Technolog Med Sci. 2016;36(1):59-63. 34. Sternfeld B, Bhat AK, Wang H, Sharp T, Quesenberry CP. Menopause, physical activity, and body composition/fat distribution in midlife women. Med Sci Sports Exerc. 2005;37(7):1195-202. 35. Day DS, Gozansky WS, Van Pelt RE, Schwarts RS, Kohrt WM. Sex hormones suppression reduces resting energy expenditure and β-adrenergic support of resting energy expenditure. J Clin Endocrinol Metabolism. 2005;90(6):3312-7.

18. Miyake R, Ohkawara K, Ishikawa-Takata K, Morita A, Watanabe S, Tanaka S. Obese Japanese adults with type 2 diabetes have higher basal metabolic rates than non-diabetic adults. J Nutr Sci Vitaminol (Tokyo). 2011;57(5):348-54.

36. Aubertin-Leheudre M, Goulet EDB, Dionne IJ. Enhanced rate of resting energy expenditure in women using hormone replacement therapy: preliminary results. J Aging Physi Activ. 2008;16(1):53-60.

2. Compher C, Frankenfield D, Keim N, Roth-Yousey L. Best practice methods to apply to measurement of resting metabolic rate in adults: a systematic review. J Am Diet Assoc. 2006;106(6):881-903. 3. Harris J, Benedict FG. A biometric study of human basal metabolism. PNAS. 1918;4(12):370-3. 4. Schofield WN. Predicting basal metabolic rate, new standards and review of previous work. Hum Nutr Clin Nutr. 1985;39(1):5-41. 5. Mifflin MD, St Jeor ST. A new predictive equation for resting energy expenditure in healthy individuals. Am J Clin Nutr. 1990;51(2):241-7. 6. FAO. Energy and protein requirements: Report of a joint FAO/ WHO/UNO expert consultation. Geneva: World Health Organization; 1985. 7. Hagedorn T, Poggiogalle E, Savina C, Coletti C, Paolini M, Scavone L, et al. Indirect calorimetry in obese female subjects: factors influencing the resting metabolic rate. World J Exp Med. 2012;2(3):58-64. 8. Krüger RL, Lopes AL, Gross JS, Macedo RC, Teixeira BC, Oliveira AR. Validation of predictive equations for basal metabolic rate in eutrophic and obese subjects. Rev Bras Cineantropom Desempenho Hum. 2015;17(1):73-81. 9. Poli VFS, Sanches RB, Moraes AS, Fidalgo JPN, Nascimento MA, Andrade-Silva SG, et al. Resting energy expenditure in obese women: comparison between measured and estimated values. Br J Nutr. 2016;116(7):1306-13. 10. Ruiz JR, Ortega FB, Rodríguez G, Alkorta P, Labayen I. Validity of resting energy expenditure predictive equations before and after an energy-restricted diet intervention in obese women. PLoS One. 2011;6 (9):e23759. 11. Weijs PJM. Validity of predictive equations for resting energy expenditure in US and Dutch overweight and obese class I and II adults aged 18-65 y. Am J Clin Nutr. 2010;88:959-70. 12. Weijs PJM, Vansant GA. Validity of predictive equations for resting energy expenditure in Belgian normal weight to morbid obese women. Clin Nutr. 2010;29(3):347-51. 13. Fontvieille AM, Lillioja S, Ferraro RT, Schulz LO, Rising R, Ravussin E. Twenty-four-hour energy expenditure in Pima Indians with type 2 (non-insulin-dependent) diabetes mellitus. Diabetologia. 1992;35(8):753-9. 14. Bitz C, Toubro S, Larsen TM, Harder H, Rennie KL, Jebb SA, et al. Increased 24-h energy expenditure in type 2 diabetes. Diabetes Care. 2004;27(10):2416-21. 15. Liu HY, Lu YF, Chen WJ. Predictive equations for basal metabolic rate in Chinese adults: a cross-validation study. J Am Diet Assoc. 1995;95(12):1403-8. 16. Miyake R, Tanaka S, Ohkawara K, Ishikawa-Takata K, Hikihara Y, Taguri E, et al. Validity of predictive equations for basal metabolic rate in Japanese adults. J Nutr Sci Vitaminol (Tokyo). 2011;57(3):224-32.

Arch Endocrinol Metab. 2019;63/1

REFERENCES

original article

Low levels of dehydroepiandrosterone sulfate are associated with the risk of developing cardiac autonomic dysfunction in elderly subjects Departamento de Ciências do Esporte, Universidade Federal do Triângulo Mineiro (UFTM), Uberaba, MG, Brasil 2 Departamento de Fisiologia, Universidade Federal de Juiz de Fora (UFJF), Juiz de Fora, MG, Brasil 3 Departamento de Endocrinologia e Metabolismo, Curso de Pós-Graduação em Ciências da Saúde, Universidade Federal do Triângulo Mineiro (UFTM), Uberaba, MG, Brasil 4 Departamento de Biociências, Universidade Federal de São Paulo (Unifesp), Santos, SP, Brasil 1

Correspondence to:

Octávio Barbosa Neto, Departamento de Ciências do Esporte, Universidade Federal do Triângulo Mineiro Rua Getúlio Guaritá, 159 38025-180 – Uberaba, MG, Brasil octavio.neto@uftm.edu.br Received on July/9/2017 Accepted on July/8/2018 DOI: 10.20945/2359-3997000000104

Marina de Paiva Lemos1, Munique Tostes Miranda1, Moacir Marocolo2, Elisabete Aparecida Mantovani Rodrigues de Resende3, Rosângela Soares Chriguer4, Carla Cristina de Sordi3, Octávio Barbosa Neto1

ABSTRACT Objective: To assess the relationships between serum dehydroepiandrosterone sulfate (DHEA-S) levels and heart rate variability (HRV) among different age groups. Subjects and methods: Fortyfive healthy men were divided into 3 groups: young age (YA; 20-39 yrs; n = 15), middle age (MA; 40-59 yrs; n = 15) and old age (OA; ≥ 60 yrs; n = 15). Hemodynamic parameters, linear analyses of HRV and concentrations of cortisol and DHEA-S were measured at rest. Results: The OA group presented a higher resting heart rate (84.3 ± 4.6 bpm) than the YA group (72.0 ± 4.4 bpm; p < 0.05). The YA group showed an attenuated variance of HRV (2235.1 ± 417.9 ms2) compared to the MA (1014.3 ± 265.2 ms2; p < 0.05) and OA (896.3 ± 274.1 ms2; p < 0.05) groups, respectively. The parasympathetic modulation of HRV was lower in both the MA (244.2 ± 58.0 ms2) and OA (172.8 ± 37.9 ms2) groups in comparison with the YA group (996.0 ± 255.4 ms2; p < 0.05), while serum DHEA-S levels were significantly lower in both the MA (91.2 ± 19.6 mg/dL) and OA (54.2 ± 17.7 mg/dL) groups compared to the YA group (240.0 ± 50.8 mg/dL; p < 0.05). A positive correlation between lower serum concentrations of DHEA-S and attenuated variance of HRV (r = 0.47, p = 0.031), as well as lower serum concentrations of DHEA-S and decreased parasympathetic modulation of HRV (r = 0.54, p = 0.010), were found. Conclusion: The present study demonstrated that the decline of plasma DHEA-S is associated with reduced cardiac autonomic modulation during the aging process. Arch Endocrinol Metab. 2019;63(1):62-9 Keywords Aging; cardiac autonomic modulation; cardiovascular disease; dehydroepiandrosterone sulfate; heart rate variability.

INTRODUCTION

rotective steroid hormones decrease with aging, particularly dehydroepiandrosterone (DHEA) and its active metabolite dehydroepiandrosterone sulfate (DHEA-S). These two endogenous hormones are synthesized from cholesterol and excreted mainly by the reticular zone of the adrenal cortex; they represent the most abundant steroid hormones in circulation across the life span (1,2). Recent scientific and public interest in DHEA-S has been driven in large part by the evidence frequently published in recent years, suggesting a strong relationship between the decline of the endogenous hormone and aging (3). An excessive amount of mineralocorticoid hormones has been linked to cardiovascular disorders such as cardiac hypertrophy, arrhythmias, endothelial and smooth muscle vascular dysfunctions. Previous studies 62

showed a causal association between steroid hormones and cardiovascular diseases (4). A large majority of research has hypothesized that the development of DHEA-S deficiencies in elderly individuals might play a substantial role in the damage of many functions and contribute to the development of several injuries, including cardiovascular impairment (5), regardless of other risk factors (6). Moreover, it has been suggested that low serum levels of DHEA-S are a predictor of cardiovascular disease mortality (7). A substantial number of investigations have focused on biomarkers that identify subjects at higher risk of developing cardiovascular disease (8). One important indicator that seems to play a determinative role is vagal and sympathetic cardiac autonomic dysfunction. In fact, increased sympathetic and/or decreased parasympathetic activity has been associated with Arch Endocrinol Metab. 2019;63/1

DHEAS-associated autonomic dysfunction in OA

SUBJECTS AND METHODS Study population Forty-five healthy men without severe complications participated voluntarily in this study and were divided into 3 groups according to age: young-man group (n = 15), composed of people between the ages of 20 and 39 years; middle-age group (n = 15), composed of people between the ages of 40 and 59 years and oldman group (n = 15), composed of people aged 60 years and over. Exclusion criteria included coronary artery Arch Endocrinol Metab. 2019;63/1

disease, valvular and congenital heart disease, congestive heart failure, diabetes mellitus, sinus tachycardia, smoking habit and psychiatric, respiratory or metabolic disorders. All subjects gave written informed consent, and the study was approved by the Ethical Committee for Research of the Federal University of Triângulo Mineiro (Protocol: 2580/2013).

Body composition and anthropometric measures Anthropometric measurements of weight, height and body mass index were taken using a portable Tanita electronic scale (Tanita HD-350®) and portable stadiometer (0.1 cm precision; Prime Med®) fixed on a wall with volunteers wearing no shoes and light clothes. The percentage of body fat and the resulting fat-free body mass were estimated using the three-skinfold method.

Experimental protocol Data collection was done from 8:00 to 10:00 a.m., 2 h after the regular first breakfast. All participants underwent anamnesis and were instructed to fast and not consume alcohol or caffeine products. Additionally, they were told not to exercise on the day of the experiment. The experimental sessions were performed in baseline condition (supine position). After 10 min of resting in a quiet, temperature-regulated room, the electrocardiographic signal was recorded for 5 min. Subjects were not allowed to sleep. The electrocardiographic signal was continuously amplified by an electrocardiogram (ECG) recorder (model ECG-5, EcafixFunbec®, São Paulo, Brazil), collected by an analogue to digital converter board (DI-194 Starter Kit, Dataq Inst., Akron, OH, USA) with a sampling rate of 240 Hz and stored on personal computer for posterior offline analysis. Blood pressure (BP) was monitored noninvasively using an automatic and oscillometric cuff (M3 Intellisense HEM-7051-E; Omron Healthcare®, Kyoto, Japan). The HR was monitored through lead II of an ECG (model ECG-5, EcafixFunbec®, São Paulo, Brazil) beat per beat.

Heart rate variability measurements The HRV was assessed in the time domain by means of time series variance. Subsequently, frequency domain analysis was performed with an autoregressive algorithm (13). In brief, a time series of the RR intervals was calculated via the Levinson-Durbin recursion, with the order of the model chosen according to Akaike’s 63

increased risk for cardiovascular disorders such as hypertension, heart failure, ventricular arrhythmias and, especially, sudden cardiac death (9). Measurement of heart rate variability (HRV) is a valid noninvasive technique for estimating the characteristics of the autonomic nervous system and quantifying modulation of the sympathetic and parasympathetic inputs (10). HRV is also believed to decline as people age, but an important scientific question is whether decreases in HRV occur naturally with age as a result of the aging process itself or as a result of pathogenic processes. Therefore, the relationship between serum levels of sex steroid hormones and autonomic functions in both sexes has become an attractive area of research. Scientific evidence has shown that elements such as aging and levels of sex hormones may also influence cardiovascular autonomic control (11,12). Data obtained by our group demonstrated that DHEA-S decline was associated with lower HRV in sedentary elderly individuals compared to physically active individuals (data not shown). Nevertheless, few marked results have been clearly reported in relation to serum DHEA-S levels and HRV in the aging process. Therefore, it is believed that lower blood concentrations of DHEA-S along with the advancement of age can interfere in the circadian oscillation of the autonomic system and thus unbalance the sympathetic-vagal activity and cardiovascular function, consequently increasing the risk of cardiovascular diseases in this population. Therefore, in the present report, we examine the serum DHEA-S levels and cardiac autonomic control using linear methods of HRV in subjects in different age groups. Our hypothesis was that DHEA-S decline would be most pronounced elderly individuals over 60 years old and that this reduction could be associated with cardiac autonomic dysfunction.

DHEAS-associated autonomic dysfunction in OA

criterion. The temporal indices analyzed were: RR intervals (iRR, ms) and variance. The variance was estimated as a marker of total variability in the time domain. The power spectral density was calculated for each RR series. Spectral components were considered: low frequency (LF: 0.04 to 0.15 Hz) and high frequency (HF: 0.15 to 0.40 Hz). The spectral components were expressed in absolute (ms2) and normalized units (nu). In addition, the LF/HF-ratio was calculated, a sensitive indicator for sympathetic activation. Normalization consisted of dividing the power of a given spectral component by the total power minus the power below 0.03 Hz and multiplying the ratio by 100 (13).

Hormonal analysis At the end of the protocol, blood samples were drawn from each participant through antecubital vein puncture of the right arm to evaluate serum hormone levels of cortisol and DHEA-S. For collection, BD Vacutainer® SST II Advance tubes were used to obtain and separate a serum hormone sample. These tubes were centrifuged for 5 min at 1000 rpm. Next, the serum in test tubes was stored at -80 °C for further analysis. The intra- and inter-assay coefficients of variation were below 8% for DHEA-S and cortisol, respectively, and were measured using the direct chemiluminescent assay method (Advia Centaur, Bayer Corporation, Tarrytown, NY, USA).

Statistical analyses Data are expressed as mean ± standard error of the mean (SEM). The normality of the data distribution was verified by the Shapiro-Wilk test, and Levene’s test was used to evaluate the homogeneity of the sample. The variables were compared among the 3 groups using a 1-way analysis of variance (ANOVA). When overall differences were found at p < 0.05, a post hoc Tukey’s test protected

least-significant difference was performed, or KruskalWallis, followed by Dunn’s post hoc test in agreement with presence or not of distribution normality and/or homogeneity of the variance, respectively. The Pearson correlation coefficient was used to test the correlation between HRV and serum DHEA-S concentrations. The level of significance was set at p ≥ 0.05 for all analyses. Analyses were conducted using SigmaStat (Jandel Scientific Software; SPSS, Chicago, IL).

RESULTS Information regarding age, body composition and anthropometric parameter recordings according to age group is shown in Table 1. The old-man group presented a significantly higher age in comparison to the middle-age and young-man groups (p < 0.05), and participants in the middle-age group were significantly older than those in the young-man group (p < 0.05). There were no significant differences between the three groups in terms of weight, BMI, muscle mass and total body fat (p > 0.05). Resting HR and BP are shown in Figure 1. The HR of elderly participants aged over 60 years at rest was higher (82.8 ± 3.2 bpm) than that of the young-man group (67.0 ± 2.1 bpm; p < 0.001) (Figure 1A). In contrast, there were no significant differences between groups in terms of systolic BP (123.5 ± 11.3 mmHg in young-man group, 126.5 ± 12.0 mmHg in middle-age group and 136.4 ± 10.4 mmHg in old-man group; Figure 1B) and diastolic BP (71.8 ± 9.5 mmHg in young-man group, 72.6 ± 10.1 mmHg in middle-age group and 82.4 ± 11.9 mmHg in old-man group; p > 0.05) (Figure 1C). Table 2 shows the HRV by linear analysis. Compared to the young-man group, the middle-age and oldman groups presented an attenuated variance of HRV

Table 1. Body composition and anthropometric characteristics YA (20-39 years)

MA (40-59 years)

OA (≥ 60 years)

Age (y)

29.2 ± 3.6

52.9 ± 4.5*

62.8 ± 2.4*†

Weight (kg)

63.8 ± 11.2

63.9 ± 11.0

65.2 ± 13.6

Height (cm)

163.5 ± 4.6

161.8 ± 7.9

160.9 ± 11.4

BMI (kg/m )

23.9 ± 5.1

24.4 ± 8.9

25.1 ± 7.3

Total fat (kg)

16.2 ± 3.0

17.2 ± 2.8

19.3 ± 2.3

Total MM (kg)

47.6 ± 5.2

46.7 ± 8.2

45.9 ± 11.3

Values are expressed as mean ± standard error (SE). BMI: body mass index; MM: muscle mass; YA: young-age; MA: middle-age; OA: old-age; respectively. *p < 0.05 vs. YA and †p < 0.05 vs. MA. P values for comparisons between groups using one-way ANOVA followed by Tukey’s post-hoc analysis.

Arch Endocrinol Metab. 2019;63/1

DHEAS-associated autonomic dysfunction in OA

(p < 0.001). The HF oscillations of HRV were lower in both the middle-age and old-man groups compared to the young-man subjects (p < 0.001). The LF/HF ratio was lower in the young-man group than in the middle-age and old-man groups (p < 0.05). No significant changes in sympathetic indices of HRV were found (p > 0.05). Figure 2 presents the serum levels of cortisol and DHEA-S in all groups. As shown in the figure, no statistically significant difference was observed between the three groups in terms of cortisol parameters (11.2 ± 1.6 mg/dL in young-man group; 9.6 ± 1.2 mg/dL in middle-age group and 10.7 ± 0.4 mg/dL in old-man group; p > 0.05) (Figure 2A). On the other hand, the

B 200

A 100

80 60

150 SBP (mmHg)

HR (bpm)

serum levels of DHEA-S were significantly lower in both the middle-age (87.4 17.8 mg/dL) and old-man (50.8 ± 14.9 mg/dL) groups compared to the young-man group (244.3 ± 49.5 mg/dL; p < 0.005) (Figure 2B). Analysis showed a significant and positive correlation between serum concentrations of DHEA-S and variance of HRV (r = 0.65, p < 0.001; Figure 3A), as well as a significant correlation between serum concentrations of DHEA-S and absolute HF oscillations of HRV (r = 0.55, p < 0.001; Figure 3B). There were no significant correlations between serum concentrations of DHEA-S and the LF component of HRV (r = 0.10, p = 0.509; Figure 3C).

100

0 C 100

DBP (mmHg)

80 60 40 20 0

YA (20-39 years)

MA (40-59 years)

OA (> 60 years)

Figure 1. Graphs showing hemodynamic parameters in young-man, middle-age and old-man. (A) heart rate, (B) systolic blood pressure and (C) diastolic blood pressure at rest. Data are mean ± standard error (SE). *p < 0.05 vs. young-man. P values for comparisons between groups using one-way ANOVA followed by Tukey’s post-hoc analysis or Kruskal-Wallis followed by Dunn’s post hoc test.

Variance, ms2

YA (20-39 years)

MA (40-59 years)

OA (> 60 years)

2860.5 ± 452.7

1034.2 ± 146.6*

702.7 ± 177.6*

LF, ms2

465.6 ± 78.6

415.4 ± 32.7

433.7 ± 154.3

LF, nu

41.2 ± 7.4

52.6 ± 1.7

48.0 ± 6.2

HF, ms

1004.2 ± 112.8

266.3 ± 36.8*

179.5 ± 36.2*

HF, nu

66.8 ± 8.1

53.5 ± 4.3

47.3 ± 4.3

LF/HF ratio

0.82 ± 0.3

1.66 ± 0.2*

2.20 ± 0.4*

Table 2. Spectral parameters of heart rate calculated from time series using autoregressive power spectral analysis at rest in young-man, middle-age and old-man

Values are expressed as mean ± standard error (SE). LF: low-frequency spectral component of HRV; HF: high-frequency spectral component of HRV; nu: normalized units. *p < 0.05 vs. YA. P values for comparisons between groups using one-way ANOVA followed by Tukey’s post-hoc analysis or Kruskal-Wallis followed by Dunn’s post hoc test.

Arch Endocrinol Metab. 2019;63/1

DHEAS-associated autonomic dysfunction in OA

B 350

300

250 DHEA-S (ug/dL)

Cortisol (µg/dL)

10 8 6

200 150

100

* YA (20-39 years)

MA (40-59 years)

OA (> 60 years)

Figure 2. Bar graphs (mean ± SE) showing serum concentrations of (A) cortisol and (B) DHEA-S among young-man, middle-age and old-man. *p < 0.05 vs. young-man. P values for comparisons between groups using one-way ANOVA followed by Tukey’s post-hoc analysis or Kruskal-Wallis followed by Dunn’s post hoc test.

7000

Variance - HRV (ms2)

6000

r = 0.65 p < 0.001

2500 2000

5000 HF - HRV (ms2)

4000 3000 2000 1000

r = 0.55 p < 0.001

1500 1000 500 0

0 0

100

200

300

400

500

600

700

DHEA-S (ug/dL)

100

200

300

400

500

600

700

DHEA-S (ug/dL)

C 2000

r = 0.10 p < 0.509

LF - HRV (ms2)

1500 1000 500

100

200

300

400

500

600

700

DHEA-S (ug/dL) YA (20-39 years)

MA (40-59 years)

OA (> 60 years)

Figure 3. Pearson’s linear correlation scatter plot between serum DHEA-S levels and variance of HRV (A), serum DHEA-S levels and high-frequency spectral component of HRV (B) and serum DHEA-S levels and low-frequency spectral component of HRV (C). 66

Arch Endocrinol Metab. 2019;63/1

DISCUSSION Studies have indicated that decreased levels of DHEA-S have been found in people with cardiovascular disease (14), and an inverse correlation between DHEA-S and cardiovascular mortality has been reported in the aging process (15). On the other hand, researchers have documented that HRV decreased with aging independent of pathological conditions or medication use (16), potentially suggesting that cardiac autonomic modulation diminishes due to normative aging and HRV changes due to chronic diseases or health-related conditions (17). Theoretically, therefore, the main finding of this large study was that a decline of serum DHEA-S level is positively correlated with lower HRV and parasympathetic modulation and negatively correlated with sympathetic activities. An important factor should be taken into account: The HRV normally decreases with age, as well as serum DHEA-S levels; therefore, there is a conflict to understand if the correlation between DHEA-S and HRV found in our study is causal or noncausal. Previous studies have demonstrated a decrease in DHEA-S concentration with aging, and this decrease is associated with greater cardiac autonomic dysfunction; other studies indicate that there is no correlation between these variables because both decline physiologically due to aging. In the current scientific literature, there are limited studies on the association between cardiac function and serum levels of DHEA-S. The effect of age on DHEA-S levels in adults has previously been described (18). Our study confirms the results of these earlier findings and clearly demonstrates that serum DHEA-S levels significantly decline with age. It is worth noting that within an individual, the levels of DHEA-S may fluctuate over time, but the general trend is a decline (19). The serum DHEA and DHEA-S have been deeply studied for their potential anti-aging effects. In humans, blood DHEA levels decline with age, suggesting that it may be a key element in the aging process (20). Studies in mice have shown that DHEA-S supplementation reverted left ventricular rigidity in aging (11). However, it is important to emphasize that the American Society of Endocrinology does not recommend the supplementation of DHEA-S for normal subjects, even during aging. Another study demonstrated an inverse relationship between heart disease and serum DHEA-S levels (21). Prior studies have shown associations between sex steroid levels, age and autonomic activity. In fact, testosterone Arch Endocrinol Metab. 2019;63/1

effects on autonomic control of nerve transduction pathways have been described, providing evidence that this hormone affects parasympathetic responses and facilitates the baroreflex sensibility in autonomic function. Although it is not an adrenal hormone, growth hormone (GH) levels in circulation begin to decline soon after attainment of adult body size and full physical and reproductive maturation. GH deficiency is associated with increased cardiovascular morbidity and mortality. Abnormalities in HRV have been found in patients with GH deficiency (22-24); however, these alterations are only associated with decreased cardiac sympathetic activity (25). These results indicate that serum steroid hormones have effects not only on sexual differentiation but also on autonomic modulation of the cardiovascular system. To our knowledge, so far, there is very little published evidence regarding the effects of aging on DHEA-S concentrations and their association with the HRV. Studying the relationship between serum sex steroid levels and HRV parameters, Dog6ru and cols. found that DHEA-S exhibited the most significant correlations with autonomic functions after controlling for the effects of age in comparison to gonadal steroids (12). In part, our results may be explained by the existence of cardiac receptors for DHEA-S verified in some studies (11). On the other hand, it was shown that DHEA-S had regulatory effects on sympathetic adrenal activity and was positively correlated with the attenuation of the sympathetic-adrenal response to hypoglycemia. The mechanisms of the effects of DHEA-S on the sympatho-vagal balance have not yet been elucidated; therefore, this action can be attributed to specific receptors and the effect of DHEA-S on the brain (26). DHEA-S has been considered a marker of good health (27). The peak of this hormone proceeds to attenuate with age more markedly than any other endogenous hormone, corroborating the experimental evidence of their involvement in age-related health disorders (19). Interaction of the DHEA-S blood levels and aging-related pathologies has been widely explored during the last decades. Several researches have shown a negative association between the levels of these hormones and the aging process, as defined by the occurrence of numerous disorders including cardiovascular disorders, as well as more definitive entities such as mortality (28). The literature reported that DHEA-S levels are much more often measured in 67

DHEAS-associated autonomic dysfunction in OA

studies than DHEA levels, which are often not reported at all. Few published studies have clearly mentioned physiological differences between DHEA to relate the concentration to various diseases, probably due to the different hormone distributions throughout life, compared to its sulfated form (29). Our findings demonstrated a decrease of HRV in the elderly. In relation to the physiological process of aging, some authors verified that increasing age causes a significant decrease in HRV (30), which is in agreement with our results. Higher HRV is a signal of good adaptation and characterizes a healthy person, while chronic reductions in resting-state HRV appear to be associated with negative cardiovascular prognostics. A study showed that attenuated HRV is related to a 32%-45% increased risk of cardiovascular events in people who are not known to have cardiovascular problems. However, a 1% increase in the parasympathetic component results in a 1% decrease for risk of fatal and nonfatal cardiovascular disease (31). We observed that middle-aged individuals and old people aged over 60 years presented a reduced parasympathetic modulation of HR than the young group, which is in agreement with some studies in the literature (32). This result may be related to a lower HRV allied with a higher resting tachycardia. Our analysis focused specifically on a subpopulation of healthy participants without cardiovascular condition and with no reported medication use during the data collection phase. Although the physiological basis of HRV indices is complex, the decreasing HF component of HRV may suggest that aging is accompanied by a reduction of overall fluctuation in cardiac autonomic input and by attenuation in vagal modulation. The changes that occur in parasympathetic modulation as a result of aging may be associated with changes in cholinergic and muscarinic pathways through which the vagal efferent signal is carried. This may include cardiac disorders in acetylcholine release response to stimulation (33), decreases in muscarinic receptor activity (34) and reductions in M2 muscarinic receptor density (35), all of which have been shown to decrease with aging. Loss of vagal reflexes seems to hinder biological functioning and capacity to respond to stimuli originating from the efferent pathway, resulting in increased vulnerability to diseases (9) that are often prevalent in individuals of advanced age (36). An elevated resting HR, even above 80 beats per minute, was demonstrated to increase the risk of 68

cardiovascular disease (37). Therefore, we elucidated in our study that old men had a higher resting HR than young men, likely to be associated with the hypoactive parasympathetic system found in this study. Our findings are in agreement with the current literature (38). A fast or irregular HR is abnormal and is the result of a problem with the heart or the irregular electrical signals in the heart (39). Knowing resting HR and how it changes over time can provide insight into cardiovascular health. The resting HR increases with age, and it can also be affected by several factors, such as caffeine, tobacco, certain medications and lifestyle. Previous studies have demonstrated that resting tachycardia is a predictor of mortality and shorter life expectancy. These authors estimated that HR increases of 10 bpm are associated with a 20% increased risk of cardiac death, and 15 bpm increases in HR were found to increase the rate of cardiovascular disease mortality (37,39). In summary, we conclude that low levels of plasma DHEA-S concentration are linked to decreases in cardiac autonomic modulation following increases of age. Authors contributions: all authors contributed to the conception and design of the study; data acquisition, analysis, and interpretation; drafting, revising, and approving the manuscript for submission. Acknowledgments: we wish to thank all volunteers who participated in this study. Cristhiane Ignácio Fernandes of the Clinics Hospital of Federal University of Triângulo Mineiro and Poliana Morais Melo who kindly referred their patients for this study. Financing statement: grants and scholarships were received by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Capes) and Fundação de Amparo à Pesquisa do Estado de Minas Gerais (Fapemig). Disclosure: no potential conflict of interest relevant to this article was reported.

REFERENCES 1. Adams JB. Control of secretion and the function of C19-delta 5-steroids of the human adrenal gland. Mol Cell Endocrinol. 1985;41(1):1-17. 2. Morales AJ, Nolan JJ, Nelson JC, Yen SS. Effects of replacement dose of dehydroepiandrosterone in men and women of advancing age. J Clin Endocrinol Metab. 1994;78(6):1360-7. 3. Ferrari E, Cravello L, Muzzoni B, Casarotti D, Paltro M, Solerte SB, et al. Age-related changes of the hypothalamic-pituitaryadrenal axis: pathophysiological correlates. Eur J Endocrinol. 2001;144(4):319-29. 4. Pitt B, Remme W, Zannad F, Neaton J, Martinez F, Roniker B, et al. Eplerenone, a selective aldosterone blocker, in patients with left Arch Endocrinol Metab. 2019;63/1

DHEAS-associated autonomic dysfunction in OA

5. Weiss EP, Villareal DT, Ehsani AA, Fontana L, Holloszy JO. Dehydroepiandrosterone replacement therapy in older adults improves indices of arterial stiffness. Aging Cell. 2012;11(5):876-84. 6. Allameh F, Pourmand G, Bozorgi A, Nekuie S, Namdari F. The association between androgenic hormone levels and the risk of developing coronary artery disease (CAD). Iran J Public Health. 2016;45(1):14-9. 7. Ohlsson C, Labrie F, Barrett-Connor E, Karlsson MK, Ljunggren O, Vandenput L, et al. Low serum levels of dehydroepiandrosterone sulfate predict all-cause and cardiovascular mortality in elderly Swedish men. J Clin Endocrinol Metab. 2010;95(9):4406-14. 8. Loyd-Jones DM. Cardiovascular risk prediction: basic concepts, current status, and future directions. Circulation. 2010;121(15):1768-77. 9. Vaseghi M, Shivkumar K. The Role of the Autonomic Nervous System in Sudden Cardiac Death. Prog Cardiovasc Dis. 2008;50(6):404-19. 10. Lahiri MK, Kannankeril PJ, Goldberger JJ. Assessment of autonomic function in cardiovascular disease: physiological basis and prognostic implications. J Am Coll Cardiol. 2008;51(18):1725-33. 11. Alwardt CM, Yu Q, Brooks HL, McReynolds MR, Vazquez R, Watson RR, et al. Comparative effects of dehydroepiandrosterone sulfate on ventricular diastolic function with young and aged female mice. Am J Physiol Regul Integr Comp Physiol. 2006;290(1):251-6. 12. Doğru MT, Başar MM, Yuvanç E, Simşek V, Sahin O. The relationship between serum sex steroid levels and heart rate variability parameters in males and the effect of age. Turk Kardiyol Dern Ars. 2010;38(7):459-65. 13. Malliani A, Pagani M, Lombardi F, Cerutti S. Cardiovascular neural regulation explored in the frequency domain. Circulation. 1991;84(2):482-92. 14. Genazzani AR, Gambacciani M, Simoncini T. The latest elaboration of the Women’s Health Initiative data on hormone replacement therapy and cardiovascular disease in postmenopausal women. Gynecol Endocrinol. 2007;23(4):183-5. 15. Cappola AR, Xue QL, Walston JD, Leng SX, Ferrucci L, Guralnik J. et al. DHEAS Levels and Mortality in Disabled Older Women: The Women’s Health and Aging Study I. J Gerontol A Biol Sci Med Sci. 2006;61(9):957-62. 16. Zulfiqar U, Jurivich DA, Gao W, Singer DH. Relation of high heart rate variability to healthy longevity. Am J Cardiol. 2010;105(8):1181-5. 17. Stein PK, Barzilay JI, Chaves PH, Domitrovich PP, Gottdiener JS. Heart rate variability and its changes over 5 years in older adults. Age Ageing. 2009;38(2):212-8. 18. Watson RR, Huls A, Araghinikuam M, Chung S. Dehydroepiandrosterone and diseases of aging. Drugs Aging. 1996;9(4):274-91. 19. Orentreich N, Brind JL, Vogelman JH, Andres R, Baldwin H. Long-term longitudinal measurements of plasma dehydroepiandrosterone sulfate in normal men. J Clin Endocrinol Metab 1992;75(4):1002-4. 20. Sulcová J, Hill M, Hampl R, Stárka L. Age and sex related differences in serum levels of unconjugated dehydroepiandrosterone and its sulphate in normal subjects. J Endocrinol. 1997;154(1):57-62. 21. Feldman HA, Johannes CB, McKinlay JB, Longcope C. Low dehydroepiandrosterone sulfate and heart disease in middle-aged men: cross-sectional results from the Massachusetts Male Aging Study. Ann Epidemiol. 1998;8(4):217-28. 22. Kuwahara S, Kesuma Sari D, Tsukamoto Y, Tanaka S, Sasaki F. Age-related changes in growth hormone (GH)-releasing hormone and somatostatin neurons in the hypothalamus and in GH cells in the anterior pituitary of female mice. Brain Res. 2004;1025(12):113-22. Arch Endocrinol Metab. 2019;63/1

23. Frutos MGS, Cacicedo L, Méndez CF, Vicent D, González M, Sánchez-Franco F.. Pituitary alterations involved in the decline of growth hormone gene expression in the pituitary of aging rats. J Gerontol A Biol Sci Med Sci. 2007;62(6):585-97. 24. Leong KS, Mann P, Wallymahmed M, MacFarlane IA, Wilding JP. The influence of growth hormone replacement on heart rate variability in adults with growth hormone deficiency. Clin Endocrinol. 2001;54(6):819-26. 25. Kursad U, Namik KE, Fatih T, Ramiz C, Ramazan T, Ibrahim O, et al. The effects of growth hormone therapy on heart rate variability in adults with growth hormone deficiency. Curr Ther Res. 2002;63(7):421-9. 26. Charalampopoulos I, Tsatsanis C, Dermitzaki E, Alexaki VI, Castanas E, Margioris NA, et al. Dehydroepiandrosterone and allopregnanolone protect sympathoadrenal medulla cells against apoptosis via antiapoptotic Bcl-2 proteins. Proc Nati Acad Sci U S A. 2004;101(21):8209-14. 27. Gray A, Feldman HA, McKinlay JB, Longcope C. Age, disease, and changing sex hormone levels in middle-aged men: results of the Massachusetts Male Aging Study. J Clin Endocrinol Metab. 1991;73(5):1016-25. 28. Mazat L, Lafont S, Berr C, Debuire B, Tessier JF, Dartigues JF, et al. Prospective measurements of dehydroepiandrosterone sulfate in a cohort of elderly subjects: relationship to gender, subjective health, smoking habits, and 10-year mortality. Proc Nati Acad Sci U S A. 2001;98(14):8145-50. 29. Kroboth PD, Salek FS, Pittenger AL, Fabian TJ, Frye RF. DHEA and DHEA-S: a review. J Clin Pharmacol. 1999;39(4):327-48. 30. Jandackova VK, Scholes S, Britton A, Steptoe A. Are Changes in Heart Rate Variability in Middle‐Aged and Older People Normative or Caused by Pathological Conditions? Findings From a Large Population‐Based Longitudinal Cohort Study. J Am Heart Assoc. 2016;5(2):e002365. 31. Hillebrand S, Gast KB, de Mutsert R, Swenne CA, Jukema JW, Middeldorp S, et al. Heart rate variability and first cardiovascular event in populations without known cardiovascular disease: meta-analysis and dose-response meta-regression. Europace. 2013;15(5):742-9. 32. Voss A, Schroeder R, Heitmann A, Peters A, Perz S. Short-Term Heart Rate Variability – Influence of Gender and Age in Healthy Subjects. PLoS One. 2015;10(3):e0118308. 33. Oberhauser V, Schwertfeger E, Rutz T, Beyersdorf F, Rump LC. Acetylcholine release in human heart atrium: influence of muscarinic autoreceptors, diabetes, and age. Circulation. 2001;103(12):1638-43. 34. Brodde OE, Konschak U, Becker K, Ruter F, Poller U, Jakubetz J. Cardiac muscarinic receptors decrease with age. In vitro and in vivo studies. J Clin Invest. 1998;101(2):471-8. 35. Poller U, Nedelka G, Radke J, Ponicke K, Brodde OE. Age-dependent changes in cardiac muscarinic receptor function in healthy volunteers. J Am Coll Cardiol. 1997;29(1):187-93. 36. Lee PY, Yun J, Bazar K. Conditions of aging as manifestations of sympathetic bias unmasked by loss of parasympathetic function. Med Hypotheses. 2004;62(6):868-70. 37. Cooney MT, Vartiainen E, Laatikainen T, Juolevi A, Dudina A, Graham IM. Elevated resting heart rate is an independent risk factor for cardiovascular disease in healthy men and women. Am Heart J. 2010;159(4):612-9. 38. Hozawa A, Ohkubo T, Kikuya M, Ugajin T, Yamaguchi J, Asayama K, et al. Prognostic value of home heart rate for cardiovascular mortality in the general population: the Ohasama study. Am J Hypertens. 2004;17(11 Pt 1):1005-10. 39. Perret-Guillaume C, Joly L, Benetos A. Heart rate as a risk factor for cardiovascular disease. Prog Cardiovasc Dis. 2009;52(1): 6-10.

ventricular dysfunction after myocardial infarction. N Engl J Med. 2003;348(14):1309-21.

review

Genetic causes of isolated short stature Gabriela A. Vasques1,2, Nathalia L. M. Andrade1,2, Alexander A. L. Jorge1,2 Unidade de Endocrinologia Genética (LIM25), Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (HCFMUSP), São Paulo, SP, Brasil 2 Unidade de Endocrinologia do Desenvolvimento, Laboratório de Hormônios e Genética Molecular (LIM42), Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (HCFMUSP), São Paulo, SP, Brasil 1

Correspondence to: Alexander A. L. Jorge Faculdade de Medicina, Universidade de São Paulo (LIM-25) Av. Dr. Arnaldo, 455, 5º andar, sala 5340 01246-903 – São Paulo, SP, Brasil alexj@usp.br Received on Nov/29/2018 Accepted on Feb/22/2019 DOI: 10.20945/2359-3997000000105

ABSTRACT Short stature is a common feature, and frequently remains without a specific diagnosis after conventional clinical and laboratorial evaluation. Longitudinal growth is mainly determined by genetic factors, and hundreds of common variants have been associated to height variability among healthy individuals. Although isolated short stature may be caused by the combination of variants, with a deleterious impact on the growth of individuals with polygenic inheritance, recent studies have pointed out some monogenic defects as the cause of the growth disorder observed in nonsyndromic children. The majority of these defects are in genes related to the growth plate cartilage and in the growth hormone (GH) – insulin-like growth factor 1 (IGF-1) axis. Affected patients usually present the mildest spectrum of some forms of skeletal dysplasia, or subtle abnormalities of laboratory tests, suggesting hormonal resistance or insensibility. The lack of specific characteristics, however, does not allow formulation of a definitive diagnosis without the use of broad genetic studies. Thus, molecular genetic studies including panels of genes or exome analysis will become essential in investigating and identifying the causes of isolated short stature in children, with a crucial impact on treatment and follow-up. Arch Endocrinol Metab. 2019;63(1):70-8 Keywords Short stature; growth; growth cartilage; growth hormone

INTRODUCTION

hort stature is defined as a condition characterized by height more than 2 standard deviation scores below the mean observed in age and sex control population (height SDS < -2) (1). Based on this definition, short stature affects 2.3% of children, and is a matter of concern for many parents seeking medical attention. Although growth disorder may be a clinical presentation of an underlying disease, in around 70% of the cases, short stature is not associated with any clinical and laboratory evidence that justify growth impairment (2). These children are usually classified as having constitutional or idiopathic short stature (ISS) (3). In this review, we also used the term isolated short stature, in view of the growing number of monogenic conditions that explain the short stature phenotype in nonsyndromic children. Height is one of the human traits with a higher degree of heritability (> 80%), which means that genetic variability is the main determinant of stature (4). Up to date, more than 600 common variants (with allele frequencies greater than 1%) distributed 70

across more than 400 regions of the genome have been independently associated with height (5). The impact of each identified common variant on stature is small (around 1-4 mm). More recently, studies have pointed out that rare variants (frequency < 1%) may exert an effect on height variability 10 to 20 times greater than that exert by common variants (about 20 mm per allele). Many of these common and rare variants are in genes associated with syndromic growth disorders or in genes involved in the development of the growth cartilage (6). Since short stature is a common clinical presentation, it is widely accepted that it is caused by common variants with polygenic inheritance (7,8). However, recent studies have challenged this dogma, and proposed that many of the children classified as ISS could instead have a monogenic defect. A part of this group would represent the mildest spectrum of phenotypic variability of syndromic conditions (9,10). For example, there are short stature individuals harboring pathogenic variants in genes responsible for the Noonan syndrome who do not present any of the other phenotypic alterations that Arch Endocrinol Metab. 2019;63/1

Genetic causes of isolated short stature

would allow the recognition of this condition clinically (11). Additionally, genes that regulate the growth plate and that had already been associated with skeletal dysplasias were recently pointed as responsible for some cases of ISS (12-16). This review provides an update on monogenic causes of isolated short stature.

GENES THAT REGULATE GROWTH PLATE Endochondral ossification is a complex process which occurs in the growth plate to promote bone elongation and consequent increase in height. It involves proliferation, hypertrophy and senescence of chondrocytes and also cartilage matrix synthesis (17). Paracrine and autocrine factors are the main regulators of endochondral ossification and defects in genes that encode or disrupt these factors (summarized in Table 1) have been associated with ISS. Each of these genes is responsible for a small proportion of cases (up to 2%), but this proportion may be significantly higher in familial short stature. Defects in genes that regulate growth plate, inherited in an autosomal dominant manner, cause a variable phenotype in terms of degree of short stature and body proportions. The atypical radiological findings do not allow the precise diagnosis and some of the patients are recognized as having a subclinical skeletal dysplasia.

SHOX The short stature homeobox (SHOX) gene is located in the pseudoautosomal region 1 of both sex chromosomes and is expressed in growth cartilage, especially in hypertrophic chondrocytes. The role of the SHOX gene as a regulator of the growth plate has not been fully understood. It is known that SHOX is a transcription factor that increases NPPB and inhibits FGFR3 expression, respectively (Figure 1A).

Both effects stimulate and coordinate chondrocytes proliferation and differentiation in order to promote longitudinal growth. In addition, SHOX interacts with the SOX trio (SOX9, SOX5 and SOX6 genes), which has an important role in cartilage matrix synthesis (18). The causative relation between SHOX defects and ISS was first described in 1997 (12). Since then, SHOX haploinsufficiency has become the main recognized monogenic cause of short stature, being responsible for 2.6% of the nonsyndromic cases of short stature. Homozygous defects in SHOX gene cause Langer mesomelic dysplasia, a rare skeletal dysplasia with severe short stature and limb aplasia or hypoplasia of the ulna and fibula. Heterozygous SHOX haploinsufficiency causes phenotypes that range from isolated short stature to the complete picture of the Leri-Weill dyschondrosteosis (LWD), a skeletal dysplasia characterized by mesomelia and Madelung deformity (i.e. shortening and bowing of the radius with dorsal subluxation of the distal ulna) (19). Around 80% of reported SHOX defects are deletions involving the gene or regulatory regions, with the remaining ones being point mutations. Although no genotypephenotype correlation has been identified in individuals with SHOX deletions encompassing exons and point mutations, deletion in downstream SHOX enhancer have been associated with a milder phenotype (18). Abnormal body proportion, defined by the [sitting height]/[height] ratio for age and sex (SH/H SDS) > 2, is present in the vast majority of children with isolated short stature caused by SHOX haploinsufficiency (20). The degree of short stature is variable, and the mean growth deficit of affected individuals is of around 12 cm, which means that there are carriers with height within the normal range. A reasonable clinical selection criterion to screen for SHOX defects in a child with isolated short stature is

Table 1. Genes involved in the endochondral ossification process that are associated with isolated short stature Gene

First report in patient classified as ISS

Frequency in ISS (%)

SHOX

1997

2.6 (1.1 to 22.2)

Mild abnormal body proportion, family member with Madelung deformity

NPR2

2013

1.8 to 6 (13.6*)

Nonspecific skeletal abnormalities, as short metacarpals

NPPC

2018

Two families described with brachydactyly

ACAN

2014

1.4

Accelerated bone maturation and early-onset osteoarthritis

(52,53)

IHH

2018

3.4

Shortening of the middle phalanx of the 5th finger

(15,54)

FGFR3

2015

Only one family described with normal body proportion

Additional common findings

(16)

(32)

* Familial cases; NA: not available; ISS: idiopathic short stature. Arch Endocrinol Metab. 2019;63/1

Genetic causes of isolated short stature

the presence of abnormal body proportion, especially if the phenotype of disproportional short stature segregates in an autosomal dominant manner and/or there is a family member with Madelung deformity. Particular attention should be given to the regulatory regions of SHOX gene, since deletions located outside the coding region are more commonly associated with short stature without other specific findings.

NPR2 and NPPC The C-type natriuretic peptide (CNP) and its receptor (NPR-B) are important regulators of the endochondral ossification process (21). CNP and NPR-B are encoded by NPPC and NPR2 genes, respectively. They are notably expressed in the hypertrophic zone of the growth plate. The CNP/NPR-B system stimulates chondrocyte proliferation and differentiation and synthesis of cartilage matrix in an autocrine/paracrine manner. The molecular mechanism that explains these actions is at least partially identified and involves the inhibition of the FGFR3 pathway (Figure 1B). After CNP binding to NPR-B, there is an intracellular accumulation of cyclic GMP (cGMP), that activates cGMP-dependent protein kinases I and II (cGKI and cGKII). cGKII inhibits the activation of RAF-1. Biallelic loss-of-function mutations in NPR2 cause acromesomelic dysplasia type Maroteaux (21). Heterozygous NPR2 mutations in a cohort of ISS children were first described in 2013 (13). Since then, other studies have replicated this finding and the prevalence of heterozygous NPR2 mutations in ISS patients has ranged from 1.8% to 13.6% (in familial cases) (22). Similar to what has been observed in patients with SHOX haploinsufficiency, carriers of NPR2 mutation have a variable degree of short stature and some carrier relatives presented height at the lower limit of the normal range. Abnormal body proportion (SH/H SDS > 2) and nonspecific skeletal abnormalities, as short metacarpals (Figure 2A), were also observed among patients with NPR2 mutations. Due to the phenotypic heterogeneity, there is, at the moment, no clinical feature that enables establishing a criterion to select short stature patients for for NPR2 molecular-genetic screening. More recently, heterozygous NPPC mutations have been identified in two families with ISS. In total, six NPPC carriers were identified, two being Brazilian and four Spanish. Their height SDS ranged from -4.3 to -2.3 and all of them also had small hands phenotype (16). 72

Figure 1. Schematic representation of chondrogenesis regulation by genes associated to isolated short stature phenotype. (A) SHOX is a transcriptional factor that enhances NPPB and SOX trio expression and inhibits FGFR3 expression. This leads to an increase in chondrocyte proliferation and differentiation and an increase in cartilage matrix synthesis. (B) CNP and FGF signaling pathways converge at the MAPK pathway. The opposite effect of CNP on FGFR3 pathway improves longitudinal bone growth by increasing chondrocyte proliferation and differentiation and cartilage matrix synthesis.

ACAN The Aggrecan gene (ACAN) encodes a proteoglycan present in the extracellular matrix. Aggrecan has a fundamental structural and functional role in the growth plate cartilage. Initially, ACAN mutations were associated with two rare types of skeletal dysplasias, one with an autosomal dominant (Spondyloepiphyseal dysplasia, Kimberley type) and another with a recessive inheritance (Spondyloepimetaphyseal dysplasia, aggrecan type) (23). In 2014, heterozygous ACAN mutations were identified as cause of short stature in three families with no skeletal findings suggestive of skeletal dysplasia. Children presented accelerated bone Arch Endocrinol Metab. 2019;63/1

Genetic causes of isolated short stature

Figure 2. Hand radiographs of children carrying NPR2 and IHH mutations. (A) Hand radiograph of a patient with heterozygous mutation in NPR2. Shortening of metacarpal is clearly observed. (B) Hand radiograph of a child with heterozygous mutation in IHH showing the shortening of the middle phalanx of the 5th finger with cone-shaped epiphyses.

maturation, even before puberty, and some subjects had accompanying early-onset osteoarthritis (14). This dual phenotypic presentation occurs because aggrecan is a component of both growth plate and articular cartilage. Since the first report, more than one hundred individuals from more than twenty families with autosomal dominant inherited short stature were identified as carriers of ACAN mutations (24). Affected children seem to have growth impairment even before birth, and mutations in this gene were reported in a cohort of short children born small for their gestational age, mainly regarding birth length (25). The majority of children with ACAN mutations have proportionate short stature with advanced bone age. Due to the poor pubertal spurt followed by early growth cessation, final height is still more compromised and adults present lower height SDS and, frequently, body disproportion. Other clinical features recognized in affected subjects are brachydactyly, mild midface hypoplasia, and flat nasal bridge. Some individuals present early-onset osteoarthritis, which appears until fourth decade of life and affects most commonly the knees, with a variable degree of severity (24). Whereas most children from cohorts of patients with ISS have delayed bone age, ACAN mutation should be suspected in a short child with advanced bone age. Arch Endocrinol Metab. 2019;63/1

IHH The Indian hedgehog gene (IHH) is expressed in prehypertrophic chondrocytes of the growth plate, and codifies a key paracrine regulator of endochondral ossification, which coordinates chondrocytes proliferation and differentiation (26). Similar to what occurs with the other genes that regulate growth plate described above, IHH defects had already been recognized as a cause of two skeletal dysplasias. Homozygous IHH mutations cause acrocapitofemoral dysplasia, characterized by severe disproportionate short stature with cone-shaped epiphyses in hands and hips. Additionally, heterozygous mutations in IHH cause brachydactyly type A1 (BDA1), characterized by a striking shortening of the middle phalanges, which can be fused with the terminal ones (27). Interestingly, short stature was not consistently reported in patients with BDA1 (28). In 2018, we described heterozygous IHH mutations as a cause of the growth impairment in an ISS cohort (frequency of 3.4%) (15). Our patients with heterozygous IHH variants did not present classical features of BDA1. The only recurrent radiological finding observed was a varying degree of shortening of the middle phalanx of the 5th finger (Figure 2B), which is the defining feature of Brachymesophalangia â&#x20AC;&#x201C; V (BMP-V). BMP-V was observed in 64.3% hand radiographs from individuals with heterozygous mutations in IHH in our cohort, which was significantly higher than that observed in a population study (12.1%) (15). Four probands were born small for gestational age considering only length at birth. Affected subjects typically had mild disproportional short stature. The severity of short stature is variable and disproportionality seems to become more pronounced over the years.

FGFR3 The fibroblast growth factor receptor-3 (FGFR3) pathway acts as a negative regulator of the growth plate chondrogenesis (Figure 1). Heterozygous gain-offunction mutations in the FGFR3 cause achondroplasia and hypochondroplasia. Achondroplasia is the most frequent skeletal dysplasia and is clinically characterized by severe disproportional short stature with rhizomelia (29). In contrast, hypochondroplasia is generally less severe and presents a broader phenotypic variability (30). Although there is an evident abnormal proportion in patients with hypochondroplasia and FGFR3 alterations 73

Genetic causes of isolated short stature

is rare in patients classified as ISS (31), some children still can be undiagnosed at first evaluation. More recently, a study identified FGFR3-activating mutation causing autosomal dominant familial proportionate short stature without other specific findings (32).

GENES RELATED TO THE GH-IGF1 AXIS Since the growth hormone (GH) and insulin-like growth factor 1 (IGF-1) have been initially recognized as the main regulators of longitudinal growth, the first researches in the field of genetics of short stature attempted to identify children with defects in the GH–IGF-1–bone axis. GH is secreted by the pituitary gland, and promotes bone elongation mainly through regulating synthesis of IGF-1, both circulating and peripheral. Growth impairment can be caused by gene defects that affect several components of this cascade (summarized in Table 2), from the synthesis of GH to the action of IGF-1. Affected subjects may not present classical features of GH/IGF-1 deficiency or resistance, in which cases they would often be classified as having ISS.

GH1 Defects in GH1 gene, which encodes GH, were firstly recognized as a cause of isolated GH deficiency (IGHD). The genetic defects responsible for this phenotype are generally deletions involving the gene or point mutations leading to a truncated protein, although some missense mutations and rare promoter region mutations have already been reported (33). Affected

children typically present proportionate short stature with low growth velocity, low IGF-1 concentration and an inadequate response during GH provocative tests. Additionally, heterozygous and homozygous mutations in GH1 have been associated with bioinactive GH, characterized by a similar phenotype to IGHD, except for normal or elevated GH levels (34). Children with GH1 defects may present a milder phenotype than that classically described, with no typical findings that allow the diagnosis of IGHD or of bioinactive GH. This may be particularly important in less severe genetic defects, as reported in a study that identified a heterozygous mutation in the GH1 gene promoter associated to ISS (35). In these cases, the etiology of short stature remains undefined after the initial clinical and laboratorial evaluation.

GHSR Two peptides stimulate GH synthesis and secretion: growth hormone-releasing hormone (GHRH) and ghrelin. Ghrelin acts through interaction with the GH secretagogue receptor (GHSR) and has also a potent orexigenic effect (36). Defects in the GHSR gene have been associated with ISS and GH deficiency with variable severity and penetrance. Both phenotypes were even described in the same family (37). Additionally, some affected children had delayed puberty (38). This heterogeneity in clinical presentation may be partially explained because gene defects can result in protein alterations that affect the binding affinity to ghrelin and the constitutive activity of the receptor.

Table 2. Genes related to GH-IGF1 axis that are associated with isolated short stature Gene

First report in patient classified as ISS

Frequency in ISS (%)

Inheritance

GH1

2003

GHSR

2006

2.0 to 2.4

AD/AR

GHD and ISS in the same family

(37,55)

GHR

1995

0 to 5.0

Laboratory suggestive of partial GH insensitivity

(56,57)

STAT5B

2018

Three families described with eczema and laboratory suggestive of partial GH insensitivity

IGF1

2012

Birth weight and birth length in the lower normal range

IGF1R

2003

1.6 to 2.0

Born small for gestational age in the most cases and elevated levels of IGF-1

IGFALS

2004

Severe deficiency of IGF-1 and IGFBP-3 disproportional to the severity of short stature

(48)

PAPP-A2

2016

High levels of IGF-1 and IGFPB-3

(50)

Additional common findings Low height velocity and delayed bone age

References (35)

(41) (45,58) (46,47,59)

NA: prevalence study is not available; ISS: idiopathic short stature.

Arch Endocrinol Metab. 2019;63/1

Genetic causes of isolated short stature

GH exerts its action by binding to the GH receptor (GHR), a member of the cytokine superfamily of receptors. Homozygous or compound heterozygous mutations in GHR gene cause complete GH insensitivity (GHI), known as Laron syndrome, characterized by extreme short stature, high or normal GH concentrations, very low IGF-1 and IGFBP-3 levels, and no increase in IGF-1 concentration after exogenous GH stimulation (39). Differently, heterozygous GHR mutations can cause a variable spectrum of GHI, ranging from total absence of GHR activation to milder impairment causing subtler clinical phenotypes. Until now, only seven patients have been reported with heterozygous GHR mutations with a dominantnegative effect causing short stature with recognizable features of partial GHI. Several other studies have reported heterozygous GHR variants in ISS patient cohorts, with a frequency between 5% and 15.5%. However, many of these variants have not been proven to be causative of short stature. It is supposed that the ISS phenotype, accompanied by some degree of GHI, may be caused by less deleterious heterozygous GHR mutations. Some authors suggested that low growth hormone binding protein (GHBP) levels could indicate a defect in the extracellular domain of the GHR in these patients (40). Hence, since the clinical characterization remains subjective, heterozygous GHR mutations may be responsible for the growth failure observed in a group of children with isolated short stature and non-classical laboratory phenotype associated with impaired GH action.

STAT5B STAT5B is an essential protein in the intracellular signaling pathway downstream of GHR activation. Homozygous inactivating STAT5B mutations cause the classical phenotype of GH insensitivity associated with immunodeficiency (mainly eczema and chronic pulmonary disease). Relatives of autosomal recessive STAT5B deficient patients who carry STAT5B mutations usually have heights within the low normal range (41). In 2018, three heterozygous STAT5B mutations with a dominat-negative effect were described in eleven individuals from three unrelated families, whose probands had undiagnosed short stature and Arch Endocrinol Metab. 2019;63/1

laboratory evaluation of mild GH insensitivity. Most of the affected individuals presented elevated IgE, mild eczema and short stature with inter- and intra-familial variability (42).

IGF1 and IGF1R IGF-1 is the main growth factor in intrauterine development and in postnatal growth and acts through the binding to a cell surface tyrosine kinase receptor called IGF1R. Deletions or homozygous loss-offunction mutations in IGF1 gene cause severe pre- and post-natal growth failure, microcephaly and retarded intellectual development (43). Affected patients present extreme low IGF-1 levels with normal or high GH concentrations. Individuals heterozygous for IGF1 variants were significantly shorter and had reduced head circumferences compared to noncarrier relatives. Affected children born from affected mothers appear to have a more compromised height, which suggest a role of placental dysfunction (44). In 2014, a complete IGF1 gene deletion in heterozygosity was reported in a patient with ISS. The affected child had birth length and weight within the low normal value and presented postnatal growth failure with low-normal serum IGF-1 (45). Patients heterozygous for IGFR1 defects have a similar phenotype to that of patients with IGF-1 mutations, except for the relatively high IGF-1 concentrations (46). Although this is a rare condition, some patients may have a less obvious clinical presentation, and short statute may be the only recognizable characteristic (47).

Ternary complex defects (IGFALS and PAPP-A2) Most of the serum IGF-1 circulates bound to IGF binding protein type 3 (IGFBP-3) and acid-labile subunit (ALS), forming a ternary complex. This complex is essential to extend serum IGF-1 half-life and to decrease its bioavailability at tissue level. On the other hand, pregnancy-associated plasma protein A2 (PAPPA2) is a serum and tissue protease responsible for the proteolysis of IGFBP-3, releasing IGF-1 from the ternary complex. Biallelic loss-of-function mutations in IGFALS result in extreme decrease in the circulating levels of functional ALS (48). The consequence of this is the impossibility to form a ternary complex with reduced IGF-1 and IGFBP-3 levels, which is reflected clinically 75

GHR

Genetic causes of isolated short stature

in mild short stature associated with delayed puberty. Over the past years, it has been postulated that heterozygous variants in IGFALS are responsible for isolated short stature phenotype. Affected children presented partial ALS deficiency and a mean decrease in height of 1 SDS (49). The opposite phenomenon, i.e. increased IGF-1 and IGFBP-3 levels, was first described in 2016. Five affected children coming from two different families had PAPPA2 deficiency caused by autosomal recessive mutations in PAPPA2 gene. In addition to variable short stature (heights ranged from -1.0 to -3.8 SDS), some patients had microcephaly, thin long bones, low bone mineral density, and insulin resistance (50).

OTHER GENE PTPN11 The protein-tyrosine phosphatase non-receptor type 11 gene (PTPN11) encodes the non-receptor Srchomology 2 (SH2) domain-containing protein tyrosine phosphatase 2 (SHP2). SHP2 participates in multiple intracellular signaling pathways, including the Ras/ MAPK cascade. Activating heterozygous mutations in PTPN11 cause the Noonan syndrome (NS), characterized by reduced postnatal growth, congenital heart disease, and facial dysmorphisms. Commonly, affected children present low serum IGF-1 level, which reflects some degree of GH insensitivity (51). Similarly to the other genes reported above, there is a variable clinical presentation in affected individuals, even within the same family. In addition, the craniofacial features change with age, therefore it can be sometimes challenging to make a clinical diagnosis of NS. Finally, pathogenic variants in PTPN11 have been identified in patients from a cohort of ISS children (11).

CONCLUSION AND FUTURE DIRECTIONS Over the past several years, an increasing number of genetic variants have been associated with short stature. Many of these genes have been long known to be causing extreme phenotypes of growth disorders, which are clinically recognized, such as skeletal dysplasias or GH resistance syndromes. Nowadays, with the advent and greater availability of next-generation sequencing techniques, it has become possible to identify several gene defects in short stature children that presented 76

clinically with the mildest spectrum of the diseases and that were initially classified as ISS. The identification of the genetic causes of short stature prevents children to undergo unnecessary exams, and can give hints on the growth outcomes, with or without recombinant human GH (rhGH). For example, it is known that patients with SHOX defects have a good response to rhGH therapy (18). Conversely, it is expected that ISS children with less severe defects of the GH-IGF-1 axis, including less severe GHR mutations, will respond less to rhGH use at regular dosage (40). Besides that, a CNP analog named vosoritide, that has been used as an experimental drug for the treatment of achondroplasia, can be in the future an option to treat children with nonsyndromic short stature, especially those with heterozygous mutations in the NPR2 or in the NPPC genes (21). The lack of specific characteristics makes accurate diagnosis difficult without the use of molecular genetic study. For this same reason, candidate gene analysis is generally not sufficient, and hence, a multiple-gene testing approach using next-generation sequencing (NGS) is preferable. The choice of the use of whole exome sequencing (WES) or gene-panel analysis of the genes will depend on the availability and on cost-benefit evaluation. Even when using the WES, the analysis of these patients should prioritize genes already associated with the isolated short stature phenotype. In the years that will follow, molecular genetic study using a panel of genes or exome analysis will become mandatory when investigating children with isolated short stature, with a crucial impact on treatment and follow-up. Grants: this work was supported by Grants 2013/03236–5 (to A.A.L.J.) from the São Paulo Research Foundation (FAPESP), Grant 304678/2012–0 (to A.A.L.J.) from the National Council for Scientific and Technological Development (CNPq) and by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – Finance Code 1658266 (to G.A.V.). Disclosure: no potential conflict of interest relevant to this article was reported.

REFERENCES 1.

Visscher PM. Commentary: Height and Mendel’s theory: the long and the short of it. Int J Epidemiol. 2013;42(4):944-5.

2. Sisley S, Trujillo MV, Khoury J, Backeljauw P. Low incidence of pathology detection and high cost of screening in the evaluation of asymptomatic short children. J Pediatr. 2013;163(4):1045-51. 3. Cohen P, Rogol AD, Deal CL, Saenger P, Reiter EO, Ross JL, et al. Consensus statement on the diagnosis and treatment of children Arch Endocrinol Metab. 2019;63/1

Genetic causes of isolated short stature

4. Silventoinen K, Sammalisto S, Perola M, Boomsma DI, Cornes BK, Davis C, et al. Heritability of adult body height: a comparative study of twin cohorts in eight countries. Twin Res. 2003;6(5):399-408. 5. Wood AR, Esko T, Yang J, Vedantam S, Pers TH, Gustafsson S, et al. Defining the role of common variation in the genomic and biological architecture of adult human height. Nat Genet. 2014;46(11):1173-86. 6. Marouli E, Graff M, Medina-Gomez C, Lo KS, Wood AR, Kjaer TR, et al. Rare and low-frequency coding variants alter human adult height. Nature. 2017;542(7640):186-90. 7.

Eichler EE, Flint J, Gibson G, Kong A, Leal SM, Moore JH, et al. Missing heritability and strategies for finding the underlying causes of complex disease. Nat Rev Genet. 2010;11(6):446-50.

8. Grunauer M, Jorge AAL. Genetic short stature. Growth Horm IGF Res. 2018;38:29-33.

21. Vasques GA, Arnhold IJ, Jorge AA. Role of the natriuretic peptide system in normal growth and growth disorders. Horm Res Paediatr. 2014;82(4):222-9. 22. Wang SR, Jacobsen CM, Carmichael H, Edmund AB, Robinson JW, Olney RC, et al. Heterozygous mutations in natriuretic peptide receptor-B (NPR2) gene as a cause of short stature. Hum Mutat. 2015;36(4):474-81. 23. Gibson BG, Briggs MD. The aggrecanopathies; an evolving phenotypic spectrum of human genetic skeletal diseases. Orphanet J Rare Dis. 2016;11(1):86. 24. Gkourogianni A, Andrew M, Tyzinski L, Crocker M, Douglas J, Dunbar N, et al. Clinical Characterization of Patients With Autosomal Dominant Short Stature due to Aggrecan Mutations. J Clin Endocrinol Metab. 2017;102(2):460-9. 25. van der Steen M, Pfundt R, Maas S, Bakker-van Waarde WM, Odink RJ, Hokken-Koelega ACS. ACAN Gene Mutations in Short Children Born SGA and Response to Growth Hormone Treatment. J Clin Endocrinol Metab. 2017;102(5):1458-67.

Dauber A, Stoler J, Hechter E, Safer J, Hirschhorn JN. Whole exome sequencing reveals a novel mutation in CUL7 in a patient with an undiagnosed growth disorder. J Pediatr. 2013;162(1):202-4 e1.

26. Minina E, Wenzel HM, Kreschel C, Karp S, Gaffield W, McMahon AP, et al. BMP and Ihh/PTHrP signaling interact to coordinate chondrocyte proliferation and differentiation. Development. 2001;128(22):4523-34.

10. de Bruin C, Finlayson C, Funari MF, Vasques GA, Lucheze Freire B, Lerario AM, et al. Two Patients with Severe Short Stature due to a FBN1 Mutation (p.Ala1728Val) with a Mild Form of Acromicric Dysplasia. Horm Res Paediatr. 2016;86(5):342-8.

27. Lai LP, Mitchell J. Indian hedgehog: its roles and regulation in endochondral bone development. J Cell Biochem. 2005;96(6):1163-73.

11. Wang SR, Carmichael H, Andrew SF, Miller TC, Moon JE, Derr MA, et al. Large-scale pooled next-generation sequencing of 1077 genes to identify genetic causes of short stature. J Clin Endocrinol Metab. 2013;98(8):E1428-37. 12. Rao E, Weiss B, Fukami M, Rump A, Niesler B, Mertz A, et al. Pseudoautosomal deletions encompassing a novel homeobox gene cause growth failure in idiopathic short stature and Turner syndrome. Nat Genet. 1997;16(1):54-63. 13. Vasques GA, Amano N, Docko AJ, Funari MF, Quedas EP, Nishi MY, et al. Heterozygous mutations in natriuretic peptide receptor-B (NPR2) gene as a cause of short stature in patients initially classified as idiopathic short stature. J Clin Endocrinol Metab. 2013;98(10):E1636-44. 14. Nilsson O, Guo MH, Dunbar N, Popovic J, Flynn D, Jacobsen C, et al. Short stature, accelerated bone maturation, and early growth cessation due to heterozygous aggrecan mutations. J Clin Endocrinol Metab. 2014;99(8):E1510-8. 15. Vasques GA, Funari MFA, Ferreira FM, Aza-Carmona M, Sentchordi-Montane L, Barraza-Garcia J, et al. IHH Gene Mutations Causing Short Stature With Nonspecific Skeletal Abnormalities and Response to Growth Hormone Therapy. J Clin Endocrinol Metab. 2018;103(2):604-14. 16. Hisado-Oliva A, Ruzafa-Martin A, Sentchordi L, Funari MFA, Bezanilla-Lopez C, Alonso-Bernaldez M, et al. Mutations in C-natriuretic peptide (NPPC): a novel cause of autosomal dominant short stature. Genet Med. 2018;20(1):91-7. 17. Nilsson O, Marino R, De Luca F, Phillip M, Baron J. Endocrine regulation of the growth plate. Horm Res. 2005;64(4):157-65. 18. Marchini A, Ogata T, Rappold GA. A Track Record on SHOX: From Basic Research to Complex Models and Therapy. Endocr Rev. 2016;37(4):417-48. 19. Jorge AA, Souza SC, Nishi MY, Billerbeck AE, Liborio DC, Kim CA, et al. SHOX mutations in idiopathic short stature and Leri-Weill dyschondrosteosis: frequency and phenotypic variability. Clin Endocrinol (Oxf). 2007;66(1):130-5. 20. Malaquias AC, Scalco RC, Fontenele EG, Costalonga EF, Baldin AD, Braz AF, et al. The sitting height/height ratio for age in healthy and short individuals and its potential role in selecting short children for SHOX analysis. Horm Res Paediatr. 2013;80(6):449-56. Arch Endocrinol Metab. 2019;63/1

28. Liu M, Wang X, Cai Z, Tang Z, Cao K, Liang B, et al. A novel heterozygous mutation in the Indian hedgehog gene (IHH) is associated with brachydactyly type A1 in a Chinese family. J Hum Genet. 2006;51(8):727-31. 29. Horton WA, Hall JG, Hecht JT. Achondroplasia. Lancet. 2007;370(9582):162-72. 30. Rousseau F, Bonaventure J, Legeai-Mallet L, Schmidt H, Weissenbach J, Maroteaux P, et al. Clinical and genetic heterogeneity of hypochondroplasia. J Med Genet. 1996;33(9):749-52. 31. Mamada M, Yorifuji T, Kurokawa K, Kawai M, Momoi T, Nakahata T. Prevalence of Mutations in the FGFR3 Gene in Individuals with Idiopathic Short Stature. Clin Pediatr Endocrinol. 2006;15(2):61-4. 32. Kant SG, Cervenkova I, Balek L, Trantirek L, Santen GW, de Vries MC, et al. A novel variant of FGFR3 causes proportionate short stature. Eur J Endocrinol. 2015;172(6):763-70. 33. Mullis PE. Genetics of growth hormone deficiency. Endocrinol Metab Clin North Am. 2007;36(1):17-36. 34. Besson A, Salemi S, Deladoey J, Vuissoz JM, Eble A, Bidlingmaier M, et al. Short stature caused by a biologically inactive mutant growth hormone (GH-C53S). J Clin Endocrinol Metab. 2005;90(5):2493-9. 35. Millar DS, Lewis MD, Horan M, Newsway V, Easter TE, Gregory JW, et al. Novel mutations of the growth hormone 1 (GH1) gene disclosed by modulation of the clinical selection criteria for individuals with short stature. Hum Mutat. 2003;21(4):424-40. 36. Sun Y, Wang P, Zheng H, Smith RG. Ghrelin stimulation of growth hormone release and appetite is mediated through the growth hormone secretagogue receptor. Proc Natl Acad Sci U S A. 2004;101(13):4679-84. 37. Pantel J, Legendre M, Cabrol S, Hilal L, Hajaji Y, Morisset S, et al. Loss of constitutive activity of the growth hormone secretagogue receptor in familial short stature. J Clin Invest. 2006;116(3):760-8. 38. Pugliese-Pires PN, Fortin JP, Arthur T, Latronico AC, Mendonca BB, Villares SM, et al. Novel inactivating mutations in the GH secretagogue receptor gene in patients with constitutional delay of growth and puberty. Eur J Endocrinol. 2011;165(2):233-41. 39. Laron Z. Laron syndrome (primary growth hormone resistance or insensitivity): the personal experience 1958-2003. J Clin Endocrinol Metab. 2004;89(3):1031-44.

with idiopathic short stature: a summary of the Growth Hormone Research Society, the Lawson Wilkins Pediatric Endocrine Society, and the European Society for Paediatric Endocrinology Workshop. J Clin Endocrinol Metab. 2008;93(11):4210-7.

Genetic causes of isolated short stature

40. Storr HL, Chatterjee S, Metherell LA, Foley C, Rosenfeld RG, Backeljauw PF, et al. Non-classical growth hormone insensitivity (GHI): characterization of mild abnormalities of GH action. Endocr Rev. 2018.

50. Dauber A, Munoz-Calvo MT, Barrios V, Domene HM, Kloverpris S, Serra-Juhe C, et al. Mutations in pregnancy-associated plasma protein A2 cause short stature due to low IGF-I availability. EMBO Mol Med. 2016;8(4):363-74.

41. Scalco RC, Hwa V, Domene HM, Jasper HG, Belgorosky A, Marino R, et al. STAT5B mutations in heterozygous state have negative impact on height: another clue in human stature heritability. Eur J Endocrinol. 2015;173(3):291-6.

51. Tartaglia M, Kalidas K, Shaw A, Song X, Musat DL, van der Burgt I, et al. PTPN11 mutations in Noonan syndrome: molecular spectrum, genotype-phenotype correlation, and phenotypic heterogeneity. Am J Hum Genet. 2002;70(6):1555-63.

42. Klammt J, Neumann D, Gevers EF, Andrew SF, Schwartz ID, Rockstroh D, et al. Dominant-negative STAT5B mutations cause growth hormone insensitivity with short stature and mild immune dysregulation. Nat Commun. 2018;9(1):2105.

52. Hu X, Gui B, Su J, Li H, Li N, Yu T, et al. Novel pathogenic ACAN variants in non-syndromic short stature patients. Clin Chim Acta. 2017;469:126-9.

43. Woods KA, Camacho-Hubner C, Savage MO, Clark AJ. Intrauterine growth retardation and postnatal growth failure associated with deletion of the insulin-like growth factor I gene. N Engl J Med. 1996;335(18):1363-7. 44. van Duyvenvoorde HA, van Setten PA, Walenkamp MJ, van Doorn J, Koenig J, Gauguin L, et al. Short stature associated with a novel heterozygous mutation in the insulin-like growth factor 1 gene. J Clin Endocrinol Metab. 2010;95(11):E363-7. 45. Batey L, Moon JE, Yu Y, Wu B, Hirschhorn JN, Shen Y, et al. A novel deletion of IGF1 in a patient with idiopathic short stature provides insight Into IGF1 haploinsufficiency. J Clin Endocrinol Metab. 2014;99(1):E153-9. 46. Abuzzahab MJ, Schneider A, Goddard A, Grigorescu F, Lautier C, Keller E, et al. IGF-I receptor mutations resulting in intrauterine and postnatal growth retardation. N Engl J Med. 2003;349(23):2211-22. 47. Ester WA, van Duyvenvoorde HA, de Wit CC, Broekman AJ, Ruivenkamp CA, Govaerts LC, et al. Two short children born small for gestational age with insulin-like growth factor 1 receptor haploinsufficiency illustrate the heterogeneity of its phenotype. J Clin Endocrinol Metab. 2009;94(12):4717-27. 48. Domene HM, Bengolea SV, Martinez AS, Ropelato MG, Pennisi P, Scaglia P, et al. Deficiency of the circulating insulin-like growth factor system associated with inactivation of the acid-labile subunit gene. N Engl J Med. 2004;350(6):570-7.

54. Hellemans J, Coucke PJ, Giedion A, De Paepe A, Kramer P, Beemer F, et al. Homozygous mutations in IHH cause acrocapitofemoral dysplasia, an autosomal recessive disorder with cone-shaped epiphyses in hands and hips. Am J Hum Genet. 2003;72(4):1040-6. 55. Inoue H, Kangawa N, Kinouchi A, Sakamoto Y, Kimura C, Horikawa R, et al. Identification and functional analysis of novel human growth hormone secretagogue receptor (GHSR) gene mutations in Japanese subjects with short stature. J Clin Endocrinol Metab. 2011;96(2):E373-8. 56. Goddard AD, Covello R, Luoh SM, Clackson T, Attie KM, Gesundheit N, et al. Mutations of the growth hormone receptor in children with idiopathic short stature. The Growth Hormone Insensitivity Study Group. N Engl J Med. 1995;333(17):1093-8. 57. El Kholy M, Mella P, Rashad M, Buzi F, Meazza C, Zahra S, et al. Growth hormone/IGF-I axis and growth hormone receptor mutations in idiopathic short stature. Horm Res Paediatr. 2011;76(5):300-6. 58. Fuqua JS, Derr M, Rosenfeld RG, Hwa V. Identification of a novel heterozygous IGF1 splicing mutation in a large kindred with familial short stature. Horm Res Paediatr. 2012;78(1):59-66. 59. Caliebe J, Broekman S, Boogaard M, Bosch CA, Ruivenkamp CA, Oostdijk W, et al. IGF1, IGF1R and SHOX mutation analysis in short children born small for gestational age and short children with normal birth size (idiopathic short stature). Horm Res Paediatr. 2012;77(4):250-60.

49. Domene HM, Scaglia PA, Martinez AS, Keselman AC, Karabatas LM, Pipman VR, et al. Heterozygous IGFALS gene variants in idiopathic short stature and normal children: impact on height and the IGF system. Horm Res Paediatr. 2013;80(6):413-23.

53. Hauer NN, Sticht H, Boppudi S, Buttner C, Kraus C, Trautmann U, et al. Genetic screening confirms heterozygous mutations in ACAN as a major cause of idiopathic short stature. Sci Rep. 2017;7(1):12225.

Arch Endocrinol Metab. 2019;63/1

case report

Aggressive papillary thyroid carcinoma in a child with type 2 congenital generalized lipodystrophy Grayce Ellen da Cruz Paiva Lima1, Virgínia Oliveira Fernandes1, Ana Paula Dias Rangel Montenegro1, Annelise Barreto de Carvalho1, Lia Beatriz de Azevedo Sousa Karbage1, Lindenberg Barbosa Aguiar1, Mário Sérgio Rocha Macedo1, Luis Alberto Albano Ferreira1, Renan Magalhães Montenegro Júnior1

SUMMARY Thyroid carcinoma (TC) is rare in children, particularly in those aged < 10 years. Several studies have demonstrated a correlation between neoplasms and hyperinsulinemia and insulin resistance, which are often associated with a higher risk for and/or aggressiveness of the neoplasm. Congenital generalized lipodystrophy (CGL) with autosomal recessive inheritance is a rare disease and is characterized by the lack of adipose tissue, severe insulin resistance, and early metabolic disturbances. Here, we reported a rare case of a type 2 CGL in a girl who presented with a papillary TC (PTC) at the age of 7 years. She had no family history of TC or previous exposure to ionizing radiation. She had a generalized lack of subcutaneous fat, including the palmar and plantar regions, muscle hypertrophy, intense acanthosis nigricans, hepatomegaly, hypertriglyceridemia, severe insulin resistance, and hypoleptinemia. A genetic analysis revealed a mutation in the BSCL2 gene (p.Thr109Asnfs* 5). Ultrasound revealed a hypoechoic solid nodule measuring 1.8 × 1.0 × 1.0 cm, and fine needle aspiration biopsy suggested malignancy. Total thyroidectomy was performed, and a histopathological examination confirmed PTC with vascular invasion and parathyroid lymph node metastasis (pT3N1Mx stage). This is the first report to describe a case of differentiated TC in a child with CGL. Severe insulin resistance that is generally observed in patients with CGL early in life, especially in those with type 2 CGL, may be associated with this uncommon presentation of aggressive PTC during childhood. Arch Endocrinol Metab.

Grupo Brasileiro para Estudos de Lipodistrofias Herdadas e Adquiridas (BRAZLIPO), Hospital Universitário Walter Cantídio, Universidade Federal do Ceará (UFC), Fortaleza, CE, Brasil 1

Correspondence to: Renan Magalhães Montenegro Júnior Av. Professor Costa Mendes, 1608 60416-200 – Rodolfo Teófilo, Fortaleza, CE, Brasil renanmmjr@gmail.com Received on May/28/2018 Accepted on Oct/30/2018 DOI: 10.20945/2359-3997000000096

2019;63(1):79-83

hyroid carcinoma (TC) is rare in children, particularly those aged < 10 years, and accounts for 1.5%–3% of all childhood cancers in North America and Europe; however, its incidence has been increasing by 1.1% each year (1). In Brazil, according to the National Cancer Institute database, the incidence of TC may be 2% of all pediatric cancers (2). The behavior of TC in children aged < 10 years differs from that in adults, because in the pediatric range there is usually at least one risk factor for papillary TC (PTC), mainly ionizing radiation exposure and family history (3). Several studies have revealed the correlation between neoplasms and hyperinsulinemia and insulin resistance (IR), which are frequently associated with a higher risk for and/or aggressiveness of the neoplasm (4-6). However, many of those studies included subjects who were obese, which characterizes many confounding variables (6-8), and data in conditions of severe IR are lacking. CGL is a rare disease with autosomal recessive inheritance characterized by a lack of adipose tissue, Arch Endocrinol Metab. 2019;63/1

hypoleptinemia, severe IR, and early metabolic disturbances such as dyslipidemia and diabetes mellitus (9,10). Here, we report a rare case of type 2 CGL in a girl who presented with PTC at the age of 7 years and who had no family history of TC or previous exposure to ionizing radiation.

CASE REPORT A 9-year-old girl with a clinical and molecular diagnosis of CGL was being followed at our center, (BRAZLIPO Program, Endocrine and Diabetes Unit, University Hospital, Federal University of Ceará, Brazil). Based on the generalized absence of adipose tissue, she was clinically diagnosed as having CGL in her first year of life. A physical examination at 7 years of age revealed a height of 143 cm, a weight of 42.1 kg, and a body mass index (BMI) of 20.5 kg/m2. She had a generalized lack of subcutaneous fat, including in the palmar and 79

INTRODUCTION

Thyroid carcinoma in CGL

plantar regions, muscle hypertrophy, intense acanthosis nigricans, and hepatomegaly (Figure 1). The patient also had a history of consanguinity. Her parents are first-degree cousins, and her brother has the same clinical diagnosis of CGL (Figure 2). In her first year of life, hypertriglyceridemia (442 mg/dL) was detected. During follow-up, her clinical and laboratory work-up revealed IR (Table 1). At 7 years of age, fasting hyperinsulinemia, severe IR, abnormal glucose tolerance, and hypoleptinemia were also observed. At this time, a genetic analysis revealed a BSCL2 gene mutation (p.Thr109Asnfs* 5), characterizing type 2 CGL. At 7 years of age, thyroid gland ultrasound revealed a hypoechoic solid nodule measuring 1.8 × 1.0 × 1.0 cm in size, with partially defined margins and multiple foci of microcalcification located in the upper third of the right lobe. According to the clinical history, the patient had no family history of TC or previous exposure to ionizing radiation. Results of a cytological evaluation of the nodule, obtained through fine-needle aspiration biopsy, suggested malignancy (Bethesda V classification). Thus, total thyroidectomy was performed. Results of a histopathological examination confirmed a classical variant of PTC, with the tumor measuring 1.2 cm (unifocal) and having vascular invasion. Perineural infiltration was not performed. Extrathyroid extension and metastasis were observed in a parathyroid lymph node (pT3N1Mx stage) (Figure 3). The patient also underwent radioiodine therapy (100 mCi), followed by suppressive levothyroxine treatment (3 mcg/kg/day), and no signs of residual disease.

Figure 2. The family pedigree of the patient showing two siblings affected by congenital generalized lipodystrophy. Table 1. Clinical and laboratory data of a patient with CGL during follow-up First evaluation

Second evaluation

Third evaluation

Age (years)

2.16

4.75

7.58

Weight

15.5

27.7

42.1

Height

122.5

143

16.6

18.4

20.5

BMI (kg/m ) 2

Glucose (mg/dL)

6,3

6,1

Insulin (µU/mL)

20.6

41.02

102

HOMA-IR

3.66

8.09

8,3

TC (mg/dL)

185

143

161

HDL (mg/dL)

Triglycerides (mg/dL)

284

324

117

TSH (µUI/mL)

2.09

1.2

2.3

Leptin (ng/mL)

1.0

A1c (%)

BMI: body mass index; HOMA: homeostasis model assessment-insulin resistance; TC: total cholesterol; HDLc: high-density lipoprotein cholesterol; TG: triglyceride; TSH: thyroid-stimulating hormone.

Figure 1. Clinical characteristics of a 7-year-old girl with a diagnosis of congenital generalized lipodystrophy. (A) Absence of adipose tissue in the face. (B) Severe acanthosis nigricans. (C and D) Absence of adipose tissue in the palmar and plantar regions, respectively. (E) Global absence of adipose tissue and muscle pseudohypertrophy. 80

Arch Endocrinol Metab. 2019;63/1

Figure 3. Histopathological examination showing normal thyroid tissue below and papillary thyroid neoplasia at the top of the image.

RESULTS AND DISCUSSION This is the first study to report about a differentiated TC (DTC) in a child with CGL. Although the patient did not present with other risk factors for TC, i.e., previous radiation exposure or a family history of TC, she had severe CGL-associated IR since early childhood. Furthermore, she had an aggressive presentation of PTC (pT3N1Mx stage). CGL is a rare congenital disorder that is characterized by total or near-total lack of body fat, low leptin levels, ectopic fat deposits, and severe metabolic disorders such as hypertriglyceridemia and IR (10). Four subtypes of CGL have been described. Subtypes 1 and 2 are responsible for 95% of described cases and occur because of mutations in the AGPAT2 and BSL2 genes, respectively, which express proteins that are critical in triglyceride and phospholipid biosynthesis, lipid droplet formation, and adipocyte differentiation (11). Low leptin and adiponectin levels, increased free fatty acids, and triglyceride depositions in the liver and skeletal muscles, which are associated with severe IR, are frequently noted (12-15). CGL because of BSCL2 mutation is the most severe form of CGL, with a pronounced lack of adipose tissue (16). It affects both the metabolic active and mechanical adipose tissues and usually results in earlier and more severe metabolic abnormalities. Mental retardation and cardiomyopathy have also been described (16). Our patient presented with clinical and biochemical phenotypic characteristics of CGL. She had hypertriglyceridemia and intense acanthosis nigricans since her first year of life. The first described Arch Endocrinol Metab. 2019;63/1

case of the association between DTC and IR was in a 13.5-year-old obese girl with acanthosis nigricans (17). Diabetes and IR are considered risk factors for DTC (18). Epidemiological studies have suggested the association, although in such studies only obese subjects were evaluated, possibly leading to the presence of a positive confounder (7,19,20). A previous crosssectional study assessed the correlation between IR and thyroid, independent of body weight, in participants grouped according to their BMI and homeostasis model assessment-IR (HOMA-IR) and concluded that individuals with higher IR had a higher number of nodules and greater thyroid volume, independent of BMI (8). Our patient had hyperinsulinemia since the 7 years of age. Insulin acts as a growth factor that stimulates cell proliferation. Some studies have described that insulin receptors (IRs) are overexposed in most DTC cases (21,22). In addition, insulin reduces insulinlike growth factor-binding protein levels, leading to increased levels of insulin-like growth factor (IGF), subsequently resulting in cell multiplication and apoptosis reduction. Insulin also increases the risk of mutations and cancer development (22). IGF-1 plays a role in various human malignancies and possibly in DTC (21,22). IGF-1 is important for thyroid growth and development, as thyroidstimulating hormone (TSH). In addition, IGFreceptors are overexpressed in DTC (21), which amplifies the anabolic effect on thyrocytes (23). Some studies have described the presence of high leptin levels in patients with DTC (24). Cheng and cols. demonstrated that leptin and leptin receptors are overexpressed in patients with PTC, which correlates with increased tumor aggressiveness (7). In contrast, our patient had very low leptin levels, which correlated to the absence of metabolic active adipose tissues. Although our patient had no clinical diagnosis of diabetes, she had altered glycated hemoglobin levels. Most studies have demonstrated the correlation between diabetes and DTC. In their case-control study, Bae and cols. observed that Korean women in the upper quarters of HOMA-IR had an odds ratio of 4.07 (95% confidence interval [CI] 2.81â&#x20AC;&#x201C;5.89, p < 0.001) for DTC. These data were adjusted for age, BMI, history of smoking, hypertension, thyroid disease, other cancers, cholesterol levels and TSH (25). In the meta-analysis conducted by Yeo and cols., women with pre-existing DM had an increased risk for 81

Thyroid carcinoma in CGL

TC (relative risk = 1.38, 95% CI 1.13–1.67) (26). A similar conclusion was observed in another review that revealed that diabetes had a possible positive association with risk for TC (27). Conversely, in a systematic review, Kitahara and cols. concluded that neither physical inactivity nor diabetes history was associated with an increased risk for TC (28). These results are controversial, and evidence is not sufficient to associate RI or diabetes with TC (25,29,30). However, it is unlikely that the association reported here is a random occurrence. The occurrence of DTC in children aged < 10 years is rare and is usually associated with the presence of identifiable risk factors such as a family history and exposure to ionizing radiation during childhood; however, this was not observed in our patient. Our patient had IR since her first year of life, which was related to the most severe subtype of CGL. Our case findings reinforce the hypothesis that IR is a trigger for CGL, independent of BMI or leptin levels. In conclusion, this is the first report to describe DTC in a child with CGL. The severe IR usually observed in this disorder early in life, especially type 2 of CGL, may be associated with the uncommon presentation of aggressive PTC during childhood. Future prospective studies are needed to better define the association between TC and severe IR and demonstrate the possible benefit of thyroid evaluation in patients with CGL. Authorship: GECPL, VFO, APDRM, ABC, LBAS, LBA, MSRA, LAAF, and RMMJ managed the patient; LBA performed imaging examinations; MSRA and LAAF performed thyroidectomy; GECPL collected data, and GECPL, VOF, and RMMJ wrote and revised the manuscript; APDRM, ABC, and RMMJ supervised the report. All authors read and approved the final manuscript for publication. Acknowledgments: we thank the patient and Hospital Universitário Walter Cantidio Endocrinology unit and Pediatric Endocrinology unit, Fortaleza, Ceará, Brazil. We also thank the librarian Andrezza Abraham Ohana de Sousa, for formatting the manuscript. Disclosure: no potential conflict of interest relevant to this article was reported.

Available at: http://www1.inca.gov.br/tumores_infantis/pdf/English_Version_tumores_Infantis06102009.pdf. 3. Rivkees SA, Mazzaferri EL, Verburg FA, Reiners C, Luster M, Breuer CK, et al. The treatment of differentiated thyroid cancer in children: emphasis on surgical approach and radioactive iodine therapy. Endocr Rev. 2011;32(6):798-826. 4. Arcidiacono B, Iiritano S, Nocera A, Possidente K, Nevolo MT, Ventura V, et al. Insulin resistance and cancer risk: an overview of the pathogenetic mechanisms. Exp Diabetes Res. 2012;2012:789174. 5. Tsugane S, Inoue M. Insulin resistance and cancer: epidemiological evidence. Cancer Sci. 2010;101(5):1073-9. 6. Rezzónico JN, Rezzónico M, Pusiol E, Pitoia F, Niepomniszcze H. Increased prevalence of insulin resistance in patients with differentiated thyroid carcinoma. Metab Syndr Relat Disord. 2009;7(4):375-80. 7. Cheng SP, Chi CW, Tzen CY, Yang TL, Lee JJ, Liu TP, et al. Clinicopathologic significance of leptin and leptin receptor expressions in papillary thyroid carcinoma. Surgery. 2010;147(6):847-53. 8. Rezzonico J, Rezzonico M, Pusiol E, Pitoia F, Niepomniszcze H. Introducing the thyroid gland as another victim of the insulin resistance syndrome. Thyroid. 2008;18(4):461-4. 9. Patni N, Garg A. Congenital generalized lipodystrophies – new insights into metabolic dysfunction. Nat Rev Endocrinol. 2015;11(9):522-34. 10. Van Maldergem L, Magré J, Khallouf TE, Gedde-Dahl T Jr, Delépine M, Trygstad O, et al. Genotype-phenotype relationships in Berardinelli-Seip congenital lipodystrophy. J Med Genet. 2002;39(10):722-33. 11. Szymanski KM, Binns D, Bartz R, Grishin NV, Li WP, Agarwal AK, et al. The lipodystrophy protein seipin is found at endoplasmic reticulum lipid droplet junctions and is important for droplet morphology. Proc Natl Acad Sci U S A. 2007;104(52):20890-5. 12. Pardini VC, Victória IM, Rocha SM, Andrade DG, Rocha AM, Pieroni FB, et al. Leptin levels, beta-cell function, and insulin sensitivity in families with congenital and acquired generalized lipoatropic diabetes. J Clin Endocrinol Metab. 1998;83(2):503-8. 13. Storz P, Döppler H, Wernig A, Pfizenmaier K, Müller G. Cross‐talk mechanisms in the development of insulin resistance of skeletal muscle cells. Eur J Biochem. 1999;266(1):17-25. 14. Carvalho MHC, Colaço AL, Fortes ZB. Citocinas, disfunção endotelial e resistência à insulina. Arq Bras Endocrinol Metabol. 2006;50(2):304-12. 15. Garg A, Chandalia M, Vuitch F. Severe islet amyloidosis in congenital generalized lipodystrophy. Diabetes Care. 1996;19(1):2831. 16. Simha V, Garg A. Phenotypic heterogeneity in body fat distribution in patients with congenital generalized lipodystrophy caused by mutations in the AGPAT2 or seipin genes. J Clin Endocrinol Metab. 2003;88(11):5433-7. 17. Vassilopoulou-Sellin R, Cangir A, Samaan NA. Acanthosis nigricans and severe insulin resistance in an adolescent girl with thyroid cancer: clinical response to antineoplastic Am J Clin Oncol. 1992;15(3):273-6.

18. Pappa T, Alevizaki M. Obesity and thyroid cancer: a clinical update. Thyroid. 2014;24(2):190-9.

REFERENCES 1. Greenlee RT, Hill-Harmon MB, Murray T, Thun M. Cancer statistics, 2001. CA Cancer J Clin. 2001;51(1):15-36. 2. Ministry of Health, National Cancer Institute (INCA); Brazilian Society of Pediatric Oncology (SOBOPE). Childhood and Adolescent Cancer in Brazil: Data from Mortality and population basedregistries. Rio de Janeiro: INCA; 2009 [access by 23 mar 2018].

19. Agate L, Lorusso L, Elisei R. New and old knowledge on differentiated thyroid cancer epidemiology and risk factors. J Endocrinol Invest. 2012;35(6 Suppl):3-9. 20. Davies L, Welch HG. Increasing incidence of thyroid cancer in the United States, 1973-2002. JAMA. 2006;295(18):2164-7. 21. Vella V, Sciacca L, Pandini G, Mineo R, Squatrito S, Vigneri R, et al. The IGF system in thyroid cancer: new concepts. Mol Pathol. 2001;54(3):121-4. Arch Endocrinol Metab. 2019;63/1

Thyroid carcinoma in CGL

22. Belfiore A, Pandini G, Vella V, Squatrito S, Vigneri R. Insulin/IGF-I hybrid receptors play a major role in IGF-I signaling in thyroid cancer. Biochimie. 1999;81(4):403-7.

27. Schmid D, Behrens G, Jochem C, Keimling M, Leitzmann M. Physical activity, diabetes, and risk of thyroid cancer: a systematic review and meta-analysis. Eur J Epidemiol. 2013;28(12):945-58.

23. Eggo MC, Bachrach LK, Burrow GN. Interaction of TSH, insulin and insulin-like growth factors in regulating thyroid growth and function. Growth Factors. 1990;2(2-3):99-109.

28. Kitahara CM, Platz EA, Beane Freeman LE, Black A, Hsing AW, Linet MS, et al. Physical activity, diabetes, and thyroid cancer risk: a pooled analysis of five prospective studies. Cancer Causes Control. 2012;23(3):463-471.

24. Hedayati M, Yaghmaei P, Pooyamanesh Z, Zarif Yeganeh M, Hoghooghi Rad L. Leptin: a correlated Peptide to papillary thyroid carcinoma? J Thyroid Res. 2011;2011:832163. 25. Bae MJ, Kim SS, Kim WJ, Yi YS, Jeon YK, Kim BH, et al. High prevalence of papillary thyroid cancer in Korean women with insulin resistance. Head Neck. 2016;38(1):66-71.

30. Luo J, Phillips L, Liu S, Wactawski-Wende J, Margolis KL. Diabetes, diabetes treatment, and risk of thyroid cancer. J Clin Endocrinol Metab. 2016;101(3):1243-8.

26. Yeo Y, Ma SH, Hwang Y, Horn-Ross PL, Hsing A, Lee KE, et al. Diabetes mellitus and risk of thyroid cancer: a meta-analysis. PLoS One. 2014;9(6):e98135.

29. Aschebrook-Kilfoy B, Sabra MM, Brenner A, Moore SC, Ron E, Schatzkin A, et al. Diabetes and thyroid cancer risk in the National Institutes of Health-AARP Diet and Health Study. Thyroid. 2011;21(9):957-63.

Arch Endocrinol Metab. 2019;63/1

case report

Congenital hyperreninemic hypoaldosteronism due to aldosterone synthase deficiency type I in a Portuguese patient – Case report and review of literature Endocrinology, Diabetes and Metabolism Department, Coimbra Hospital and University Center, Coimbra, Portugal 2 Pediatric Unit, Coimbra Hospital and University Center, Coimbra, Portugal 3 Pediatric Endocrinology Unit, Coimbra Hospital and University Center, Coimbra, Portugal 1

Correspondence to: Adriana de Sousa Lages Praceta Prof. Mota Pinto 3000-075 – Coimbra, Portugal adrianamslages@gmail.com Received on Fev/20/2018 Accepted on Nov/14/2018 DOI: 10.20945/2359-3997000000107:

Adriana de Sousa Lages1, Beatriz Vale2, Patrícia Oliveira1, Rita Cardoso3, Isabel Dinis3, Francisco Carrilho1, Alice Mirante3

SUMMARY Hyperreninemic hypoaldosteronism due to aldosterone synthase (AS) deficiency is a rare condition typically presenting as salt-wasting syndrome in the neonatal period. A one-month-old Portuguese boy born to non-consanguineous parents was examined for feeding difficulties and poor weight gain. A laboratory workup revealed severe hyponatremia, hyperkaliaemia and high plasma renin with unappropriated normal plasma aldosterone levels, raising the suspicion of AS deficiency. Genetic analysis showed double homozygous of two different mutations in the CYP11B2 gene: p.Glu198Asp in exon 3 and p.Val386Ala in exon 7. The patient maintains regular follow-up visits in endocrinology clinics and has demonstrated a favourable clinical and laboratory response to mineralocorticoid therapy. To our knowledge, this is the first Portuguese case of AS deficiency reported with confirmed genetic analysis. Arch Endocrinol Metab. 2019;63(1):84-8

INTRODUCTION

ldosterone is a mineralocorticoid hormone secreted exclusively in the zona glomerulosa (ZG) of the adrenal cortex and acts in distal renal tubules by increasing sodium reabsorption and promoting urinary potassium excretion. The aldosterone synthesis is dependent on aldosterone synthase (AS), an enzyme encoded by the CYP11B2 gene, one of the cytochrome P450 enzymes (P450c11Aldo). AS, previously named corticosterone methyloxidase is expressed in the adrenal cortex and is responsible for catalysing the final three steps of the aldosterone biosynthesis: from 11-desoxycorticosterone (DOC) to corticosterone, then to 18-hidroxicorticosterone (18-OHB) and finally to aldosterone (1,2). Congenital hyperreninemic hypoaldosteronism due to defects in AS caused by inactivating mutations in the CYP11B2 gene has an unknown prevalence and is usually associated with an autosomal recessive pattern of inheritance. Two distinct forms of AS deficiency 84

have been described, type I and type II, based only on the biochemical profile: no AS catalytic activity and low 18-hydroxycorticosterone (18-OHB) levels in AS deficiency type I and residual enzymatic catalytic activity and elevated 18-OHB levels in AS deficiency type II (3). Typically, the disease manifests in the first weeks of life with nausea, vomiting, feeding problems and failure to thrive in the neonatal period. Isolated aldosterone deficiency is associated with neonatal salt-wasting syndrome resulting in hyponatremia, hyperkalaemia, metabolic acidosis and marked elevated renin with low or unappropriated normal aldosterone levels (4-15). Usually, clinical severity improves with age and patients are frequently asymptomatic during adulthood despite not having mineralocorticoid therapy (16). Most of the cases reported in the literature are from Iranian Jewish patients (5,16,17), but cases from Turkey (14,18) , Japan (7,8) and Israel (9,19) have also been described. To our knowledge, there has been no Arch Endocrinol Metab. 2019;63/1

Congenital hyperreninaemic hypoaldosteronism

CASE PRESENTATION We report a case of a one-month-old infant delivered by caesarean section at 35 weeks from a dichorionic diamniotic twin pregnancy with a birth weight of 2,350g and a length of 46 cm. The parents are Portuguese and non-consanguineous. Our patient presented 1-week complaints of an increased number of dejections and vomiting predominantly after feeding. At the first examination in a local paediatric hospital, he presented severe signs of dehydration (heart rate 160 bpm, blood pressure 92/58 mmHg, abnormally prolonged capillary refill time, deeply sunken eyes, mottled extremities), failure to retrieve weight compared to birth weight (2,340g) and marked hypotonia. He had a normal male phenotype with no genital anomalies, and no skin hyperpigmentation was described. A laboratory examination revealed an elevated plasma potassium level of 7.4 mmol/L [normal range (NR) 3.5-5.1], a low plasma sodium level of 126 mmol/L (NR 137145) and metabolic acidosis (pH 7.16 pCO2 46 mmHg HCO3- 16.4 mmol/L Lactates 5.3 mmol/L Anion Gap -13.6 mmol/L). Prompt therapy with 5% dextrose and 0.45% sodium chloride (NaCl) as well as infusion of sodium bicarbonate were initiated, and the patient was transferred to our central medical unit. During the hospital admission, because of a clinical presumptive diagnose of congenital adrenal hyperplasia, he was given therapy with hydrocortisone (2.5 mg 6/6h) and oral NaCl supplement (0.8 mEq/kg/day) with initial favourable clinical and laboratory response. However, a hormonal workup revealed normal plasma levels of adrenocorticotropic hormone (ACTH) (11.8 pg/mL – NR < 46), cortisol (10.9 µg/dL – NR 5.0-25.0), 17-OH-progesterone (17-OHP) (10.0 ng/mL), androstenedione (0.9 ng/mL) and dehydroepiandrosterone sulfate (DHEA-SO4) (32.5 µg/dL) with marked elevated renin (> 500 µUI/mL) levels and unappropriated normal aldosterone [12.4 ng/dL; measured by chemiluminescent immunoassay (CLIA) on Liaison®], ruling out the first clinical suspicion of congenital adrenal hyperplasia (CAD) and raising the suspicion of primary hypoaldosteronism as the probable cause of the severe neonatal salt-wasting syndrome (Table 1). Ultrasound investigation of the Arch Endocrinol Metab. 2019;63/1

kidneys revealed no abnormalities, and there were no signs of enteropathy, urinary tract infection or obstruction. The patient was discharged with an oral 20% NaCl supplement (0.4 mL, 8 times/day after feeding) and ion-exchange resin – sodic phase (1.8g, 3 times/day). At 54 days old, he had his first paediatric endocrinology appointment with new laboratory evaluation, confirming the results previously obtained and maintenance of an elevated plasma potassium level of 5.95 mmol/L (NR 3.5-5.1), so therapy with fludrocortisone (0.075 mg/ day, 0.018 mg/kg/day) and NaCl supplementation were associated. Genetic analysis was performed with direct DNA sequence analysis of the entire coding regions of the CYP11B2 gene and revealed that our patient is a doublehomozygous carrier of two mutations: in exon 3, codon 198 with replacement of glutamic acid for aspartic acid - c.594A > C (p.Glu198Asp), and in exon 7, codon 386 with replacement of valine for alanine - c.1157T > C (p.Val386Ala). Genotyping of these variations in both parents revealed that both were heterozygous carriers of the same two mutations, c.594A > C (p.Glu198Asp) and c.1157T > C (p.Val386Ala) – mutation in cis – which implies a 25% risk of AS deficiency in offspring. The patient maintains regular follow-up visits to endocrinology clinics, is currently 5 years old and good clinical effect on body growth and normalization of laboratory abnormalities after introduction of mineralocorticoid therapy. The dose of oral fludrocortisone has been stable at 0.075 mg/day, in two divided doses.

DISCUSSION Aldosterone is secreted on the ZG of the adrenal gland under control of three principal factors: angiotensin II, potassium and, to a lesser extent, ACTH. The first two secretagogues stimulate aldosterone secretion mainly by increasing the transcription of the CYP11B2 gene. Distinctly, ACTH acutely stimulates the early pathways of adrenal steroidogenesis, promoting a 10%-20% elevation of the aldosterone circulating levels (20). Mineralocorticoid deficiency can be divided in two categories: congenital and acquired syndromes. Mutations in the gene encoding the AS enzyme, exclusively found in the ZG, are associated with isolated mineralocorticoid deficiency. Nevertheless, functional mineralocorticoid deficiency may also be related to mutations in the mineralocorticoid receptor or in the 85

previous report of Portuguese cases of AS deficiency, especially with confirmed genetic analysis.

Congenital hyperreninaemic hypoaldosteronism

gene encoding the epithelial sodium channel (ENaC) (21). Regarding primary defects in aldosterone biosynthesis, mutations in AS limit the activation of DOC to aldosterone through three terminal subsequent steps catalysed by the mitochondrial CYP enzyme 11B2 (CYP11B2). Patients with AS deficiency can be classified as type I or type II according to the variable biochemical phenotype (based on 18-OHB and aldosterone levels). Both cases are rare and are inherited in an autosomal recessive pattern (3). Our patient presented with severe salt-wasting syndrome with important signs and symptoms of dehydration, feeding difficulties and failure to thrive in the neonatal period. Clinical presentation along with a typical biochemical profile with hyponatremia, hyperkalaemia, normal cortisol and sex steroids, high plasma renin levels and unappropriated normal aldosterone levels suggested the underlying diagnosis,

posteriorly confirmed by genetic analysis of CYP11B2 gene mutations on the index case. In the neonatal period, clinical presentation can be dramatic, with significant hemodynamic impact and life-threating episodes of seizure and coma. Typically, we assist an improving of clinical severity with age, and adults are frequently asymptomatic despite no mineralocorticoid therapy. This fact can be associated with a gradual declining dependency on aldosterone during lifetime for normal ionic imbalance due to possible extra-adrenal compensatory mechanisms and alternative ACTH-dependent pathways for mineralocorticoid biosynthesis (22). Occasionally, during adulthood, patients can present with orthostatic hypotension and hyperkalaemia in particular situations (as dehydration and heat stroke). A complete past medical history, with detailed childhood development and other medical conditions associated (such as nausea, vomiting, feeding problems and deficit

Table 1. Initial and sequential plasma levels (ionogram and hormonal profile) in Portuguese patient with congenital hyperreninemic hypoaldosteronism due to aldosterone synthase deficiency 13/10/2012 presentation Weight (g) Height (cm) Age

2,340 46 31 days

5/11/2012

13/12/2013

02/01/2014

7/10/2014

21/4/2016

13/3/2018

2,980

4,240 56 91 days

4,740 57.5 110 days

10,100 78.5 18 months

12,900 95.1 3 years+7 months

17.400 106.4 5 years+6 months

54 days

Normal range

Basal plasma levels Na+ (mmol/L)

126

140

141

139

140

142

140

137-145

K+ (mmol/L)

7.4

5.95

5.49

4.61

4.06

4.39

4.1

3.5-5.1

ACTH (pg/mL)

11.8

< 46.0

Basal cortisol (µg/dL)

10.9

5.0-25.0

Basal 17-OHP (ng/mL)

10.0

Renin (µUI/mL) (uU/mL)

> 500

208.2

26.5

0.5

1.9

0.5

1.0-16.0 7-76

Aldosterone (ng/dL) (pg/mL)

12.4

9.8

6.4

1.1

1.2

16.2

24.6

2.8-39.9 40-310

Free testosterone (pg/mL)

2.81

Androstenedione (ng/mL)

0.9

DHEA-SO4 (µg/dL)

32.5 Oral 20% NaCl; Exchange resin sodic phase

Oral 20% NaCl supplement; Fludrocortisone 0.05 + 0.025 mg

Fludrocortisone 0.05 + 0.025 mg

Therapy

ACTH: adrenocorticotropic hormone; 17-OHP: 17-OH-progesterone; DHEA-SO4: dehydroepiandrosterone sulfate.

Arch Endocrinol Metab. 2019;63/1

Congenital hyperreninaemic hypoaldosteronism

Arch Endocrinol Metab. 2019;63/1

the report of cases not linked to the CYPB11B2 gene mutations is important precisely to estimate the proportion of patients without positive genetic analysis and contribute to a broad comprehension of the molecular basis of the condition (6,9). Unfortunately, in our country, we did not have access to measurement of plasma or urinary 18-OHB levels and corticosterone levels that clearly distinguish AS deficiency type I from type II. However, the genetic analysis and similarity to the genetic profile previously described by Portrat-Doyen S. and cols. together with the patient’s clinical presentation strongly supported the diagnosis of AS deficiency type I for the first time in a Portuguese patient (25).

CONCLUSIONS AS deficiency is a rare case of hyperreninemic hypoaldosteronism inherited in an autosomal recessive pattern. This condition represents a disorder of terminal biosynthesis of aldosterone with a typical manifestation of salt-wasting disorder in early life. Proper diagnosis of AS deficiency is essential for correct lifelong management, and genetic confirmation of CYP11B2 mutation allows for evaluation of familial adult members, information regarding the implications on offspring and reducing potential life-threatening risks associated with the disease. This is the first report of a Portuguese patient with presumed AS deficiency type I in whom the molecular basis has been clarified, matching the clinical and laboratory diagnosis initially suspected. Mineralocorticoid therapy allowed remarkable weight recovery and total resolution of the initial symptoms and laboratory abnormalities. Expectedly, during adulthood, these patients present a favourable clinical course despite no fludrocortisone therapy and may only show an asymptomatic persistent abnormal steroid pattern throughout life. Acknowledgments: the authors thank Dr. Ana Gabaral and Dr. Joaquim de Sá for the genetic evaluation and counselling of the patient and his family, as well as the Galician Foundation of Genomic Medicine (Santiago de Compostela, Spain) for the molecular study. Funding statement: the authors declare that no funding was received for this publication. Disclosure: no potential conflict of interest relevant to this article was reported. 87

in weight gain), is essential to identify the correct diagnosis (1,16,23). It is also important to establish a correct differential diagnose with another neonatal salt-wasting syndromes such as congenital adrenal hyperplasia (CAH). In the latter, besides the clinical similarity at presentation, patients frequently have genital abnormalities (clitoral hypertrophy, labia partially or completely fused in girls) and a hormonal profile that is clearly distinct – instead of an isolated aldosterone deficiency with exclusively mineralocorticoid deficiency, on most patients (> 95%) with CAD due to 21-hydroxylase deficiency (CYP21A2), we found a combined aldosterone and cortisol synthesis deficiency associated with raised 17OHP, with elevated adrenal androgens as a hallmark of the diagnosis (24). Within this line, the therapy strategy is different and must include life-long glucocorticoid and mineralocorticoid replacement (16). Typically, patients with AS deficiency respond well to fludrocortisone therapy and may also benefit from salt supplementation specifically in the neonatal period. In our patient, NaCl supplementation was discontinued at 2 years of age, and maintenance of mineralocorticoid therapy with fludrocortisone in a stable dose of 0.075 mg allowed a catch-up growth with a favourable clinical and biochemical response. Generally, genetic analysis of AS deficiency cases identified mutations on the CYP11B2 gene. Our patient is a double-homozygous carrier for two sequence changes leading to amino acid substitutions: E198D in exon 3 and V386A in exon 7. Both parents are heterozygous carriers for the same two mutations, which justifies the fact that neither have any clinical manifestation of the disease – mutation in cis. The combination of these two mutations encodes enzymes with a reduced residual 11β-hydroxylase activity; however, with no broad catalytic activity, the clinical phenotype arises (25). Although most cases of AS deficiency reported a mutation on the CYPB11B2 gene, this condition has recently been associated with cases of patients with clinically and biochemically presumed AS deficiency with no identified mutations on the CYP11B2 gene, emphasising a bigger heterogeneity and possible other mechanisms associated with the disease – mutations in genes encoding other renin-aldosterone system components (such as angiotensinogen, angiotensinconverting enzymes and angiotensin II-receptor) or other regulatory genes of AS function. Encouraging

Congenital hyperreninaemic hypoaldosteronism

REFERENCES 1. Hui E, Yeung MC, Cheung PT, Kwan E, Low L, Tan KC, et al. The clinical significance of aldosterone synthase deficiency: report of a novel mutation in the CYP11B2 gene. BMC endocrine disorders. 2014;14(1):29. 2. Root AW. Disorders of aldosterone synthesis, secretion, and cellular function. Curr Opin Pediatr. 2014;26(4):480-6. 3. White PC. Aldosterone synthase deficiency and related disorders. Mol Cell Endocrinol. 2004;217(1):81-7. 4. Collinet E, Pelissier P, Richard O, Gay C, Pugeat M, Morel Y, et al. [Four cases of aldosterone synthase deficiency in childhood]. Arch Pediatr. 2012;19(11):1191-5. 5. Katznelson D, Sack J, Kraiem Z, Lunenfeld B. Congenital hypoaldosteronism. Thirteen year follow-up in identical twins. Horm Res. 1979;11(1):22-8. 6. Kayes-Wandover KM, Tannin GM, Shulman D, Peled D, Jones KL, Karaviti L, et al. Congenital hyperreninemic hypoaldosteronism unlinked to the aldosterone synthase (CYP11B2) gene. J Clin Endocrinol Metabol. 2001;86(11):5379-82. 7.

Kondo E, Nakamura A, Homma K, Hasegawa T, Yamaguchi T, Narugami M, et al. Two novel mutations of the CYP11B2 gene in a Japanese patient with aldosterone deficiency type 1. Endocr J. 2013;60(1):51-5.

8. Kuribayashi I, Kuge H, Santa RJ, Mutlaq AZ, Yamasaki N, Furuno T, et al. A missense mutation (GGC [435Gly]→ AGC [Ser]) in exon 8 of the CYP11B2 gene inherited in Japanese patients with congenital hypoaldosteronism. Hormone Res. 2003;60(5):255-60. 9. Leshinsky-Silver E, Landau Z, Unlubay S, Bistrizer T, Zung A, Tenenbaum-Rakover Y, et al. Congenital hyperreninemic hypoaldosteronism in Israel: sequence analysis of CYP11B2 gene. Hormone Res. 2006;66(2):73-8. 10. Peter M, Sippell WG. Congenital hypoaldosteronism: the VisserCost syndrome revisited. Pediatr Res. 1996;39(3):554-60. 11. Peter M, Nikischin W, Heinz-Erian P, Fussenegger W, Kapelari K, Sippell W. Homozygous deletion of arginine-173 in the CYP11B2 gene in a girl with congenital hypoaldosteronism. Corticosterone methyloxidase deficiency type II. Horm Res. 1998;50(4):222-5. 12. Peter M, Bunger K, Drop S, Sippell WG. Molecular genetic study in two patients with congenital hypoaldosteronism (types I and II) in relation to previously published hormonal studies. Eur J Endocrinol. 1998;139(1):96-100.

14. Üstyol A, Atabek ME, Taylor N, Yeung MC, Chan AO. Corticosterone methyl oxidase deficiency type 1 with normokalemia in an infant. J Clin Res Pediatr Endocrinol. 2016;8(3):356-9. 15. Wikiera B, GŁaÇb E, Barg E, Noczyn8ska A. Congenital hypoaldosteronism associated with nails hypothrophy – case report and review of the literature. Pediatr Endocrinol Diabetes Metab. 2008;14(4):253-6. 16. Rösler A. The natural history of salt-wasting disorders of adrenal and renal origin. J Clin Endocrinol Metab. 1984;59(4):689-700. 17. Rösler A, Rabinowitz D, Theodor R, Ramirez LC, Ulick S. The nature of the defect in a salt-wasting disorder in Jews of Iran. J Clin Endocrinol Metab. 1977;44(2):279-91. 18. Nomoto S, Massa G, Mitani F, Ishimura Y, Miyahara K, Toda K, et al. CMO I deficiency caused by a point mutation in exon 8 of the human CYP11B2 gene encoding steroid 18-hydroxylase (P450C18). Biochem Biophys Res Commun. 1997;234(2):382-5. 19. Pascoe L, Curnow KM, Slutsker L, Rösler A, White PC. Mutations in the human CYP11B2 (aldosterone synthase) gene causing corticosterone methyloxidase II deficiency. Proc Natl Acad Sci U S A. 1992;89(11):4996-5000. 20. Rainey WE. Adrenal zonation: clues from 11beta-hydroxylase and aldosterone synthase. Mol Cell Endocrinol. 1999;151(1-2):151-60. 21. Dtattani MT, Gevers EF. Endocrinology of fetal development. In: Shlomo Melmed KSP, Larsen PR, Kronenberg HM, editors. Williams textbook of endocrinology. 13th ed. Philadelphia: Elsevier; 2016. 22. Freel EM, Ingram M, Wallace AM, White A, Fraser R, Davies E, et al. Effect of variation in CYP11B1 and CYP11B2 on corticosteroid phenotype and hypothalamic-pituitary-adrenal axis activity in hypertensive and normotensive subjects. Clin Endocrinol (Oxford). 2008;68(5):700-6. 23. Ulick S, Gautier E, Vetter KK, Markello JR, Yaffe S, Lowe CU. An aldosterone biosynthetic defect in a salt-losing disorder. J Clin Endocrinol Metab. 1964;24:669-72. 24. Baranowski ES, Arlt W, Idkowiak J. Monogenic disorders of adrenal steroidogenesis. Hormone Res. 2018;89(5):292-310. 25. Portrat-Doyen S, Tourniaire J, Richard O, Mulatero P, AupetitFaisant B, Curnow KM, et al. Isolated aldosterone synthase deficiency caused by simultaneous E198D and V386A mutations in the CYP11B2 gene. J Clin Endocrinol Metab. 1998;83(11): 4156-61.

13. Rubio-Cabezas O, Regueras L, Muñoz-Calvo M, Bartolomé M, Pozo J, Argente J. Primary hypoaldosteronism and moder-

ate bilateral deafness in a child with a homozygous missense mutation (Thr318Met) in the CYP11B2 gene. An Pediatr (Barc). 2010;73(1):31-4.

Arch Endocrinol Metab. 2019;63/1

case report

A rare mutation in hypophosphatasia: a case report of adult form and review of the literature Department of Internal Medicine, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de investigación Sanitaria Gregorio Marañón, Madrid, Spain 2 Emory University School of Medicine, Departments of Human Genetics and Medicine, Atlanta, GA, USA 3 Emory University School of Medicine, Diabetes and Endocrinology Section, Atlanta, GA, USA 1

Francisco Galeano-Valle , Jaime Vengoechea , Rodolfo J. Galindo 2

SUMMARY Hypophosphatasia is a rare inborn error of metabolism characterized by low serum alkaline phosphatase activity due to loss-of-function mutations in the gene encoding the tissue-nonspecific isoenzyme of alkaline phosphatase (TNSALP). Extracellular accumulation of TNSALP substrates leads to dento-osseous and arthritic complications featuring tooth loss, rickets or osteomalacia, and calcific arthopathies. Mild hypophosphatasia usually has autosomal dominant inheritance, severe cases are either autosomal recessive or due to a dominant negative effect. Clinical manifestations of hypophosphatasia are extremely variable, ranging from life threatening to asymptomatic clinical presentations. The clinical presentation of the adult-onset hypophosphatasia is highly variable. Fractures, joint complications of chondrocalcinosis, calcifying polyarthritis and multiple pains may reveal minor forms of the disease in adults. It is important to recognize the disease to provide the best supportive treatment and to prevent the use of anti-resorption drugs in these patients. Bonetargeted enzyme-replacement therapy (asfotase alfa) was approved in 2015 to treat pediatriconset hypophosphatasia. We present a case of a 41-year-old male diagnosed with adult form of hypophosphatasia with a rare ALPL mutation that has been previously described only once and review the literature on the adult form of the disease and its genetic mechanism. Arch Endocrinol Metab. 2019;63(1):89-93

INTRODUCTION

ypophosphatasia (OMIM 146300, 241500, 241510) is a rare inborn error of metabolism characterized by low serum alkaline phosphatase (ALP) activity (hypophosphatasaemia) due to lossoffunction mutations within the gene that encodes the tissue-nonspecific isoenzyme of ALP (ALPL). In hypophosphatasia, extracellular accumulation of ALP substrates, including inorganic pyrophosphate, an inhibitor of mineralization, explains the dentoosseous and arthritic complications featuring tooth loss, rickets or osteomalacia, and calcific arthropathies (1). In mild hypophosphatasia, there is functional loss of one of the copies of the gene, leading to autosomal dominant inheritance. In severe hypophosphatasia, the mutations affect both alleles of the gene. This could be through autosomal recessive transmission or because of an autosomal dominant mutation with a dominant negative effect, in which the gene product from one allele interferes with homo-dimerization (2). The prevalence of severe and moderate hypophosphatasia Arch Endocrinol Metab. 2019;63/1

Correspondence to: Rodolfo J. Galindo Emory University School of Medicine, Division of Endocrinology, Diabetes and Metabolism 69 Jesse Hill Jr. Dr., Glenn Bld, Suite 202 30303 – Atlanta, GA, USA rodolfo.galindo@emory.edu Received on Aug/26/2018 Accepted on Dec/11/2018 DOI: 10.20945/2359-3997000000108

forms were estimated at 1/300,000 and 1/6,370 patients in Europe, respectively (3). Clinical manifestations of hypophosphatasia are extremely variable and seven major clinical forms are identified. Fractures, joint complications of chondrocalcinosis, calcifying polyarthritis and multiple pains may reveal minor forms of the disease in adults. It is important to recognize the disease to provide the best treatment, to prevent fractures, which are frequently complicated and associated with pseudarthrosis. Moreover, it’s extremely important to prevent the inappropriate use of anti-resorption drugs, frequently prescribed for the fractures related to bone fragility, and attributed to primary osteoporosis in these patients (1,4-6). Bone-targeted enzyme-replacement therapy with asfotase alfa was approved in 2015 to treat pediatriconset hypophosphatasia. Currently, there is no wellestablished treatment available for the correction of the bone fragility in adult hypophosphatasia. We present a case of a 41-year-old male diagnosed with adult form of hypophosphatasia with a rare ALPL gene mutation that has been previously described only once and review 89

Adult-onset hypophosphatasia

the literature on the adult form of the disease and its genetic mechanism.

CASE REPORT A 41-year-old Caucasian male presented to the endocrinology clinic with a long standing history of asthenia, constipation and depressed mood. Additionally, the patient related he had right lower ribs pain for several months. He denied any history of fractures, teeth loss, cavities, muscle pain, intellectual disability or vitamin supplementation. He had a family history of premenopausal osteoporosis in several family members, with poor response to bisphosphonates, and fractures. In addition, the patient had one sister with long-term decreased plasmatic ALP during adulthood, fractures and poor dentition (Figure 1). Physical examination revealed slight lack of enamel in teeth. Plasmatic calcium, phosphate, magnesium, thyroid and parathyroid hormone, kidney function, albumin and 25-hydroxyvitamin D (25(OH)D) were normal. Historical test results revealed decreased ALP for at least 2 years, ranging 18-20 U/L (normal range 45-115 U/L). Bone-specific ALP was 4.8 μg/L (normal range in males 6.5-20.1 μg/L). Vitamin B6 was 328.7 nmol/L (normal range 20-125 nmol/L). Vitamin A, B1, B2, B3, B5 and B12 were normal. Radiograph of the ribs did not reveal abnormalities. Kidneys ultrasound showed normal kidneys. After genetic counseling,

78 Suicide

HTN

83 Diverticulitis

Depression

ALPL gene (NM_000478.5) Sanger sequencing was performed at a CLIA-certified molecular diagnostic lab (Prevention Genetics, Marshfield, Wisconsin, USA). This showed that the patient was heterozygous for a pathogenic variant, c.1474del, which is predicted to result in a frameshift and premature protein termination (p.Ala492Profs*29). The classification as pathogenic was established by the clinical laboratory according to the 2015 ACMG/AMP guidelines. The diagnosis of autosomal dominant hypophosphatasia (adult form) was made. The patient was not enable to use enzyme replacement therapy (ERT) and the current treatment is basically symptomatic (analgesics, antidepressants), and focused on maintaining 25(OH)D within normal range and regular supervision by a multidisciplinary team including a dentist.

DISCUSSION The first case of hypophosphatasia was reported in 1948 by J. C. Rathbun (7) and the first identified ALPL mutation was reported in 1988 (8). In humans, four genes account for ALP. Three genes encode the tissuespecific intestinal, placental and germ-cell ALP, whereas the fourth gene, ALPL, encodes TNSALP, which is abundant in the skeleton, liver, kidney and developing teeth. TNSALP is actually a family of isoforms that differ by post-translational modifications. Homodimerization of TNSALP monomers is required for catalytic

90 Multiple medical problerns

62 T2DM

62 Osteoporosis Osteoporosis

20 34 Depression Asymptomatic

39 Long standing decreased ALP Fractures, poor dentition

6 4 rnonths Asymptomatic Asymptomatic

5 Poor dentition

Osteoporosis

91 Osteoporosis Knee injury at 40

Rotator cuff injury

50 Knee replacernent

41 Costal pain asthenia, constipation, depressed mood

Figure 1. Pedigree of the patient’s family. HTN: hypertension; ALP: alkaline phosphatase; T2DM: type 2 diabetes mellitus. 90

Arch Endocrinol Metab. 2019;63/1

activity (9). ALPs circulate as soluble homodimers that are cleared by the liver (10). There is deficiency of all TNSALP isoforms in hypophosphatasia (9). The prevalence of severe and moderate hypophosphatasia forms were estimated at 1/300,000 and 1/6,370 respectively in the European population (3). Three TNSALP phosphocompound substrates accumulate extracellulary in hypophosphatasia: both phosphoethanolamine (PEA) and inorganic pyrophosphate (PPi) in urine and blood and pyridoxal 5â&#x20AC;&#x2122;-phosphate (PLP) in plasma which is the active form of vitamin B6 and a cofactor for several enzymatic reactions including neurotransmitters (1). PPi is a potent inhibitor of mineralization and its superabundance leads to the impairment of hydroxyapatite crystal formation and growth, thereby producing rickets and osteomalacia, respectively in children and adults, and a wide range of other symptoms including calcific arthropathies in some affected adults (4,6). Hypophosphatasia shows an extraordinary range of severity that spans from death in utero with an unmineralized skeleton to dental complications or calcific periarthritis without bone disease in adulthood. Although its clinical spectrum is a continuum, hypophosphatasia has been classified into seven major clinical forms. Its outcome is conditioned principally by any skeletal complications, generally being worse with early life presentation (2,11,12). Adult-onset hypophosphatasia typically presents during middle age (13). The main symptom is pain caused by fractures due to osteomalacia and PPi arthropathy, including pseudogout. The most frequent fractures involve the metatarsals. These fractures are recurrent, usually show a delayed consolidation and may lead to pseudarthrosis. The other characteristic fractures (or pseudofractures) affect laterally and proximally in the subtrochanteric femoral region (5,12-14). Dental abnormalities include enamel disorders, loose teeth and premature tooth loss. Calcific periarthritis, ossification of ligaments and nephrocalcinosis may be present. This form can become debilitating due to recurrent fracturing, skeletal and joint pain, and muscle pain. Recurring headaches and psychiatric symptoms (insomnia, anxiety, depression) are frequent (5,6,12-15). Due to the extraordinary range of variability of the clinical features of the adult form, this is probably the most underdiagnosed form. Delayed diagnose is very common. A study showed that the onset of symptoms Arch Endocrinol Metab. 2019;63/1

in adulthood occurred at a median age of 44 years and the median age at diagnosis was 49 years. At the time of presentation, one third of patients appeared asymptomatic (12). Hypophosphatasia has been diagnosed traditionally when persistent hypophosphatasemia matches a medical history, physical examination, routine laboratory studies, and radiographic findings consistent with the diagnosis. The degree of hypophosphatasemia and TNSALP substrate accumulation generally reflects the severity of hypophosphatasia (1,6). TNSALP substrate excess in hypophosphatasia is marked with greatest sensitivity and specificity by elevated serum PLP (1,7). ALPL gene analysis is expected to reveal a defect in all patients with hypophosphatasia (2). Although persistent hypophosphatasaemia is the hallmark for the diagnosis of all forms of hypophosphatasia, it is not usually recognized in the clinical setting in hospitalized adult patients and it is rarely investigated further (16). Hypophosphatasaemia can also result from use of certain drugs and conditions (17). Assaying serum PLP is particularly helpful when hypophosphatasaemia has an explanation other than hypophosphatasia, because an elevated level might be expected exclusively in hypophosphatasia as the activities of all TNSALP isoforms, not just from bone, are low, and the other causes of hypophosphatasaemia seem to particularly suppress bone TNSALP activity (1,6). Documentation of an elevated PEA level in blood or urine supports a diagnosis of hypophosphatasia. However, PEA excretion can be unremarkable in mild hypophosphatasia (17). Currently, assays for PPi are carried out only in research laboratories (1). Radiological findings of adult hypophosphatasia include osteopenia, poorlyhealing metatarsal stress fractures, pseudofractures, pyrophosphate arthropathy and calcific periarthritis (14,18,19). Z-scores assessed by DXA are only slightly reduced in most adults (1,14). Weak muscles appear normal on routine laboratory testing (20). Although hypophosphatasia can typically be diagnosed without ALPL mutation analysis, this information is crucial for understanding inheritance. Hypophosphatasia derives from any mutation in the ALPL gene located on chromosome 1p36.1 that causes decreased TNSALP activity and increased levels of its substrates. All patients with hypophosphatasia carry one or two mutations involving ALPL (6). Three hundred and fifty one mutations have been identified and are reported in the ALPL gene mutation database 91

Adult-onset hypophosphatasia

(http://www.sesep.uvsq.fr/03_hypo_mutations.php, accessed on March 24, 2018) in North American, Japanese, and European patients, indicating a very strong allelic heterogeneity in the disease. This variety of mutations results in highly variable clinical expression and in a great number of compound heterozygous genotypes (21). The majority of the known mutations are missense point mutations with the remainder being composed of microlesions, splicing mutations, nonsense mutations, and a nucleotide substitution affecting the major transcription initiation site (17,22-24). The high clinical variability of the disease is correlated to the pattern of inheritance and depends on the large number of missense mutations and their variable effect on TNSALP activity. Autosomal dominant and autosomal recessive transmission of these defects generally explain mild versus severe hypophosphatasia, respectively. Missense mutations that interfere with the formation of the TNASLP dimer can decrease enzymatic function considerably and result in a dominant negative effect, accounting for cases of autosomal dominant perinatal hypophosphatasia. Significantly different phenotypic presentations of the disease may even occur within a family (2,15). Despite our patient having mild and unspecific symptoms, persistently low ALP levels and the strong family history of bone and joint problems lead to the suspicion of hypophosphatasia, that was confirmed by genetic testing. Genetic counseling was performed to inform possible affected relatives. This patient was heterozygous in exon 12 of the ALPL gene for a variant defined as c.1474del, which is predicted to result in a frameshift and premature protein termination (p.Ala492Profs*29) and therefore the diagnosis of autosomal dominant hypophosphatasia (adult form) was made. This variant, along with another ALPL variant, has been reported by Brun-Heath and cols. (the report uses a non-current reference transcript so the variant is described as c.1471del) in a patient with perinatal lethal hypophosphatasia (24). In addition, this variant has been only observed in 1 of 236,966 alleles in a public database, indicating it is rare (http://gnomad. broadinstitute.org/variant/1-21904036-CG-C). All the reported deletions result in a frameshift with early termination and mRNA decay or significantly shorter proteins. In that reported case, the mutation only affected the last 30 amino acids of the protein, a region where no missense mutation had ever been described, however the fetus was affected with perinatal lethal 92

hypophosphatasia. In vitro experiments performed using a protein with a deletion of the last 30 amino acids showed that in the absence of this region, the protein was not excreted but retained a normal enzymatic activity. This indicates that, because the deletion occurs in the last exon of the gene, it escaped mRNA decay, and this region was necessary for membrane anchoring but not for enzymatic activity (25). The lethal phenotype observed for that patient suggested that membrane anchoring is essential for TNSALP function and confirmed the importance of the carboxy-terminal part of the protein. Finally, as previously reported (26), the mutations resulting in deletions and insertions resulting in frameshift are responsible for the more severe forms of hypophosphatasia, due to the aberrant product of the gene (24). We performed molecular analysis of the ALPL gene only, it is possible that a modifier variant elsewhere in the genome could be a contributor to the patient’s phenotype. Management of adult patients with hypophosphatasia must include assessment of bone and joint complications, in addition to chronic pain and mood disorders (5). Antiresorptive therapies are not recommended, as they may worsen underlying osteomalacia (27). Currently, there is no established treatment available for the correction of the bone fragility in adult hypophosphatasia. Bonetargeted ERT (asfotase alfa) was approved in 2015 to treat pediatric-onset hypophosphatasia. However, the adult form management is typically supportive (6,28). Recombinant PTH was tried on various clinical cases and it had positive results. In a clinical trial, asfotase alfa improved functional outcomes in some adolescents and adults with hypophosphatasia. However, the data is still limited to make strong recommendations (5). In conclusion, Hypophosphatasia is a rare inborn error of metabolism with a wide range of clinical features. Adult form accounts for the most common and the least severe form and it is often difficult to be recognized with a delayed diagnosis and inappropriate treatments. ALPL mutation testing is being increasingly used in clinical practice, confirming the need to manage mutation findings by thorough clinical examination to distinguish hypophosphatasia patients with subclinical manifestations from those with biochemical abnormalities but who are otherwise asymptomatic. The mutation c1474del has been previously described only once in medical literature. Funding: this work was not supported by any grant. Arch Endocrinol Metab. 2019;63/1

Adult-onset hypophosphatasia

Disclosure: no potential conflict of interest relevant to this article was reported.

REFERENCES 1. Whyte MP. Hypophosphatasia – aetiology, nosology, pathogenesis, diagnosis and treatment. Nat Rev Endocrinol. 2016;12(4):23346. 2. Whyte MP, Zhang F, Wenkert D, McAlister WH, Mack KE, Benigno MC, et al. Hypophosphatasia: validation and expansion of the clinical nosology for children from 25 years experience with 173 pediatric patients. Bone. 2015;75:229-39. 3. Mornet E, Yvard A, Taillandier A, Fauvert D, Simon-Bouy B. A molecular-based estimation of the prevalence of hypophosphatasia in the European population. Ann. Hum. Genet. 2011;75(3):439-45. 4. Conti F, Ciullini L, Pugliese G. Hypophosphatasia: clinical manifestation and burden of disease in adult patients. Clin Cases Miner Bone Metab. 2017;14(2):230-4. 5. Briot K, Roux C. Adult hypophosphatasia. Arch Pediatr. 2017;24:5S71-5. 6. Whyte MP. Hypophosphatasia: an overview for 2017. Bone. 2017;102:15-25. 7. Rathbun JC. Hypophosphatasia: a new developmental anomaly. Am J Dis Child. 1948:75;822-31. 8. Weiss MJ, Cole DE, Ray K, Whyte MP, Lafferty MA, Mulivor RA, et al. A missense mutation in the human liver/bone/kidney alkaline phosphatase gene causing a lethal form of hypophosphatasia. Proc Natl Acad Sci U S A. 1988;85(20):7666-9. 9. Millan JL. Mammalian alkaline phosphatases: from biology to applications in medicine and biotechnology. Weinheim, Germany: Wiley-VCH; 2006. 10. Young GP, Rose IS, Cropper S, Seetharam S, Alpers DH. Hepatic clearance of rat plasma intestinal alkaline phosphatase. Am J Physiol. 1984;247(4 Pt 1):G419-26. 11. Whyte MP. Hypophosphatasia. Chapter 22. In: Thakker RV, Whyte MP, Eisman J, Igarashi T, editors. Genetics of bone biology and skeletal disease. 1st ed. London, UK: Academic Press; 2013. p. 337-60. 12. Berkseth KE, Tebben PJ, Drake MT, Hefferan TE, Jewison DE, Wermers RA. Clinical spectrum of hypophosphatasia diagnosed in adults. Bone. 2013;54(1):21-7.

15. Bianchi ML. Hypophosphatasia: an overview of the disease and its treatment. Osteoporos Int. 2015;26(12):2743-57. 16. Maman E, Borderie D, Roux C, Briot K. Absence of recognition of low alkaline phosphatase level in a tertiary care hospital. Osteoporos Int. 2016;27(3):1251-4. 17. McKiernan FE, Dong J, Berg RL, Scotty E, Mundt P, Larson L, et al. Mutational and biochemical findings in adults with persistent hypophosphatasemia. Osteoporos Int. 2017;28(8):2343-8. 18. Whyte MP. Atypical femoral fractures, bisphosphonates, and adult hypophosphatasia. J Bone Miner Res. 2009;24(6):1132-4. 19. McKiernan FE, Berg RL, Fuehrer J. Clinical and radiographic findings in adults with persistent hypophosphatasemia. J Bone Miner Res. 2014;29(7):1651-60. 20. Seshia, SS, Derbyshire, G, Haworth, JC, Hoogstraten, J. Myopathy with hypophosphatasia. Arch Dis Child. 1990;65(1):130-1. 21. Taillandier A, Domingues C, Dufour A, Debiais F, Guggenbuhl P, Roux C, et al. Genetic analysis of adults heterozygous for ALPL mutations. J Bone Miner Metab. 2018;36(6):723-33. 22. Mornet E, Hofmann C, Bloch-Zupan A, Girschick H, Le Merrer M. Clinical utility gene card for: hypophosphatasia – update 2013. Eur J Hum Genet. 2014;22(4). 23. Riancho-Zarriabietia L, García-Unzueta M, Tenorio JA, GómezGerique JA, Pérez VLR, Heath KE, et al. Clinical, biochemical and genetic spectrum of low alkaline phosphatase levels in adults. Eur J Int Med. 2016;29:40-5. 24. Brun-Heat I, Taillandier A, Serre JL, Mornet E. Characterization of 11 novel mutations in the tissue non-specific alkaline phosphatase gene responsible for hypophosphatasia and genotype-phenotype correlations. Mol Genet Metab. 2005;84(3):273-7. 25. Di Mauro S, Manes T, Hessle L, Kozlenkov A, Pizauro JM, Hoylaerts MF, et al. Kinetic characterization of hypophosphatasia mutations with physiological substrates. J Bone Miner Res. 2002;17(8):1383-91. 26. Mornet E. Hypophosphatasia: the mutations in the tissue-nonspecific alkaline phosphatase gene. Hum Mutat. 2000;15(4):309-15. 27. Lawrence JE, Saeed D, Bartlett J, Carrothers AD. Adult-onset hypophosphatasia diagnosed following bilateral atypical femoral fractures in a 55-year-old woman. Clin Cases Miner Bone Metab. 2017;14(3):347-53. 28. Whyte MP. Hypophosphatasia: enzyme replacement therapy brings new opportunities and new challenges. J Bone Miner Res. 2017;32(4):667-75.

13. Weber TJ, Sawyer EK, Moseley S, Odrljin T, Kishnani PS. Burden of disease in adult patients with hypophosphatasia: Results from two patient-reported surveys. Metabolism. 2016;65(10):1522-30.

14. Schmidt T, Mussawy H, Rolvien T, Hawellek T, Hubert J, Rüther W, et al. Clinical, radiographic and biochemical characteristics of adult hypophosphatasia. Osteoporos Int. 2017;28(9):2653-62.

Arch Endocrinol Metab. 2019;63/1

Instructions for authors GENERAL INFORMATION

should be 2,000 words or less, with no more than four figures and tables, and no more than 30 references.

We emphasize the importance of following these instructions carefully. Failure to do so will delay the processing of your manuscript. Manuscripts should be submitted solely to the AE&M and should not have been published, or be under consideration for publication in any substantial form, in another periodical-either professional or lay. Manuscripts should be submitted in English. Proofreading by a scientific editing service is strongly recommended; the following companies are suggested: Voxmed Medical Communications, American Journal Experts and PaperCheck. Manuscripts that successfully complete the peer-review process and are recommended for publication will only be accepted and published upon receipt of a certificate proving professional academic English proofreading. In extraordinary circumstances, the certificate can be waived by editorial decision. All submissions are initially evaluated in depth by the scientific editors. Papers that do not conform with the general criteria for publication will be returned to the authors without detailed review, typically within three to five days. Otherwise, manuscripts will be sent to reviewers (most commonly two).

We emphasize that only case reports that offer important basic translational or clinical contributions, preferentially together with a review of the literature, will be considered for publication.

Letters to the Editor Letters to the Editor may be submitted in response to manuscript that has been published in the Journal. Letters should be short commentaries related to specific points of agreement or disagreement with the published manuscript. Letters are not intended for the presentation of original data unrelated to a published article. Letters should be no longer than 500 words, with no more than five complete references, and should not include any figures or tables.

MANUSCRIPT PREPARATION MANUSCRIPT CATEGORIES Reports of original research may be submitted to AE&M as Original Articles or Brief Reports. Other special categories of manuscripts are described below. All manuscripts must adhere to the word count limitations, as specified below, for text only; word count does not include the abstract, references, or figures/tables and their legends. Word count must be shown on the title page, along with the number of figures and tables. The format is similar for all manuscript categories, and it is described in detail in the “Manuscript Preparation” section.

Original Articles The Original Article is a scientific report of the results of original research that has not been published or submitted for publication elsewhere (either in print or electronically). It represents a substantial body of laboratory or clinical work. In general, Original Articles should not exceed 3,600 words in the main text, include more than six figures and tables, or more than 35 references.

Review Articles The AE&M publishes Review Articles that show a balanced perspective on timely issues within the field of clinical endocrinology. All reviews are submitted upon invitation and are subject to peer review. Articles in this category are requested by the Editors to authors with proven expertise in the field. Authors considering the submission of uninvited reviews should contact the editors in advance to determine whether the topic that they propose is of current potential interest to the Journal. Review articles should be no longer than 4,000 words in the main text, include no more than four figures and tables, and no more than 60 references. The author should mention the source and/or request authorization for use of previously published figures or tables.

Consensus Statements Consensus Statements related to the endocrine and metabolic health standards and healthcare practices may be submitted by professional societies, task forces, and other consortia. All such submissions will be subjected to peer review, must be modifiable in response to criticism, and will be published only if they meet the usual editorial standards of the Journal. Consensus Statements should typically be no longer than 3,600 words in the main text, include no more than six figures and tables, and no more than 60 references.

Brief Report The Brief Report consists of new data of sufficient importance to warrant immediate publication. It is a succinct description of focused study with important, but very straightforward, negative or confirmatory results. Brevity and clarity are always likely to enhance the chance of a manuscript being accepted for publication. A maximum of 1,500 words in the main text plus up to 20 references and normally no more than two illustrations (tables or figures or one of each) are acceptable for Brief Reports.

Case Report A Case Report is a brief communication presenting collected or single case reports of clinical or scientific significance. These reports should be concise and focused on the issue to be discussed. They should address observations of patients or families that add substantially to the knowledge of the etiology, pathogenesis, and delineation of the natural history or management of the condition described. Case Reports

GENERAL FORMAT The Journal requires that all manuscripts be submitted in a single-column format that follows these guidelines: • The manuscript must be submitted in MS-Word format. • All text should be double-spaced with 2 cm margins on both sides using 11-point type Times Roman or Arial font. • All lines should be numbered throughout the entire manuscript and the entire document should be paginated. • All tables and figures must be placed after the text and must be labeled. Submitted papers must be complete, including the title page, abstract, figures, and tables. Papers submitted without all of these components will be placed on hold until the manuscript is complete.

ALL SUBMISSIONS MUST INCLUDE: • A cover letter requesting the evaluation of the manuscript for publication in AE&M, and any information relevant to the manuscript. Elsewhere on the submission form, authors may suggest up to three specific reviewers and/or request the exclusion of up to three others.

The manuscript must be presented in the following order: 1. Title page. 2. Structured abstract (or summary for case reports). 3. Main text. 4. Tables and figures. They must be cited in the main text in numerical order. 5. Acknowledgments. 6. Funding statement, competing interests and any grants or fellowships supporting the writing of the paper. 7. List of references.

Title Page The title page must contain the following information: 1. Title of the article (a concise statement of the major contents of the article). 2. Full names, departments, institutions, city, and country of all co-authors. 3. Full name, postal address, e-mail, telephone and fax numbers of the corresponding author. 4. Abbreviated title of no more than 40 characters for page headings. 5. Up to five keywords or phrases suitable for use in an index (the use of MeSH terms is recommended). 6. Word count – excluding title page, abstract, references, figures/tables and their legends. 7. Article type

Structured Abstracts All Original Articles, Brief Reports, Reviews, Case Reports should be submitted with structured abstracts of no more than 250 words. The abstract must be self-contained and clear without reference to the text, and should be written for general journal readership. The abstract format should include four sections that reflect the section headings in the main text. All information reported in the abstract must appear in the manuscript. Please use complete sentences for all sections of the abstract.

Introduction

Photographs

The article should begin with a brief introductory statement that places the study in historical perspective, and explains its objective and significance.

The AE&M strongly prefers to publish unmasked patient photos. We encourage all prospective authors to work with families prior to submission and address the issue of permission for review and possible publication of patient images. If your submission contains ANY identifiable patient images or other protected health information, you MUST provide documented permission from the patient (or the patient’s parent, guardian, or legal representative) before the specific material circulates among editors, reviewers and staff for the purpose of possible publication in AE&M. If it is necessary to identify an individual, use a numerical designation (e.g. Patient 1) rather than using any other identifying notations, such as initials.

Materials and Methods These should be described and referenced in sufficient detail for other investigators to be able to repeat the study. The source of hormones, unusual chemicals and reagents, and special pieces of apparatus should be stated. For modified methods, only the modifications need be described.

Results and Discussion The Results section should briefly present the experimental data in text, tables, and/ or figures. For details on preparation of tables and figures, see below. The Discussion should focus on the interpretation and significance of the findings, with concise objective comments that describe their relation to other studies in that area. The Discussion should not reiterate the Results.

Units of Measure Results should be expressed in metric units. Temperature should be expressed in degrees Celsius and time of day using the 24-hour clock (e.g., 0800 h, 1500 h).

Standard Abbreviations All abbreviations must be immediately defined after it is first used in the text.

Authorship The AE&M ascribes to the authorship and contributorship guidelines defined by the International Committee of Medical Journal Editors (www.ICMJE.org). Unrestricted joint authorship is allowed. A maximum of two corresponding authors is allowed. The uniform requirements for manuscripts submitted to medical journals state that authorship credit should be based only on substantial contribution to: 1. The conception and design, or analysis and interpretation of data. 2. The drafting of the article or its critical review for important intellectual content. 3. The final approval of the version to be published. All these conditions must be met. The corresponding author is responsible for ensuring that all appropriate contributors are listed as authors, and that all authors have agreed with the content of the manuscript and its submission to the AE&M.

Experimental Subjects To be considered for publication, all clinical investigations described in submitted manuscripts must have been conducted in accordance with the guidelines of The Declaration of Helsinki, and must have been formally approved by the appropriate institutional review committees or their equivalent. The study populations should be described in detail. Subjects must be identified only by number or letter, not by initials or names. Photographs of patients’ faces should be included only if scientifically relevant. The authors must obtain written consent from the patient for the use of such photographs. For further details, see the Ethical Guidelines. Investigators must disclose potential conflict of interest to study participants and should indicate in the manuscript that they have done so.

Conflict of interest

Acknowledgments The Acknowledgments section should include the names of those people who contributed to a study but did not meet the requirements for authorship. The corresponding author is responsible for informing each person listed in the acknowledgment section that they have been included and providing them with a description of their contribution so they know the activity for which they are considered responsible. Each person listed in the acknowledgments must give permission – in writing, if possible – for the use of his or her name. It is the responsibility of the corresponding author to provide this information.

References References to the literature should be cited in numerical order (in parentheses) in the text and listed in the same numerical order at the end of the manuscript on a separate page or pages. The author is responsible for the accuracy of references. The number of references cited is limited for each category of submission, as indicated above.

Tables Tables should be submitted in the same format as the article (Word), and not in another format. Please note: we cannot accept tables as Excel files within the manuscript. Tables should be self-explanatory and the data they contain must not be duplicated in the text or figures. Tables must be constructed as simply as possible and be intelligible without reference to the text. Each table must have a concise heading. A description of experimental conditions may appear together with footnotes at the foot of the table. Tables must not simply duplicate the text or figures.

Figures and Legends All figures must display the figure number. Sizing the figure: the author is responsible for providing digital art that has been properly sized, cropped, and has adequate space between images. All color figures will be reproduced in full color in the online edition of the journal at no cost to the authors. Authors are requested to pay the cost of reproducing color figures in print (the publisher will provide price quotes upon acceptance of the manuscript).

Experimental Animals A statement confirming that all animal experimentation described in the manuscript was conducted in accordance with accepted standards of humane animal care, as outlined in the Ethical Guidelines, should be included in the manuscript.

Molecular Genetic Description • Use standard terminology for variants, providing rs numbers for all variants reported. These can be easily derived for novel variants uncovered by the study. Where rs numbers are provided, the details of the assay (primer sequences, PCR conditions, etc.) should be described very concisely. • Pedigrees should be drawn according to published standards (See Bennett et al. J Genet Counsel (2008) 17:424-433 - DOI 10.1007/s10897-008-9169-9).

Nomenclatures • For genes, use genetic notation and symbols approved by the HUGO Gene Nomenclature Committee (HGNC) – (http://www.genenames.org/). • For mutation nomenclature, please use the nomenclature guidelines suggested by the Human Genome Variation Society (http://www.hgvs.org/mutnomen/) • Provide information and a discussion of departures from Hardy-Weinberg equilibrium (HWE). The calculation of HWE may help uncover genotyping errors and impact on downstream analytical methods that assume HWE. • Provide raw genotype frequencies in addition to allele frequencies. It is also desirable to provide haplotype frequencies. • Whenever possible, drugs should be given their approved generic name. Where a proprietary (brand) name is used, it should begin with a capital letter. • Acronyms should be used sparingly and fully explained when first used.

Papers must be written in clear, concise English. Avoid jargon and neologisms. The journal is not prepared to undertake major correction of language, which is the responsibility of the author. Where English is not the first language of the authors, the paper must be checked by a native English speaker. For non-native English speakers and international authors who would like assistance with their writing before submission, we suggest Voxmed Medical Communications, American Journal Experts or PaperCheck. ISSN 2359-3997 © A&EM – Rua Botucatu, 572 – conjunto 83 – 04023-062 – São Paulo, SP, Brazil

A conflict of interest statement for all authors must be included in the main document, following the text, in the Acknowledgments section. If authors have no relevant conflict of interest to disclose, this should be indicated in the Acknowledgments section.