israel journal of psychiatry and related sciences

israel journal of

psychiatry

In schizophrenia, how do you get from here

Vol. 49 - Number 1 2012

ISSN: 0333-7308

002

Editorial: Pediatric Bipolar Disorder

S. Arbelle and R.H. Belmaker

Volume 49, Number 1, 2012 Israel Journal of Psychiatry and Related Sciences

003

to here?

Xeplion®, a new once-monthly injectable schizophrenia therapy,1 significantly reduces relapse.2 With early onset of efficacy3,4 and good tolerability,1–6 Xeplion can help your patients shape a future in a way that they wish.

Prevalence, Clinical Presentation and Differential Diagnosis of Pediatric Bipolar Disorder Benjamin I. Goldstein and Boris Birmaher

015

Evidence-Based Assessment Strategies for Pediatric Bipolar Disorder

Eric A. Youngstrom, Melissa McKeown Jenkins, Amanda Jensen-Dossand and Jennifer Kogos Youngstrom

028

Biological Evidence for a Neurodevelopmental Model of Pediatric Bipolar Disorder Donna J. Roybal, Manpreet K. Singh, Victoria E. Cosgrove, Meghan Howe, Ryan Kelley, Naama Barnea-Goraly and Kiki D. Chang

Pediatric Bipolar Disorder Part I: Diagnosis

044

Diagnostic Implications of Informant Disagreement About Rage Outbursts: Bipolar Disorder or Another Condition?

Gabrielle A. Carlson and Margaret Dyson

052

Beyond dogma: from diagnostic controversies to data about pediatric bipolar disorder and children with chronic irritability and mood dysregulation Daniel P. Dickstein and Ellen Leibenluft

062

Preventing relapse, enabling futures

For comprehensive information please refer to full Prescribing information as approved by the Israeli Health Authority.

References: 1. Xeplion prescribing information. 2. Hough D et al. Schiz Res 2010; 116: 107-117.

3. Pandina GJ et al. J Clin Psychopharmacol 2010; 30: 235-244. 4. Kramer M et al. Int J Neuropsychopharmacol 2010; 13: 635-647. 5. Gopal S et al. J Psychopharmacol Online First, published on July 8, 2010 as doi:10.1177/0269881110372817. 6. Hoy SM et al. CNS Drug Rev 2010; 24(3): 227-244.

A Magnetic Resonance Spectroscopy Study of the Anterior Cingulate Cortex In Youth with Emotional Dysregulation

Janet Wozniak, Atilla Gönenç, Joseph Biederman, Constance Moore, Gagan Joshi, Anna Georgiopoulos, Paul Hammerness, Hannah McKillop, Scott E. Lukas and Aude Henin

israel journal of

psychiatry and related sciences EDitor

David Greenberg DEPUTY EDITORS

David Roe Rael Strous Gil Zalsman

003 > Prevalence, Clinical

Eli L. Edelstein Founding Editor

Heinz Z. Winnik Editorial Board

Alean Al-Krenawi Alan Apter Elliot Gershon Talma Hendler Ehud Klein Ilana Kremer ltzhak Levav Yuval Melamed Shlomo Mendlovic Ronnen Segman Eliezer Witztum Zvi Zemishlany International Advisory Board

Gabrielle A. Carlson and Margaret Dyson

Bipolar Disorder

PAst Editor

Yoram Barak

Presentation and Differential Diagnosis of Pediatric Bipolar Disorder

Benjamin I. Goldstein and Boris Birmaher

015 > Evidence-Based Assessment Strategies for Pediatric Bipolar Disorder

Eric A. Youngstrom, Melissa McKeown Jenkins, Amanda Jensen-Dossand and Jennifer Kogos Youngstrom

028 > Biological Evidence for a Neurodevelopmental Model of Pediatric Bipolar Disorder

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062 > A Magnetic Resonance Spectroscopy Study of the Anterior Cingulate Cortex In Youth with Emotional Dysregulation

Janet Wozniak, Atilla Gönenç, Joseph Biederman, Constance Moore, Gagan Joshi, Anna Georgiopoulos, Paul Hammerness, Hannah McKillop, Scott E. Lukas, and Aude Henin

070 > News and Notes 072 > Abstracts

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052 > Beyond dogma: from diagnostic controversies to data about pediatric bipolar disorder and children with chronic irritability and mood dysregulation

Hebrew Section

Donna J. Roybal, Manpreet K. Singh, Victoria E. Cosgrove, Meghan Howe, Ryan Kelley, Naama Barnea-Goraly and Kiki D. Chang

Yoram Bilu Aaron Bodenheimer Carl Eisdorfer Julian Leff Margarete Mitscherlich-Nielsen Peter Neubauer Phyllis Palgi Leo Rangell Melvin Sabshin Robert Wallerstein Myrna Weissman Assistant Editor

Informant Disagreement About Rage Outbursts: Bipolar Disorder or Another Condition?

002 > Editorial: Pediatric S. Arbelle and R.H. Belmaker

Vol. 49 - Number 1 2012

044 > Diagnostic Implications of

Pediatric Bipolar Disorder Part I: Diagnosis

Book reviews editor

The Official Publication of the Israel Psychiatric Association

William Utermohlen (1933-2007), a London artist, was diagnosed with Alzheimer’s disease in 1995 after neuropsychological and imaging tests, although his symptoms began four years earlier. His last works include a series of self-portraits which highlight the changing self- and pictorial image of an Alzheimer’s patient. The portraits suggest a growing abstraction that could be linked to visuospatial deficits. Four of the portraits are: A. 1996 Self-Portrait; B. 1997 Self-Portrait; C. 1998 Self-Portrait; D. 2000 Head. The artist expresses sadness, anxiety, resignation and feelings of feebleness.

In the last portrait the head is drawn and erased at the same time, as if he has assimilated his drawing with his destiny – to subsist while disappearing. (Copyright Galerie Beckel-Odile-Boicos, Paris) Esther-Lee Marcus, Herzog Hospital, Jerusalem

Isr J Psychiatry Relat Sci - Vol. 49 - No 1 (2012)

Editorial: Pediatric Bipolar Disorder Psychiatric diagnosis is currently in the headlines, both in psychiatric scientific literature and in the popular press. Preliminary reports of the changes due with DSM-5 have generated immense controversy. The diagnosis of childhood bipolar disorder, however, has been in controversy for several years, well before the current debate about DSM-5. It is important to note that changes, even major changes, in psychiatric diagnosis are nothing new. One of us (RHB) was enrolled in a psychoanalytically oriented residency program at Duke in 1972 and had a new patient with discrete recurrent periods of extreme anxiety who was not responding to psychotherapy and it was decided to search the literature. There was an article by Donald Klein entitled “Delineation of two drug-responsive anxiety syndromes” (1). Based on that article the patient was given imipramine and observed the kind of results at a low dose with a dramatic therapeutic benefit that usually only happens when a new therapy is discovered. Later on it takes higher dose, larger samples and there are more modest effects. This syndrome was later defined as panic disorder but it is hard for young psychiatrists nowadays to realize that in 1971 the nomenclature did not include the concept of panic disorder. Not that it was given a different name: The basic concept simply did not exist.

It is also hard to imagine nowadays that in Klein and Davis’s Diagnosis and Drug Treatment of Psychiatric Disorder 1969, the first textbook of psychopharmacology, depression was considered a rare disorder which responded about two-thirds of the time to imipramine or other early tricyclic antidepressants (including the placebo effect that was already recognized). As depression became more and more commonly diagnosed with increasingly wide diagnostic criteria, depression has become a very common disease with a very low placebodrug difference. So in this case the same name has evolved into an almost completely changed psychobiology.

Classically, pediatric bipolar disorder was considered rare, if it was recognized to exist at all. In the book one of us (RHB) edited in 1980, the chapter on childhood mania discussed this as a rare series of case reports (2). It was common at that time to say that children had affective systems that were not capable of true depression or mania. Many articles discussed brain neurochemistry of prepubertal rodents in order to explain what was then thought to be a clinical fact. The concepts discussed in 2

these previous historical sentences are now considered to be in great doubt, if not absolutely wrong. Depression in some forms is apparently quite prevalent in prepubertal children, although the extent of usefulness of serotonergic reuptake inhibitors in children earlier than adolescence is still questionable.

The current special issue of the Israel Journal of Psychiatry devoted to pediatric bipolar disorder represents our belief that open intellectual debate that exposes our own professional uncertainties to the scientific and general public is the best way to maintain the leadership and value of psychiatry. There is nothing that generates as much respect and cooperation as a public witnessing physicians’ dedication to the truth. We know of terribly difficult behavioral disorders in patients who are children and we also know neighbors, relatives and friends who have suffered because of severe emotional or behavioral disorders in their children. Many of these disorders involve aggressiveness, impaired impulse control, sleeplessness and sometimes sadness or hypersexuality. Some of these syndromes may be related in family history studies to bipolar disorders and some may respond to some medications that also help adult bipolar patients. Other syndromes in childhood may not respond to such pharmacologic treatment and may respond to family therapy or other psychosocial therapies. Many of these symptoms overlap with symptoms in other childhood disorders. The present issue represents our belief that many of these questions are open and we struggle to treat individual patients with an open mind to several outstanding scientific problems.

Simultaneously we are part of the world wide effort of the scientific and psychiatric community to study these questions such that we will be able to provide treatment that will improve year by year for a better future care for our patients.

References 1. Klein DF. Delineation of two drug-responsive anxiety syndromes.

Psychopharmacologia 1964;5:397-408.

2. Carlson GA. Manic-depressive illness and cognitive immaturity. In: Belmaker RH, Van Praag HM, editors. Mania, an evolving concept.

New York: Spectrum Publications, 1980.

R.H. Belmaker, MD Assistant Director, Beersheva Mental Health Center Hoffer-Vickar Professor of Psychiatry, Ben-Gurion University of the Negev belmaker@bgu.ac.il

Shoshana Arbelle, MD Director, Child and Adolescent Psychiatry Clinic, Soroka Medical Center

Guest Editors

Benjamin I. Goldstein and Boris Birmaher Isr J Psychiatry Relat Sci - Vol. 49 - No 1 (2012)

Prevalence, Clinical Presentation and Differential Diagnosis of Pediatric Bipolar Disorder Benjamin I. Goldstein, MD, PhD,1,2 and Boris Birmaher, MD2 1

Department of Psychiatry, Sunnybrook Health Sciences Centre, University of Toronto Faculty of Medicine, Toronto, Canada Western Psychiatric Institute and Clinic, University of Pittsburgh School of Medicine, Pittsburg, Pennsylvania, U.S.A.

2

ABSTRACT Background: Over the past 20 years, the evidence regarding pediatric bipolar disorder (BP) has increased substantially. As a result, recent concerns have focused primarily on prevalence and differential diagnosis.

Method: Selective review of the literature.

Results: BP as defined by rigorously applying diagnostic criteria has been observed among children and especially adolescents in numerous countries. In contrast to increasing diagnoses in clinical settings, prevalence in epidemiologic studies has not recently changed. BPspectrum conditions among youth are highly impairing and confer high risk for conversion to BP-I and BP-II. Compared to adults, youth with BP have more mixed symptoms, more changes in mood polarity, are more often symptomatic and seem to have worse prognosis.

The course, clinical characteristics, and comorbidities of BP among children and adolescents are in many ways otherwise similar to those of adults with BP. Nonetheless, many youth with BP receive no treatment and most do not receive BP-specific treatment.

Conclusion: Despite increased evidence supporting the validity of pediatric BP, discrepancies between clinical and epidemiologic findings suggest that diagnostic misapplication may be common. Simultaneously, low rates of treatment of youth with BP suggest that withholding of BP diagnoses may also be common.

Clinicians should apply diagnostic criteria rigorously in order to optimize diagnostic accuracy and ensure appropriate treatment.

BACKGROUND Pediatric bipolar disorder: unicorn or ubiquitous?

The concept of children and adolescents suffering from bipolar disorder (BP) is not a new one. However, whereas case descriptions of pediatric mania have been available for nearly a century (1, 2) it is only within approximately the last two decades that rigorous research on this topic has been conducted.1 Questions have been raised as to reasons for increased attention to pediatric BP, and simplistic conspiracy theories abound: an American invention, a fabrication born of Big Pharma influence, self-serving researchers seeking to create a niche (3).

Nonetheless, arguments against the existence of pediatric BP have waned in recent years, and one hopes that the quality of the research cited in this and other articles in this edition of the Journal had a salutary effect.

More recently, prevalence and diagnostic accuracy have become the primary controversies. Prior to the last twenty years, childhood mania was considered exceedingly rare, and there are still settings in which this is the case (4). This stood in contrast to findings that up to twothirds of adults with BP report child- or adolescent-onset of impairing mood symptoms (5-7), and approximately 10% report childhood (<13 years of age) onset of mania or significant manic symptoms (5, 7). An influential 1995 paper by Wozniak and colleagues indicated that 16% of children presenting for treatment at a tertiary academic child psychiatric clinic evidenced symptoms consistent with mania, and raised the question of whether pediatric BP was being overlooked (8). By many accounts, concerns regarding missed diagnoses of BP and underestimates of prevalence have been replaced with con1 For the purpose of this review, unless otherwise indicated, the term BP encompasses all subtypes (I, II, cyclothymia, not-otherwise-specified [NOS]), and the term pediatric refers to children and/or adolescents â&#x2030;¤19 years of age.

Address for Correspondence: Dr. B. Goldstein, Department of Psychiatry, Sunnybrook Health Sciences Centre; 2075 Bayview Ave., FG53, Toronto, Ontario, M4N-3M5, Canada â&#x20AC;&#x2020; benjamin.goldstein@sunnybrook.ca

3

Prevalence, Clinical Presentation and Differential Diagnosis of Pediatric Bipolar Disorder

cerns regarding misdiagnoses of BP and over-estimates of prevalence. These concerns are in part owing related to the possible over-use of mood-stabilizing medications.

Although prescriptions for mood-stabilizing medications for children have indeed increased dramatically (9), unfortunately the majority of adolescents with BP do not access treatment for their illness (10). Similarly, although concerns have been raised regarding increased use of the BP diagnosis among youth (11), the number of youth who receive diagnoses of BP in clinical settings falls far short of what would be expected based on the population prevalence of BP (12).

Pediatric BP diagnosis presents a challenging dialectic. Withholding of diagnoses and treatment of BP from patients who truly have BP presents substantial morbid risks, including suicidality and marked functional impairment (13, 14). However, unnecessary diagnoses and unnecessary exposure to mood-stabilizing medications risk unduly invoking concerns about a life-long illness, pre-empting psychosocial treatments, delayed and/or suboptimal pharmacological treatment of other psychiatric conditions such as major depressive disorder (MDD) or attention-deficit hyperactivity disorder (ADHD), and significant physical risks (15). As such, one focus of this review is on summarizing recent literature that can inform considerations regarding accurate diagnoses of individual children and adolescents with and without BP. Another focus of this review is on highlighting various demographic, clinical, and familial characteristics that are salient to the diagnosis, monitoring, and treatment of youth with BP. PREVALENCE The prevalence of BP among youth varies depending on how and where the sample is ascertained and the methods used to diagnose BP. Moreno and colleagues reported a 40-fold increase in visits for BP among youth in managed care between 1994-1995 and 2002-2003 (11). However, diagnoses were determined via billing codes, which are of uncertain reliability and which may be influenced by external factors such as â&#x20AC;&#x153;up-codingâ&#x20AC;? in order to ensure that children receive sufficient mental health services. That is, clinicians may diagnose pediatric BP because treatment for this diagnosis is often subject to fewer constraints within managed care organizations, whereas diagnoses such as conduct disorder often have comparatively less allocation of resources or have low expenditure limits relative to BP. Moreover, 4

the estimated change was likely inflated by counting multiple visits by the same patients, and frequent use of health services is common in BD (16). In addition, the baseline proportion of psychiatric visits for pediatric BD in 1994-5 was 0.42%, meaning that fewer than 1 in 200 children and adolescents receiving psychiatric care carried a diagnosis of BP. Over a similar time period, rates of hospital discharges of children with a primary diagnosis of BD increased from 1.3 per 10,000 in 1996 to 7.3 per 10,000 in 2004 (17). Therefore, these large relative increases may be accentuated by what some would describe as an exceedingly low initial base rate, particularly in light of the fact that child- or adolescentonset is common among adults with BP (5-7).

The recent National Comorbidity Survey ReplicationAdolescent Supplement (NCS-A) found that approximately 1% of adolescents have strictly defined BP-I and if subsyndromal symptoms of BP are included, the rates increase to approximately 6% (18). The prevalence of BP-I or -II in the NCS-A doubled between ages 13-14 and 17-18 years of age (12). Previous epidemiologic data from the Oregon Adolescent Depression Project (OADP) nearly 20 years prior indicated a combined prevalence of 5.7% for full- and sub-threshold BP (0.1% BP-I) among adolescents (19). The 2002 Canadian Community Health Survey included a proxy for BP comprising episodes with sufficient symptoms and severity to be characterized as mania, but with the exception that duration of symptoms did not have to reach a full week (20). Similar to the NCS-A finding of increasing prevalence with age, that study found a nearly two-fold increased prevalence between adolescence (15-18 years, 2.1%) and young adulthood (19-24 years, 3.8%). A recent meta-analysis of epidemiological studies of pediatric BP included 16,222 youths (7-21 years) from 12 studies (6 from U.S., 6 international) conducted between 1985 and 2007 (21). The mean prevalence of BP spectrum disorders was 1.8% (95% confidence interval [CI] 1.1%3.0%), and the mean prevalence of BP-I was 1.2% (95% CI 0.7%-1.9%). Rates of BP spectrum disorders in studies of adolescents only (12 years and older) averaged 2.7% (95% CI 1.6-4.6%), higher than the overall prevalence in studies combining children and adolescents (1.8%, 95% CI 1.1-3.0%). Methodological differences may explain in part the variability in prevalence. For example, the OADP found only 0.1% prevalence of BP-I, contrasting other epidemiologic samples with rates of up to 2-3% of BP-I among adolescents (22, 23). The OADP enrolled students from the high-school setting (vs. households)

Benjamin I. Goldstein and Boris Birmaher

and did not interview parents, either of which may have contributed to the low BP-I prevalence, although other factors may also contribute. Perhaps surprisingly, the mean rate of BP in the 6 studies from the U.S. (1.7%) did not differ from the mean rate in the 6 studies from outside the U.S. (1.9%), this despite the fact that two U.S. studies included BP-spectrum conditions other than BP-I and BP-II and therefore had the highest prevalence (18, 19). Importantly, and in contrast to temporal trends in clinical diagnoses, there was no evidence of increasing prevalence of BP spectrum disorders over time. In summary, there has been stable prevalence over time of youth BP spectrum (particularly adolescent BP) as ascertained by rigorous semi-structured interviews in unselected epidemiologic sample, where there has been increased prevalence of youth BP in clinical settings. Explanations for this phenomenon include higher rates of treatmentseeking for pediatric BP over time, or insufficiently stringent application of diagnostic criteria in clinical settings. At least in Canada and the U.S. the former explanation does not appear likely, as rates of treatmentseeking are disturbingly low (discussed below) (10, 18, 20). Therefore, strategies for addressing false positive diagnoses of BP among youth likely need to be informed by a better understanding of what is driving the excess of clinical diagnoses. Similarly, strategies for addressing untreated BP in the community need to be informed by a better understanding of barriers to accurate diagnoses and appropriate treatment. Thus far, rigorous epidemiologic studies have focused on adolescents, such that little is known regarding the epidemiology pre-adolescent BP. Pharmaco-epidemiologic studies that have examined pre-adolescent BP have not employed standardized assessments. Although these studies can address billing diagnoses, they cannot address questions about the epidemiologic prevalence of rigorously defined BP. Given that the prevalence of BP was substantially higher among older adolescents vs. younger adolescents in the NCS-A, it is possible that the prevalence of BP among pre-adolescent children is even lower. However, definitive conclusions are deferred pending large epidemiologic studies of children.

CLINICAL PRESENTATION Manic/hypomanic Symptoms

The Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) symptom criteria for BP are the same for children, ado-

lescents and adults. However, as discussed below there are developmental differences in the presentation of mania/hypomania in youth. Symptoms of mania are the hallmark of BP. Either elation/euphoria or irritability are required. Other symptoms include grandiosity, distractibility, decreased need for sleep, increased amount and/or rate of speech, increased rate of thoughts or rapid flow of expressed ideas, increased involvement in risky pleasurable activities, increased motoric activity or restlessness, and increased productivity or goaldirected activity. Because silly, rambunctious, and/or impulsive behavior often characterizes childhood and adolescence, it is important particularly for hypomania to be able to distinguish normal childhood behavior from psychiatric symptoms. In order to be considered a pathological symptom, elation must be inappropriate to context and associated with a change in functioning, and the same applies for grandiosity. Beyond these general considerations, it is central to accurate diagnoses to determine whether a given symptom is pathological for an individual child in a particular situation or setting. Take for example a child who has clear-cut ADHD, who usually has significant insomnia, and who is consistently silly and somewhat defiant. If this child on a given day is hyperactive, silly, distractible, and defiant with his teacher, that would not comprise a distinct mood-related change from baseline behavior. But take for example a child who does not have ADHD, who is consistently agreeable and well-behaved, and who is generally subdued with regard to expression of affect.

If this child suddenly presents as hyperactive, silly, distractible, and defiant for several days, then it becomes important to determine whether these are symptoms of hypomania or are better explained by other factors (e.g., stress, substance use). In terms of sleep specifically, it is critical to parse insomnia from reduced need for sleep. The former is associated with difficulty rousing whereas the latter may in fact be characterized by early waking and intact alertness despite substantially fewer hours of sleep. Case-based descriptions of how children with mania differ from healthy children and from adults with mania are available (24). Because irritability is a symptom common to multiple psychiatric disorders (e.g., MDD, generalized anxiety disorder, oppositional defiant disorder), one approach that has been taken in order to optimize diagnostic specificity is to require elation or grandiosity (25). However, DSM-IV-TR does not necessitate this, and indeed studies from different research groups have questioned the 5

Prevalence, Clinical Presentation and Differential Diagnosis of Pediatric Bipolar Disorder

necessity of elation/euphoria (26, 27). Findings from the COBY study, for example, suggest that in about 80% of the cases both elation and irritability are present during the most severe symptomatic episodes among BP youth and, with few exceptions, the course, comorbidity and family psychiatric history of youth with solely irritable mania/hypomania does not substantially differ from that of youth with solely elation or those with both elation and irritability (27).

Manic/hypomanic Episodes

The diagnosis of bipolar I disorder (BP-I) is given when a patient has had at least one clear manic or mixed manic (mania concurrent with depression) episode in his/her lifetime. An episode is a period of time during which symptoms comprise a noticeable change from that person’s baseline, whether that baseline is one of health or one that is affected by symptoms of a comorbid condition such as anxiety or attention-deficit hyperactivity disorder (ADHD). If the requirement for episodes were to be waived, this raises concerns about misdiagnosis, particularly among youth with ADHD which has multiple over-lapping symptoms. To count as a manic episode, symptoms must cause marked functional impairment and must last at least one week or necessitate hospitalization.

A diagnosis of bipolar II disorder (BP-II) is given when a patient has had at least one hypomanic episode (similar symptoms, but absent major functional impairment, psychosis, or the need for hospitalization) and one major depressive episode in his/her lifetime. Other BP-spectrum diagnoses are less clearly defined, and include cyclothymia (numerous brief depressive and hypomanic intervals without prolonged recovery for ≥1 year) and BP not otherwise specified (BP-NOS; described below). There is substantial consensus that episodes are one of the hallmarks of BP and that phenotypes characterized by chronic irritability and ADHD, absent episodicity, often are not consistent with a diagnosis of BP (28, 29).

Bipolar Disorder Not Otherwise Specified and Subthreshold Bipolar Disorder

Although BP is classically thought of in terms of the acute manic episodes of BP-I, there is convergent evidence from adolescent and adult epidemiologic studies that subthreshold BP or BP-NOS (henceforth BP-NOS) is a more common presentation (18, 30). In addition, there is also convergent evidence from clinical and epidemiologic studies that BP-NOS is clinically impairing, and clinical studies suggest further that BP-NOS is 6

familial and predictive of conversion to BP-I and BP-II (18, 19, 30-33). However, in comparison with BP-I or – II, DSM-IV criteria for BP-NOS are less clearly defined.

American Academy of Child and Adolescent Psychiatry (AACAP) practice parameters advise as a clinical guideline that BP-NOS should be used to describe youth with brief hypo/manic episodes lasting hours to less than four days, or describe youths with chronic manic-like symptoms that comprise their baseline level of functioning (34). Because of an important need for a clearer definition of what comprises BP-NOS, the COBY study offered an operationalized definition requiring that symptoms must be evident for a minimum of four hours in a day on a minimum of four separate lifetime days in order to be classified as BP-NOS (35). These children have very similar symptoms, comorbidities, and family histories to children with BP-I (31, 35). Moreover, 45% of these children will go on to meet strict criteria for BP-I or BP-II within five years, and nearly two-thirds of BP-NOS youth with family history of BP “convert” to BP-I or BP-II (36). Even in epidemiologic samples, sub-threshold episodic BP is associated with substantial functional impairment and comorbidity, and rates of treatment use that approach that of BD (19, 33). However, the Longitudinal Assessment of Manic Symptoms (LAMS) study suggests that despite the fact that symptoms of mania are evident in approximately 40% of children (6-12 years of age) attending outpatient psychiatric clinics, most youth presenting with these symptoms (75%) do not meet the criteria for BP-I, -II, or -NOS, highlighting the importance of ensuring minimal symptom number and duration criteria are met before assigning a BP-spectrum diagnosis (37).

AACAP vs. NICE

The DSM-IV-TR criteria for manic and hypomanic episodes do not differ for children and adolescents, although clinical judgment is required to allow for developmentally-sensitive approaches to inquiring about and classifying symptoms. The AACAP practice parameters advise that these unaltered criteria should be employed with children and adolescents, and allow for use of BP-I, BP-II, or BP-NOS among children and adolescents (34). In contrast, the U.K.’s National Institute for Health and Clinical Excellence (NICE) clinical guideline for BP suggests diagnostic modifications for children and adolescents (38). The guideline acknowledges that BP-I can be diagnosed in pre-pubertal children, but requires that euphoria is present and does not allow irritability as a core diagnostic criterion. For adolescents, the NICE guide-

Benjamin I. Goldstein and Boris Birmaher

line indicates that “irritability can be helpful in making a diagnosis if it is episodic, severe, results in impaired function and is out of keeping or not in character” (p. 56), but should nonetheless not be used as a core diagnostic criterion. According to NICE, use of the BP-II diagnosis is not advised among children or adolescents, with the exception of “older or developmentally advanced” adolescents, in which case adult criteria should be used.

Further elaboration of international differences in rates of BP and in diagnostic criteria can be found in the article

by Carlson and Dyson in this journal.

Course and Outcome

Information regarding the clinical course of adolescent BP was until recently limited to relatively small studies.

However, larger studies have yielded crucial longitudinal data (31, 39, 40). The course of adolescent BP following first hospitalization for mania is characterized by both recovery and recurrence (40). Geller and colleagues recently published eight-year follow-up data regarding a cohort of pre-pubertal children and early adolescents with BP-I, and found that subjects spent 60% of the time symptomatic (either in full-threshold mood episodes or with clinically significant sub-threshold symptoms), and continue experiencing mood episodes in youngadulthood (39). The COBY study, the largest of its kind (N=413), suggests that in many ways the longitudinal course of youth BP-I mirrors that of adults: most experience episodic recovery and recurrences; depression is the prevailing polarity; and subsyndromal symptoms, particularly of the mixed and depressive type, predominate (31). However, compared to adults with BP-I, youth with BP-I spend more time with syndromal and clinically significant subsyndromal symptoms (59% vs. 47%), spend more time in mixed episodes, and have far more changes in polarity and in symptomatic status (41). Across subtypes of BP in COBY (including types I, II, and NOS), this illness is characterized by recovery (eight contiguous weeks of remission) and recurrences (31). During four years of prospective follow-up, participants spent 16.6% (2 months/year) of the time in full-threshold mood episodes and 41.8% (5 months/year) of the time suffering from sub-threshold but clinically significant mood symptoms. Changes in mood polarity were common, and 51% had ≥5 annual polarity changes (note: polarity changes are not always part of full-threshold mood episodes, so that this is not synonymous with DSM-IV rapid-cycling).

Finally, COBY provides validation for the operationalized definition of BP-NOS described above. Nearly 40%

of children and adolescents with BP-NOS “convert” to BP-I or BP-II during prospective follow-up, thus demonstrating that in addition to significant episodicity and symptomatic impairment, the COBY-operationalized diagnosis of BP-NOS frequently forebodes more classical BP-I and BP-II (31, 35). Whereas studies to date demonstrate diagnostic continuity of pediatric BP (31, 39, 40), there is evidence from adults of diagnostic conversion over time, most commonly to primary psychotic disorders (42). Longer follow-up of extant pediatric BP cohorts will be needed to determine the rate of conversion to primary psychotic disorders.

Bipolar Disorder in School-age Children vs. Adolescents

Relatively few studies have directly compared the symptoms and clinical presentations of children with BP to those of adolescents. One study compared children with BP to adolescents with childhood-onset BP and adolescents with adolescent-onset BP, finding that euphoria was more common among adolescents with childhood-onset BP, whereas irritability was least common among adolescents with adolescent-onset BP (43).

Childhood-onset BP was associated with greater severity of increased energy, and this was observed among children with BP as well as among adolescents with childhood-onset BP. Findings from some of the larger cohorts of BP youth suggest no significant differences in symptoms between children and adolescents with BP (25, 44). Several studies have found that the prevalence of ADHD and/or ODD may be higher among children versus adolescents with BP (45, 46). Recent findings based on the National Hospital Discharge Survey suggest that children with BP are most likely to have been in a mixed episode (32%), followed by adolescents (25%) and adults (13%) (17).

This topic was also examined comprehensively in the COBY study. Familial loading of psychopathology may be greater in childhood-onset versus adolescentonset BP (47). Adolescents were more likely to have had a lifetime major depressive episode, and were more likely to have had depression as the initial polarity of illness, whereas children were more likely to have first presented with manic/hypomanic symptoms. Manic and depressive symptom severity was greater among adolescents vs. children, and this was true also for the severity of most individual symptoms (48). Comorbid conduct disorder and comorbid SUD were more common among adolescents than among children, comor7

Prevalence, Clinical Presentation and Differential Diagnosis of Pediatric Bipolar Disorder

bid ADHD was more common among subjects with childhood-onset ADHD, and panic disorder was most common among adolescents with adolescent-onset BP. Bipolar Disorder in Preschool-age Children

In comparison to the topic of BP among school-age youth, BP among preschoolers is perhaps more controversial and has been the subject of comparatively little research to date. One of the few “minimal standard” recommendations in the AACAP practice parameter for BP is that caution is advised before diagnosing preschoolers with BP, due to uncertain validity (34). That said, several groups have reported on small samples of preschoolers who present with symptoms of hypo/ mania (49-54). In one cases series, preschool mania was consistently characterized by strong family history of mood disorders and by antecedent ADHD (54). Perhaps surprisingly, descriptions of preschoolers with BP have often included classical features. For example, specific symptoms of mania such as elation and grandiosity have been prominent in several reports, and the course of illness in a series of 26 patients was significant for high recovery and relapse rates (i.e., episodicity) (49, 51, 55). One study included 26 preschoolers with BP as well as comparison groups of preschoolers with depression, disruptive behavior disorders, and no psychiatric disorders (50). Even after controlling for comorbid ADHD, preschoolers with BP demonstrated significantly greater functional impairment than did preschoolers with disruptive behavior disorders or healthy preschoolers.

Clearly, the diagnosis of BP in preschoolers should be used judiciously, and prevalence estimates in this age range are not presently available. Extant challenges in the accurate diagnosis of BP in school-age children, particularly those related to developmentally sensitive symptom ascertainment, are further accentuated in the preschool age group. However, compelling descriptions of directly observed manic symptoms have been published. Kraepelin referred to the case of a 5-year-old boy with mania (2) p.167). Poznanski and colleagues described the case of a 4-year-old child with maternal history of BP who presented with recurrent brief hypomanias against a background of consistent ADHD symptoms (56). In that case report, the inclusion of parent and teacher reports, the nuanced behavioral descriptions including developmental context, and the care taken to demonstrate differences from the usual ADHD symptoms together make a compelling argument for preschool BP. In our view, BP is likely less common 8

among preschoolers than among school-age children and adolescents, however recognition of how symptoms of BP manifest in a preschooler can provide a framework for when to include BP on the differential diagnosis in such young children.

Suicidality

Similar to adults, BP among youth is a potent risk factor for completed suicide (57-59). Whether in community or clinical samples, approximately 3 in 4 youth with BP endorse lifetime suicidal ideation (19, 35). The lifetime prevalence of suicide attempts among youth with BP varies across studies, but appears to be at least 20% and sometimes nearly 50% (13, 60, 61). Epidemiologic findings from the U.S. indicate that the lifetime prevalence of suicide attempts among adolescents with BP spectrum disorders (44%) was double that of adolescents with MDD (22%) which was in turn far greater than that of healthy adolescents (1%) (19). Moreover, adolescents with BP in this sample make more attempts, make more lethal attempts, and are younger at the time of their first attempt.

The question arises as to which youth among those with BP are at greatest risk for attempting suicide. The prevalence of suicide attempts appears to be greater among older youth (13, 62). With the exception of older age, findings from the COBY study do not suggest any demographic predictors of suicide attempts (13).

Interestingly, rates of suicide attempts did not significantly differ across BP subtypes. Clinical predictors of lifetime suicide attempt include mixed episodes, psychosis, psychiatric hospitalization, comorbid panic disorder, comorbid SUD, poor family functioning, family history of suicide attempt, history of physical or sexual abuse, suicidal ideation, and non-suicidal self-injury (13, 62).

Impairment in Functioning and Quality of Life

The NCS-A characterized impairment as “some,” “a lot,” or “extreme” (12). Fully 90% of adolescents with BP endorsed severe impairment, whereas this was true for 74% of adolescents with MDD, 49% of adolescents with disruptive behavior disorders, and 26% of adolescents with anxiety disorders. A recent study found lower quality of life among youth BP than among youth with other medical and psychiatric disorders (14). Quality of life in important domains such as family, friends, and school was especially reduced compared to other youth, and was even poorer than among youth with MDD. Comorbid anxiety disorders and disruptive behavior disorders, especially in the context of maternal mood

Benjamin I. Goldstein and Boris Birmaher

disorders, appear to be associated with worse family functioning among youth with BP (63).

Medical and Mental Health Service Utilization

Epidemiologic findings from studies in the U.S. and Canada suggest that under-treatment of BP among adolescents is problematic, as only 45-55% of adolescents with BP report accessing any mental health services in their lifetime (19, 20). Treatment rates are especially poor for adolescents with BP when disorder-specific services are examined, rather than any overall mental health services.

Only 22.2% of adolescents with BP-I or –II in the NCS-A report accessing treatment in their lifetimes specifically targeting BP (10). By comparison, 59.8% of adolescents with ADHD and 39.4% of adolescents with MDD or dysthymia reported lifetime use of services targeting those disorders. However, findings based on health insurance claims indicate that those adolescents with BP who do access treatment incur markedly increased behavioral health costs than adolescents with other mood disorders or non-mood disorders (16). Youth diagnosed with BP do often access treatment for ADHD, depression, and disruptive behavior (64). It is possible that some treatments for these problems may benefit youth with BP (e.g., cognitive-behavioral therapy, family therapy). However, failure to integrate the BP diagnosis could lead to suboptimal psychosocial treatment, which relies on appropriate psycho-education (e.g., misinterpreting manic symptoms as “behaving badly”), or to potentially mood-destabilizing pharmacologic interventions (e.g., stimulants, anti-depressants), in addition to prolonging the delay to appropriate treatment. Unfortunately, it is precisely the adults with youth-onset BP who report both the most prolonged delays in treatment for BP and most severe courses of illness (historically and prospectively) (6, 7, 65, 66).

Psychiatric Comorbidity

Comorbidity is the norm in BP, and the majority of adults with BP have ≥2 other psychiatric conditions, most commonly anxiety disorders and substance use disorders (SUD) (30). A meta-analysis of children and adolescents with BP found that ADHD (62%) was the most common comorbidity, followed by oppositional defiant disorder (ODD; 53%), anxiety disorders (27%), conduct disorder (CD; 19%), and SUD (12%) (67). Comorbidities such as eating disorders and pervasive developmental disorders occur less commonly. ADHD appears to be more common among children with BP, whereas panic disorder, conduct disorder, and SUD appear to be more common

among adolescents with BP (48). Studies suggest that comorbidities may exacerbate the course and outcome of BP. For example, comorbid ADHD has consistently been associated with decreased response to mood-stabilizing medications, and this effect is especially pronounced among adolescents (vs. children) and among those with BP-I (68). Comorbid anxiety disorders have been associated with greater depression severity, and with reduced efficacy of antimanic treatment (69, 70). Finally, comorbid SUD are associated with concerning outcomes such as medication non-adherence, suicide attempts, legal problems, and teenage pregnancy and abortion (40, 71). The impact of comorbidity, particularly ADHD (72), on treatment decisions is elaborated elsewhere in this collection.

Medical Comorbidity

Medical comorbidity is a major concern in BP. Cardiovascular disease is both exceedingly prevalent and premature among adults with BP, leading to excessive cardiovascular mortality (73). Although psychiatric medications are associated with metabolic disturbances, the association between BP and cardiovascular disease was observed prior to the advent of modern medications (2).

Metabolic syndrome components (dyslipidemia, hyperglycemia, hypertension, and obesity) are also exceedingly prevalent among adults with BP, and are associated with a more pernicious course of illness, including increased functional impairment, suicide attempts, and manic and depressive episodes (74). Recent findings suggest that despite their young age, children and adolescents with BP may also incur increased risk of medical comorbidities.

Between 28-36% of youth with BP suffer from multiple medical conditions, whereas this is true for only 8% of youth with other psychiatric disorders combined (75, 76).

Obesity, hypertension, and diabetes are highly prevalent and often precede BP, and use of specialty cardiology services is doubled. Correlates of overweight/obesity among youth with BP include history of physical abuse, comorbid SUD, psychiatric hospitalizations, and exposure to multiple classes of mood-stabilizing medication (77). Migraine, asthma, and neurological conditions such as epilepsy may also co-occur disproportionately with BP (75, 76).

Differential Diagnosis

The primary differential diagnosis of pre-adolescent BP is ADHD. The overall rate of comorbid ADHD among studies of pediatric BP (62%) (67) is problematic because the extent of overlapping symptoms of ADHD presents unique diagnostic challenges. Methods for distinguishing 9

Prevalence, Clinical Presentation and Differential Diagnosis of Pediatric Bipolar Disorder

BP from the more prevalent ADHD have been described previously. The two primary distinguishing features of BP are the discrete episodes of BP and the distinguishing symptoms of mania (78). Different approaches have been taken to delineate BP (with or without ADHD) from ADHD. One approach is to “double count” symptoms.

That is, if a child is highly distractible and hyperactive, then these two symptoms would be counted toward a diagnosis of ADHD as well as toward a manic episode (i.e., BP). Proponents of this strategy argue that it is impossible to reliably attribute the “cause” of one symptom to one disorder over another. An advantage of this strategy is that it requires less clinical discretion and judgment, which may enhance reliability if at the expense of validity. The primary disadvantage of this approach is that it may sacrifice specificity, leading to numerous diagnoses of BP among youth with ADHD. An alternative approach is to endeavor to determine whether any overlapping symptoms are clearly exacerbated in the context of mood disturbance. That is, if ADHD is present, overlapping symptoms such as distractibility or hyperactivity are only counted toward a diagnosis of mania or hypomania if they intensify concurrently with episodes of elation or irritability. The same strategy can be applied to diagnoses of generalized anxiety disorder or oppositional defiant disorder, other comorbidities that include more chronic symptoms that overlap with manic symptoms. For example, a child with generalized anxiety disorder consistently experiences irritability, impaired concentration, and restlessness. Therefore, in order to meet criteria for mania or hypomania, there would need to be a distinct exacerbation in these symptoms, as well as at least two additional symptoms of mania.

One symptom that generates substantial diagnostic uncertainty is irritability. The DSM-IV-TR indicates that irritability is a core symptom of mania and hypomania.

Provided that ≥4 other symptoms of mania are present, an episode of increased irritability even in the absence of elation is sufficient to warrant a diagnosis of mania or hypomania. Irritability can pose diagnostic challenges among youth because it is also a diagnostic criterion for major depressive episodes among youth, generalized anxiety disorder, and oppositional defiant disorder. Irritability also frequently accompanies pervasive developmental disorders, conduct disorder, ADHD, substance use disorders, and obsessive compulsive disorder. As such, it is important to determine whether mania or hypomania is a likely factor in explaining irritability or whether irritability is better explained in a given patient by other forms 10

of psychopathology including several of those described above. It is crucial for the purpose of differential diagnosis to clarify whether there are episodes of irritability, or episodic unequivocal exacerbations in baseline irritability, that are associated temporally with other manic symptoms. Irritable mania/hypomania in the absence of elation was a relatively uncommon scenario in the COBY study, however it is important to note that the 10% of patients with this presentation had demographic, clinical, and familial characteristics that were highly comparable to subjects whose hypo/manic episodes include elation (27). In summary, the keys to interpreting irritability with respect to a possible BP diagnosis are the determination of episodicity and of temporal contiguity with sufficient other symptoms of mania.

The concept of chronic, non-episodic irritability is central to differential diagnosis, and has led to the consideration of a new proposed diagnosis for the upcoming DSM-V, Temper Dysregulation Disorder with Dysphoria (TDD) or more recently Disruptive Mood Dysregulation Disorder (DMDD), based on research regarding severe mood dysregulation (SMD; severe, nonepisodic irritability with hyperarousal symptoms), which was earlier described as “broad phenotype” BP (29, 79). However, children with SMD (of whom 86% have ADHD, 85% have ODD and 75% have both) (29), have different symptoms, comorbidities, family histories, neuropsychology, and neurobiology from children with BD-I (29)(80-83). By definition, these children do not have distinct hypomanic/manic episodes. Use of a BP diagnosis in these cases is of questionable value because of the cross-sectional differences noted above, and because SMD-like phenotypes do not appear to be particularly predictive of future BP (29).

Familial High-Risk for Bipolar Disorder

BP is among the most highly familial of psychiatric illnesses. Twin studies suggest that heritability of BP is approximately 0.7-0.8, whereas heritability for MDD is approximately 0.3 (84). Evidence from bottom-up (children as probands) studies suggests that the prevalence of BP is increased among relatives of children and adolescents with BP when compared to healthy children or those with other psychiatric illnesses such as ADHD or anxiety disorders (85, 86). In addition, multiple studies have examined for the presence of psychiatric disorders among the offspring of parents with BP, and these studies consistently demonstrate increased risk of mood disorders among offspring (87, 88). Recent find-

Benjamin I. Goldstein and Boris Birmaher

ings from the large-scale Pittsburgh Bipolar Offspring Study (BIOS) indicate that offspring of parents with BP (N=388; mean age 11.9 years) have approximately a 13-fold increased risk (10.6% vs. 0.8%) compared to control offspring (N=251) of having bipolar spectrum disorders (BP-I, -II, or –NOS) (32). Although most cases were BP-NOS, the rate of BP-I among high-risk offspring (2.1%) was significantly higher than among control offspring (0%). Of note, 75.6% of BP offspring who had any bipolar spectrum disorder had onset prior to age 12. Preliminary analysis showed that after 10 years of follow-up rates of BP in the offspring of the parents with BP were 20-fold greater compared to offspring of controls (89). Recent findings in a large sample of adolescent offspring (mean age 16.7 years) of parents with BP found that 8.5% had a bipolar spectrum disorder, and 4.3% had BP-I specifically (90). Some studies have found lower rates of bipolar spectrum disorders than those described above (91, 92), and possible reasons for this discrepancy include nationality, age of subjects at intake, sample size, and interpretation of symptoms among children. Nonetheless, approximately 90% of school-aged offspring of parents with BP do not suffer from BP, raising the question of who among these offspring is at especially increased risk. Risk factors for BP among school-aged offspring may include antecedent anxiety disorders and disruptive behavior disorders, and the risk of BP may be increased if both parents have BP (93). Although odds ratios are greatest for bipolar spectrum disorders, offspring of parents with BP also incur increased risk for anxiety disorders, depressive disorders, and disruptive behavior disorders.

Clinical High-Risk for Bipolar Disorder

Several studies suggest that pre-natal and peri-natal risk factors, as well as stressful life events, may contribute to risk for BP, albeit that the data are more tenuous than those relating to schizophrenia and major depression, respectively (94, 95). Several psychiatric disorders may commonly precede the onset of BP. The incidence of BP among clinically-ascertained children and adolescents with MDD appears to be approximately 15-20% within 3-6 years, with higher rates generally observed among inpatient samples and in studies with longer follow-up. Risk factors for BP among adolescents with depression include rapid-onset of depression, familial loading of mood disorders, the presence of psychotic features, and the presence of treatment-emergent mania (96). Epidemiologic data suggest that anxiety disorders

and oppositional defiant/conduct disorders may also be strongly predictive of subsequent BP, although in these cases clinical risk factors for conversion to BP have yet to be identified (23). Perhaps surprisingly, it is not as clear that ADHD is a risk factor for BP, particularly in the absence of other comorbidities (97).

Summary Taken together, the literature to date suggests several conclusions. BP as defined by rigorously applying diagnostic criteria has been observed among children and more commonly in adolescents in numerous countries.

The prevalence of clinically meaningful BP-spectrum conditions is greater than that of BP-I, and, importantly, BP-NOS among youth is often a “gateway” to BP-I or BP-II. Substantially increased use of the BP diagnosis has been observed in clinical but not epidemiologic studies, potentially implicating non-adherence with diagnostic criteria. The course, clinical characteristics, and comorbidities of BP among children and adolescents are in many ways similar to those of adults with BP, and continuity of pediatric BP into adulthood has recently been demonstrated. Together with family studies, treatment studies and neurobiological studies, these data provide increased support for the validity of pediatric BP. The challenge of how to reduce the disparity between clinical and epidemiologic findings remains, and this may be in part due to the difficulties ascertaining symptoms such elation and grandiosity in children. The complexity of BP, particularly the high rate of comorbidity with diagnoses that include overlapping symptoms, is also likely contributory. Up to 55% of youth with BP receive no treatment whatsoever, and rates of diagnosis-specific treatment lag well behind those among youth with ADHD and MDD. Redoubled effort is warranted to ensure that clinicians screen for and treat BP among youth when indicated, and that diagnoses of and treatment for BP are only given after systematically ascertaining the necessary symptoms and episodes of mania and hypomania. In addition, clinically applicable biomarkers and psychometrically sound screening strategies summarized elsewhere in this edition of the Journal offer hope that diagnostic accuracy will improve further in coming years.

Key Points • Billing diagnoses of pediatric bipolar disorder have increased dramatically, whereas epidemiologic stud11

Prevalence, Clinical Presentation and Differential Diagnosis of Pediatric Bipolar Disorder

•

•

• •

•

• •

•

ies employing standardized interviews suggest relatively stable prevalence.

There is increasing consensus that pediatric mania or hypomania can be euphoric, irritable, or both, provided that sufficient other symptoms are present, and that symptoms track together episodically.

Similar to bipolar I disorder, sub-threshold bipolar disorder (e.g., bipolar disorder not otherwise specified) is associated with suicidality, significant functional impairment, and substantial comorbidity. If defined by an episodic course, nearly half of cases sub-threshold bipolar disorder “convert” to bipolar I or II disorder over five years.

The course of pediatric bipolar disorder is characterized by recovery, recurrence, and persistence into young adulthood.

Compared to the course of adult bipolar disorder, the course of pediatric bipolar disorder is characterized by a greater proportion of time symptomatic, a greater proportion of time in mixed states, and more frequent polarity switches.

Approximately 50% of youth with bipolar disorder receive no treatment. Among those who do receive treatment, approximately 50% do not receive bipolarspecific treatment, raising concerns about exposure to antidepressants and/or stimulants in the absence of mood-stabilizing medication.

Psychiatric and medical comorbidities are common, present diagnostic and treatment challenges, and vary depending on age and gender.

Adherence with established diagnostic criteria, including the requirements regarding sufficient number of symptoms and the presence of episodes, may serve to optimize diagnostic accuracy; automatic “doublecounting” of overlapping symptoms is not advised.

Children of parents with bipolar disorder are at increased risk for several psychiatric diagnoses, but especially bipolar disorder. Clinical risk factors for pediatric bipolar disorder include major depressive disorder, anxiety disorders, and disruptive behavior disorders.

Acknowledgements Dr. Goldstein is supported by the Canadian Institutes of Health Research, the Depressive and Bipolar Disorder Alternative Treatment Foundation, the Heart and Stroke Foundation of Ontario, the Ministry of Health and Long-Term Care of Ontario, an investigator-initiated grant from Pfizer, and by donations to the Sunnybrook Foundation.

Dr. Birmaher is supported by the National Institute of Mental Health (MH59929, MH60952), and by an Endowed Chair in Early-onset Bipolar Disease.

12

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69. Sala R, Axelson D, Castro-Fornieles J, et al. Comorbid anxiety in children and adolescents with bipolar spectrum disorders: Prevalence and clinical correlates. J Clin Psychiatry 2010; 71:1344-1350.

70. Joshi G, Mick E, Wozniak J, et al. Impact of obsessive-compulsive disorder on the antimanic response to olanzapine therapy in youth with bipolar disorder. Bipolar Disord 2010; 12:196-204.

71. Goldstein BI, Strober MA, Birmaher B, et al. Substance use disorders among adolescents with bipolar spectrum disorders. Bipolar Disord 2008; 10:469-478.

72. Scheffer RE, Kowatch RA, Carmody T, et al. Randomized, placebocontrolled trial of mixed amphetamine salts for symptoms of comorbid ADHD in pediatric bipolar disorder after mood stabilization with divalproex sodium. Am J Psychiatry 2005; 162:58-64.

73. Goldstein BI, Fagiolini A, Houck P, et al. Cardiovascular disease and hypertension among adults with bipolar I disorder in the United States.

Bipolar Disord 2009; 11:657-662.

74. Fagiolini A, Kupfer DJ, Houck PR, et al. Obesity as a correlate of outcome in patients with bipolar I disorder. Am J Psychiatry 2003; 160:112-117.

75. Jerrell JM, McIntyre RS, Tripathi A. A cohort study of the prevalence and impact of comorbid medical conditions in pediatric bipolar disorder. J Clin Psychiatry 2010; 71:161-168.

76. Evans-Lacko SE, Zeber JE, Gonzalez JM, et al. Medical comorbidity among youth diagnosed with bipolar disorder in the United States. J Clin Psychiatry 2009; 70:1461-1466.

77. Goldstein BI, Birmaher B, Axelson DA, et al. Preliminary findings regarding overweight and obesity in pediatric bipolar disorder. J Clin Psychiatry 2008; 69:1953-1959.

78. Youngstrom EA, Birmaher B, Findling RL. Pediatric bipolar disorder: Validity, phenomenology, and recommendations for diagnosis. Bipolar Disord 2008; 10(1 Pt 2):194-214.

79. Leibenluft E, Charney DS, Towbin KE, et al. Defining clinical phenotypes of juvenile mania. Am J Psychiatry 2003; 160:430-437.

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80. Brotman MA, Kassem L, Reising MM, et al. Parental diagnoses in youth with narrow phenotype bipolar disorder or severe mood dysregulation.

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81. Brotman MA, Schmajuk M, Rich BA, et al. Prevalence, clinical correlates, and longitudinal course of severe mood dysregulation in children. Biol Psychiatry 2006; 60:991-997.

82. Rich BA, Schmajuk M, Perez-Edgar KE, et al. Different psychophysiological and behavioral responses elicited by frustration in pediatric bipolar disorder and severe mood dysregulation. Am J Psychiatry 2007; 164:309-317.

83. Rich BA, Grimley ME, Schmajuk M, et al. Face emotion labeling deficits in children with bipolar disorder and severe mood dysregulation. Dev Psychopathol 2008; 20:529-546.

84. Goodwin FK, Jamison K. Manic-depressive illness: Bipolar disorders and recurrent depression. New York, N.Y.: Oxford University, 2007.

85. Geller B, Tillman R, Bolhofner K, et al. Controlled, blindly rated, directinterview family study of a prepubertal and early-adolescent bipolar I disorder phenotype: Morbid risk, age at onset, and comorbidity. Arch Gen Psychiatry 2006; 63:1130-1138.

86. Wozniak J, Biederman J, Monuteaux MC, et al. Parsing the comorbidity between bipolar disorder and anxiety disorders: A familial risk analysis.

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88. Duffy A, Alda M, Kutcher S, et al. Psychiatric symptoms and syndromes among adolescent children of parents with lithium-responsive or lithium-nonresponsive bipolar disorder. Am J Psychiatry 1998; 155:431-433.

89. Birmaher B. The current status of child and adolescent bipolar disorder.

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90. Nurnberger JI, Jr., McInnis M, Reich W, et al. A high-risk study of bipolar disorder: Childhood clinical phenotypes as precursors of major mood disorders. Arch Gen Psychiatry 2011; 68:1012-1020.

91. Duffy A, Alda M, Hajek T, et al. Early course of bipolar disorder in highrisk offspring: Prospective study. Br J Psychiatry 2009; 195:457-458.

92. Hillegers MH, Reichart CG, Wals M, et al. Five-year prospective outcome of psychopathology in the adolescent offspring of bipolar parents. Bipolar Disord 2005; 7:344-350.

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94. Pavuluri MN, Henry DB, Nadimpalli SS, et al. Biological risk factors in pediatric bipolar disorder. Biol Psychiatry 2006; 60:936-941.

95. Tsuchiya KJ, Byrne M, Mortensen PB. Risk factors in relation to an emergence of bipolar disorder: A systematic review. Bipolar Disord 2003; 5:231-242.

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Isr J Psychiatry Relat Sci - Vol. 49 - No 1 (2012)

Eric A. Youngstrom et al.

Evidence-Based Assessment Strategies for Pediatric Bipolar Disorder Eric A. Youngstrom, PhD,1 Melissa McKeown Jenkins, MA, 1 Amanda Jensen-Doss, PhD, 2 and Jennifer Kogos Youngstrom, PhD1 1

Department of Psychology, University of North Carolina at Chapel Hill, North Carolina, U.S.A. Department of Psychology, University of Miami, Miami, Florida, U.S.A.

2

ABSTRACT Evidence-based assessment of pediatric bipolar disorder has advanced rapidly in the last two decades, moving from isolated clinical case descriptions to what is now a portfolio of techniques that include checklists from multiple informants, semi-structured diagnostic interviews and severity ratings, and technologies that allow daily tracking of mood and energy over the course of treatment. This review critically appraises (a) the need for evidence-based assessment of bipolar disorder as a common component of clinical practice, (b) triggers that warrant assessment of bipolar, (c) when best to deploy different techniques over the course of diagnosis and treatment, and (d) promising new developments in assessment. A decision-making framework is adapted from evidence-based medicine to guide assessment sequences in a patient-centered approach. Emphasis is placed on approaches that currently have the best validity and are feasible in most clinical practice settings. These methods increase accuracy and address many controversies surrounding pediatric bipolar diagnoses.

Conventional wisdom was that bipolar disorder most often manifested during young adulthood. Although there were occasional case reports in childhood or early adolescence, pediatric bipolar disorder (PBD) was considered exotic, and it was not part of the core training for physicians or mental health professionals working with youths. Even now, most textbooks and training materials focus on bipolar disorder as an â&#x20AC;&#x153;adultâ&#x20AC;? condition. As

a result, practitioners have had minimal training in the assessment of PBD. Should busy clinicians invest the time and effort to learn about evidence-based assessment strategies for pediatric bipolar disorder? Given the stakes involved in making this diagnosis correctly, as well as the rapid advances in the evidence base over the last several years, there are few niches that could provide so substantial a return on investment. Other papers in this special issue review the distinction between PBD and other forms of mood dysregulation and aggression (1, 2) and the evidence for the validity of PBD as distinct from ADHD, depression, or other more common developmental psychopathology (3). This review will address key topics, such as why to assess for PBD, when it is clinically indicated, how to change assessment strategies to match the individual needs of the patient over the course of treatment, and what promising future directions might be worth adding to clinical practices in the future.

Why add formal assessment procedures for PBD to the clinical toolbox?

The place where PBD seems most scarce is in textbooks.

There are now several thousand peer reviewed articles describing and validating pediatric bipolar disorder, drawn from dozens of independent research groups around the world (4). A recent meta-analysis of epidemiological studies found that ~2% of children and adolescents in the community - not clinics - meet criteria for bipolar spectrum diagnoses (5), with equal rates in the U.S.A. versus the rest of the world. A Canadian study published after the meta-analysis replicated the 2% figure (6). Increased rates of clinical diagnoses started from a baseline of almost never diagnosing PBD (7), and clinical and epidemiological rates are now converging.

Where have these bipolar cases been hiding? Often in

Address for Correspondence: Eric Youngstrom, Department of Psychology, University of North Carolina, CB #3270, Davie Hall, Chapel Hill, NC 27599-3270, U.S.A. â&#x20AC;&#x2020; eay@unc.edu

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Evidence-Based Assessment Strategies for Pediatric Bipolar Disorder

plain sight. Both community (8, 9) and clinical studies (10-14) indicate that PBD is highly impairing. However, when families seek services, PBD often is missed. If the mood symptoms are prominent, then the most likely diagnosis is major depression, contributing to the finding that one third of all cases with depression prove to have a bipolar spectrum disorder when followed longitudinally (15, 16). If the energy and attention problems are salient, then the likely diagnosis is ADHD or ODD, particularly in Europe and Israel, whereas aggression is more likely to attract a conduct disorder label, and psychosis a schizophrenia diagnosis – especially in ethnic minorities in the U.S.A (17). Because bipolar is an episodic illness, with dramatically different presentations during different phases, it is exceptionally challenging for clinicians to develop a good prototype for the “typical” case. Prototype matching is a main way that experienced clinicians formulate cases (18), but it performs badly with PBD (19, 20). Vignette studies demonstrate tremendous range of opinion, often varying by global region, when clinicians examine cases with potential PBD (21, 22). Clinical PBD diagnoses rarely agree with each other or with structured interview results at better than chance rates (23), contributing to the long lag between onset of problems and diagnosis in youths (24) and adults (25, 26).

Diagnostic disagreement is less surprising considering the dearth of formal training about PBD, forcing practitioners to learn as they work. Using evidence-based assessment tools can help close the gap, especially if practitioners can easily incorporate the methods without additional time, expense or training. PBD assessment has evolved rapidly, with dozens of tests now having published validity data. The challenges now are choosing the best from among contenders, and understanding each tool’s role at different stages of assessment and treatment.

When Is Assessment of PBD Clinically Indicated?

Evidence-based medicine (EBM) uses probability of diagnosis as a way of organizing clinical decisions about assessment and treatment (27). Every case has a possibility of having PBD, albeit often low. Test scores, risk factors, and other pieces of evidence refine our estimates of the probability. When the probability is sufficiently low, the diagnosis can be “ruled out,” at least until new information triggers re-evaluation (see Figure 1). When enough confirmatory evidence accumulates, then the probability rises enough that we make the diagnosis and concentrate on organizing the treatment around it. This Bayesian framework is similar to clinical thinking such as the “Bipolarity 16

Index of Suspicion” (28, 29). Figure 1 illustrates how diagnostic probability maps onto clinical actions. EBM refers to two major choice points along this continuum: The Wait-Test Threshold, and the Test-Treatment Threshold (27). Below the Wait-Test Threshold, a diagnosis is considered “ruled out.” Above the Test-Treatment Threshold, a diagnosis is considered firm enough to begin treatment.

Between the two thresholds is where additional assessment is needed to either push the probability below the Wait-Test or above the Test-Treatment Threshold. EBM does not attach specific numbers to these thresholds.

Where to set the bar is a clinical judgment, depending on risks and benefits. Formal approaches for integrating these utilities into decision-making may gain popularity as technology reduces the inconvenience associated with computation (27, 30). Table 1 lists steps in evidence-based assessment of PBD detailed below.

An Evidence-Based Process for the Diagnosis of PBD

• Step 1. Know the base rate of PBD in your setting.

The first piece of evidence to incorporate in fast, frugal PBD assessment is its base rate in a clinical setting.

PBD rates vary widely depending on where one works.

PBD is rare in the general community, but somewhat more common in outpatient practices, and even more in practices that specialize in mood disorders. Table 2 lists benchmarks from different settings. In many settings, PBD rates will fall below the clinician’s WaitTest threshold. For example, if a clinician decides that conditions seen in fewer than 1 in 20 cases do not warrant extra assessment unless other warning signs are evident, then their Wait-Test threshold is 5%. If working where <5% of cases might have PBD, then they do not need to include PBD assessment measures as part of their standard intake procedure. When the target is already rare, low scores on the test will not add information, and high scores will still usually be false positives. On the other hand, if working where PBD might be more common - such as an inpatient unit - assessment methods can quickly move some cases below the Wait-Test threshold, and others closer to the Treatment zone.

• Step 2. Assess PBD risk factors. There are risk factors and cues that should trigger further assessment. Most well-established is a family history of bipolar disorder (31, 32) (see Table 3). Bipolar in a first degree relative is linked with at least a five-fold increase in risk for PBD, and second-degree relatives with at least half as much risk (33). Other warning signs for PBD

28

treat any other treatconditions any other conditions

Assessment: Low Assessment: assessment Steps 1, 2, Steps 3. No 1, further 2, 3.

No further for bipolar Probability/ Low Low disorder unless there is a new assessment for bipolar for bipolar assessment Not Mood risk factor Probability/ Probability/ disorder unless there is a new disorder unless there isorachange new Not Mood Not MoodDiagnosis risk factor or risk change factor orTreatment: change 0% Diagnosis Diagnosis Treatment:Treatment: No intervention for bipolar; Bipolarity IndexNo intervention treatfor any other conditions 0% for bipolar; No intervention bipolar;

Bipolarity Bipolarity Index of Index Suspicion of Suspicion of Suspicion

0%

Major Depressive Episode (Common; Specific to Bipolar) Major Depressive Episode Not Major Depressive Episode (Common;(Common; Not Specific Bipolar)to Bipolar) NottoSpecific

Specifier)Specifier) Psychosis Psychosis (Fairly (Rare; Assessment: (Fairly (Fairly Rare; more Highly Steps 4, 5, 6. Use more (Rare; (Rare; Assessment: Assessment: Rare; more Rare; more common Specific to specific measures, semiHighly Highly Medium 5, 6.

Use more Steps 4, 5, Steps 6. Use4,more common common due to structured interviews, life Bipolar) Specific toSpecific to Medium Medium Probability/ specific measures, semispecific measures, semiHypomania due to due to bipolar than charting to gather enough data structured interviews, life structured interviews, life Bipolar) Bipolar) Probability/ (Uncommon; Cyclothymic otherHypomania Probability/ Hypomania to confirm or disconfirm bipolar bipolar than bipolar than charting to gather enough data charting to gather enough data Positive Specific to causes(Uncommon; in or NOS (Uncommon; diagnosis.

Cyclothymic Cyclothymic other other to confirm or disconfirm bipolar to confirm or disconfirm bipolar Mania Positive Positive youth) Specific toSpecific to Bipolar) causes in causes in or NOS or NOS diagnosis. diagnosis.

Screener Treatment: Mania Mania youth) Bipolar) Bipolar) youth) (Fairly Rare; Screener Screener Treatment:Treatment: Secondary interventions and non-specific +and low risk Fairly Secondary Secondary interventions interventions and (Fairly Rare; (Fairly Rare; treatments Refractory/Recurrent Specific to non-specific non-specific + low risk + low risk Fairly Fairly Depression Bipolar) Refractory/Recurrent treatments treatments Early Onset Specific toSpecific to Refractory/Recurrent (Less Common; Not Depression Depression Depression Early Onset Bipolar) Bipolar) Early Onset to Bipolar)Depression (Less (Less Common; Not Specific (Less Common; NotDepression Specific toSpecific Bipolar)to Bipolar) (Less (Less Common; Test-Wait Greater risk of Common;Common; Family History of Bipolar Disorder Bipolar) Test-Wait Test-Wait Wait-Test Threshold risk of Greater risk of (Fairly SpecificGreater to Bipolar) Family History FamilyofHistory BipolarCommon; ofDisorder BipolarNot Disorder Assessment: Bipolar) Bipolar) ThresholdThreshold (Fairly Common; (Fairly Common; Not Specific NottoSpecific Bipolar)to Bipolar) Steps 1, 2, 3. No further

Figure 1. Integrated Model of Evidenced-Based Assessment for Pediatric Bipolar

Assessment: Steps 7, 8, 9, 10. Assess Assessment: Assessment: Figure 1. factors that might change 100% HighSteps 7, 8, Steps 9, 10. 7, Assess 8, 9, 10. Assess Integrated Model of Evidenced-Based Assessment for Pediatric Bipolar treatment effectiveness.

Figure 1. Figure 1. factors thatfactors might change that might change 100% High 100% High Monitor process & adherence.

Probability/ Integrated Model Integrated of Evidenced-Based Model of Evidenced-Based Assessment Assessment for Pediatricfor Bipolar Pediatric Bipolar treatment effectiveness. treatment effectiveness.

Measure “midterm” for Mania, Monitor process & adherence.

Monitor process & adherence.

Probability/ Probability/ treatment Measure “midterm” Measurefor “midterm” foradjustment and Bipolar Mania, Mania, Mixed, outcomes. treatment adjustment and treatment adjustment and Depression Mixed, Bipolar Mixed, Bipolar outcomes. outcomes. Treatment: Acute Depression Depression Treatment:Treatment: Aggressive Interventions Mania Treat-Test Acute Acute (medication, hospitalization) AggressiveAggressive Interventions Interventions Threshold (or Mixed Mania Mania Treat-Test Treat-Test Test-Treatment (medication, (medication, hospitalization) hospitalization) Specifier) Threshold Threshold (or Mixed(or Mixed Psychosis

EVIDENCE-BASED ASSESSMENT OF BIPOLAR EVIDENCE-BASED EVIDENCE-BASED ASSESSMENT ASSESSMENT OF BIPOLAR OF BIPOLAR 28 28

Eric A. Youngstrom et al.

17

Evidence-Based Assessment Strategies for Pediatric Bipolar Disorder

Table 1. Ten Steps of Evidence-Based Assessment for Pediatric Bipolar Disorder Step

Rationale

Additional Time and Cost

Know base rate in your setting

Important starting point to anchor evaluations

Time: 0 Cost: 0

Any risk factors?

Risk factors raise “index of suspicion,” enough in combination will elevate into assessment or possibly treatment zones

Time: 2-10 min Cost: 0

Information from broad, externalizing scales

Low externalizing on parent report usually rules bipolar out High parent report another “red flag” High youth report, teacher report double odds; Low scores less informative

Time: none if already part of routine assess Cost: : none if already part of routine assess

Add brief screens for family history, hypomania, mania

Brief family history measure may add new information Parent report screens replace Externalizing score – more specific to bipolar, but highly correlated (no “double dipping”)

Time: 5 minutes for family, 2 minutes for practitioner Cost: None – best instruments are in public domain

Get multiple perspectives – and plan for differences

Parent report helpful in establishing diagnosis, change in functioning; youth and teacher report helpful for measuring pervasiveness and also motivation for treatment

Time: 5 minutes for each informant, 2 minutes for practitioner Cost: None – best instruments are in public domain

Intensive Assessment for bipolar

Clinical interview focusing on mood presentation and specific symptoms Semistructured interviews: KSADS, MINI Life charting – paper, online, smartphone application

Time: 30-120 minutes Cost: 0 to US $4.00 for applications (ILS 0 to 15 new shekels)

Additional assessment for treatment planning

Rule out general medical conditions, other medications; Family functioning, quality of life, personality, school adjustment, comorbidities

Time: Variable Cost: Variable

Process monitoring (“quizzes and homework”)

Life charts, mood & energy checkups at each visit, medication monitoring, therapy assignments

Time: < 5 min per day for family, < 5 min per visit for practitioner Cost: None

Progress and outcome (“midterm and final exams”)

Repeat assessment with main severity measures – interview and/or parent report most sensitive to treatment effects

Time: 10 to 40 minutes Cost: None

Maintenance

Discuss continued life charting; review triggers, critical events and life transitions

Time: Negligible Cost: None

Table 2. Base rates of pediatric bipolar disorder in different settings.

Setting

Base Rate

Population

General Population

2% (4% for spectrum)

Global metaanalysis (5)

Outpatient or Community Mental Health

5% to 10%

Various

County Wards (DCFS) (93)

11%

State of Illinois

Specialty Outpatient Service (94)

15% to 20%

New England, Midwestern USA

Incarcerated Adolescents (95) (96)

2% to 22%

Chicago & Texas

Inpatient and Psychiatric Hospitalization (97) (50)

25 to 40%

All of U.S.A. (record surveillance)

include psychosis – more commonly due to a mood disorder than schizophrenia among children or adolescents (34); early onset depression – which appears to be bipolar spectrum illness in a third of cases dur18

ing follow-up (15); and sleep disturbance – especially periods of decreased need for sleep without associated fatigue (35). Additional clinical presentations that warrant increased attention include bouts of episodic aggression (2, 36) or someone initiating a referral specifically to evaluate PBD. Although these frequently prove to have a different etiology, PBD should be discounted based on disconfirming evidence.

• Step 3. Evaluate information from broad measures.

Many clinicians routinely use instruments measuring multiple factors (37, 38). These types of instruments are sensitive to PBD (meaning that most cases with PBD score high), but not very specific to PBD (meaning that non-bipolar cases also tend to score high on the same scales) (39-41). Although PBD frequently involves a “profile” of elevations on multiple problem behavior scales, the Externalizing score captures most information relevant to possible bipolarity: If Externalizing is extremely elevated, the odds of PBD triple or quadru-

Eric A. Youngstrom et al.

Table 3. Clinical “red flags” that should trigger thorough evaluation of possible pediatric bipolar disorder Red Flag

Description

Reason

Family history of Bipolar*

PBD has genetic contribution Family environment can amplify risk Family environment affects treatment adherence and relapse

5x – 10x increase for 1st degree relative 2.5x-5x for 2nd degree relative 2x for “fuzzy” BP in relative Probe histories of depression, suicide, alcohol and drug, psychosis, and antisocial behavior for possible undiagnosed bipolar (33, 98)

Early Onset Depression

Onset < 25 years Also treatment resistant, recurrent, or atypical depression may be more likely to be bipolar

First clinical episode is often depression 20% to 35% of pediatric depressions ultimately show bipolar course (99, 100)

Antidepressant Coincident Mania

Manic symptoms while being treated with antidepressants

FDA recommends assessing for hypomania, family history of bipolar before beginning antidepressant “Switch” is often previously undiagnosed PBD (101)

Episodic Mood Lability

Rapid switching between depressive and manic symptoms; depressive and manic symptoms at the same time

Common presentation Episodicity more suggestive of mood diagnosis (4)

Episodic Aggressive behavior

Episodic; high-energy. Not instrumental or planned; reactive

Not specific, but common (4, 36)

Psychotic features

True delusions/hallucinations in the context of mood

Delusions/Hallucinations common during mood episode Bipolar more common as source of psychosis than schizophrenia in children (34, 36)

Sleep Disturbance

Decreased need for sleep Less sleep but maintains high energy

More specific to bipolar Indicates sleep hygiene component of treatment

ple. Conversely, low Externalizing scores make PBD much less likely, decreasing the odds by a factor of as much as 20 (40). Externalizing scores provide a distilled “bottom line”: Although PBD frequently shows a constellation of multiple elevations across subscales, no other scales provide significant incremental information after interpreting Externalizing (40, 42, 43).

These initial steps in assessment (i.e., considering the base rate, risk factors, and scores on broad tests) add little or no time to the first interview. The steps reorganize readily available data according to value with regard to PBD. Patients with two or three of these “red flags” are too risky to ignore possible PBD, but also often will not have PBD. These are the cases where more assessment is clearly indicated.

• Step 4. Consider adding a mania measure. The fourth step in assessment would be to gather brief screening instruments focusing on manic symptoms, ideally from the parent or adult most familiar with the youth’s behavior. Some manic symptoms will be more specific to PBD even if they are not associated with the most impairment. Symptoms such as elated mood, grandiosity and unstable self-esteem, and decreased need for sleep have fewer likely causes than irritability and aggression. Instruments that include more content specific to mania (44-46) significantly outperform broad scales at discriminating PBD from non-PBD. It

is easiest for clinicians to simply substitute them for externalizing scores when formulating impressions about possible bipolarity. The more specific mania checklist replaces the Externalizing score in PBD algorithms, because it is the single most valid checklist score capturing the parent’s impressions about the key behaviors for diagnosis (47).

Because mania scales are more specific to PBD, high scores help move towards ruling the diagnosis “in.” EBM has a mnemonic, “SpPIn and SnNOut”: On a Specific test, a Positive score helps rule In; on a Sensitive tests, a Negative score helps rule Out (27).

Low mania scale scores may cancel out one or two risk factors, and high scores provide a stronger surge in the index of suspicion. Note the asymmetry: Finding a family member affected with bipolar increases the PBD probability, but lack of a family history does not decrease risk as much (47). Low scores on sensitive tests (e.g., CBCL Externalizing) are more decisive than high scores on the same instrument (27). Table 4 compares the CBCL and measures more specific to PBD. • Step 5. Get multiple perspectives – and plan for differences in view. In every published study to date, parentreported manic symptoms consistently show greater diagnostic validity than youth- or teacher-report (40).

Parent report shows large effect sizes discriminating PBD from non-PBD cases, whereas youth report 19

Evidence-Based Assessment Strategies for Pediatric Bipolar Disorder

Table 4. Areas Under the Curve (AUCs) and Likelihood Ratios for Selected Measures When Discriminating PBD from All Other Cases Seeking Outpatient Mental Health Services AUC (Citation)

Test Score

Diagnostic Likelihood Ratio

Parent General Behavior Inventory -- Hypomanic/ Biphasic (46)

.84 (40)

<15 16-24 25-39 40-48 49+

.2 1.1 2.2 4.8 9.2

CBCL Externalizing T-Score (102)

.78 (40)

<54 54-56 65-69 70-75 76-80 81+

.04 .5 1.3 2.1 2.7 4.3

YSR Externalizing T-Score (103)

.71 (40)

<49 49-55 56-69 70-76 77+

.3 .5 1.4 2.3 3.0

Adolescent General Behavior Inventory – Hypomanic/Biphasic (104)

.64 (40, 41)

<10 10-37 38-45 46+

.3 1.0 2.0 3.9

CBCL Externalizing T-Score (102)

.82 (40)

<58 58-67 68-72 73+

.1 .5 1.5 3.9

Parent General Behavior Inventory -- Hypomanic/ Biphasic (46)

.81 (40)

<11 11-20 21-30 31-42 43-50 51+

.1 .5 1.3 2.3 4.9 6.3

Screening Measure Adolescents (11 to 18)

Children (5 to 10 years)

Note: All studies used some version of KSADS interview by a trained rater combined with review by a clinician to establish consensus diagnosis. Diagnostic Likelihood Ratio (DLR) refers to the change in probability associated with the test score. Likelihood ratios of 1 indicate that the test result did not change impressions. DLRs larger than 10 or smaller than .10 are frequently clinically decisive; 5 or .2 are helpful, and between 2.0 and .5 are small enough that they rarely result in clinically meaningful changes of formulation (27).

shows medium effects, and teacher report falls in the medium to small range, often not significant (48, 49).

When multiple informants note problems, the youth has a more severe and impairing condition (50, 51).

When youths have PBD, then their self-reported or teacher-reported levels of behavior problems are significantly higher than typical for youths with other diagnoses (52). However, cross-informant agreement about youth functioning is modest, commonly hovering in the range of r = .2 to .3 (53), so “statistically significant” agreement frequently looks like contradictory perspec20

tives at the level of the individual case. For example, if the parent reports an Externalizing score of 80, then a teacher reporting a score of 60 looks like a major difference of opinion unless benchmarked against typical agreement levels (teacher scores would average 56 for that level of parental concern) (52).

Thus seeming disagreement may actually reflect a fair amount of cross-situational consistency, and one informant is often much more concerned about mood symptoms than others. Contrary to conventional belief that youths are the most accurate informant about their own moods (54), parent report is more accurate for the purpose of detecting PBD, possibly because hypomanic symptoms are not dystonic to the person experiencing them and because compromised insight is a feature of hypomania and mania (55, 56). Teachers do not observe some hallmark features of mania, such as decreased need for sleep; and they also tend to attribute many of the other symptoms to ADHD or oppositionality (57). Clinical judgments about individual credibility have meaningful impact on the reliability and validity of parent and youth report. However, parent credibility on average was not connected to their current stress level or history of mood disorder (58).

Similarly, parent report remained significantly more valid even if the parent has a history of mood disorder.

The evidence-based plan of action would be (a) always try to involve a parent in the evaluation of potential PBD, (b) consider multiple reporters as informative about the degree and contexts of impairment, but less helpful in differential diagnosis (47), and (c) use clinical judgment to decide about specific people’s credibility, rather than using simple heuristics (such as “discount parents who have bipolar disorder themselves”) that have failed to demonstrate statistical validity (58).

• Step 6. Intensive assessment methods for PBD. Through application of the first five steps, practitioners will be able to rule PBD out in the majority of cases, and with a high degree of confidence. In statistical parlance, cases testing “not bipolar” will have a high negative predictive value – these decisions will almost always be correct in most settings. This is valuable information: When bipolar is ruled out, something else will usually be ruled in. Once bipolar has been excluded, then the practitioner can treat that other condition with greater confidence. If the diagnosis is ADHD, then stimulant medication can be tried, or antidepressants used for depression or anxiety, with less concern about possible adverse events (59). The

Eric A. Youngstrom et al.

practitioner will also be able to document the “due diligence” about considering alternative diagnoses It is the “test positives”- the cases with a family history and/or high scores on Externalizing, and then a high score on a mania screen - that are more ambiguous. The index of suspicion/probability estimate will be in the mid-range for these cases. So long as we do not lump probabilities of 51% or higher together and treat them as “bipolar,” we will not be “over-diagnosing.” Mid-range cases are the ones where systematic, intensive assessment of bipolarity is indicated.

At a minimum, more intensive assessment of PBD involves a thorough clinical evaluation, combining interview with the youth, direct observation of mental status, and discussion with at least one collateral informant most familiar with the youth’s behavior.

Structured approaches (60-62) cover all symptoms of hypomania and mania, even if the family does not see them as a central part of the presenting problem. Clinicians are often reluctant to use structured approaches, believing that clients dislike structured approaches, or that they damage rapport, are not reimbursable, or they constrain professional autonomy (18).

Surprisingly, none of these concerns are supported by data: client surveys indicate they prefer the thoroughness of structured approaches, without decrement in rapport or engagement (63). Medicaid and insurance companies will reimburse for intensive diagnostic interviewing, especially when screenings or other findings establish medical necessity. Semi-structured approaches also offer more latitude for clinical judgment while retaining the comprehensiveness of a structured approach (61, 62). Agreement between “clinical diagnoses as usual” and semi-structured approaches is typically poor (64), particularly for bipolar disorder (23, 65). Semi-structured approaches are more reliable, detect more comorbidity, and follow DSM criteria more consistently – reducing differences due to training or conceptualization (22, 66) and also shrinking potential bias due to race or ethnicity (67). We propose a hybrid model: if regular intake does not use a semi-structured interview, then the practitioner can add the mood modules of an interview such as a KSADS whenever the index of suspicion is in the “Assessment Zone.”

Additional diagnostic modules could also be selected to investigate competing diagnostic hypotheses or common comorbidities.

Other methods are also available for helping establish a PBD diagnosis. One of the most promising is “life

charting” or “mood charting” (68), tracking changes in mood and energy on a daily basis. The diagnostic power emerges from the repetition and finer-grained resolution compared to retrospective reports about several weeks or a lifetime of functioning. Life charting evolved rapidly from paper and pencil measures to electronic versions that are available on the Web or as applications for smart phones (a Google search for “mood charting” finds the most current versions).

The decrease in cost and advances in convenience and functionality make these an attractive method for gathering data about mood and energy changes. These are valuable in documenting pronounced shifts in energy and affect, and they also become an aid in monitor progress during treatment, as detailed below.

Other assessment techniques have accrued some research or clinical interest, but cannot be considered “evidence-based assessment” tools for clinical application yet. These include genetic tests, fMRI and other imaging tests, neurocognitive assessments, projective testing such as the Rorschach, or even published instruments that are commercially distributed but do not have any peer reviewed studies demonstrating validity. Imaging and genetics are only beginning to use clinically more realistic designs, with fewer exclusionary criteria and a greater emphasis on generalizability, including high rates of depression or ADHD in the comparison group (69).

• Step 7. Assessment for treatment planning. After gathering enough information to make a clear decision about PBD status, the last step before shifting to acute treatment is to collect any other key information that might change our choice of treatment: common comorbidities (36), current medications or substance use (which might interact with other drugs), prior medication trials, personality traits, stability of the family, academic functioning, and quality of life (70). Comorbid substance use may change the initial approach to treatment. Conversely, comorbid ADHD may not require different intervention initially, but instead involves monitoring whether symptoms subside with successful mood stabilization, versus warranting adjunctive intervention after mood stabilization has had time (59). Careful review of medical history ensures that what appear to be mood symptoms are not the result of some other general medical condition or drug side effect. Bipolar disorder is linked with low levels of personality traits such as conscientiousness, which often lead to forgetting appointments, home21

Evidence-Based Assessment Strategies for Pediatric Bipolar Disorder

work, medication, and other accidents of omission that can undermine treatment (71). Poor family functioning predicts earlier onset, poor response during treatment, and rapid relapse (59). Effective interventions that reduce conflict and improve communication are being explored as adjunctive treatments for PBD (59). Short and simple instruments assessing family functioning may be most practical for busy practitioners. Assessing quality of life can help define objectives beyond mere symptom reduction and thus improve engagement with treatment. Again, some of the best tools are short and also in the public domain (72). Finally, it is crucial to assess and document potential suicidality (73).

• Steps 8 & 9. Measuring process and outcome. Once sufficient data confirm a PBD diagnosis, the focus shifts to treatment (27). Assessment plays a different important role during treatment (74). The key questions change from “what is the problem?” and “what are the causes?” to “how bad is the problem?” and “are we making progress towards our goals?” The simple acts of measuring severity and defining targets are themselves associated with better outcomes (75). The idea of going on a diet without measuring weight is absurd. It is similarly helpful to mark the starting point and goal while trying to manage mood and behavior. Some methods used in differential diagnosis will not contribute as much during active treatment. Repeating a KSADS interview or neurocognitive testing to check for loss of diagnosis or measurable change rarely makes sense in practice.

Measures of mood severity are worth repeating if they are brief enough to be well-tolerated, yet still are valid.

Assessment during treatment has many parallels to teaching. A “final exam” outcome evaluation should be comprehensive, covering not just key themes but also related material. A fairly intensive “midterm” assessment could evaluate progress and guide adjustments in the next phases. Brief and frequent evaluations - such as quizzes, homework assignments, and diaries - now have direct analogs in the mood assessment portfolio. Intensive interviews about the severity of mood, such as the CDRS-R (76) or KSADS Mania Rating Scale (62), provide valuable information about one aspect of functioning, but they require a considerable amount of time to complete and “grade” – similar to essays on a midterm or final. Their time demands prohibit frequent use in practice, and their narrow focus means that a comprehensive picture should augment via checklists (the “multiple choice” analog of the mood battery). Assessment best supports treatment by 22

blending brief “process” measures (Step 8) with more intensive strategies quantifying severity or functioning at the beginning, middle, and end of treatment.

Chronologically, these assessment tactics can weave together, just as Steps 8 and 9 are interdigitated here.

Some behavior rating scales offer “good enough” validity in terms of sensitivity to severity and to treatment effects that they can be used instead of repeated semi-structured interviews in clinical practice (77, 78).

Again, price and speed break ties between otherwise equally valid tools. The few studies investigating comparative treatment sensitivity find similar effect size estimates whether using parent-reported checklists versus semi-structured parent and youth interviews (78, 79). Parent checklists show stronger correlations than youth checklists do with criteria such as interview severity ratings or treatment effects. All things being equal, longer instruments will be more reliable, and reliability sets the upper limit on validity (80).

Despite this psychometric principle, shorter versions of parent checklists are equally as sensitive to treatment effects as the full length versions, because they dropped weak items less specific to PBD. Thus, practitioners can use shorter versions as a baseline, midterm, and “final exam” and sacrifice little compared to doing a longer interview, and nothing compared to using a longer checklist.

Practitioners should always try to involve the parent when working with mood disorder. This is standard practice working with young children, but becomes more variable when working with adolescents. Parents are helpful in identifying presence of mood disorder; they are sensitive to treatment effects even in blinded studies, and they are pivotal for retention in outpatient services. Most often the parent initiates the referral and provides transportation to sessions (81). If the parent does not feel heard, services often terminate prematurely.

Despite the advantages of parent report for diagnosing PBD, there still is a major role for cross-informant perspectives in the context of treatment planning (74).

Youth report, although second best to caregiver report at identifying mania (40, 47), is crucial for evaluating depression. Youth report also reveals the degree of insight and motivation for treatment (81). When parents report concerns that the youth denies or minimizes, then the practitioner and youth likely have discordant views about medication or therapy techniques.

Compliance will be poor as a result. Teacher report is

Eric A. Youngstrom et al.

not as helpful as parent or youth report for identifying PBD (48, 57), but it can be valuable for understanding school functioning and interventions planning. When multiple informants agree about the presence of mood problems, then severity is clearly much worse (50, 82).

How often should mood ratings be repeated?

Although clinical trials use them weekly (78), there are diminishing returns. Once or twice – baseline and “final exam”- are good standard practice, and a “midterm” evaluation to make sure that there has been symptom reduction after an adequate trial of the therapy could be worthwhile. Assessments may detect early response and guide more rapid treatment adjustments (83), suggesting extra panels of assessment at the beginning of treatment or following major changes in regimen.

Clinicians often assess mood and energy informally during therapy or medication checks. Two simple modifications transform this into a powerful assessment strategy: (a) use a consistent scale, and (b) write it down (84). The choice of scale probably does not matter: A scale from 1 to 7, such as the Clinical Global Impressions scale uses (85), is simple enough that even children understand it, and more complex scales do not gain any sensitivity with their exaggerated appearance of precision. Writing down ratings over time exposes trends. A good minimum standard would be to incorporate a “mood and energy checkup” into the treatment note, so that each visit documents whether there has been a change in energy or mood during the intervening period (47).

Life charting is especially valuable for tracking treatment response, treatment emergent side effects, and triggering events linked to mood exacerbations (86). Life charts map naturally onto the “three column charts” and “five column charts” of classic cognitive behavioral therapy (87). Three column charts note times of intense emotional reaction, along with the triggering event and the attached cognition or interpretation. Life charts already record the emotion and the trigger, providing excellent source material for practicing the therapy skills.

If there were significant comorbidities, or multiple impaired domains, then the “midterm” examination may include either a broad instrument or select scales to check that the other concerns are responding to treatment. Often good PBD treatment reduces anxiety or attention problems, but sometimes these problems persist even when mood symptoms subside (59). The frequent persistence is a line of evidence suggesting

that PBD and ADHD may be a true comorbidity (88).

Stimulant medication can be well tolerated, particularly when mood stabilizers are already in place (59, 89).

Assessment identifies if there are lingering symptoms that merit adjunctive treatment, and then monitors for treatment emergent changes in mood or energy.

Other components for the mid-term exam may include assessment of family functioning, of substance use, or any other factors that might moderate treatment effects.

Measures of effect size are group statistics, not directly applicable to individual cases. There are several research definitions of treatment response and “clinically significant change” (90). Although these apply directly to individual cases, they have not become popular with practitioners. Practitioners tend to like people and not numbers; clinical significance definitions often set a high bar that is not achieved by many cases; and there is a fear of being evaluated by third party (or by consumers). However, without assessment we cannot learn from our mistakes (18); otherwise, in mental health, greater experience is not associated with better outcomes.

• Step 10. Maintenance monitoring. Once acute treatment concludes successfully, the last role for assessment is to provide early warning of potential relapse. Life charting and online methods can note changes in sleep or energy that might signal an incipient mood episode (28). Because these methods are novel, there are not yet clear evidence-based practice standards. The proactive practitioner develops a plan for self-monitoring, including identifying key triggers and warning signs that the person’s mood may be “roughening” or destabilizing.

Benefits of an Evidence Based Assessment Approach to Pediatric Bipolar Disorder

The assessment algorithm described here has several strengths. First, the approach is more accurate than unaided clinical decision making for PBD (21), replicating a well-established finding in literally hundreds of studies across clinical professions (18, 91). Second, information is used more consistently and efficiently. When clinicians read a vignette, hear about a family history of bipolarity, or see an elevated test score, they tend to attach different weights and meanings. An EBM approach weights the findings based on empirical validity. The more that clinicians use the EBM approach, the more consistent their interpretations of the same information will be, and the less contradictory opinions will result. Using the nomogram (a type of chart that yields Bayesian probabilities without 23

Evidence-Based Assessment Strategies for Pediatric Bipolar Disorder

requiring any computation; see Appendix I) or other rapid interpretive approaches have shown dramatic increases in the precision of risk estimates for PBD (21). Third, the EBA approach eliminates a tendency to over-estimate the probability of PBD. The cognitive decision-making literature shows that humans focus more on cues of risk, and intuitively overestimate the probability of negative outcomes – erring on the side of caution for evolutionarily adaptive reasons (92). This evolved bias can lead to clinicians over-estimating the probability of negative outcomes such as PBD or suicide risk. EBM interprets objective inputs as objectively as possible, eliminating the potential for cognitive biases to distort the interpretation. Fourth, the algorithm is highly feasible. Thinking about the base rate, knowing the weight to assign to different risk factors, and knowing the information value linked to scores on broad-band assessment tools all add little or no time or cost to the intake process (see Table 1). It is a way of “working smarter,” integrating these pieces of information into an “index of suspicion” that then guides the next clinical action. Adding a mania-specific measure also is highly feasible: The three measures with the strongest evidence base are also three of the shortest, and all are currently in the public domain. Thus adding a mania measure costs nothing, takes minimal time, and a one page version appears as helpful as longer or commercially distributed versions.

What Are Future Directions for Evidence-based Assessment of Pediatric Bipolar Disorder?

There has been remarkable progress in the assessment of PBD over the last two decades. There remains much to do before assessment “matures” to fully realize its potential for the identification and management of PBD. One frontier involves instrument translation and validation in languages other than English, and developing low cost tools that require minimal infrastructure, such as SMS text message mood charts. The next decade will bring decreases in the cost of technologies such as imaging and gene testing or proteomics, as well as advances in the delivery of computer-based performance measures.

None of these technologies or refinements will replace the clinician. A skilled professional remains essential to frame the questions of assessment, organize the tools, integrate the information, and interpret the data in a way that conveys meaning and motivation to the patient. Advances in assessment require new skills from the practitioner, the most central of which is the ability to balance and shift between technical and quantitative aspects of testing (27) and humanistic, qualitative aspects of interpretation (75).

24

The methods presented here push for more systematic evaluation, incorporating validated tools, and shifting to a Bayesian framework for thinking about probability, risks, and benefits. To deliver any benefit, though, practitioners must develop competence and comfort with the concepts, so that they can explain findings in clear terms to a lay audience, and help patients to see how accurate assessment gives them power over their mood to change their lives for the better.

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Scheffer RE, Kowatch RA, Carmody T, Rush AJ. Randomized, placebocontrolled trial of mixed amphetamine salts for symptoms of comorbid ADHD in pediatric bipolar disorder after mood stabilization with divalproex sodium. Am J Psychiatry 2005;162:58-64.

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99. Kochman FJ, Hantouche E, Ferrari P, Lancrenon S, Bayart D, Akiskal HS. Cyclothymic temperament as a prospective predictor of bipolarity and suicidality in children and adolescents with major depressive disorder. J Affect Disord 2005;85:181-189.

Appendix 1. Nomogram for combining probability with likelihood ratios EVIDENCE-BASED ASSESSMENT .1

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Straus et al. (27) provide the rationale and examples of using the nomogram. Jenkins et al. (21) illustrate using a case with possible PBD.

Appendix 1. Nomogram for combining probability with likelihood ratios.

Straus et al. (27) provide the rationale and examples of using the nomogram. Jenkins et al. (21) illustrate using a case with possible PBD 27

Isr J Psychiatry Relat Sci - Vol. 49 - No 1 (2012)

Biological Evidence for a Neurodevelopmental Model of Pediatric Bipolar Disorder Donna J. Roybal, MD,1 Manpreet K. Singh, MD,1 Victoria E. Cosgrove, PhD,1 Meghan Howe, LCSW,1 Ryan Kelley, BS,2 Naama Barnea-Goraly, MD,2 and Kiki D. Chang, MD1 1

Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University, Stanford, California, U.S.A. Center for Interdisciplinary Brain Sciences Research, Stanford University, Stanford, California, U.S.A.

2

ABSTRACT Bipolar disorder (BD) is a chronic illness with high morbidity and mortality. Pediatric onset BD has a more severe course of illness with higher rates of relapse and psychosocial impairment. Discovering interventions early in the course of BD in youth is paramount to preventing full illness expression and improve functioning in these individuals throughout the lifespan. It is therefore important to understand the mechanisms involved in the development of BD in order to determine which youth are at most risk and provide biological targets for early intervention. To serve this cause, we propose a neurodevelopmental model of BD, based on the existing data that implicate prefrontal â&#x20AC;&#x201C; subcortical network dysfunction, caused by pre-existing genetic susceptibility and triggered by pathological reactions to stress and chronic inflammatory processes.

Introduction Bipolar disorder (BD) is a chronic, debilitating illness with a lifetime worldwide prevalence of 4.8% and more disability-adjusted life-years lost than major neurological conditions or cancer (1). Pediatric onset BD (PBD) may predict a more severe course of illness (2-8) with high relapse, recurrence, psychosocial impairment, substance use, and suicide at twice the rate of attempted suicides when compared to individuals with unipolar depression (9). Given the high morbidity and mortality associated

with PBD, it is important to identify the mechanisms that lead to PBD in order to design better interventions (10), as there is a 10% less likelihood of recovery each year treatment is delayed (11). Despite the adverse impact of this illness, the field has not yet clearly elucidated the developmental pathophysiology of BD (12).

Nonetheless, advances in neuroimaging have allowed researchers to begin to formulate how BD begins and develops in children. Neurobiological studies demonstrate that BD is a brain-based disorder (13, 14). There are therefore brain structural, functional, and chemical changes that occur during the development and course of the disorder. Studies using different types of Magnetic Resonance Imaging (MRI) have found abnormal brain structure, function, and neurochemistry in BD patients. Results from these studies, as well as from other biological studies of BD youth, have begun to allow us to formulate theoretical models of BD development in children and adolescents.

A proposed neurobiological model for the development of BD in youth

In this paper, we will integrate selected findings from MRI studies in youth with and at-risk for BD, as well as data from adult BD studies, with genetic and other biologic findings to generate a neurobiological model of BD development in youth. The model in brief is such: Children with family histories of BD and mood disorders inherit various genes that create varying levels of risk for BD. These genes translate to neural circuitry and structure that support abnormal mood regulation. Early in life this is detectable as aberrant circuitry between the prefrontal cortex (PFC) and subcortical limbic structures responsible for emotional processing (prefrontal-subcortical circuits). These disruptions

Address for Correspondence: Donna Roybal, MD, Stanford University School of Medicine, Division of Child and Adolescent Psychiatry, 401 Quarry Road, Stanford, CA 94305-5719, U.S.A. â&#x20AC;&#x2020; droybal@stanford.edu

28

Donna J. Roybal et al.

are detectable as white matter and functional connectivity abnormalities, leading to failure of efficient prefrontal regulation over subcortical structures, and thus gradually increasing mood dysregulation. Over childhood and through puberty into adolescence, these abnormal circuits become reinforced and strengthened through increased environmental stress and maladaptive responses to stress that thereby further create environmental stress in a cyclical fashion. Maladaptive stress reactions may be measured by heightened proinflammatory cytokines, which may lead to further neurodevelopmental abnormalities. Once this abnormal circuitry is well-established, anatomic markers may eventually arise that may be unique to children with BD, such as decreased amygdalar volume (15) and these abnormalities may create further vulnerabilities in other brain areas involved with emotional regulation, such as the ventrolateral PFC (VLPFC), the anterior cingulate cortex (ACC), thalamus, striatum, hippocampus, and the cerebellar vermis (16-23). Abnormal reciprocal connections between the dorsolateral PFC (DLPFC) and the amygdala may further be the source of emotional regulation and cognitive difficulties (21, 24-26).

Eventually, with repeated mood episodes, prefrontal structures undergo glial and neuronal cell loss, further denigrating the ability of the PFC to regulate mood.

This condition leads to rapid cycling and treatment resistance and less stress needed for the next mood episode, consistent with the kindling theory of mood disorders (27). In this paper, we will present the relevant biological findings that provide the basis for this proposed neurodevelopmental model of PBD. Structural Magnetic Resonance Imaging (MRI) Findings Structural MRI studies in adults and youth with BD have primarily focused on volumetric analyses of whole brain, individual lobes, PFC, striatum, amygdala, hippocampus, and thalamus.

Studies of overall brain volume in youth with BD are inconsistent in their findings, but at least two studies have found decreased overall brain volume in patients with PBD when compared to healthy controls (HC) (24, 28), suggesting reductions in total cerebral volumes that may indicate increased early apoptotic pruning (28).

Lobar structural MRI studies also support this idea, as parietal and temporal reductions in areas responsible for attention, facial recognition, and memory have

been found (22). The superior temporal gyrus (STG) in the temporal lobe appeared particularly sensitive to volumetric reductions in PBD youth when compared to HC (29). Such structural MRI studies of lobar volumes provide evidence of cortical morphometric abnormalities already present in youth with BD. Given the high importance of the prefrontal cortex (PFC) in emotional regulation, many structural MRI studies have focused on this area. Relevant areas of the PFC that are involved with emotion regulation, attention, executive functioning, and reward processing and motivation include the DLPFC, VLPFC, ACC and subgenual ACC (sgACC), and ventral prefrontal cortex (VPFC). Decreased DLPFC (30) and VLPFC (31) volumes have been found in PBD subjects, with VLPFC volume inversely correlated with increasing age in PBD (31). Three studies have also shown decreased ACC volumes in BD youth (32-34). One study measured volumetric changes in nine youth before and after developing fully syndromal BD and found bilateral ACC and sgACC volume reductions after illness onset (35).

Kalmar et al. also found reduced volume in a region encompassing the VPFC to the ACC in a small longitudinal study of youth with BD ages 10-21 scanned two years apart (36). Volumetric findings of the VPFC may also be gender specific, as Najt et al. found enlargement of the VPFC in females with PBD, while males showed VPFC volumetric reductions (37). These volume reductions may be reversible, however, as volume increases are seen in the PFC longitudinally when adults with BD are treated with lithium over time (38). Furthermore, youth with BD who were exposed to mood stabilizers had larger sgACC volumes than those who were not (39). Thus, PFC regions appear to be impacted in PBD, with regional volume loss after the onset of BD, and likely continuing to become more apparent in adulthood, after sustained illness (40), with potential reversal of volume loss due to mood stabilizer treatment.

Other studies have focused on the striatal structures, primarily the caudate, putamen, and nucleus accumbens. These structures are involved in movement, habitformation, impulse control, reward processing, and decision-making and are central in prefrontal-striatalsubcortical circuits governing these functions. Caudate and putamen findings in PBD have been inconsistent, with some studies showing enlargement (24, 34), and others showing no differences (41), or a possible inverse relationship to age (42). Enlargement of these structures may be due to neuronal proliferation, aberrant synaptic 29

Biological Evidence for a Neurodevelopmental Model of Pediatric Bipolar Disorder

pruning, or a compensatory neuronal response to some putative toxic event. Data on the nucleus accumbens is inconsistent with regards to increases or decreases in size in PBD over HC. Trends for increased volumes have been found in prepubertal youth with BD, but not postpubertal youth with BD when compared with HC (43).

These data, however, may be confounded by the fact that decreased striatal volumes are also found in youth with attention-deficit/hyperactivity disorder (ADHD), which is a common comorbidity in PBD (44). A more recent study examined youth with BD, youth with BD and comorbid ADHD, and HC. Youth with BD and comorbid ADHD had moderately increased nucleus accumbens volumes when compared to HC. Youth with ADHD had decreased putamen and caudate volumes compared to the other groups. No difference was found between youth with BD with comorbid ADHD or without (45). Another recent study showed increased caudate volumes in youth with BD and no ADHD compared to youth with both BD and ADHD. Youth with ADHD in this study also had decreased caudate, putamen, and globus pallidus volumes compared with both HC and BD groups (46).

Thus, while the striatum appears to be a key factor in the neuropathophysiology of BD, the nature of involvement may differ depending on the presence or absence of comorbid ADHD symptoms.

The amygdala is responsible for emotional valence and perception, learning, and memory and thus has been extensively studied in PBD (47). Most studies in youth with BD have found decreased amygdalar volumes (22, 24, 30, 34, 41, 48, 49), the most replicated neuroanatomical finding in PBD. Bitter et al. found that during their first manic episode, adolescents with newly diagnosed PBD had no difference in amygdalar volumes when compared to HC or to adolescents with ADHD only.

However, one year later, the adolescents with BD showed significantly less growth in amygdalar volume when compared to either HC or the ADHD group (50). These findings suggest that amygdalar volumes in youth with BD may only be found abnormally low after the onset of mania, and is therefore likely a sequela of BD rather than a cause. In support of this theory are studies in adults with BD, which often have found increased amygdalar volume compared with HC (15, 51, 52), which may be due to exposure to medications such as lithium (53) or due to other mechanisms caused by repeated mood episodes or exogenous factors other than medications.

Additionally, a greater number of life events has been found to be associated with decreased amygdala as well 30

as nucleus accumbens volumes in youth with BD (54). If such stressful events do contribute to smaller amygdalar volume, it is less likely that repeated mood episodes are at the root of enlarged volumes in adults. Nonetheless, it is possible that the amygdala and other subcortical structures are morphometrically responsive in a differential manner to environmental factors such as life stress and psychotropic medications versus endogenous factors, such as mood episodes.

Hippocampal volumetric findings are less consistent. The hippocampus is involved with stress regulation, memory, spatial coding, appraisal, and emotional responses via inhibitory pathways to other subcortical structures. Two studies have shown reductions in hippocampal volume (22, 55) when comparing youth with BD to HC, but two other studies have shown no difference (24, 41). A recent study examining a familial BD sample showed hippocampal volume was inversely correlated to anxiety scores (56), suggesting that heterogeneity of sample for lifetime stress exposure and degrees of pathologic reaction to stress may account for the mixed hippocampal findings in the literature.

Nevertheless, the hippocampus remains a structure sensitive to morphometric changes under stress. Given the known cognitive deficits found in BD, it will be important to further study the impact of exogenous factors on this structure.

The thalamus relays information to different brain areas and regulates states of sleep, wakefulness, and arousal. However, no published studies have found volumetric differences in the thalamus in PBD relative to HC (22, 24, 41, 57). Lastly, several other areas of the brain that have volumetric differences in adults with BD when compared to HC but not in PBD include the corpus callosum (58) and the pituitary gland (59). The cerebellar vermis has also had increasingly more focus as a structure involved with emotion regulation, but to date only trend level reductions have been found in youth with BD (23).

As the above studies were conducted in youth with fully syndromal BD, the question arises as to whether these findings are an underlying cause of BD, or are instead caused by the repeated mood episodes inherent to BD. Many confounding factors exist in these studies, including medication exposure, comorbidities, age at illness onset, or substance use. Additionally, clinical heterogeneity of study population may mean neurobiological heterogeneity, which may â&#x20AC;&#x153;wash outâ&#x20AC;? or obscure underlying biological differences. Thus, examining youth before illness

Donna J. Roybal et al.

onset, when ostensibly fewer of these confounding factors exist, and again after illness onset in a longitudinal manner, would be ideal. Researchers have attempted to reduce the impact of these factors by examining child offspring of parents with BD. Such youth are considered at highrisk (HR) for developing BD, particularly those offspring already with mood symptoms (60). In one study of HR youth, Singh et al. found no overall structural abnormalities in a sample of asymptomatic and symptomatic HR youth relative to HC (61), but did find enlargement of the PFC in asymptomatic HR youth compared to symptomatic HR and HC groups. A different study of asymptomatic HR youth found gray matter volume increases in the parahippocampal gyri (62), suggesting either BD trait related structural changes that predate onset of symptomatic illness or a marker of resilience to mood disorder development given that these offspring were healthy. The finding of decreased amygdalar volumes found in PBD also has not been reported in at-risk samples (61-63) or in first episode mania samples. Karchemskiy et al. studied symptomatic at-risk offspring of parents with BD, theoretically closer to BD onset than healthy offspring, and found no significant volumetric differences in the amygdala, hippocampus, and thalamus (63). These findings suggest that volumetric reduction of these subcortical structures is likely a consequence of the bipolar disease process rather than an etiological finding or risk factor.

Taken together, these studies indicate structural abnormalities in relevant PFC and subcortical regions in youth with BD. Longitudinal studies are needed to determine whether these volumetric findings are indeed risk factors or consequences of BD, but HR studies so far support that these morphometric abnormalities are indeed consequences. Such longitudinal studies thus far have found ACC volume loss (64) and persistently decreased amygdalar volume in adolescents with BD over time (48). Further studies such as these and in larger sample sizes are needed to address developmental factors that may influence results from cross-sectional neuroimaging studies.

White Matter and Diffusion Tensor Imaging (DTI) Converging evidence suggests white matter (WM) alterations are involved in the pathophysiology of BD (65). WM hyperintensities seen on T2 MRI images are the most consistent finding in BD and have been reported in adults and children with BD (65) as well as

in unaffected siblings of adults with BD (66). Clinically, a greater severity of WM hyperintensities has been associated with more hospitalizations and poorer response to treatment (67, 68). Furthermore, studies have also found altered WM volume in PFC and limbic structures (29, 69-73). Other WM studies in BD indicate a disruption of anterior limbic circuitry, including prefrontal-striatal and perhaps thalamic pathways, the cerebellum, and medial temporal limbic areas (74, 75). Finally abnormal WM motor pathways such as the corticospinal tract and internal capsule (76, 77) are also reported in BD, and these disruptions may contribute to the symptom of hyperkinesis. Therefore, given the role of prefrontalstriatal circuitry in mood regulation, alterations in the WM linking these areas together could then manifest as mood dysregulation and eventually, fully syndromal BD. Diffusion tensor imaging (DTI) studies in BD have allowed for a more detailed investigation of how WM tracts are involved in BD. DTI is an MRI based method that measures water diffusion and is most commonly used for the investigation of brain WM structure. Water within a WM tract, is directionally restricted and is often measured as fractional anisotropy (FA). FA is an index of degree of anisotropy of water diffusion in a white matter voxel. Diffusion perpendicular to the axon is restricted by the cell sheath and myelin, and is quantitatively measured as radial diffusivity (RD) (78). Water diffusion is faster along its axis, and is quantitatively measured as axial diffusivity (AD). DTI therefore allows for a 3-dimensional analysis of axonal water diffusion and is a more sensitive measure of WM tract integrity than volumetric measurements.

To date, there are 32 published DTI studies on BD. Of these studies, seven involve children and adolescents. Taken together, DTI studies of both adults (70, 79-100) and youth (76, 101-106) with BD show WM disruptions in the PFC/frontal cortex, the corpus callosum (CC) and association areas (65), including the superior longitudinal fasciculus (SLF) (86, 99, 103), which connects the PFC to the occipital lobe, and in the inferior longitudinal fasciculus (ILF) (99, 106), which connects the temporal to the occipital lobe. Studies in adults with BD have also shown alterations in the uncinate fasciculus, which connects the PFC to subcortical structures, including the amygdala (95, 107).

Despite the importance of the amygdala in emotion regulation and the substantial amygdalar morphometric and functional abnormalities reported in youth with BD, DTI findings have not been as robust for WM tracts 31

Biological Evidence for a Neurodevelopmental Model of Pediatric Bipolar Disorder

connecting the amygdala to other structures such as the CC and PFC. For example, one study found no DTI differences in WM connecting the subgenual cingulate to the amygdala-hippocampal complex between youth with BD and HC (90). More studies specifically examining white matter tracts connecting amygdala to the PFC need to be conducted in youth, as several studies in adults with BD have reported FA abnormalities in these areas (95, 107, 108).

Other adult BD studies have also found WM differences depending on the subjectsâ&#x20AC;&#x2122; mood state. For example, depressed adult subjects with BD show WM alterations in fronto-limbic connections, CC, cingulum, corona radiata, SLF, and ILF (84, 99). There is also evidence that adults with BD continue to have WM structural differences in these same areas when euthymic (87, 97), suggesting that WM alterations in BD may be state and trait related. In summary, DTI studies in adults and youth with BD have so far shown that microstructural WM abnormalities exist in both cognitive and emotion regulatory pathways.

There are few DTI studies examining youth at highrisk for BD. In a study involving both HR youth (symptomatic with one affected first-degree relative) and those already with BD, both groups showed reduced FA relative to HC in bilateral SLF I, with HR youth having a greater FA value than BD youth (103). In another cross-sectional DTI study of HR youth, Versace et al.

(106) found a linear increase with age in FA and a linear decrease with age in RD in HC in the left CC and right ILF. However, in HR offspring a linear decrease in FA and an increase in RD with age were found in the left CC and no relationship was found in the right ILF. These studies suggest that aberrant connections exist in association fibers and the CC in HR youth. These studies also suggest that prefrontal WM changes seen in adults with BD may not develop until later in the course of BD, perhaps after the first manic episode.

Given the findings of widespread WM abnormalities in youth with and at risk for BD, these studies support the concept that abnormal neuronal connectivity is a significant aberrant neurodevelopmental process in BD. However, studies are limited due to varying methodologies and small sample sizes. Combining these studies with other modalities, such as task-activation or resting state fMRI, would demonstrate if indeed functional loss occurs in these altered WM tracts and provide clinical relevance (65, 109). For example, Sui et al. recently examined adults with BD using functional MRI and 32

reported dysfunction in the DLPFC and thalamus with altered WM integrity in the anterior thalamic radiation and uncinate fasciculus, which connects the VPFC to the limbic system (108). As with structural MRI, longitudinal studies are needed to further elucidate how connectivity changes before and after disease onset; as yet there are no published longitudinal DTI studies in youth with or at-risk for BD. Functional MRI (fMRI) FMRI studies examine which areas of the brain respond to particular tasks completed in the MRI scanner, primarily by measuring levels of blood oxygen (BOLD signal) and provide an excellent probe for potential endogenous illness related effects on brain function.

Both emotional regulation and cognitive processing have been explored by fMRI studies in PBD. FMRI studies have primarily implicated the PFC, amygdala, and striatum as areas exhibiting abnormal activation patterns in subjects with PBD. Various types of tasks have elicited abnormal PFC activation in youth with BD. A study using an emotional Stroop paradigm (matching the color of negatively valenced words to the color of either of two adjacent circles) demonstrated greater VLPFC activation in non-euthymic youth with BD compared with HC (110).

In a similar study using the same paradigm, euthymic youth with BD showed reduced VLPFC and DLPFC activation when matching negatively valenced words (111). These studies suggest that youth with BD experience altered PFC function during cognitive tasks that concomitantly require emotional processing and that mood state may also affect the degree of PFC engagement during these tasks.

The PFC is also abnormally activated in youth with BD during visuospatial working memory tasks that also present emotionally valenced visual stimuli. Youth with BD have been shown to have greater activation than HC in the DLPFC during such a task. In this same study, negatively valenced pictures also invoked greater activation in the DLPFC and other frontal areas over HC (21).

Additionally, facial processing tasks have also demonstrated an overactivated PFC. Youth with BD perceived greater hostility and felt more fear to neutral faces than HC and demonstrated greater activation in the VPFC (112). Reduced VLPFC activation when viewing angry and happy relative to neutral faces was also found in youth with BD (113).

Donna J. Roybal et al.

Youth with BD also appear to have difficulty engaging the VPFC during tasks that require response inhibition, which is congruent with the difficulties many of these patients have with impulsivity and motor hyperactivity.

During an fMRI study where subjects performed a motor inhibition task, youth with BD had decreased VPFC activation compared with HC during failed inhibitory trials (114). In other studies where youth with BD demonstrated successful inhibition, increased DLPFC overactivation compared with HC was shown (115, 116). Youth with BD also activated the DLPFC and primary motor cortex greater than HC in a task requiring response flexibility, suggesting greater activation in DLPFC required to inhibit prepotent responses (117).

Psychotropic medications have also been shown to affect PFC activation. In studies where youth with BD were treated with a second generation atypical antipsychotic, then switched to lamotrigine monotherapy and asked to perform various tasks requiring response inhibition, interference, and working memory, reductions of mania symptoms in BD youth after lamotrigine monotherapy were associated with increased engagement of the ventral medial PFC and the DLPFC (118120). In the only published study of pre- and posttreatment medication effects on brain activation in HR youth with BD, subjects treated with divalproex showed a correlation between a decrease in depression symptom severity with a decrease in DLPFC activation (121).

Medication may therefore help engage the PFC during cognitive tasks in youth with BD, but further studies on the effects of medication on HR youth are needed before clinical conclusions can be drawn.

Collectively, these fMRI studies suggest that children have aberrant PFC engagement prior to and after onset of BD diagnosis. Unlike adult studies which show predominantly DLPFC and VLPFC hypoactivity (122, 123), studies in youth with BD have often shown DLPFC overactivation, indicating that this hyperactivity may be present early in the course of PBD, but then eventually lead to hypoactivity in the setting of subcortical-limbic hyperactivity as an adult, mirroring structural MRI and histopathological findings of decreased DLPFC volume in adults with BD (124).

The PFC, however, is not an isolated structure and has robust connections to other areas relevant to emotional regulation, particularly the amygdala. FMRI studies of the amygdala consistently demonstrate overactivation in youth with BD during face processing and Stroop paradigms. Amygdalar hyperactivity has been

shown in youth with BD when viewing neutral faces (125) as well as angry and happy faces (113). Pavuluri et al. used a task in which subjects were asked to judge positive or negative facial expression (directed emotional processing) and determine whether faces showing similar affect were older or younger than 35 years old (incidental emotional processing). Increased amygdalar activation in youth with BD when compared to HC was found during incidental emotional processing relative to directed, suggesting more intense automatic emotional reactivity (126). In addition, amygdalar hyperactivation was also demonstrated in a study using emotionally valenced words in a Stroop paradigm (111). Although not found in all studies, this amygdalar hyperactivity appears to be a fairly consistent finding in youth with BD. Such amygdalar hyperactivity is consistent with the aforementioned findings of decreased amygdalar volume in PBD, as adolescents with BD have demonstrated an inverse correlation between amygdalar hyperactivity and volume (127).

Clinical trials have also found effects of psychotropic medications on amygdalar activation levels.

Improvements in depression symptom severity in youth with BD have been correlated with decreased amygdalar activation in response to negatively valenced pictures following an open-label lamotrigine treatment study (118, 128). However, amygdalar overactivation was not reduced in studies of response inhibition, interference, and working memory in youth with BD treated with a second generation atypical antipsychotic and then switched to lamotrigine monotherapy (118-120). Thus it is not yet clear how or in what condition antimanic medications may affect amygdalar function.

The caudate, putamen, and nucleus accumbens comprise the striatum, which is another central part of prefrontal-subcortical circuits involved in mood regulation. The thalamus is also part of this circuit, serving as a relay station between the PFC and subcortical structures. Visuospatial, face processing, and response inhibition tasks have all shown increased activation in these areas in youth with BD. For example, subjects with PBD were found to have greater activation than HC in the left putamen and left thalamus during a visuospatial working memory task. When positively valenced pictures were shown in this same study, greater activation in bilateral caudate and thalamic regions were shown in youth with BD, whereas HC had no activation during the same task (21). In a study where neutral faces were shown, youth with BD perceived greater hostility and felt more fear 33

Biological Evidence for a Neurodevelopmental Model of Pediatric Bipolar Disorder

when compared to HC and had greater activation in the putamen and nucleus accumbens (125). Similarly, HC showed increased bilateral striatal activation over youth with BD during failed inhibitory trials in a motor inhibition task (114). Youth with BD therefore appear to consistently overactivate striatal structures when presented with emotionally valenced material and during cognitive tasks, suggesting a compensatory mechanism for completing such tasks when compared to HC. These previous fMRI studies support the idea that neural activation during emotion and cognitive processing is aberrant in PBD. The activation differences observed suggest that youth with BD engage prefrontal, amygdalar, and striatal areas abnormally to accomplish emotional processing and cognitive tasks. Are these independent findings or are they somehow connected? Functional connectivity analyses of fMRI data may help to answer this question.

For example, during a task independent resting condition, youth with BD were found to have reduced functional connectivity between DLPFC, superior temporal gyrus, thalamus and striatum compared with HC (129). This abnormal prefrontal-striatal circuitry during rest supports the concept of abnormal circuits being central to the neuropathophysiology of BD. These connectivity problems could develop prior to the first manic episode and lead to functional abnormalities before morphometric abnormalities are detected. Future fMRI studies should examine functional connectivity, or blending fMRI with DTI to correlate functional connectivity differences with aberrant white matter connectivity, and focus on asymptomatic and symptomatic youth at high-risk for BD to examine whether there is early functional network impairment that can then be altered by intervention.

Magnetic Resonance Spectroscopy (MRS) Proton magnetic resonance spectroscopy (1H-MRS) is an MRI-based technology that provides quantitative molecular level biochemical information about particular regions of the brain. N-acetyl aspartate (NAA) and creatine (Cr) are healthy nerve cell markers thought to be involved in maintaining fluid balance, energy production, and myelin formation in the brain. PBD studies have shown altered concentrations of these neurometabolites, predominantly in the PFC. Decreased NAA concentrations in the DLPFC and medial PFC were found in three studies of youth with BD (130-132). However, DLPFC NAA levels were found to be normal in youth at high risk for BD, who have not yet had a manic episode (133). This sug34

gests that decreased NAA concentrations in the DLPFC, which is found in adults with BD (134), may develop as the disorder progresses into adulthood. Since NAA is found in healthy neurons, this concept is consistent with the previously mentioned findings of decreased DLPFC activation and volume in adults with BD, a finding that is not consistently found in youth with BD. Brain myoinositol (mI) is a marker for cellular metabolism and related second messenger signaling pathways and is thought to be involved in myelin sheet and cell membrane synthesis (135); concentrations of mI levels may correlate with myelin turnover. Increased mI concentrations have been reported in the ACC of bipolar manic youth (20, 135, 136) and in the VLPFC of youth with bipolar depression (137). However, studies in adults with BD have found brain mI levels to be decreased (138) or unchanged, compared with HC (20, 139-141). Finally, mI concentrations were reported to be decreased in the cerebellar vermis in symptomatic youth at high-risk for BD (142), indicating abnormal cellular metabolism in this area as well, and supporting previous findings of decreased vermal NAA in HR youth (143). The cerebellar vermis is a less studied region that is involved with mood regulation, and has been found to have abnormal volume (23, 144) and activation (21) in adults and youth with BD. Glutamate is a neurometabolite that may be another useful early indicator for PBD. Studies in children 6-12 years old with BD have found state-dependent increases in glutamate alone or in both glutamate and its precursor storage form, glutamine (together with glutamate referred to as Glx). These findings occurred in the basal ganglia and PFC/frontal lobes (133), in youth with BD with comorbid ADHD (145). This finding was also shown in the ACC in both unmedicated (146) and medicated (147) youth with BD taking risperidone. A recent study of pediatric offspring of parents with BD found decreased absolute glutamate concentrations in the ACC and a trend for decreased glutamate relative to creatinine, but only in youth who had developed fully syndromal mania (148). Therefore, for HR youth, abnormal glutamatergic functioning may again develop only sometime after fully syndromal clinical mania.

Some studies have also shown no differences in glutamate concentrations in the DLPFC (130, 149). These discrepant findings could be due to different sampling criteria, varying field strengths, varying protocols for spectral acquisition and analysis, or other confounding variables. Nonetheless, these findings could indicate

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abnormal neuronal excitation in the PFC in youth with BD, consistent with the above fMRI findings.

It should be noted that the PBD MRS literature is somewhat difficult to summarize, given discrepant findings and methodologies. For example, some studies report absolute concentrations of metabolites, while others use ratios to creatine. These inconsistencies make it difficult to conclude what the relationship is between PBD and detectable metabolite concentrations. Like fMRI, MRS studies are also limited by state-dependent features of BD (150), and may not represent processes specific to emotion regulation or independent of medication effects. However, while the actual role of these neurochemicals in the development of BD is not yet clear, what is known is that there are aberrations in these neurometabolite levels in key brain regions that as yet provide overall support for the developmental model presented here.

Genetics Family, adoption, and twin studies have clearly indicated that BD is a highly heritable disorder. For example, literature suggests monozygotic concordance rates ranging from 56-80%, while family studies suggest an 80% heritability rate (151).

Moreover, a meta-analysis found that offspring of adults with BD are 4 times more likely to develop a mood disorder compared to children of parents without a psychiatric illness (152). Such “bipolar offspring” have a higher risk than the general population for the development of BD specifically (153, 154), with rates of bipolar spectrum disorders reported in 14-50% in these offspring.

Furthermore, family studies suggest that early onset BD is associated with a greater genetic load for BD than for adult onset BD (155, 156).

Because no single gene has been implicated through repeated linkage and genome wide association (GWAS) studies, BD is thought to be a genetically complex disorder caused by a combination of many genes, each conferring a small risk. Through linkage and candidate gene association studies, genes such as those that code for catechol-O-methyltransferase (COMT), GRK 3- BETA, brain-derived neurotrophic growth factor (BDNF), monoamine oxidase (MAOA), the dopamine transporter, the G72/G30 gene (157), and the serotonin transporter (SLC6A4) have all been implicated in adult BD. However, few studies have linked these polymorphisms with pediatric BD. For example, Geller

and cook found no association with COMT (158), the dopamine transporter gene, or the short/long polymorphism of the promoter region of the gene encoding the serotonin transporter (HTT) (159) despite such associations in studies of adults with BD. However, the dopamine D2 receptor (DRD2) gene, a single nucleotide polymorphism (T/T genotype for a T/C) in the glycogen synthase kinase 3-beta (GSK 3-beta) gene, and the polymorphism in the BDNF gene,Val66Met (i.e., where alternative alleles lead to the substitution of valine for methionine in the BDNF molecule) have been significantly associated with early onset BD (160). These findings need replication, as a recent family-based association study found no association of the BDNF met allele, nor the s allele of the 5-HTTLPR or the COMT gene, with a pediatric BD sample (161). Recent GWAS have identified Ankyrin-G (ANK3) and the alpha-1C subunit of the L-type voltage-gated calcium channel (CACNA1C) as susceptibility genes for bipolar disorder in adult samples (162), but as of yet, there have been no studies on these genes in pediatric samples.

Other genetic approaches, such as searching for copy number variants (CNV) specific to early-onset BD, appear to be important for future study of BD now that GWAS have not been conclusive (163). Despite no candidate genes being linked conclusively to early-onset BD, age at onset of BD may be genetically mediated by other methods, Faraone et al. (164) found age of onset of mania to be significantly heritable, and linked to loci on chromosomes 12p (marker D12S1292), 14q (marker GATA31B), and 15q (marker GATA50C). However, a large “mega-analysis” of over 2,000 probands found no association of any single nucleotide polymorphisms with age at onset (165), so genes controlling onset age are still not clear. Phenotypic anticipation, which refers to the increasing disease severity and earlier age of onset of an illness through successive generations, may also have genetic underpinnings. The relationship between anticipation and the existence of expanding trinucleotide-repeat (TNR) sequences have been reported in other disorders such as Huntington’s disease and fragile X syndrome. To date, there has been inconclusive evidence regarding TNR expansion associated with anticipation in adults with BD (166).

Thus, although the role of individual genes in the pathophysiology of BD is not entirely clear, BD remains highly heritable, and probably involves many genes that confer risk for the disorder. This risk likely interacts with environmental factors, such as psychosocial 35

Biological Evidence for a Neurodevelopmental Model of Pediatric Bipolar Disorder

stress, to create pathological responses to stress by way of mood dysregulation and eventually full mood episodes. However, the role of environmental factors on both gene transcription and the onset of pediatric BD remains unclear. Clearly, genes do not confer risk in isolation as most candidate genes implicated in BD code for proteins that regulate neurotransmitters, modulate ion (sodium and calcium) channels, or affect other brain factors. Therefore, they affect brain structure and function/development in specific ways to create risk for BD development. One example of how these susceptibly genes may create risk for BD is the s-allele of the 5-HTTLPR, which is thought to confer small, but clear, increased risk for BD (167). The s-allele has been associated with increased amygdalar activation in healthy adults (168, 169). Thus, overactivation of the amygdala to emotional stimuli in the context of other genetic/neurobiologic risk factors for BD, may eventually lead to full mood episodes and amygdalar/ limbic hyperactivity in youth with BD, as described above. Future studies need to investigate how genetic risk factors lead to brain/stress response to create risk for BD. These genes could also moderate other factors involved in stress response, such as inflammation (see below). Such genetic underpinnings are clearly present from birth, but may be regulated differently at various times during development. These genes may interact with environmental factors in epigenetic ways to drive brain development toward or away from the development of mood disorders.

Biological Serum Inflammatory Markers The unique sensitivity to psychosocial stressors in individuals with BD may be measured biologically by altered cytokine levels. Cytokines are proteins that promote (pro-inflammatory) or impede (anti-inflammatory) the inflammatory response, and thus indicate internal responses to environmental stressors. Experiencing environmental stressors likely alters the balance of inflammatory response by changing patterns of cytokine secretion (170, 171). Interleukin (IL)-6 and Tumor Necrosis Factor (TNF)-α are pro-inflammatory cytokines, and IL-10 is anti-inflammatory/immuno-regulatory in nature.

During exposure to stress in a laboratory setting, healthy (172-174) and depressed (175) individuals have shown elevated inflammatory cytokines. Furthermore, it is thought that responding to psychosocial life stress alters patterns of cytokine secretion by simultaneously enhanc36

ing and suppressing components of the immune system (176). For youth burdened with stressors, secretion of anti-inflammatory/immuno-regulatory cytokines (i.e., IL-10) may be attenuated in favor of pro-inflammatory cytokine (i.e., IL-6, TNF-α) secretion and a high pro-/ anti-inflammatory ratio (177).

Studies of adults with BD have so far used crosssectional, case-control designs and suggest that levels of pro-inflammatory cytokines, such as IL-6 and TNFα, are elevated while levels of anti-inflammatory cytokines, such as IL-10, are decreased (178). Four studies found increased levels of IL-6 and/or TNF-α during both episodes of mania and depression in individuals with BD compared with controls (33, 179-181). One report found no differences in IL-10 levels between controls and BD patients experiencing mania (182).

These findings support that fluctuations in inflammatory cytokine markers are non-specific for the type of mood episode but that symptomatic patients differ significantly from HC. Cytokine levels have not yet been reported in pediatric BD. However, Pandey et al. have preliminary unpublished data finding elevated TNF-α and IF-1beta levels in 22 children and adolescents with BD compared with 21 controls (183). Inflammatory cytokine markers may therefore reflect disease state in those with BD, as stressful life events such as trauma are putative risk factors for BD (184). Further studies showing the relationship between these markers and life stress in youth with and at high-risk for BD are needed to elucidate this relationship.

Because of their effects on neuronal and glial apoptosis, cytokines may be an important mediator in the stresskindling model of BD development (185). Simeonova et al. previously showed that elevated anxiety, a proxy for stress response, was correlated with decreased hippocampal volume in youth with BD (56). Elevated inflammatory cytokines could be mediating this effect and be detectable at a functional neuronal level. In a recent study, 31 adults showed significant elevations in soluble TNF-alphaRII (receptor) and IL-6 after administration of the Trier Social Stress Test (TSST) (186). The degree of increase of TNFalphaRii was positively correlated with dorsal ACC and anterior insula activation while performing a social rejection fMRI task. Thus, exaggerated inflammatory response could be linked to both hippocampal atrophy and abnormal activation of limbic areas. Inflammation during brain development has been linked with behavioral abnormalities in animal studies (187, 188). Therefore, it is possible that the abnormal response to stress in at-risk individuals

Donna J. Roybal et al.

Figure 1. Putative model for the development and course of early onset bipolar disorder

leads to inflammatory cytokine states that then adversely affect brain development, resulting in BD symptomatology. Additional studies of inflammatory processes in response to stress in youth with and at risk for BD are needed to test this hypothesis.

Conclusions Our theoretical model for the development of BD in children and adolescents as described in the introduction is based upon several lines of neurobiological evidence drawn from studies employing neuroimaging, genetic, and inflammation-related probes. Children who have genetic loading for BD may express this propensity as a heightened emotional response to stress, seen as amygdalar overactivation and inefficient regulation of subcortical activation by prefrontal structures.

Mood dysregulation and psychosocial dysfunction in the context of psychosocial stress then occur. Brain networks responsible for mood regulation may already be developing abnormally, but are further disrupted

from normal development and are reinforced into abnormal patterns by repeated pathological emotional responses to stress. Clinically, these disrupted networks, which involve the DLPFC, ACC (dorsal and ventral/ subgenual), VLPFC, amygdala/hippocampus, and striatum, may lead to symptoms of depression and mania.

Without treatment, children may eventually develop a fulminant manic episode. These children may possess further functional abnormalities such as a lost inverse functional connectivity between the amygdala and the DLPFC. Prolonged and repeated mood episodes may lead to morphometric changes such as deceased amygdalar volume and eventually neurodegeneration of the PFC, which further disrupts crucial prefrontalsubcortical circuits and leads to rapid cycling, treatment resistance, and high morbidity and mortality. Postulated relationships between PFC and subcortical structures as BD advances over the lifetime are illustrated in Figure 1. As seen in this figure, after adolescent first mania, studies have shown increased PFC activation, decreased amygdalar volume with increased amygdalar activation, 37

Biological Evidence for a Neurodevelopmental Model of Pediatric Bipolar Disorder

and decreased sgACC volume. When adults with BD are imaged, however, both decreased PFC volume and activation is found with increased amygdalar activation and increased sgACC activation. When exactly, however, this transition to adult-type findings in youth with BD occurs is not clear.

Youth at high risk for BD do not show most of the structural and neurochemical changes prior to the onset of a fully syndromal mania. There is a relative lack of structural abnormalities in symptomatic youth at high risk for BD, but as these youth typically have a prolonged prodromal state of subthreshold mood symptoms and functional impairment (189, 190), it is likely that connectivity and functional abnormalities are already present causing current symptomatology and pathological stress response. Thus, it is possible that if underlying functional connectivity and activation abnormalities are addressed early enough, such morphometric changes and neurodegeneration could be prevented. Early interventions may include psychotherapy (191) and medications (60, 192, 193) which have the potential to alter abnormal functional activity and connectivity (121). Further studies examining functional connectivity (combining fMRI with WM correlates via DTI or higher resolution WM mapping methods), resting states, and advanced mapping techniques with genetic and neuroimmune correlates are needed to support, refute, and/or refine the developmental model of BD presented here.

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Isr J Psychiatry Relat Sci - Vol. 49 - No 1 (2012)

Diagnostic Implications of Informant Disagreement About Rage Outbursts: Bipolar Disorder or Another Condition?

Gabrielle A. Carlson, MDS,1 and Margaret Dyson, MA2 1

Department of Child and Adolescent Psychiatry, Stony Brook University School of Medicine, Stony Brook, New York, U.S.A. Department of Psychology, Stony Brook University, Stony Brook, New York, U.S.A.

2

ABSTRACT Background: Modest agreement between parent- and teacher-reports of child behavior is a common finding.

This study examines diagnoses made when significant disparity occurs in parent- and teacher-reports of rage behaviors.

Methods: Parents and teachers of 911 5-18 year-olds referred for psychiatric outpatient services completed rating scales and received a psychiatric evaluation blind to parent- and teacher-ratings. Children with rage outbursts (n=431, 47.2%) were assessed for diagnosis, family history, and clinical variables.

Results: Children were 12.0 (3.6) years; 26.5% were female. Bipolar disorder was rare (11.2%) in this sample; however, in children with parent- and teacher-reported rages, severe mood dysregulation was the most common condition (54.4%). In parent only reported rages, anxiety disorders were most common (40.6%) diagnoses, and in teacher only reported rages, learning/language disorders were the most common (46.0%) diagnoses.

Conclusion: The context in which a rage outburst occurs may impact the diagnosis; however, diagnosis alone does not explain this difficult and impairing behavior.

Background Children with prolonged, explosive outbursts, also called rages, are often referred to outpatient clinics (1) and hospitalized psychiatrically (2). They are more likely to be

expelled, placed on home instruction, or in special education settings (3). Despite their prevalence, impact and severity, our understanding of these behaviors remains unsatisfactory.

A factor analysis of rage behaviors of inpatient children revealed anger (violent threats, cursing, yelling/ screaming, hitting and kicking, pushing/pulling, and wall punching) and a distress (whining, crying and anxiety) factors (4). The mean duration of these outbursts in inpatients was 45-50 minutes (5). In an outpatient sample, outbursts in over 50% of tantrums lasted longer than 30 minutes! (6).

Behavioral components of rages and normal preschooler tantrums have some similarities. A factor analysis of preschooler tantrums revealed “aggressive/ destructive” (kicking, hitting, throwing, breaking), nondestructive aggression (non-directed kicking, stamping, hitting wall), oral aggression (biting and spitting), and self-directed aggression (hitting self, head banging, breath holding, and biting) factors (7). An important difference (besides size and age) is that “normal” tantrums lasted about 12 +12 minutes, whereas tantrums of children with disruptive behavior and mood disorders lasted longer, 20 + 19minutes (7).

The diagnostic significance of rage behaviors (in contrast to general aggression) has recently become the focus of research (1-3, 6). Mick and colleagues (8) hypothesized that the severity and intensity of irritability varies by diagnosis. The severest level of irritability is characterized by outbursts that are often violent, prolonged, and largely unprovoked (or an incongruent reaction to an event). Behaviors were associated with their definition of mania rather than oppositional defiant disorder (ODD), major depressive disorder (MDD)

Address for Correspondence: Gabrielle A. Carlson, MD, Department of Child and Adolescent Psychiatry, Stony Brook University School of Medicine, Putnam Hall-South Campus, Stony Brook, NY 11794-8790, U.S.A. Gabrielle.Carlson@StonyBrook.edu

44

Gabrielle A. Carlson and Margaret Dyson

or attention deficit-hyperactivity disorder (ADHD) (8). This definition of mania is based predominantly on parent-report, is very chronic (starting in early childhood and without clear episodes), and not necessarily characterized by euphoria or grandiosity (9).

Leibenluft and colleagues (10) sought to identify and label with “severe mood dysregulation” (SMD) a similar population of children. SMD is defined as pervasive anger/irritability, explosive behavior in response to minor provocation, and DSM IV (11) mania “B criteria” (insomnia, agitation, distractibility, racing thoughts or flight of ideas, pressured speech, intrusiveness). The diagnosis cannot be made in the presence of elated mood, grandiosity, episodic decreased need for sleep, schizophrenia, pervasive developmental disorder, posttraumatic stress disorder, MDD, or substance-use disorder. Using this designation, these researchers contrasted irritable, explosive children with classic manic children/ adolescents and found genetic (12), fMRI (13), and treatment response differences (14). Consequently, the SMD diagnosis has prompted further investigation (15).

One consistent observation that has plagued the clinical assessment of children has been the low agreement between parent- and teacher-ratings. Specifically, correlations between parent- and teacher-reports of externalizing disorders average around r=0.3 (16). Despite this modest concordance, understanding the context in which the child’s behavior is observed has theoretical utility (17) and important practical implications (18, 19). Since the controversy surrounding juvenile bipolar disorder is centered on children with explosive outbursts (8), we sought to examine children with this behavior to better characterize and diagnose them.

It was hypothesized that children with rages will be characterized differently depending on whether their rages are endorsed by parents only (parent-reported rages - PRR), teachers only (teacher-reported rages - TRR), or both informants (both report rages-BRR). Further, we explore Child Mania Rating Scale (CMRS) (20), demographic, diagnostic, and family history variables. Based on our prior work (2, 4, 5, 19), we hypothesized that mania/bipolar disorder would not account for the majority of children with PRR or TRR, but rates of bipolar disorder would be higher when informants agreed. We anticipated children with CMRS scores >20 would occur more frequently in children with bipolar disorder and that irritability and hyperactivity items would account for high scores. Based on the ADHD literature (21), we speculated that children with BRR would show the most

psychopathology, such as earlier onset and more family psychopathology. Finally, we posited that SMD and comorbid ADHD and ODD would occur more often in children with BRR than TRR or PRR (22).

Methods Participants included 911 school-aged children and adolescents (between ages 5-18) referred to a child psychiatry outpatient clinic during the academic years between 2005-2008, who received a thorough psychiatric evaluation. Children were not evaluated unless rating scales were received from both parents and a teacher.The study was approved by the Stony Brook Institutional Review Board.

As part of the evaluation, parents and the teacher completed the Child Behavior Checklist (CBCL) and Teacher Report Form (TRF) (23, 24), respectively, and the parent and teacher versions of the Child and Adolescent Symptom Inventory (CASI, 25, 26). The CASI is a DSMIV-based rating scale, which uses a 4-point Likert-scale (0-never, 1-sometimes, 3-often, 4-very often) for each symptom. It has good concurrent validity with structured interviews (25) and has been used previously to study manic symptoms on the children’s inpatient unit (27, 28). It was used to guide the interviewers toward the most clinically relevant symptoms that led to referral, unlike semi-structured interviews (e.g., Kiddie-Schedule for Affective Disorders and Schizophrenia-Present and Lifetime [KSADS –PL], 29) that follow the same format regardless of presenting problem. In the clinic, parents were interviewed first to obtain a history and description of the child’s symptoms, then the child was interviewed separately. If there were discrepancies between parentand child-report, the child was told of parent observations, and the clinician resolved the discrepancy with both informants if needed. If parents described elated mood, decreased need for sleep, goal-directed hyperactivity or racing thoughts in their child (i.e., items in the screen interview of the KSADS-PL), then parent and child were interviewed with the K-SADS-PL (29). We were interested in whether current rages were influenced by current (rather than past) mania.

Parents and teachers completed the CMRS (20), which solicits symptoms of mania using a 4-point Likert-scale.

The CMRS total score of > 20 has been found to distinguish mania from ADHD with a sensitivity of .81 and specificity of .94 (20). Because both parents and teachers completed the CMRS, this study used the specific item on that rating scale about rages: “Does this child have 45

Diagnostic Implications of Informant Disagreement About Rage Outbursts

rage attacks, intense and prolonged temper tantrums ‘sometimes, often, or very often.’” We were thus able to determine which children had rages in only one versus both settings.

Parents completed a biographical form which elicited information about problems during pregnancy, delivery, infancy (e.g., if child was fussy, hyperactive, sleep/feeding problems, difficult to comfort), and the toddler period (e.g., eating/ sleeping problems, aggression toward peers, tantrums). They also completed a family history form assessing ADHD, anxiety, depression, schizophrenia, bipolar disorder, autism spectrum disorder, drug abuse, alcohol abuse, learning disability, mental retardation, obsessive-compulsive disorder, tic disorder, mood swings in first- and second-degree relatives.

Finally, parents completed an inventory of rage behaviors (available from authors), which asks what precipitates a child’s rage, what s/he does during a rage, the frequency and duration of rages, whether the behaviors were chronic or episodic, and age of onset This measure is used to quantify information about the outbursts used for the SMD diagnosis.

The designation of SMD (10) was made by (a) using the CASI (25) to recover the symptom of irritability occurring often or very often from parent and teacher endorsements on ODD, anxiety, mania, and depressionirritability items (since irritability must be pervasive); (b) the DSM IV “B” symptoms of mania; and (c) rages defined as responses to requests or denial of a wish met with verbally insulting, threatening, and/or physically destructive behavior that occurred at least weekly based on the parent-completed Rages Inventory. Although the SMD criteria “require” rages to occur three times a week, the relevant Rages Inventory choices were weekly or daily. There were no differences in rates of severe and chronic irritability in children whose parents endorsed explosive outbursts weekly (98.6%) or daily (100%), so data were combined.

Four child/adolescent psychiatry faculty members with 20-30 years of experience evaluating youth with severe psychopathology made best estimate diagnoses based on 3-hour interviews with parent and child using the CASI as a guide for systematic symptom review (2).

The assessments included reviews of school and other past information (e.g., report cards, prior evaluations) as was available. An extensive report that provides diagnostic justification is generated for the children.

The reliability diagnosis was made based on this report.

Kappa agreement between two psychiatrists for major 46

diagnostic categories (ADHD, any anxiety disorder, any depressive disorder, bipolar disorder, any pervasive developmental disorder) ranged from k=.78 (depression) to 1.0 (ADHD, bipolar disorder) (n=50).

To test our hypotheses, multinomial logistic regression was conducted to determine which factors are associated with children with parent- (PPR), teacher(TRR), and both-reported rages (BRR). The demographic, clinical information, best estimate diagnoses, and family history of psychopathology variables were entered into separate models predicting the specific informant variable (i.e., PRR, TRR and BRR) (Table 1). Additionally, we conducted a combined/adjusted model to determine the unique effects of these predictor variables while controlling for other variables. As such, predictor variables with at least one statistically significant bivariate association (p < .05) were simultaneously entered into the adjusted model (Table 2).

Results Clinic sample information. Of the 911 children and adolescents referred for evaluation, 431 (47.2%) had rage outbursts. Half had them by PRR (n=219, 50.8%), onefifth by TRR (n=87, 20.2%), and the remainder by BRR (n=125, 29.0%). The average age was 12.0 (3.6) years, the average IQ was 95.7 (14.5), and 114 (26.5%) were female. Sixty-one percent (n=210/350) of children with PRR had CBCL aggression subscale T-scores> 67; 73% (n = 156/212) of children with TRR had CBCL aggression T-scores >67.

Child Mania Rating Scale (CMRS). On the CMRS, 116 (33.7%) of children with any parent-report of rages (PRR + BRR) had scores > 20, with an average score of 16.9 (SD =8.2). Of those with any teacher-report of rages (TRR + BRR), 85 (40.1%) had CMRS scores > 20, with an average score of 17.6 (SD= 8.6). Teacher-rated CMRS scores when no rages were observed were very low (2.3%, M= 6.4, (SD=5.4); parent-rated CMRS scores when no rages were endorsed were similar (5.5%, M= 6.4, SD= 6.9).

Four symptom groups were rank-ordered on the CMRS: irritability (not counting the rages item), hyperactivity/increased energy, euphoria, and grandiosity.

When rages were endorsed, items describing irritability had the highest scores, followed by hyperactivity, euphoria, and grandiosity symptoms. Otherwise, hyperactivity items had the highest scores, followed by irritability, euphoria, and grandiosity.

Gabrielle A. Carlson and Margaret Dyson

Table 1. Comparison of demographic and diagnostic differences in outpatient sample comparing children with rages at home, in school, and in both settings and bivariate associations (unadjusted).

Parent Teacher Rages Rages N=219 N=87

Both N=125

Both Vs. Parent Only OR

Both Vs. Teacher Only

95% CI

X2

p

OR

95% CI

X2

p

OR

95% CI

X2

p

.88-1.03

1.25

.263

1.19

1.04-1.20 9.37

.002

Predictor Demographics Mean [SD} age at referral- 12.0(3.6)

12.8 (3.2)

11.4 (3.8)

10.9 (3.7) .85

.80-.91

22.30

.000 .96

Female 26.5%; n=114

29.7% 65

16.1% 14

28.0% 35

.92

.57-1.50

.11

.739 2.03 1.01-4.05

4.00 .045

2.20 1.16-4.18 5.82

.016

white 83.8%; n=361

89% 195

75.9% 66

80% 100

1.27

.66-2.46

8.23

.004 1.27

.52

.49

.023

Any infancy problems 44.7% 47.9% n=192 105

24.1% 21

53.2% 66

1.23

.79-1.92

.88

.348 3.57 1.95-6.54

.000 17.06 .000 2.90

1.66-5.06 13.94

toddler tantrums 49.5%; n=213

44.7% 98

33.3% 29

69.4% 86

2.79 1.75-4.44 18.72

.000 4.52 2.51-8.13

.069 25.42 .000 1.62

.96-2.72

3.31

Age of onset bypreschool-66.8% n=288

59.4% 62.1% 130 54

83.9% 104

3.56 2.06-6.16 20.53

.000 3.18 1.66-6.06 .663 12.32

.000 .983

.54-1.49

.190

Special Education55.3%; n=238

47.9% 104

66.7% 58

60.8% 76

1.70

.020 .78

.003 .76

.384 .456

.27-.77

8.79

ADHD + ODD27.1%; n=117

19.2% 42

26.4% 23

41.6% 52

3.00 1.84-4.89 19.37

.000 1.98 1.09-3.59

.660 5.09

.024 .66

.37-1.18

1.95

Any learning/ language disorder n=145

31.1% 68

46.0% 40

29.6% 37

.78

.58-1.57

.08

.779

.014 5.87

.015

.53

.32-.88

5.99

Any anxiety disorder-33.6%) n=145

40.6% 17.2% 89 15

32.8% 41

.71

2.07

.45-1.13 .713

.000 6.20

.013

3.29

1.77-6.10

14.23

Any Depression diagnosis-21.6% n=93

24.3% 53

11.5% 10

24.0% 30

.98

.59-1.64

.00

.983 2.43 1.12-5.28

.015

.025 2.47

1.19-5.12

5.95

Any SMD-32.5% n=140

26.0% 17.2% 57 15

54.4% 68

3.39 2.13-5.39

26.64

.000 5.73 2.73-11.06 .015

27.00 .000 1.69

.90-3.18

2.63

.66-2.46

.473

.27-.91

5.19

Clinical Information

1.09-2.66 5.42

.44-1.38

Best Estimate Dx

.49

.28-.87

2.34 1.20-4.58

5.03

Family History 1st and 2nd degree relatives Any ADHD-31.4% n=135

34.2% 75

20.7% 18

33.9% 42

.98

.618-1.57

.01

.944

1.96

1.04-3.72 4.29

.04

2.00

1.11-3.60

Any Depression 54.9%; n=236

63.0% 138

37.9% 33

52.4% 65

.65

.41-1.01

.65

.056

1.80

1.03-3.15

4.28

.04

2.79

1.67-4.66 15.37

.000

Any Alcoholism 47.0%;n=202

55.7% 122

34.5% 30

40.3% 50

.54

.34-.84

7.42

.006

1.28

.73-2.27

.74

.390

2.39

1.43-4.01

.001

Any â&#x20AC;&#x153;Mood Swingsâ&#x20AC;?

31.8% n=137

37.9% 83

19.5% 17

29.8% 37

.70

.44-1.12

2.25

.133

1.75

.91-.3.37

2.81

.094

2.51

1.38-4.56 9.18

.002

Any Bipolar 26.7%; n=115

32.0% 70

19.5% 17

22.6% 28

.62

.37-1.03

3.39

.006

1.20

.61-2.36

.28

.596

1.93

1.06-3.53 4.62

.031

# psychiatric disorders in family mean (SD) 4.3 (3.8)

5.1 (4.2)

2.8 (2.8)

3.8 (3.4) .91

.86-.97

8.77

.003

1.11

1.01-1.22

4.98

.026

1.22

1.12-1.33

.000

5.29

10.94

20.67

.021

47

Diagnostic Implications of Informant Disagreement About Rage Outbursts

Table 2. Predictor effects on parent and teacher concordance for rage outbursts-combined -variable model (adjusted) Combined-Variable Model Both Vs. Parent Only

Both Vs. Teacher Only

Parent Only Vs. Teacher Only

OR

95% CI

X

p

OR

95% CI

X

p

OR

95% CI

X2

p

Predictor Demographics Mean age at referral % female % white

.86 1.10 .73

.79-.93 .62-1.97 .35-1.53

13.12 .11 .71

.000 .737 .399

.98 2.12 1.09

.89-1.09 .97-4.64 .47-2.51

.13 3.51 .04

.721 .061 .841

1.15 1.92 1.50

1.05-1.26 .92-3.98 .70-3.20

8.38 3.05 1.09

.004 .081 .296

Clinical Information % infancy problems Age of onset in preschool toddler tantrums Special Education

1.12 1.15 1.63 1.62

.65-1.92 .48-2.75 .77-3.41 .95-2.76

.16 .10 1.65 3.11

.692 .749 .199 .078

2.32 .80 4.49 .59

1.14-4.70 .30-2.13 1.93-10.45 .29-1.17

5.38 .20 12.10 2.30

.020 .652 .001 .130

2.07 .69 2.76 .36

1.08-3.98 .31-1.56 1.28-5.96 .20-.67

4.83 .79 6.68 10.51

.028 .374 .010 .001

Best Estimate Diagnosis ADHD + ODD Any learning/language disorder Depression Any anxiety disorder % Severe Mood Dysregulation

3.33 .97 1.57 .90 3.34

1.86-5.91 .56-1.68 .83-2.96 .52-1.55 1.93-5.75

16.86 .01 1.95 .15 18.74

.000 .905 .163 .700 .000

2.47 .55 2.29 2.44 4.68

1.21-5.01 .29-1.06 .94-5.59 1.12-5.31 2.23-9.82

6.23 3.23 3.29 5.07 16.67

.013 .072 .070 .024 .000

.74 .57 1.46 2.72 1.40

.38-1.46 .32-1.01 .65-3.26 1.35-5.48 .68-2.88

.75 3.66 .84 7.85 .85

.386 .056 .360 .005 .356

Family History 1st and 2nd degree relatives Any ADHD Any Depression Any Alcoholism Any â&#x20AC;&#x153;Mood Swingsâ&#x20AC;?

Any Bipolar # psychiatric disorders in family

1.32 1.21 .76 1.01 .69 .88

.71-2.46 .63-2.30 .40-1.41 .50-2.04 .35-1.36 .77-1.01

.75 .33 .77 .00 1.17 3.51

.385 .567 .379 .980 .279 .061

1.52 1.22 .972 1.12 .52 .999

.67-3.45 .53-2.81 .43-2.19 .44-2.86 .21-1.30 .83-1.20

1.00 .216 .01 .05 1.95 .00

.317 .642 .946 .815 .163 .989

1.15 1.01 1.29 1.11 .76 1.13

.55-2.41 .48-2.13 .63-2.65 .48-2.57 .34-1.70 .96-1.33

.14 .00 .48 .06 .44 2.24

.707 .980 .490 .811 .506 .135

2

Children with rages: Demographic and clinical information. Based on the adjusted model (Table 2), of the 431 children with rages, those with PRR were significantly older than those with BRR or TRR. Children with TRR were more likely to be in special education compared to PRR. Half of the children with BRR had problems in infancy, and two-thirds had tantrums as toddlers with the onset of their behavior disorders by at least preschool.

Children with rages: Diagnosis information.

Approximately three-quarters of the sample of children with rages had any attention deficit-hyperactivity disorder diagnosis (n=329, 76.3%), but fewer children had ADHD without oppositional defiant disorder (ODD) (n=212, 49.2%). There were no significant differences across informant groups in rates (PRR=51.6%; TRR= 51.7%; BRR=43.2%, p=.283). ODD alone was rare (n=10, 2.3%). Combined ADHD plus ODD occurred disproportionally among children with BRR with odds ratios in the adjusted model of 3.33 (CI 1.86-5.91) and 2.47 (CI 1.21-5.01) compared to PRR and TRR, respectively.

Half the children with TRR had any learning/language disorders, significantly more often than other groups. This association did not hold in the adjusted 48

2

model largely due to high rates of comorbidity between learning/language disorders and ADHD in this sample (86%).

Anxiety disorders were the most common diagnoses for children with PRR and were least likely to occur in children with TRR. In the adjusted model, the odds ratio of an anxiety disorder diagnosis in any parentreport of rages (PRR or BRR) compared to TRR was between 2.34-3.29.

One-third of children appeared to have SMD with over half being children with BRR. In the adjusted model), odds ratios compared to children with PRR and TRR were 3.34 (CI 1.93-5.75) and 4.68 (CI -2.23-9.82), respectively.

Rates of actual bipolar disorder (mania, hypomania or bipolar not otherwise specified) were low (n=48, 11.2%) in this clinic sample (not shown). There was a trend for rates of bipolar disorder to be higher in children with BRR (16%), 10.6% of children with PRR, and 5.7% of children with TRR (X 2 , df =5.61 , p=0.061). Frequency of CMRS-Parent scores >20 in raging children with and without bipolar disorder were significantly different (43.8% Vs. 25.4%, X2=7.21, df=1, p=0.007). CMRS-Teacher scores >20 did not differ by

Gabrielle A. Carlson and Margaret Dyson

bipolar diagnosis (29.2% Vs. 21.5%, X2=1.46, ns).

Family history of psychiatric disorders. An overall mean of 4.3 (3.8) psychiatric conditions occurred in families of children with rages, with significantly higher rates in children with PRR compared to TRR or BRR. A family history of depression (54.9%), mood swings (37.9%), bipolar disorder (26.7%) and alcoholism (47%) was distributed preferentially to children with PRR. However, in the adjusted model, a family history of psychiatric disorder was not statistically significant for children with PRR. Discussion Children with rages comprised almost half of this outpatient clinic, similar to the 50-60% rates of conduct disorder prior to 1994 when it was used to diagnose overt aggression (30). Nevertheless, children with rages are not a homogeneous group and findings often depend on who is reporting the rage outbursts. Those with BRR are younger, have had their behavior problems longer, and have their psychopathology best explained not by ADHD or ODD alone, but by their combination. In comparison, ADHD and learning/language disorders were most often diagnosed in TRR. SMD had a robust association with who reported rages. However, this may be an artifact of how the diagnosis is made. That is, irritability has to be evident in more than one setting thus it is not surprising that rates were highest (54.4%) in children with BRR. Nevertheless, SMD would appear to fit as an explanatory condition for rages better than bipolar disorder which, in this outpatient sample, had a low base rate and accounted for little in the way of diagnosis. Indeed, rates of parent- or teacher-endorsed manic symptoms (CMRS >20) were quite high (35-40%, respectively) with irritability and hyperactivity/increased energy accounting for most of the score. This contrasts with Pavuluriâ&#x20AC;&#x2122;s bipolar sample where not only were the total CMRS-P scores higher (36.8), but elated mood and grandiosity scores were much higher than in this sample with rages. In sum, children with rages, who have ADHD symptoms and irritability/mood lability have serious mood problems, but they do not necessarily have mania even when there are multiple informants reporting rages.

Anxiety disorders were more likely in children with PRR vs. TRR and remained so in the adjusted model.

Anxiety disorders are under-emphasized as a condition in which children have severe outbursts. A partial expla-

nation for this being a parent-reported phenomenon may be that older, self-conscious children are more likely to regulate their emotions until they are in a familiar environment and fear embarrassing themselves in front of peers and teachers at school.

Teacher-reports reflected more youth in special education and with learning/language disorders. The finding did not hold in the adjusted model, suggesting that the oppositional/mood dysregulation behaviors were more compelling and that children were being placed in special education because of rages, not their learning problems. Many of the children were already receiving special accommodations. However, these accommodations may not be helping enough, resulting in psychiatric referral.

Family psychopathology was most prevalent in children with PRR with an average of 5 (4.2) conditions.

This finding did not hold in the adjusted model as a predictor. Nevertheless, mood instability and alcoholrelated problems occurred at significantly high rates in this sample of children with PRR and remains clinically relevant.

This study has several limitations. First, most of the information was based on parent and teacher questionnaires, which are limited in accuracy by memory (though no more so than interview-gathered information).

Family history was obtained from the family history form and reflects what the parent believes or is told, not necessarily vetted through professional re-diagnosis. Family members, therefore, may or may not have the conditions which the primary informant endorses.

The Rages Inventory that has been used in the Stony Brook inpatient and outpatient departments for five years was developed because none of the existing rating scales allows one to establish outburst precipitants, frequency, duration, and specific behaviors. It is not designed to rate severity but rather the composition of the outbursts.

Finally, the diagnoses used in this study are best estimate diagnoses, not diagnoses from the K-SADS-PL (29). It has been our experience after many years of using the K-SADS (27, 28) that using the CASI to guide the interview is less frustrating for the patients and more informative for the clinicians who needs to understand the patient as well as make a diagnosis. Additionally, using the same system to interview the child and obtain ratings from teachers provides a more comprehensive understanding of the child. Nonetheless, we are aware that research mandates advocate the use of structured interviews (31). Thus, we used the K-SADS if screening 49

Diagnostic Implications of Informant Disagreement About Rage Outbursts

information suggested possible bipolar disorder.

The clinical relevance of our findings is noteworthy.

Children who have rage outbursts are not a homogenous group diagnostically (1, 2). Moreover, who reports on the outbursts appears to have some diagnostic significance. Children with BRR are the youngest, have had problems with aggression since toddlerhood, meet criteria for combined ADHD and ODD, or possibly a new diagnostic condition, SMD. Regarding implications for intervention, these findings suggest that BRR will not only require treatment for ADHD but more comprehensive, novel treatments.

Children with BRR are perhaps more likely to have bipolar disorder than those with rages in only one setting.

However, bipolar disorder, by virtue of its relative rarity, does not account for the majority of children with rages, suggesting that medicating only with a “mood stabilizer” like lithium or an anticonvulsant is likely to be both inadequate and misguided. Indeed, circumstantial data substantiates this (32, 33). Treatment aimed at ADHD and aggression (15, 34) demonstrates some efficacy, but even those treatments are not as robust as what is needed.

For children with PRR, anxiety disorders should be assessed and ruled out. Children with TRR are more likely to have learning/language disorders, suggesting it is important to be aware of potential educational difficulties involved.

In conclusion, rage outbursts are a complicated phenomenon. It is important to be mindful of informant source when collecting information and that discrepant information is a clue to meaningful diagnostic and treatment implications. Although there are instances when bipolar disorder may underlie the rage behaviors, other conditions do so more frequently.

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18. De Los Reyes A, Henry DB, Tolan PT, Wakschlag LS. Linking informant discrepancies to observed variations in young children’s disruptive behavior. J Abnorm Child Psychol 2009;37:637-652.

19. Carlson GA, Blader JC. Diagnostic implications of Informant disagreement for manic symptoms. J Child Adolesc Psychopharmacology 2011; 21:399-405.

20. Pavuluri MN, Henry DB, Devineni B, Carbray JA, Birmaher B. Child mania rating scale: Development, reliability, and validity. J Am Acad Child Adolesc Psychiatry 2006; 45:550-560.

21. Mannuzza S, Klein RG, Moulton JL 3rd. Young adult outcome of children with “situational” hyperactivity: A prospective, controlled follow-up study. J Abnorm Child Psychol 2002;30:191-198.

22. Carlson GA. Who are the children with severe mood dysregulation, a.k.a. “rages”? Am J Psychiatry 2007;164:1140-1142.

23. Achenbach TM. Manual for the child behavior checklist 4-18 profile.

Burlington:University of Vermont Dept Psychiatry, 1991.

24. Achenbach TM. Manual for the teacher report form. Burlington: University of Vermont, Dept Psychiatry, 1991.

25. Sprafkin J, Gadow KD, Salisbury H, Schneider J, Loney J. Further evidence of reliability and validity of the child symptom inventory-4: Parent checklist in clinically referred boys. J Clin Child Adolesc Psychol 2002;31:513-524.

26. Lavigne JV, Cromley T, Sprafkin J, Gadow KD. The child and adolescent symptom inventory-progress monitor: A brief diagnostic and statistical manual of mental disorders, 4th edition - referenced parent-report scale for children and adolescents. J Child Adolesc Psychopharmacol 2009;19:241-252.

27. Grayson P, Carlson GA. The utility of a DSM-III-R-based checklist

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in screening child psychiatric patients. J Am Acad Child Adolesc Psychiatry 1991;30:669-673.

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29. Kaufman J, Birmaher B, Brent D, Rao U, Flynn C, Moreci P, Williamson D, Ryan N. Schedule for affective disorders and schizophrenia for school-age children - present and lifetime version (K-SADS-PL): Initial reliability and validity data. J Am Acad Child Adolesc Psychiatry 1997; 36:980-988.

30. Connor DF. Aggression and antisocial behavior in children and adolescents. New York: Guilford Press, 2002: p. 43.

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Child Adolesc Psychiatry 2001; 40:871-878.

32. Wagner KD, Redden L, Kowatch RA, Wilens TE, Segal S, Chang K, Wozniak P, Vigna NV, Abi-Saab W, Saltarelli M. A double-blind, randomized, placebo-controlled trial of divalproex extended-release in the treatment of bipolar disorder in children and adolescents. J Am Acad Child Adolesc Psychiatry 2009;48:519-532.

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34. Blader JC, Schooler NR, Jensen PS, Pliszka SR, Kafantaris V. Adjunctive divalproex versus placebo for children with ADHD and aggression refractory to stimulant monotherapy. Am J Psychiatry 2009;166:1392-1401.

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Isr J Psychiatry Relat Sci - Vol. 49 - No 1 (2012)

Beyond dogma: from diagnostic controversies to data about pediatric bipolar disorder and children with chronic irritability and mood dysregulation Daniel P. Dickstein, MD,1 and Ellen Leibenluft, MD2 1

Pediatric Mood, Imaging, & NeuroDevelopment Program, Bradley Hospital, Alpert Medical School of Brown University, East Providence, Rhode Island, U.S.A. 2 Section on Bipolar Spectrum Disorders, Emotion and Development Branch, National Institute of Mental Health (NIMH), Bethesda, Maryland, U.S.A.

ABSTRACT From the mid-1990s through the present, studies have demonstrated a significant rise in the numbers of children and adolescents diagnosed with bipolar disorder (BD). Why is this? The present manuscript reviews several possibilities, most notably ambiguity in the diagnostic criteria for mania and how they may apply to children with functionally-impairing irritability.

Furthermore, we discuss ongoing phenomenological and affective neuroscience research approaches to address those children most on the fringes of our current psychiatric nosology. In summary, these studies suggest that BD youths may be distinguished on some measures from those with chronic irritability and severe mood dysregulation, although the two groups also have some shared deficits.

INTRODUCTION Pediatric bipolar disorder (BD) continues to be among the most controversial of all psychiatric disorders affecting children and adolescents today. In particular, while pediatric BD was once thought to be exceedingly rare, recent studies demonstrate a marked increase in numbers of children and adolescents receiving the diagnosis of BD. For example, the percentage of children and adolescents discharged from psychiatric hospitals in the U.S. with a diagnosis of BD has surged from less than 10% in the mid-

1990s to more than 20% in the mid-2000s (1). This rise is not only an inpatient phenomenon as another study demonstrated a forty-fold rise in the incidence of outpatient visits assigned the diagnosis of BD during a similar period, from 25/100,000 in 1993-1994 to 1003/100,000 in 20022003 (2). Moreover, this increase is not just occurring in the U.S., but in other countries as well. For example, rates of under 19 year olds admitted to German psychiatric hospitals increased 68.5% from 1.13/100,000 in 2000 to 1.91/100,000 in 2007, an increase which exceeded the general trend for mental health disorder admissions (3). It remains unclear if these trends represent increased awareness of a serious problem (akin to recognition of the prevalence and impact of childhood depression in the 1980s), a non-specific rise in children and adolescents diagnosed with psychopathology (1), or misdiagnosis.

The purpose of the manuscript is to explore the controversy surrounding pediatric BD by: (a) discussing factors related to why more children are being diagnosed with BD, including new interpretations of diagnostic criteria; (b) reviewing research approaches to advance our phenomenological and biological understanding of irritability in children; (c) presenting potential noslogical changes in DSM-V related to these research findings that will likely impact how BD is diagnosed, especially in children and adolescents.

FACTORS RELATED TO THE RISE OF PEDIATRIC BD The controversy about pediatric BD centers not just on the observation that more children are being diagnosed with BD, but also on the question of why? While we

Address for Correspondence: Daniel P. Dickstein, MD, PediMIND Program, Bradley Hospital, 1011 Veterans Memorial Parkway, East Providence RI 02915, U.S.A. â&#x20AC;&#x2020; Daniel_Dickstein@Brown.edu

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really do not know the cause for this rise, and likely have no way of knowing definitively, there are several possible explanations.

One factor that may have contributed to the increased rates in the diagnosis of BD in children is ambiguity in the DSM-IV criteria for a manic episode. According to DSM-IV, a manic episode consists of (“A” criterion) “a distinct period of abnormally and persistently elevated, expansive or irritable mood,” lasting at least 1 week (or any duration if hospitalization is necessary). This period must be accompanied by at least three of the following “B” symptoms (at least four if the mood was only irritable): 1. inflated self-esteem or grandiosity, 2. decreased need for sleep (e.g., feels rested after only 3 hours of sleep), 3. more talkative than usual or pressure to keep talking, 4. flight of ideas or subjective experience that thoughts are racing, 5. distractibility (i.e., attention too easily drawn to unimportant or irrelevant external stimuli), 6. increase in goal-directed activity (at work, at school, or sexually) or psychomotor agitation, or 7. excessive involvement in pleasurable activities that have a high potential for painful consequences (e.g., engaging in unrestrained buying sprees or sexual indiscretions). Three aspects of these criteria make establishing the diagnosis of BD difficult, especially in children: (a) duration of a manic episode, (b) irritability vs. euphoria in defining a manic episode, and (c) overlap with other illnesses, including attention deficit hyperactivity disorder (ADHD).

First, with respect to the DSM-IV criterion specifying the minimum duration of a manic episode, the key problem is insufficient detail about the temporal characteristics of the manic symptoms. Notably, these characteristics are much more poorly specified for manic than for depressive episodes. Specifically, the DSM-IV “A” criteria for a major depressive episode requires that the depressive symptoms last “most of the day, nearly every day.” In contrast, the “A” criterion for a manic episode requires only “a distinct period” lasting 1 week. How much of that week (or more) must the mood change persist? Should it be most of the day every day, or parts of days? If parts of days, then how do we determine if a child with several irritable periods in a single week, with resultant impairment, is having a manic episode, or instead a series of temper tantrums that might be part of typical development? What is the shortest duration of these symptoms that would be considered a manic episode versus a developmentally appropriate mood fluctuation? This nosological inconsistency has led to divergent views about the course of BD, most prominently – but not exclusively – expressed by those studying chil-

dren, with some adhering to the classical view that pediatric BD is an episodic illness, with sustained periods (days to weeks) of mania, depression, and euthymia (normal mood) (4, 5), while others maintain that pediatric BD is a chronic illness, with fluctuations between all three mood states occurring as rapidly as within a single day (known by some as “ultradian cycling”) (6-11). Both views are held by clinicians working with adults and children with BD, although it is possible such non-DSM terms, including ultradian cycling, have created more confusion rather than less. In a related manner, data from the BRIDGE study (Bipolar Disorders: Improving Diagnosis, Guidance, and Education) suggest that it may be more appropriate to define manic episodes on a continuum, rather than categorically defining who does and who does not have BD. Specifically, they found that 47% (2,647/5,635) of adults with unipolar major depression episode met criteria for the bipolar specifier (i.e., short-lived manic episodes with full “B” symptoms), with similar rates of external validators of BD, such as family history of mania/hypomania and multiple prior mood episodes (11). However, it should be noted that the BRIDGE study’s findings are somewhat limited due to lack of reliability among clinician raters and the lack of direct interviews of family members to validate patient reports of family history. Nevertheless, the temporal duration and fluctuation of mania is very much the subject of ongoing research in both children and adults.

The definition of an episode is also germane to the common problem of sorting out what is a temper tantrum, or anger outburst, and what is irritable mania. One possible solution is reaffirming the DSM requirement that a manic episode requires the combination of mood change (elevated, expansive, or irritable) plus sufficient “B” symptoms and resultant functional impairment, rather than just mood symptoms or just “B” symptoms alone. However, this is only a partial solution given the abovementioned issues related to the duration of the mood-defining symptoms that allow for interpretation, rather than providing a clear-cut rule.

The second aspect of the DSM-IV mania criteria that often leads to confusion is whether the “abnormally and persistently” altered mood is elevated/expansive (known commonly as “euphoria”) or irritable. Although euphoric mood is uniquely part of mania, the presence of euphoria is not necessary to diagnose BD because irritable mood can also qualify for a manic episode. These are differentially weighted in DSM-IV, so that the patient must have three associated “B” symptoms if the mood is primarily euphoric, and four if the mood is primarily irritable, 53

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to qualify for a manic episode. Moreover, irritability is not specific to mania. Instead, it is an explicit diagnostic criterion for several DSM-IV disorders, such as generalized anxiety disorder, post-traumatic stress disorder, and child-specific modified criteria for a major depressive episode. In addition, irritability is implied by criteria for oppositional defiant disorder (ODD), although the word irritability is not used explicitly. Furthermore, irritability is an associated symptom in pervasive developmental delay spectrum disorders (autism, Asperger’s) and ADHD (12). Further complicating matters is the fact that DSM-IV does not provide (a) a clear definition of irritability for any of these disorders, (b) developmentally informed examples of how these symptoms differ among these disorders – i.e., in children, adolescents, young adults, and adults; or (c) examples of how irritability associated with mania is different from that present in typical-development – i.e., a temper tantrum. Thus, the same functionally-impairing irritability might be called mania by some clinicians and not by others, depending on how they interpret the “A” and “B” criteria for mania.

One final factor adding to the confusion is the fact that some have suggested that euphoria is not necessary for establishing a diagnosis of BD (13).

The third DSM-IV related factor leading to potential confusion in the diagnosis of pediatric mania is the diagnostic overlap between the criteria for a manic episode and those for ADHD combined type. Although both mania and ADHD can be characterized by irritability, it is important to note that BD is classified as an episodic mood disorder, whereas ADHD is a chronic behavioral disorder.

Moreover, some of the “B” symptoms are uniquely found in mania, such as hypersexuality, while other mania “B” symptoms overlap with the diagnostic criteria for ADHD (14, 15). For example, distractibility is an explicit diagnostic criterion for both mania and ADHD. Moreover, while the criterion wording is different, other symptoms of ADHD and mania appear to overlap. For example, how does one distinguish psychomotor agitation in mania from hyperactivity in ADHD? Pressured speech in mania from talking excessively, blurting out answers, and not playing quietly (ADHD)? Flight of ideas in mania from interrupting, not waiting their turn, and being “on the go” in ADHD? Thus, these diagnostic criteria often leave clinicians struggling to determine if a child has BD, ADHD, or the combination.

Beyond DSM noslogical issues, some suggest that that the increased rates of the BD diagnosis in youths is the logical extension of phenomenological studies of bipo54

lar adults conducted during the 1980s-1990s, in which many patients reported that their first episode of mania occurred when they were a child or adolescent (16-18).

Perhaps the most widely circulated example of this was Kay Redfield Jamison’s An Unquiet Mind (published 1995), in which Dr. Jamison, a prominent researcher working on BD and related conditions, disclosed her own experience with BD, including the fact that her first manic episode occurred when she was a senior in high school (19). Thus, the increase in pediatric BD may represent greater awareness that serious psychopathology may present first in childhood, akin to greater acceptance in the 1980s that major depressive disorder can, and often does, present in childhood.

A third factor which may play a role in the increased numbers of children diagnosed with BD is the fact that atypical anti-psychotic medications were marketed in the 1990s to both physicians and consumers as “mood stabilizers.” Specifically, the suggestion is that clinicians may have been more inclined to diagnose children presenting with moodiness and irritability as having BD, despite not fully meeting DSM-IV criteria for a manic episode 12, because atypical anti-psychotic agents were marketed as “mood stabilizers” with few side effects and without the requirement for blood draws (unlike older agents such as lithium or valproate). In support of this position, researchers have expressed concern that the term “mood stabilizer” lacks the pharmacological precision of other medication classes, such as anti-depressant or anti-anxiety medications (21), and that such imprecision invited their use in people who are “moody” but did not meet criteria for mania. Further support comes from Olfson et al., who found that prescriptions for atypical anti-psychotic medications for children rose six-fold from 1993-2002 (roughly the same period as the rise in children and adolescents diagnosed with BD), from 201,000 to 1,224,000 prescriptions (20). Moreover, Olfson et al. note that this rise remained in males despite controlling for other disorders which might warrant treatment with atypical anti-psychotic medications, including tic, disruptive behavior, and autism-spectrum disorders.

Nevertheless, such associational data certainly cannot demonstrate causality. With respect to Olfson’s data, it remains unclear if the six-fold rise in prescriptions for atypical anti-psychotic medication for children was due to better recognition, as had occurred in pediatric depression, or an over- or misdiagnosis of BD. Indeed, arguing against a possible link between the use of atypical anti-psychotic agents and rising rates of pediatric BD,

Daniel P. Dickstein and Ellen Leibenluft

Pringsheim et al. found a 114% increase in anti-psychotic prescriptions for Canadian children (from 308,490 in 2005 to 661,300 in 2009), but most of these were for children with ADHD (17%). Such prescriptions for ADHD youth showed a consistent yearly increase. In contrast, prescriptions for youth with mood disorders represented 16% of atypical anti-psychotic prescriptions from 20052009, and yearly usage fluctuated up and down (21).

In sum, some speculate about a possible link between atypical anti-psychotic medication being marketed as “mood stabilizers” and the rise in children and adolescents diagnosed with BD, but the data are far from clear.

However, it is clear that these medications are now FDA approved for the treatment of BD manic and mixed episodes in children and adolescents as well as the treatment of irritability associated with Autism Spectrum Disorders (22).

It is also clear that there is rising concern at all levels-among parents, clinicians, researchers, the lay press, and government officials-about the growing numbers of children receiving these medications and about their now known side-effects, including metabolic syndrome and diabetes.

RESEARCH TO MOVE THE FIELD BEYOND CONTROVERSY The rise in numbers of youth diagnosed with BD is likely to be multi-factorial. Therefore, it is important to focus on research strategies employed to move the field beyond dogma to data. This is all the more important to educate clinicians about the latest research, as they work to help families daily.

One such strategy is to clarify potential DSM noslogical ambiguity by studying rigorously the phenomenology of pediatric BD, compared to children whose primary DSM psychiatric disorder is often comorbid to BD. For example, Geller et al. conducted a multi-group study to address concerns about diagnostic overlap between pediatric BD and ADHD. She compared BD (N=93), ADHD (N=81), and typically-developing control (N=94) children and adolescents, and found that five symptoms significantly distinguished the BD from ADHD youths and typicallydeveloping controls: 1. elation, 2. grandiosity, 3. flight of ideas/racing thoughts, 4. decreased need for sleep, and 5. hypersexuality. Importantly, a companion article shared examples of how these symptoms would present in pediatric and adult patients with mania in comparison to how they would relate to typical development (23, 24).

Besides multi-group studies using DSM-defined groups, others have operationalized research-oriented

criteria for sub-populations to advance our understanding of whether pediatric BD is characterized by mood episodes or by chronic irritability (and related issues of how to define an episode and the inter-episode illness burden).

Such criteria have also advanced our understanding of episodes of elevated/expansive versus irritable mood in pediatric BD. Among these approaches, we would like to highlight two: 1. Leibenluft et al.’s criteria for severe mood dysregulation (SMD) and 2. the Course and Outcome of Bipolar Youth (COBY) study’s definition of bipolar disorder not otherwise specified (BD-NOS). Both approaches were selected because their goal is to advance our understanding of children on the edges of our diagnostic system who are often “diagnostically homeless,” in that simply diagnosing them with a behavioral disorder (e.g., ADHD, ODD, or conduct disorder) does not capture the perturbation in mood noted by patients, their parents, and the clinicians working with them (25).

Severe Mood Dysregulation (SMD) vs. NarrowPhenotype Bipolar Disorder (NP-BD)

Leibenluft et al. suggested a system of putative BD phenotypes that differ in the presence of 1. euphoria vs. irritability and 2. episodic vs. chronic course (5, 26). The rationale for this approach was to facilitate pathophysiological and longitudinal research for these clinically distinct presentations, each of which may or may not ultimately represent a bipolar spectrum disorder. The most clearly “bipolar” of these presentations was defined as “narrow-phenotype pediatric BD” (NP-BD) and included children with a history of at least one episode meeting DSM-IV duration criteria of mania (seven or more days) or hypomania (4-7 days plus at least 1 major depressive episode), including functionally impairing elevated or expansive mood (euphoria) (12).

Juxtaposed to NP-BD youths, Leibenluft suggested criteria for “severe mood dysregulation” (SMD) to capture children suffering from chronic (rather than episodic) irritability (rather than euphoria) (Table 1).

The SMD criteria have three central features: 1. abnormal baseline mood (anger or sadness), 2. chronic/nonepisodic irritability, and 3. ADHD-like symptoms of hyperarousal that can be confounded with some of the “B” symptoms of mania. Unlike other DSM-IV conditions where irritability is a symptom that is not defined, SMD criteria draw on affective neuroscience research to define it as “markedly increased reactivity to negative emotional stimuli manifest verbally or behaviorally.”

Exclusion criteria specify that these SMD subjects 55

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Table 1. Severe Mood Dysregulation (SMD) Diagnostic Criteria Inclusion criteria 1. Age 7-17 years, with symptom onset before age 12.

2. Abnormal mood (specifically, anger or sadness) present at least ½ of the day most days and of sufficient severity to be noticeable by others (e.g., parents, teachers, or peers).

3. Hyperarousal, as defined by >3: insomnia, agitation, distractibility, racing thoughts or flight of ideas, pressured speech, or intrusiveness.

4. Compared to peers, the child exhibits markedly increased reactivity to negative emotional stimuli manifest verbally or behaviorally-i.e., temper tantrums out of proportion to the inciting event and/or child’s developmental stageoccurring >3 times/week during past 4 weeks.

5. Symptoms are present for >12 months without >2 months symptom-free.

6. Symptoms are severe in >1 setting and mild in a 2nd setting.

Exclusion Criteria 1. Child has any “cardinal” BD symptoms: elevated/expansive mood, grandiosity, or episodically decreased need for sleep.

2. Distinct episodes >4 days.

3. Individual meets diagnostic criteria for schizophrenia, schizophreniform disorder, schizoaffective illness, pervasive developmental disorder, or post-traumatic stress disorder.

4. Individual meets criteria for substance use disorder in the past 3 months.

5. IQ<80.

6. Symptoms are direct physiological effect of drug of abuse or general medical/neurological condition.

cannot demonstrate cardinal features of mania, including elevated/expansive mood, grandiosity, or episodically decreased need for sleep. Unlike children with ADHD, SMD youths must have an abnormal baseline mood, whereas irritability is an associated, but not required, feature of ADHD. From the outset, Leibenluft et al. stated that it was unclear whether children with SMD have a developmental presentation of BD, an illness along the depressive spectrum, or another disorder.

Over the past eight years, Leibenluft’s group at the National Institute of Mental Health Division of Intramural Research Programs has used the SMD criteria to recruit and study over 150 SMD youths (and over 150 NP-BD youths). Both SMD and NP-BD youths are similarly impaired as indicated by Children’s Global Assessment Scale (CGAS) rating at initial evaluation (47.4+9.0 for SMD, 51.1+10.8 for NP-BD – both considered “moderate” impairment) as well as similar number of psychiatric medications (1.37+1.45 for SMD, 2.40+1.70 for NP-BD) and prior psychiatric hospitalizations (40.4% hospitalized at least once for SMD, 63% for NP-BD). With respect to family history, data indicate that parents of NP-BD youths 56

were significantly more likely to have BD themselves than were parents of SMD youths (27).

To begin to address the question of whether SMD youths develop manic episodes as adults, Brotman et al. conducted a post-hoc analysis of the Great Smokey Mountain Study (GSMS), a longitudinal, population-based community survey of children and adolescents in North Carolina that started in 1992. For this study, SMD criteria were extracted from the Child and Adolescent Psychiatric Assessment (CAPA) used by the GSMS because SMD criteria did not exist when the GSMS started. Among 1,420 children participating in the first wave of the GSMS, the lifetime prevalence of SMD in children 9-19 years old was 3.3%. Most of these children meeting SMD criteria (67.7%) had an Axis I diagnosis, most commonly ADHD (26.9%), conduct disorder (25.9%), and/or oppositional defiant disorder (24.5%). In young adulthood (mean age 18.3+2.1 years), those who met SMD criteria during the first wave (mean age 10.6+1.4 years) were significantly more likely to be diagnosed with a depressive disorder (OR 7.2, CI 1.3-38.8, p=0.02) than were youths who never met SMD criteria (28). This suggests that SMD in childhood is associated with unipolar depression, rather than BD, later in life. Of note, this finding aligns with another study using data from the Children in the Community Study of 776 youths evaluated longitudinally that showed youths with chronic irritability predicted increased risk for major depression, generalized anxiety disorder, and dysthymia in young adulthood (29).

Using prospectively gathered longitudinal data from the NIMH sample, only one of 84 SMD subjects (1.2%) experienced a (hypo)manic or mixed episode during a median of 28.7 months of follow up. In contrast, 58 of 93 NP-BD participants (62.4%) experienced such a (hypo) manic or mixed episode (30). This suggests that SMD youths are unlikely to develop manic or mixed episodes.

Moreover, this work should be considered preliminary, as these participants continue to be followed into adulthood and this a somewhat small non-epidemiological sample.

Nevertheless, it is consistent with others’ longitudinal studies confirming the association between irritability (in many cases in the form of ODD) and subsequent unipolar depression, rather than bipolar disorder (31-33).

Brain/Behavior Interactions Underlying SMD vs. NP-BD

Beyond phenomenology, it is important to understand how the neurobiology mediating the symptoms of SMD or NP-BD may be similar or different. Towards that end, studies using affective neuroscience techniques, includ-

Daniel P. Dickstein and Ellen Leibenluft

ing out-of-scanner computerized behavioral tasks, task-dependent functional magnetic resonance imaging (fMRI), psychophysiology techniques including the measurement of evoked response potentials (ERP), and magnetoencephalography have begun to shed light on these issues. Taken as a whole, these studies have begun to show brain/behavioral alterations in SMD and NP-BD youths in cognitive processes including emotional face processing, frustration tolerance, and cognitive flexibility.

Emotional face processing is an important psychological process whose study can advance our understanding of how the pathopshyiology of SMD and NP-BD youths may be similar or different. Studies indicate that our brains are hard-wired to respond to human faces from birth (34-37). The face serves as our canvas to display our emotional state to others, and recognition of others’ emotional state based on their facial display are important parts of affect regulation (38, 39). Studies indicate that children with NP-BD make significantly more errors categorizing emotional faces than both typically developing children and those with anxiety disorders (40, 41).

Similar deficits have been identified in youths who are at elevated risk for developing BD because they have a firstdegree relative with BD (42). FMRI studies have shown that youths with NP-BD have altered prefrontal cortex– amygdala–striatal neural activation compared with typically developing children when viewing faces, including pictures of faces with happy, angry, or neutral emotions (43-45). With respect to SMD youths, both SMD and NP-BD participants required more intense facial displays than controls to correctly identify disgusted, surprised, fearful, and happy faces (46). However, two recent fMRI studies suggest that the neural underpinnings of face processing differ between SMD and NP-BD youths. In the first, when rating their subjective fear of neutral faces, SMD participants had significantly decreased amygdala neural activation vs. those with either NP-BD, ADHD, or typically-developing controls (47). In the second, using an implicit face-emotion processing task, NP-BD participants had significantly less amygdala activity in response to angry vs. neutral faces than either SMD or control participants (48). Taken as a whole, these data suggest that different neural mechanisms mediate face processing deficits in children and adolescents meeting either SMD or NP-BD criteria. These differences between SMD and NP-BD youths in the brain/behavior interactions underlying face processing suggest that the neurobiology underlying chronic irritability may differ from that of episodic euphoria.

Another way to advance what is known about irritability in pediatric BD is to administer computerized behavioral tasks that induce frustration via rigged feedback.

From an affective neuroscience perspective, irritability can be defined as increased reactivity to negative emotional stimuli, such as frustration due to the inability to achieve a goal (26). One example of a frustration-inducing paradigm is a study by Rich et al. that paired a computerized attention task, known as the affective Posner task, with EEG recordings that allowed the measurement of ERPs (49). In this task, participants viewed a fixation cross, followed by a cue presented in one of three horizontal boxes, followed by a stimulus presented on either the left or the right side. Participants were asked to indicate which side the stimulus was on. During the first task, feedback consisted of “good job” for correct responses and “incorrect” for incorrect responses. The second task added a monetary contingency, with correct responses earning ten cents and incorrect or no responses losing ten cents. The third task added frustration to these contingencies, with 56% of trials involving correct responses receiving incorrect feedback (i.e., correct response resulting in “Wrong!

Lose 10 cents!”). During the frustration condition, NP-BD youths (N=35) had lower P3 amplitude than either SMD (N=21) or typically-developing controls (N=26), reflecting impairments in executive attention in the BD group. In contrast, regardless of condition, SMD youths had lower N1 amplitude than either NP-BD or control participants, reflecting impairments in the initial stage of attention. This suggests that the pathophysiology of irritability may differ between SMD and NP-BD youths (49); in both groups, there is attentional impairment, but the precise nature of that impairment differs between groups.

Rich et al. recently used this affective Posner paradigm and magnetoencephalography (MEG) to further advance our understanding of the pathophysiology of frustration in SMD and NP-BD youths. MEG allows neural events, such as those mediating the response to frustration in the affective Posner task, to be identified with far greater time precision than task-dependent fMRI. To do this, MEG pairs the great temporal resolution of electroencephalography (EEG) with spatial resolution of structural MRI. This study compared NP-BD, SMD, and control participants (20 in each group) during performance of the affective Posner task. Following negative feedback, NP-BD participants had greater superior frontal gyrus activation and decreased insula activation than SMD and controls, while SMD participants had greater anterior cingulate cortex and medial frontal gyrus activation than controls.

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In addition, SMD youths had greater self-reported arousal following negative feedback than either controls or NP-BD participants (50). These data showing that SMD youths have neural and self-reported alterations to negative feedback compared to controls suggest that these SMD youths with functionally-disabling chronic irritability have biological alterations predisposing to frustration and irritability. The fact that BD youths differ from both SMD and control participants in their neural response to negative feedback further supports the position that children with episodic euphoria and irritability are not the same biologically as children with chronic irritability.

Yet a third psychological process that can be used to probe the brain/behavior interactions underlying irritability in children and adolescents is cognitive flexibility, which refers to the ability to adapt one’s thinking and behavior in response to changing rewards (51). Cognitive flexibility is relevant to BD and SMD because both conditions may involve functionally-impairing irritability. In their daily life, children with less cognitive flexibility may be less able to adapt to social feedback and rewards, such as praise or reprimand from teachers, parents or peers.

In turn, they may experience frustration; as noted above, frustration can be defined from an affective neuroscience perspective as the emotional state that occurs when an individual performs an action in the expectation of a reward but does not receive a reward. Such frequent frustration may lead to functionally impairing irritability at home or school (49, 52).

Cognitive flexibility can be studied in the lab using computerized reversal learning tasks, whereby participants use trial-and-error, learning to determine which of two stimuli is initially rewarded, and then adapt their responses when the previously rewarded stimulus is now punished. Studies have shown that both NP-BD and SMD youths have impaired cognitive flexibility on reversal learning tasks, though these deficits may be more consistent among NP-BD than SMD youths (53, 54). Furthermore, a recent fMRI study showed that both SMD and NP-BD participants had similar decreases in caudate activation, vs. controls, during reversal errors, but that SMD participants had decreases in inferior frontal gyrus activation vs. both NP-BD and controls (55). Taken as a whole, this suggests that children with chronic irritability and those with episodic euphoria may both have behavioral deficits in cognitive flexibility, and that the mediating neurocircuitry is similar between groups but not identical. Ongoing studies are evaluating the specificity of these alterations compared to youths with disruptive behavior disorders, such 58

as ADHD, or anxiety. Ultimately, such work may suggest novel treatment targets, including both medications and psychotherapies to address specific brain/behavior alterations in cognitive flexibility and adaptability.

Work is ongoing to flesh out similarities and differences among children and adolescents meeting SMD and NP-BD criteria on these and other affective neuroscience constructs. Ultimately, such pathophysiological alterations may suggest targets for potential treatment, including medications, psychotherapies, and even cognitive remediation (i.e., using special computer games to build cognitive/emotional skills and thus “retrain the brain” and improve a child’s function).

Course and Outcome of Bipolar Illness in Youth Study (COBY)

Another important approach to addressing the controversy about pediatric BD was taken by the Course and Outcome of Bipolar Illness in Youth study (COBY). Rather than creating substantially new criteria, COBY sought to determine how children with prolonged episodes of mania or hypomania fitting DSM-IV criteria were different or similar from those with more short-lived episodes.

To address this goal, the COBY study team, including sites at the University of Pittsburgh, Brown University, and the University of California Los Angeles started a multi-site longitudinal phenomenology study with support from the National Institute of Mental Health. They sought to enroll and follow longitudinally children meeting DSM-IV criteria for type I BD (BD-I; at least one manic episode lasting seven or more days) or type II BD (BD-II; at least one hypomanic episode lasting four to seven days plus at least one major depressive episode).

However, unlike other studies that excluded children whose symptoms of irritability and/or euphoria were sub-syndromal (i.e., not meeting DSM-IV definition for either BD-I or -II), COBY also enrolled children with “BD not otherwise specified” (BD-NOS). To standardize the BD-NOS group, the COBY study operationalized BD-NOS criteria that were more specific than DSM-IV’s definition (i.e., those “who do not meet criteria for a specific type of BD”) (4). COBY BD-NOS criteria consisted of: A. clinically relevant BD symptoms of euphoric or irritable mood lasting a minimum of 4 hours within a 24-hour period, B. at least 2 “B” symptoms if the mood was primarily euphoric (3 if primarily irritable), and C. at least 4 cumulative lifetime days meeting these criteria.

Despite much controversy about how such BD-NOS children with frequent sub-syndromal manic symptoms

Daniel P. Dickstein and Ellen Leibenluft

would compare to more classic BD sub-types, thus far, COBY data have shown striking phenomenological similarities between those with BD-I, BD-II, and BD-NOS. At intake, COBY BD-I (N=255), BD-II (N=30), and BD-NOS (N=153) participants do not differ in age of onset of BD symptoms, duration of illness, lifetime rates of comorbid psychiatric disorders, suicidal ideation, or types of manic symptoms present during the most serious lifetime episode. In fact, elevated and/or expansive mood was found in 91.8% of BD-I and 81.9% of BD-NOS participants.

However, BD-I participants had significantly more severe manic symptoms, greater overall functional impairment, and higher rates of psychiatric hospitalization, psychosis, and suicide attempts than those with BD-NOS (56).

After 4 years of longitudinal follow up, COBY study data indicate no significant between-group difference among BD-I, BD-II, and BD-NOS participants in terms of rate of recovery from the index episode (BD-I 68%, BD-II 79%), BD-NOS 66%). Interestingly, BD-II participants were significantly more likely to have a recurrence than BD-I or BD-NOS (BD-I 58%, BD-II 87%, BD-NOS 46%).

Furthermore, compared to the other two groups, BD-NOS participants had significantly longer mean time to recovery from the index episode (BD-I 52.0, BD-II, 42.1, and BD-NOS 140.2 weeks) and significantly longer mean time to recurrence (BD-I 45.0, BD-II 19.0, BD-NOS 69.0 weeks). This convincingly demonstrates that the interepisode illness burden is quite high among BD youths, regardless of whether they have full duration manic or hypomanic episodes fulfilling DSM-IV criteria for BD type I or type II, or whether they have shorter-lived episodes fulfilling COBY criteria for BD-NOS. Additionally, this suggests the possibility that BD-NOS participants have a more chronic course, despite having shorter episodes.

Importantly, with longitudinal follow up, some BD-NOS participants did develop full symptoms of mania or hypomania. For example, after 4 years of longitudinal follow up, 38% of BD-NOS participants converted to either BD type I or II (57). After 5 years of longitudinal follow up, 45% (63/140) had converted from BD-NOS to either BD type I (32/63) or type II (31/63), with the strongest predictor of conversion being first- or second-degree family history of mania or hypomania ascertained at study intake (58).

Taken as a whole, COBY data indicate remarkable phenomenological similarity between BD-I and BD-II youths with full-duration episodes of mania and hypomania, and those BD-NOS youths with short-lived episodes of irritability and/or elation. It also suggests the need for greater study of intra-episode mood fluctuations in BD youths,

potentially employing ecological momentary analysis, as has been shown feasible in a pilot study of youths with mood disorders by Axelson et al. (59).

Hunt et al. have also recently examined COBY intake data to determine potential differences in BD youths whose most severe lifetime manic episode involved irritability only without elation, elation only without irritability, and both irritability and elation. Of 361 COBY participants, irritable-only mania was present in 10% of the sample, elation-only in 15%, and both irritability and elation in the remaining 75%. Irritable-only COBY participants were significantly younger than the other two groups, but there were no other significant sociodemographic differences. There were also no other significant between-group differences in BD subtype (I, II, NOS), rate of psychiatric comorbidities, severity or duration of illness, or family history of mania in first- or second-degree relatives. This study using the relatively large well-phenotyped COBY sample speaks to one of the major controversies about pediatric BD, namely the contention that it predominantly involves irritability rather than euphoria. Instead, these data suggest that irritable-only and euphoria-only mania are rare, with most BD youths having both (60).

POTENTIAL DSM CHANGES TO ADDRESS THE CONTROVERSY The process of updating the DSM nosology to reflect current research on psychiatric disorders is underway as this manuscript is being prepared, with DSM-V scheduled for publication in May 2013. Until that time, it remains uncertain which proposed changes will and will not make the final cut. However, there are several potential changes related to pediatric BD that are available on the DSM-V website (www.dsm5.org). First, DSM-V planners propose to adopt DSM-IV’s “most of the day, every day” major depressive episode criteria to define mania and hypomania. A second potential change is the creation of a new diagnosis for children with chronic, nonepisodic irritability. Initially, the potential new diagnosis was known as “temper dysregulation disorder with dysphoria (TDDD).” However, based on feedback, this has been renamed “disruptive mood dysregulation disorder (DMDD).” Informed by Leibenluft’s criteria for severe mood dysregulation and resultant research, this potential new diagnosis requires severe recurrent temper outbursts in response to common stressors that are out of proportion to the situation and occur three or more times per week. In addition, the mood between temper outbursts 59

pediatric bipolar disorder, chronic disability and mood dysregulation

must be persistently negative (i.e., irritable, angry, and/ or sad). The onset of these symptoms must be before age 10 years. The symptoms must be present for at least 12 months, with no symptom free interval lasting 3 or more months, and functional impairment must occur in two settings (and be severe in at least one). These criteria do not require the ADHD-like hyperarousal found in Leibenluft et al.â&#x20AC;&#x2122;s SMD criteria. Reaction to the DSMâ&#x20AC;&#x2122;s consideration of DMDD has been mixed. Some have expressed concern that it may be premature to add this new disorder, or that it may result in a label change (from BD to DMDD) without substantial difference in the treatment they receive or their outcome (61). Whether these and other changes related to BD in children and adolescents will make it into the published DSM-V remains unknown, though we believe it is important for clinicians to stay apprised of developments, as well as research supporting or not supporting potential changes, including by checking the DSM-V website (www.dsm5.org).

CONCLUSION In summary, there are many reasons why increasing numbers of children and adolescents are being diagnosed with BD, most notably potential ambiguity and/ or variations in how clinicians interpret DSM manic episode diagnostic criteria. To address questions about the phenomenology of pediatric BD, research has begun to examine systematically the manifestations of both episodic and chronic irritability in children and adolescents. Employing a number of techniques, from longitudinal phenomenology studies through specialized computer tasks and brain scans, these studies suggest that children with an episodic course of euphoria and/ or irritability may differ from those with chronic irritability with respect to emotional face processing, frustration, and cognitive flexibility. However, these children share similar clinical attributes, including high rates of impairment, including need for psychiatric hospitalization and psychotropic medications. Ongoing and future work will address how such data can inform our diagnostic procedures as well as treatment options.

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Isr J Psychiatry Relat Sci - Vol. 49 - No 1 (2012)

A Magnetic Resonance Spectroscopy Study of the Anterior Cingulate Cortex In Youth with Emotional Dysregulation Janet Wozniak, MD, *1,3 Atilla Gönenç, PhD, * 2,3 Joseph Biederman, MD, 1,3 Constance Moore, PhD, 4 Gagan Joshi, MD,1,3 Anna Georgiopoulos, MD,1,3 Paul Hammerness, MD,1,3 Hannah McKillop, BA,1 Scott E. Lukas, PhD, 2,3 and Aude Henin, PhD1,3 *Joint first authors 1 Pediatric Psychopharmacology Unit, Massachusetts General Hospital, Boston, Massachusetts, U.S.A. 2 Neuroimaging Center, McLean Hospital, Belmont, Massachusetts, U.S.A. 3 Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, U.S.A. 4 University of Massachusetts at Worcester, Massachusetts, U.S.A.

ABSTRACT Background: The main aim of this study was to use proton Magnetic Resonance Spectroscopy (MRS) to identify brain biomarkers for emotional dysregulation in youth as measured by subscales of the Child Behavior Checklist (CBCL).

Methods: We measured glutamate (Glu) concentrations in the anterior cingulated cortex (ACC) of 37 pediatric subjects (aged 6-17 years) using high field (4.0 Tesla) proton Magnetic Resonance Spectroscopy (MRS).

Subjects were grouped based on combined T scores on three subscales (Anxiety/Depression, Aggression and Attention) of the CBCL previously associated with deficits in the regulation of emotion. Subjects were stratified into those with high (>180) (N=10) and low (<180) (N=27) scores.

Limitations: Limitations include small sample size, wide age range studied, focus on Anterior Cingulate Cortex (ACC) only, and that some subjects received psychopharmacological treatments.

Results: We found a statistically significant correlation between Glu levels in the ACC and CBCL dysregulation profile scores among subjects with high dysregulation profile scores.

Conclusions: These results suggest that glutamatergic dysregulation in the ACC may represent a useful bio-

marker of emotional dysregulation in youth. Further investigation into the causality, time line and utility as a predictive metric is warranted.

INTRODUCTION Despite ongoing controversy on how to best categorize emotional volatility in the young, there is no debate that a sizeable minority of youth is affected with various forms of emotional regulation deficits which are associated with high levels of morbidity and disability (1-8).

Recent efforts at operationalizing emotional regulation deficits have relied on the Child Behavior Checklist (CBCL), a paper and pencil empirically derived scale with excellent psychometric properties (9-18).

Recent work by our group and others have documented that a profile consisting of marked (>2SD) elevations of three of the CBCL clinical scales (Anxiety/ Depression, Aggression and Attention [A-A-A profile]) was associated with very severe morbidity and dysfunction including suicidality and need for hospitalization, regardless of diagnosis, hence termed by some the “dysregulation profile” (6, 19-28). The same profile has also been associated with increased likelihood to satisfy diagnostic criteria on structured diagnostic interview for bipolar disorder (29, 30) and hence termed the

Address for Correspondence: Janet Wozniak, MD, Massachusetts General Hospital, Department of Psychiatry, 15 Fruit Street, Yawkey 6A, Boston, MA 02114, U.S.A. jwozniak@partners.org

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Janet Wozniak et al.

CBCL-Juvenile bipolar profile. More recent work has linked an intermediate profile characterized by moderate scores (>1 SD) on the same CBCL scales with deficient emotional self regulation (DESR). However, whether deficits in emotional regulation are associated with unique biomarkers remains unknown.

One approach non-invasively to identify brain biomarkers is magnetic resonance imaging neuroimaging methodology. Proton Magnetic Resonance Spectroscopy (1HMRS) examines brain biochemistry in various regions of the brain and allows in vivo quantification of metabolic changes including those related to glutamate (Glu), the most abundant neurotransmitter in the brain. However, Glu analysis via 1HMRS is challenging due to its J-coupled multiple resonance patterns and overlapping resonances from other metabolites primarily glutamine (Gln).

Although separating glutamate from glutamine levels can help in understanding the pathophysiology of various psychopathological states, field strengths less than 2.0 Tesla do not allow to resolve the resonances of Glu and Gln. Thus, often times the composite peak (Glx) is reported rather than the individual Glu and Gln levels (31).

A number of prior studies have linked abnormalities in Glx to mood disorders. In bipolar disorder, almost all studies report elevated Glx independent of disease state (32-39). However, as the majority of these previous 1HMRS results come from 1.5 Tesla strength imagers, few studies have quantified glutamate and glutamine separately. Furthermore, children and adolescents have been relatively understudied in general as well as with high field strength magnets.

The main aim of this study was to use 1HMRS to identify biomarkers of emotional regulation deficits in youth using a high field scanner capable of differentiating Glu from other metabolites. To this end, we conducted a 4.0 T proton Magnetic Resonance Spectroscopy study focusing on the anterior cingulate cortex (ACC) in 37 youth with high (>1SD) and low (<1SD) score on the CBCL A-A-A profile. The ACC was chosen because of its importance in cognitive and emotional regulation and because previous studies have reported neurometabolite abnormalities in mood disordered youth in the ACC (40-42). We hypothesized that Glu may represent a useful biomarker of emotional dysregulation in youth and that higher Glu levels would predict more emotional regulation deficits as indicated by higher CBCL scores. To the best of our knowledge this is the first examination of biomarkers of emotional regulation deficits in youth using a high field 1HMRS scan.

METHODS Participants

The 37 participants were ages 6-17 years old and either probands (N=24) or controls (N=13) from a high risk offspring study of youth (6-24 years) recruited based on having a parent with bipolar disorder or in the case of controls, without a family history of mood disorder or personal history of mood disorder or major psychiatric disorder. Controls were recruited to match the age and sex of the high risk sample. For this high risk offspring study 91 potential participants were screened, 61 met the inclusion and exclusion criteria, and of this group 37 were aged 6-17 years and had a completed CBCL. Participants were recruited from advertisements to the public in the local media as well from the Massachusetts General Hospital Pediatric Psychopharmacology Clinic and Research Program. Exclusion criteria included clinically significant chronic medical conditions, organic brain disorders, documented mental retardation, phobia of small spaces, contraindication to MRI including presence of metal or surgical devices, and pregnancy.

Female participants of child bearing potential received a urine pregnancy test prior to scanning.

Procedures

Prior to enrollment, participants were screened by phone to describe study procedures and evaluate study eligibility. Study procedures were approved by the MGH and McLean Hospital human subjects Internal Review Boards (IRBs). Consent was obtained from a parent and the child provided written assent. Participants were compensated for their participation. Only anonymous de-identified data are presented.

Prior to scanning, all subjects were assessed diagnostically using the Kiddie Schedule for Affective Disorders and Schizophrenia, Epidemiologic Version for DSM-IV (K-SADS-E) (43). In addition to a diagnostic interview, participants were assessed using clinician-administered measures of mania and depression: the Young Mania Rating Scale (YMRS) (44) and the Child Depression Rating Scale (CDRS) (45). These measures were administered by board-certified child and adult psychiatrists who had been trained to reliability. Socioeconomic Status (SES) was assessed using the Hollingshead Socioeconomic Status scale. IQ was assessed using the Wechsler Abbreviated Scale of Intelligence Scale (WASI) (46) Vocabulary and Matrix Reasoning subtests.

Parents (usually the mother) completed the Child 63

Magnetic Resonance Spectroscopy of the Anterior Cingulate Cortex In Emotional Dysregulation

Behavior Checklist (CBCL) (9). T scores from subscales of interest included the Anxiety/Depression, Aggression and Attention subscales (CBCL A-A-A). Due to small sample size, 37 subjects (N=13 healthy comparison participants and N=24 high-risk offspring) were grouped into two groups based on their T-scores on the CBCL A-A-A profile: high score group (>180) (N=10) and low score group (<180) (N=27). The 10 subjects in the high score group included only high risk offspring. The 27 subjects in the low score group comprised all 13 healthy controls and 14 high risk offspring. A T-score of 60 is one standard deviation from normal based on well established norms for the CBCL. The high score group (>180) reflects subjects whose scores on the three subscales on average are at least one standard deviation from normal. A T-score of 60 or greater is considered to be of clinical concern and thus the high score group comprises subjects with a clinical picture generally meeting standards for psychiatric intervention.

Imaging Procedures

Data acquisition was performed on a 4.0 T Varian Unity/Inova whole body MR scanner (Varian NMR Instruments, Palo Alto, CA) equipped with proton volumetric head coil. The MR protocol consisted of anatomical and spectral data acquisitions. Anatomical MR images were used for patient positioning, voxel localization and tissue segmentation. Spectral data were acquired from a 2cmx2cmx2cm voxel localized on the ACC using PRESS (point-resolved spectroscopic sequence) (TR=2000ms, TE=30ms, number of averages=128, acquisition time<5 minutes). Manual shimming within the voxel produced unsuppressed water signal linewidths of less than 11 Hz. A systematic approach to voxel positioning was used in all subjects. Voxels were placed on the ACC on midsagittal T1-weighted images, anterior to genu of the corpus callosum, and positioned on the midline on axial images.

MRS Data Processing

All MRS processing was conducted blinded to diagnosis and group assignment. The automated spectral-fitting package LCModel (version 6.2-1F) and the standard vendor-supplied simulated basis set were used for quantification of metabolite concentrations (Figure 1).

The basis set included alanine, aspartate, creatine, phosphocreatine, gamma-aminobutyric acid, glucose, glutamine, glutamate, glycerophosphocholine, phosphocholine, myo-inositol, lactate, n-acetylaspartate, n-acetylaspartylglutamate, syllo-inositol and taurine.

Data and fitting quality were visually verified and fur64

ther assessed by the percent standard deviation of the estimated concentration of each metabolite (CRLB), linewidth (FWHM) and signal-to-noise (SNR), all calculated

by LCModel. The results were presented in institutional units (I.U.) and no attempt was made to convert IU to absolute concentrations due to the lack of knowledge about the Glu T1 and T2 relaxation times. Glu levels were corrected for the cerebrospinal fluid (CSF) and gray matter (GM) fraction. Tissue-segmentation of T1-weighted images into GM, white matter (WM), and CSF was automatically done using an open source software, â&#x20AC;&#x153;NVMâ&#x20AC;? (freely available from Neuromorphometrics, Inc. at http://neuromorphometrics.org:8080/nvm/).

Statistical Analysis

Statistical analysis was performed using the IBM SPSS software (version 19.0.0.1 for Macintosh). Chi-Squared tests (for categorical variables) and t-tests (for continuous variables) were used to compare demographic and clinical characteristics across groups (low score and high score). Correlation between the clinical index and metabolite levels was carried out with Pearson bivariate correlation as well as partial correlation controlling for age, sex, and medication status (on/off). All tests were two-tailed, except for correlation analysis. Since a directional prior hypothesis had been made, the correlations Figure 1. Representative proton magnetic resonance spectrum of the anterior cingulate cortex at 4 Tesla collected at TE=30ms with a point-resolved spectroscopy sequence along with spectra of Glu. The real part of the frequencydomain data (phased and referenced FFT of raw input data with no smoothing) is plotted as the black curve. The red curve is the LCModel fit to this data. Also plotted as the gray curve is the baseline. Below is the fitting line for Glu only. Cho = Choline; Cr = Creatine; Glx = Glutamine + Glutamate; Glu = Glutamate; NAA = N-Acetyl Aspartate; mI = myo-inositol; ppm = parts per million.

Janet Wozniak et al.

were evaluated with one-tailed tests. A p-value of < 0.05 was considered statistically significant.

RESULTS Subject characteristics are summarized in Table 1. Groups were comparable with respect to age, gender, IQ and socioeconomic status. YMRS, CDRS and CBCL A-A-A scores were statistically significantly higher in the high CBCL score group than the low CBCL score group.

Four subjects (15%) in the low CBCL score group and seven subjects (70%) in the high CBCL score group (all high risk offspring subjects) were taking one or more types of medication at the time of scans. The medication class rates are shown in Table 1.

Good quality MRS data were obtained with low CRLB, high SNR and low FWHM from both groups as shown in Table 2. There were no between group differences in any of these measures. Unobstructed clear Glu peak is demonstrated in Figure 1.

Within the low dysregulation profile score group, Glu levels were increased in high-risk offspring subjects (n=14; mean CBCL score=161.29±10.49; mean

Glu level=6.00±1.95) when compared with the healthy controls (n=13; mean CBCL score=154.38±7.37; mean Glu level=4.88±2.07) but did not reach statistical significance (two sample t-test; t = 1.963, d.f. = 25, p = 0.06 (2-tailed). Hence control and high-risk offspring subjects in the low dysregulation profile score group have been combined into a single group and compared with the high dysregulation profile group.

Despite absence of statistically significant differences in Glu levels between the low and high dysregulation profile groups (Table 2), there was a positive correlation between glutamate levels with the CBCL dysregulation profile scores in the high score group (Pearson correlation=0.659, p=0.019 (1-tailed)) (Figure 2). This finding held true when partial correlation controlling for age, sex, and medication status (on/off) was carried out (correlation=0.759, p=0.024 (1-tailed), df=5). The CBCL-Glu correlation was not significant in the low score group (p=0.111 (1-tailed)) or in the total (low+ high score groups) dataset (p=0.170 (1-tailed)).

Glu levels were increased in youth with high dysregulation profile scores (n=10; mean CBCL score=207.40±15.51; mean Glu level=5.45±1.77) when

Table 1. Demographic and Clinical Characteristics of Study Participants in Low versus High CBCL Score Groups Low Score Group mean ± SD

High Score Group mean ± SD

Subgroups

Controls (n=13)

High Risk Offspring (n=14)

Combined (n=27)

High Risk Offspring (n=10)

Comparison (Low Score-Combined vs High Score Group)

Age (years)

11.50 ± 3.90

12.04 ± 3.11

11.78 ± 3.56

11.50 ± 3.50

NS: t = 0.212, d.f. = 35, p = 0.833

Males (N; %)

9; 69

8; 57

17; 63

8; 80

NS: d.f. = 1, χ2 = 0.967, p = 0.326

IQ

103.00 ± 17.08

104.43 ± 12.66

103.74 ± 14.51

106.44 ± 12.80

NS: t = 0.497, d.f. = 34, p = 0.622

SES

1.83 ± 0.58

2.23 ± 0.941

2.04 ± 0.81

1.90 ± 0.74

NS: d.f. = 3, χ2 = 0.437, p = 0.932

YMRS

0.17 ± 0.39

5.50 ± 7.47

2.96 ± 5.98

14.01 ± 11.03

t = 3.006, d.f. = 11.025, p = 0.012

CDRS

17.75 ± 1.36

22.63 ± 8.42

20.30 ± 6.73

38.41 ± 12.25

t = 4.432, d.f. = 11.077, p = 0.001

CBCL (T score A-A-A)

154.38 ± 7.37

161.29 ± 10.49

157.96 ± 9.61

207.40 ± 15.51

t = 11.688, d.f. =35, p < 0.001

Diagnoses (N) Bipolar Disorder Major Depression Generalized Anxiety Disorder Oppositional Defiant Disorder Conduct Disorder Attention Deficit Hyperactivity Disorder

0 0 0 0 0 0

5 3 0 2 1 2

5 3 0 2 1 2

8 7 5 7 3 6

Medication Classes (N) Atypical Antipsychotics Antidepressants Stimulants Mood Stabilizers Other

0 0 0 0 0

3 4 0 0 0

3 4 0 0 0

3 4 1 2 4

Continuous variables expressed as mean ± SD. YMRS, Young Mania Rating Scale; CDRS, Children’s Depression Ratio Scale; CBCL, Child Behavior Checklist; SES, Socio-economic status; IQ, Intelligence Quotient; NS, non-significant.

65

Magnetic Resonance Spectroscopy of the Anterior Cingulate Cortex In Emotional Dysregulation

Table 2. Magnetic Resonance Spectroscopy Data of Study Participants in Low versus High CBCL score groups Low Score Control Group (n=13)

Low Score At Risk Group (n=14)

Low Score Group Combined (n=27)

High Score Group (n=10)

Comparison

SNR

12.37 ± 5.02

11.60 ± 5.70

NS: t = 0.400, d.f. = 35, p = 0.692

FWHM (ppm)

0.05 ± 0.01

0.05 ± 0.02

NS: t = 0.514, d.f. = 35, p = 0.610

10.04 ± 3.11

10.11 ± 2.89

NS: t = 0.063, d.f. = 35, p = 0.950

5.47 ± 2.05

5.45 ± 1.77

NS: t = 0.016, d.f. = 35, p = 0.987

Glu CRLB (%) Mean Glu (I.U.)

4.88 ± 2.07

6.00 ± 1.95

All variables expressed as mean ± SD. SNR, Signal to Noise Ratio; FWHM, Full Width at Half Max; CRLB, Cramer-Rao Lower Bound; Glu, Glutamate; NS, non-significant.

compared with just the healthy controls from the low dysregulation profile score group (n=13; mean CBCL score=154.38±7.37; mean Glu level=4.88±2.07) (two sample t-test; t = 10.88, d.f. = 21, p < 0.001 (2-tailed)).

DISCUSSION This study found a positive correlation between emotional dysregulation as measured by CBCL A-A-A scores (>180) and glutamate concentrations in the ACC in youth at high risk for bipolar disorder. Although in need of confirmation in larger studies, these findings Figure 2. Study Participant CBCL A-A-A Scores (Low and High) versus ACC Glutamate Levels

Solid lines represent the linear fits to the low score group data (black) and high score group data (grey). Dashed lines represent 95% confidence intervals. CBCL, Child Behavior Checklist; A-A-A, Anxiety/Depression, Aggression, Attention subscale; ACC, Anterior Cingulate Cortex.

66

suggest that glutaminergic dysregulation could represent a biomarker for emotional dysregulation in youth at risk for bipolar disorder.

Our finding of higher Glu levels in mood disordered youth with high CBCL dysregulation profile score is consistent with previously reported glutamatergic abnormalities in bipolar disorder and with a literature that suggests that glutamatergic abnormalities are a prominent feature of mood disorders (47). In major depressive disorder and bipolar disorder, serum, plasma and ACC levels of glutamate have been found to be altered (47-49). Glutamate level in the frontal cortex has been reported to be elevated in postmortem brains of patients with bipolar disorder and major depression (50). Glutamate is thought to be a marker of glial cell functioning and glial cell number and density reduction has been consistently demonstrated in mood disorders in the ACC in postmortem studies (51, 52). In bipolar disorder, almost all MRS studies report elevated Glx independent of disease state (31, 36, 38, 48, 53-57), making it a most consistent finding in the MRS literature.

Our 1HMRS ACC findings are also consistent with the literature that has previously found the ACC to be the site of neurometabolite abnormalities in mooddisordered youth. Davanzo et al. found significantly higher myo-inositol/creatine-phosphocreatine and mI levels in the ACC in bipolar youth versus healthy subjects or those with intermittent explosive disorder (40, 41). Cecil et al. (42) also found ACC abnormalities in mood disordered children, while Auer et al. reported ACC abnormalities in mood disordered adults (55).

On the other hand, our findings are discrepant with those of Singh et al. (58) who reported that high-risk offspring for bipolar disorder with subsyndromal symptoms of mania did not exhibit differences in Glu or Gln. They are also discrepant with findings by Moore and colleagues who reported that unmedicated youth with bipolar disorder had significantly lower Glx/Cr lev-

Janet Wozniak et al.

els than healthy comparison subjects and medicated subjects with bipolar disorder (39, 59). More work is needed to reconcile these discrepant findings.

However, despite the positive correlation between Glu levels with the CBCL dysregulation profile score, there were no statistically significant Glu differences between the low versus high CBCL dysregulation profile groups.

There could be several possible explanations for this finding: First, the low dysregulation profile group comprised a mixture of offspring of controls and bipolar disorder parents. It is possible that Glu is elevated only among youth at risk for bipolar disorder who also exhibit emotional dysregulation. This possibility is supported by our finding that there was a significant difference between high-risk offspring and healthy controls among the high emotional dysregulation group, but not the low dysregulation group.

Thus, it would be important for subsequent studies to examine whether emotional dysregulation, as indexed by the CBCL represents a marker of risk or an endophenotype in these offspring at risk for bipolar disorder.

While no previous study has specifically correlated HMRS findings with the CBCL dysregulation profile, our 1HMRS results are also consistent with those from several studies that have connected the CBCL A-A-A dysregulation profile to genetic and other biomarkers.

Althoff et al. have demonstrated in a very large sample that this CBCL profile is heritable, using latent class analysis (60). Doyle et al. in a genetic linkage study of 154 families estimated the heritability of this CBCL profile at 0.71 (61). Boomsma et al. (62) examined longitudinal data on Dutch mono- and dizygotic twin pairs (N = 8013 pairs) and found that 80% of the stability in childhood CBCL-Dysregulation profile was a result of additive genetic effects.

Zepf et al. (63) linked the profile to brain chemistry and reaction time. These authors used a placebo-controlled double-blind within-subject crossover design to compare the reaction times of high and low scorers on this CBCL-Dysregulation profile after a rapid tryptophan depletion test (RTD) (which lowers the central-nervous system 5-HT synthesis rate). Subjects with a high CBCL- Dysregulation score showed a slower reaction time under RTD compared to patients with low CBCLDysregulation profile. Another study found endocrinological correlates to the CBCL-Dysregulation profile.

Basal serum TSH was measured in 114 children and adolescents with (N=53) and without (N=61) the CBCLDysregulation profile; TSH was elevated in those with the CBCL-Dysregulation profile compared to controls (64).

Ducharme et al. reported on 193 healthy children aged 6-18 and found the Aggressive Behavior CBCL subscale alone to be correlated with bilateral striatal volumes and right ACC cortical thickness (65). Taken together, these studies all provide evidence that the CBCL A-A-A profile may be uniquely useful in the search for biomarkers of emotional dysregulation in the young.

This study has important strengths. Our definition of deficits in emotional regulation was anchored on a unique profile of the CBCL, an empirically derived scale with excellent psychometric properties, previously shown to discriminate youth with deficits in emotional regulation. By using a high field MRI scanner, the size of brain tissue volumes from which chemical information was obtained, was decreased which was an important consideration for acquiring MRS data from young children who have smaller brain volumes than adults. In addition, the improved signal to noise ratio at high field increased the metabolite signal enabling more accurate quantification including differentiation of Glu and Gln. On the other hand, results of this study must be considered in light of some limitations. Our sample size was relatively small, resulting in very small cell sizes limiting the power of the study and increasing the possibility of spurious findings. Thus, our findings must be considered as preliminary until replicated with larger samples. To facilitate recruitment, this study included youth with a wide age range 6-17 years providing an additional confounding factor. Little is known about neurodevelopmental changes occurring during these years in the functioning of the ACC among typically developing youth. Such disparate ages would likely provide a confounding factor making a significant finding less likely. It is all the more remarkable that a correlation between CBCL scores and glutamate was noted. In addition, age was not statistically different between our two groups of interest, low and high scorers. Nonetheless, future confirmatory studies would benefit from examination of this brain region in youth of a narrower age range to remove any effects occurring during normal maturation. Although our focus on the ACC was well grounded on previous studies and theoretical considerations, future studies should examine other brain regions as well. Some of the subjects received pharmacologic treatment, which may have confounded the findings. In fact, that 70% of the high score group were taking one or more types of psychotropic medications at the time of the scan and that these medications were varied is a significant weakness of the 67

Magnetic Resonance Spectroscopy of the Anterior Cingulate Cortex In Emotional Dysregulation

study. Future studies would benefit from study of either treatment naïve or treatment free subjects.

Despite these considerations, our findings suggest that, among youth at risk for bipolar disorder, there is a relationship between emotional regulation deficits and neurometabolite glutamate in the ACC. Although additional work is needed to replicate these findings and further examine the implications of glutaminergic dysregulation in the ACC on the development of emotional dysregulation, our findings may have important scientific and clinical implications. Biomarkers of risk for emotional dysregulation may allow the identification of subjects at risk for this serious clinical problem as well as increase our understanding of the neural and biochemical bases of emotional dysregulation in youth.

In addition, the construct of emotional dysregulation is consistent with the NIMH Research Domain initiative and may provide a fruitful area of scientific inquiry in the quest for biomarkers of psychopathological dysfunction.

Acknowledgements This study was funded, in part, by National Institutes of Health (NIH) grants K08MH001503 and R01MH066237 to Dr. Wozniak, the Susan G. Berk Endowed Fund for Juvenile Bipolar Disorder, the Heinz C. Prechter Bipolar Research Fund, and the support of members of the MGH Pediatric Psychopharmacology Council. In addition this work was supported by a NARSAD Young Investigator Award in collaboration with a donation from the SHINE Initiative (Henin), and a Massachusetts General Hospital Claflin Distinguished Scholars Award to Dr. Henin. This study was also funded in part by MH073998 to Dr. Moore. We would like to acknowledge Dave Crowley, BA, Caroline Rycyna, BA, and Laura Rindlaub for their contributions to the study.

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‫דיווח ועד האיגוד הפסיכיאטרי לאספה הכללית ‪ -‬ירושלים‬ ‫‪ 5‬בינואר ‪2012‬‬

‫‪1 .1‬גובשו ההתאמות והתיקונים שיש לערוך בתכנית להעברת‬ ‫האחריות על בריאות הנפש לקופות החולים‪.‬‬

‫‪7 .7‬דווח על התחלת התהליך לבחירת הוועדים המקומיים ועל‬ ‫הצגת המועמדות ל"יו"ר הנבחר" לקראת הכנס הקרוב‪.‬‬

‫‪2 .2‬נידונו הסוגיות הפסיכיאטריות הייחודיות בהסכם‬ ‫הרופאים‪ ,‬כגון מסוכנות ושחיקה‪ ,‬המצריכות מציאת‬ ‫פתרונות‪ ,‬וכן נידון הצורך בהכרה במקצוע הפסיכיאטריה‬ ‫כולו כמקצוע במצוקה‪.‬‬

‫‪8 .8‬המשתתפים בישיבה עודכנו בדבר כוונתו של מנכ"ל משרד‬ ‫הבריאות להעביר את האחריות הביטוחית על בריאות‬ ‫הנפש לקופות החולים בצו שיינתן על ידי שר הבריאות ושר‬ ‫האוצר עד מרץ ‪.2012‬‬

‫‪3 .3‬הוצג ערעורה של ההסתדרות הרפואית על ההחלטה שלא‬ ‫לכלול את הפסיכיאטריה במסגרת המקצועות שבהם‬ ‫רופאים עובדי המדינה רשאים לתת חוות דעת רפואית‬ ‫בהליכים נגד המדינה ללא צורך בקבלת היתר מוועדת‬ ‫החריגים‪ .‬סוכם כי האיגוד לא יפנה ללשכה המשפטית‬ ‫בהר"י להמשך הטיפול בנושא‪.‬‬

‫‪9 .9‬בישיבת הוועד הקרובה יידונו הנושאים הבאים‪:‬‬ ‫ •היבטים מקצועיים בטיפול האמבולטורי יוצגו על ידי נציג‬ ‫פורום המרפאות‪ ,‬אשר ישתתף באופן קבוע בישיבות‬ ‫הוועד המרכזי‪.‬‬ ‫ •סוגיית האזוריות בפסיכיאטריה ומשמעויותיה‪.‬‬ ‫ •העברת מידע לגבי תופעות הלוואי מתרופות‬ ‫פסיכיאטריות למטופלים‪.‬‬ ‫ •משמעות הפגיעה ברופאים הגמלאים תוצג על ידי נציג‬ ‫הגמלאים בוועד‪.‬‬

‫‪4 .4‬גובשה התכנית המדעית לכינוס האיגוד התלת יומי ב–‪.2012‬‬ ‫‪5 .5‬הוצגו בקשות האיגוד שהוגשו לשכת האתיקה של הר"י‬ ‫בעניין הצורך להגביל את הפרסום של תלונות שלא‬ ‫נבדקו נגד רופאים וכן להגביל את פרסום הפרוטוקולים‬ ‫המפורטים של דיוני הוועדה‪ .‬סוכם כי תועבר ללשכת‬ ‫האתיקה דרישה שתלונות נגד פסיכיאטרים יידונו במסגרת‬ ‫ועדת האתיקה של האיגוד בלבד‪.‬‬ ‫‪6 .6‬הוצגו הישגי ‪ 9‬החברים שיוענק להם "אות מפעל חיים"‬ ‫בכנס הפסיכיאטריה ב–‪.2012‬‬

‫איגוד הפסיכיאטריה בישראל‪ :‬ההסתדרות הרפואית ‪ -‬המועצה המדעית ‪Israeli Psychiatric Association -‬‬ ‫יו"ר‪ :‬פרופ' זאב קפלן ‪President: Prof. Z. Kaplan /‬‬ ‫‪Zeev.kaplan@pbsh.health.gov.il‬‬

‫המרכז לבריאות הנפש באר שבע‬

‫מזכיר‪ :‬ד"ר נמרוד גריסרו ‪President: Dr. N. Grisaru /‬‬ ‫‪grisarun@gmail.com‬‬

‫ טל'‪ ;08-6401606 :‬פקס‪08-6401621 :‬‬ ‫ רח' הצדיק מירושלים ‪ ,2‬באר שבע‪ ,‬ת"ד ‪ 4600‬‬ ‫ ‪Hazadik from Jerusalem St. P.O. Box 4600‬‬

‫גזבר‪ :‬ד"ר בוריס נמץ ‪Treasurer: Dr. B. Nemets /‬‬ ‫‪nemetz@bgu.ac.il‬‬

‫‪Beer-Sheva Mental Health Center‬‬

‫ ‪www.psychiatry.org.il‬‬

‫יו"ר נבחר‪ :‬פרופ' משה קוטלר ‪Elected President: Prof. M. Kotler /‬‬ ‫‪Moshe.kotler@beerness.health.gov.il‬‬

‫יו"ר יוצא ואחראי קשרי חו"ל‪ :‬פרופ' אבי בלייך ‪/‬‬

‫‪President Emeritus and Foreign Affairs: Prof. A. Bleich‬‬ ‫‪ableich@lev-hasharon.co.il lean@bgu.ac.il‬‬

‫‪70‬‬

‫להתנהגות מתפרצת‪.‬‬ ‫שיטה‪ :‬הורים ומורים של ‪ 911‬ילדים בני ‪ 18-5‬שהופנו‬ ‫למרפאה הפסיכיאטרית מילאו שאלונים‪ .‬הילדים עברו הערכה‬ ‫פסיכיאטרית‪ ,‬מבלי שהבודק היה מודע לממצאי השאלונים‪.‬‬ ‫לילדים שדווח כי הם סובלים מהתפרצויות זעם (‪ 431‬ילדים‪,‬‬ ‫‪ )47.2%‬נעשתה הערכה לאבחנה‪ ,‬נמדדו משתנים קליניים‬ ‫ונלקחה היסטוריה משפחתית‪.‬‬ ‫תוצאות‪ :‬הילדים היו בני ‪ )3.6( 12‬שנים; ‪ 26.5%‬היו בנות‪.‬‬ ‫הפרעה דו–קוטבית הייתה נדירה במדגם זה (‪ ,)11.2%‬אולם אצל‬ ‫ילדים שגם המורים וגם ההורים דיווחו על התפרצויות זעם‬ ‫שלהם‪ ,‬הפרעה קשה בוויסות מצב הרוח הייתה נפוצה (‪.)54.4%‬‬ ‫בקרב ילדים שרק הוריהם דיווחו על התפרצויות זעם האבחנה‬ ‫הנפוצה ביותר הייתה של חרדה (‪ .)40.6%‬בקרב ילדים שרק‬ ‫המורים דיווחו על התפרצויות זעם שלהם‪ ,‬לקות שפתית ולקות‬ ‫למידה היו האבחנה הנפוצה ביותר (‪.)46%‬‬ ‫מסקנה‪ :‬הסביבה שבה קורות התפרצויות הזעם יכולה‬ ‫להעיד על האבחנה‪ ,‬אולם האבחנה לבדה אינה מסבירה את‬ ‫הקושי ואת ההפרעה בהתנהגות‪.‬‬ ‫מעבר לדוגמה‪ :‬מחילוקי דעות אבחנתיים לנתונים‬ ‫על הפרעה דו־קוטבית בקרב ילדים ואיריטבליות‬ ‫כרונית הכוללת הפרעה בוויסות מצב הרוח‬ ‫ד‪.‬פ‪ .‬דיקשטיין וא‪ .‬לייבנלופט‪ ,‬מזרח פרובידנס‪ ,‬ארה"ב‬

‫מחקרים רבים הראו שמאמצע שנות התשעים ועד היום חלה‬ ‫עלייה משמעותית במספר הילדים והמתבגרים המאובחנים‬ ‫כלוקים בהפרעה דו–קוטבית‪.‬‬ ‫מאמר זה בוחן כמה הסברים אפשריים לכך‪ ,‬ובעיקר את‬ ‫אי–הבהירות בקריטריונים לאבחנה של מצב מאני ואת הקשר‬ ‫בינה לבין האבחנה של ילדים הסובלים מאיריטביליות המובילה‬ ‫להפרעה בתפקוד‪ .‬כמו כן‪ ,‬במאמר מוצגות גישות מחקריות‬ ‫עכשוויות בתחום הפנומנולוגי והאפקטיבי ‪ -‬הנוירו–מדעי‪,‬‬ ‫לשם אפיון הילדים הללו בצורה הטובה ביותר‪.‬‬

‫‪71‬‬

‫ממחקרים אלו עולה שהפרעה דו–קוטבית אצל צעירים‬ ‫שונה בכמה מדדים מההפרעה של איריטביליות כרונית הכוללת‬ ‫חוסר ויסות קשה של מצב הרוח‪ ,‬אף על פי שיש חסרים אחדים‬ ‫המופיעים בשתי ההפרעות הללו‪.‬‬ ‫‪)MRS) Magnetic Resonance Spectroscopy‬ו‬ ‫ב־‪Anterior Cingulate Cortex‬נ(‪)ACC‬‬ ‫אצל צעירים הסובלים מחוסר ויסות רגשי‬ ‫ג'‪ .‬ווזניאק‪ ,‬א‪ .‬גוננץ'‪ ,‬י‪ .‬בידרמן‪ ,‬ס‪ .‬מור‪ ,‬ג‪ .‬ג'וסי‪,‬‬ ‫א‪ .‬ג'ורגיאופולוס‪ ,‬פ‪ .‬המרנס‪ ,‬ה‪ .‬מק קילופ‪ ,‬ש‪.‬א‪ .‬לוקאס‬ ‫וא‪ .‬הנין‪ ,‬קיימברידג'‪ ,‬ארה"ב‬

‫רקע‪ :‬המטרה העיקרית של מחקר זה היא להשתמש בפרוטון‬ ‫‪ MRS‬כדי לזהות סמנים ביולוגיים במוח לחוסר ויסות רגשי‬ ‫אצל צעירים‪ ,‬כפי שמצב זה נמדד בתתי–סקלות של ה–‪.CBCL‬‬ ‫שיטות‪ :‬נמדדו ריכוזים של גלוטמט ב–‪ ACC‬של ‪ 37‬נבדקים‬ ‫צעירים (בני ‪ 17-6‬שנים)‪ .‬השתמשנו בפרוטון ‪ MRS‬בעצמה של‬ ‫‪ 40‬טלסה‪ .‬הנבדקים קובצו על בסיס ערכי ‪ T‬משולבים בשלוש‬ ‫תתי–סקלות (חרדה‪/‬דיכאון‪ ,‬תוקפנות וקשב) של ה–‪,CBCL‬‬ ‫שנמצא לפני כן כי הן קשורות לחסרים בוויסות הרגשי‪ .‬הנבדקים‬ ‫חולקו לשתי קבוצות ‪ -‬בקבוצה אחת נכללו ‪ 10‬משתתפים‬ ‫שנמצאו אצלם ערכים גבוהים (>‪ )N=10( )180‬ובקבוצה השנייה‬ ‫נכללו ‪ 27‬משתתפים שנמצאו אצלם ערכים נמוכים (<‪.)180‬‬ ‫מגבלות‪ :‬מגבלות המחקר הן המדגם הקטן‪ ,‬טווח הגילים‬ ‫הגדול‪ ,‬ההתמקדות ב–‪ ACC‬בלבד וכן העובדה שכמה נבדקים‬ ‫קיבלו טיפול תרופתי פסיכיאטרי‪.‬‬ ‫תוצאות‪ :‬נמצאה קורלציה מובהקת סטטיסטית בין רמת‬ ‫גלוטמט ב–‪ ACC‬לבין ערכים גבוהים בפרופיל של חוסר ויסות‬ ‫רגשי כפי שנמדד באמצעות ה–‪.CBCL‬‬ ‫מסקנות‪ :‬תוצאות אלו מצביעות על כך שחוסר ויסות‬ ‫גלוטמטרגי באזור ה–‪ ACC‬יכול להיות סמן ביולוגי טוב לחוסר‬ ‫ויסות רגשי אצל צעירים‪ .‬נדרשים מחקרים נוספים בתחום‬ ‫הנסיבתיות‪ ,‬המהלך והתועלת של בדיקה זו כמדד לניבוי‪.‬‬

‫כתב עת ישראלי‬ ‫לפסיכיאטריה‬ ‫תקצירים‬ ‫שכיחות‪ ,‬ביטוי קליני ואבחנה מבדלת‬ ‫של הפרעה דו־קוטבית בקרב ילדים‬ ‫ב‪.‬א‪ .‬גולדשטיין וב‪ .‬בירמהר‪ ,‬טורונטו‪ ,‬קנדה‬

‫רקע‪ :‬לאורך עשרים השנים האחרונות הצטבר מידע רב בנוגע‬ ‫להפרעה דו–קוטבית בקרב ילדים‪ .‬בשל כך התמקד העיסוק‬ ‫בתחום בשכיחות התופעה ובאבחנה מבדלת‪.‬‬ ‫שיטה‪ :‬סקירת ספרות סלקטיבית‪.‬‬ ‫תוצאות‪ :‬הפרעה דו–קוטבית שהוגדרה על ידי קריטריוני‬ ‫אבחנה נוקשים‪ ,‬נמצאה במדינות רבות אצל ילדים ובעיקר‬ ‫אצל מתבגרים‪ .‬בניגוד לעלייה באבחנת ההפרעה במרכזי‬ ‫טיפול קליניים‪ ,‬לא נמצא שינוי בשכיחות האבחנה במחקרים‬ ‫אפידמיולוגיים‪ .‬מצבים על הרצף הדו–קוטבי אצל צעירים‬ ‫מובילים להפרעה בתפקוד ומעידים על סיכון גבוה למעבר‬ ‫להפרעה דו–קוטבית ‪ I‬ו–‪ .II‬בהשוואה למבוגרים‪ ,‬אצל צעירים‬ ‫הסובלים מהפרעה דו–קוטבית נראים יותר סימפטומים‬ ‫ויותר קוטביות במצב הרוח‪ .‬לעתים קרובות הם גם יותר‬ ‫סימפטומטיים והפרוגנוזה שלהם גרועה יותר‪ .‬מהלך ההפרעה‪,‬‬ ‫אפיוניה הקליניים והתחלואה הנלווית דומים בשאר המדדים‬ ‫להפרעה זו בקרב מבוגרים‪ .‬למרות זאת צעירים רבים הלוקים‬ ‫בהפרעה הדו–קוטבית אינם מטופלים כלל ורבים אינם מקבלים‬ ‫טיפול ספציפי להפרעה‪.‬‬ ‫מסקנה‪ :‬למרות המידע שמצטבר‪ ,‬אשר תומך בתוקף‬ ‫של אבחנה של הפרעה דו–קוטבית בקרב צעירים‪ ,‬הפער בין‬ ‫הממצאים הקליניים לממצאים האפידמיולוגיים מצביע על‬ ‫שכיחות גבוהה של אבחנה לא מספקת‪ .‬במקביל‪ ,‬שכיחות‬ ‫נמוכה של טיפול ספציפי מרמזת על הימנעות ממתן אבחנה‪ .‬על‬ ‫הקלינאים ליישם בקפדנות את קריטריוני האבחנה כדי לשפר‬ ‫את דיוק האבחנות ולהבטיח טיפול הולם‪.‬‬ ‫הערכה מבוססת ראיות של‬ ‫מחלות דו־קוטביות בקרב ילדים‬ ‫א‪ .‬א‪ .‬יאנגסטרום‪ ,‬מ‪ .‬מקאוון ג'נקינס‪ ,‬א‪ .‬ג'נסן־דוס‪,‬‬ ‫וג'‪ .‬קוגוס יאנגסטרום‪ ,‬צ'אפל היל‪ ,‬ארה"ב‬

‫ההערכה מבוססת הראיות של מחלות דו–קוטביות בקרב‬ ‫ילדים התקדמה במהירות בשני העשורים האחרונים‪ ,‬ועברה‬ ‫מתיאורי מקרה בודדים‪ ,‬לקובץ של שיטות הכוללות רשימת‬ ‫סימפטומים ממקורות רבים‪ ,‬ראיונות מובנים חלקית‪ ,‬סולמות‬

‫‪israel journal of‬‬

‫‪psychiatry‬‬ ‫כרך ‪ ,48‬מס' ‪2011 ,1‬‬

‫של חומרה וטכנולוגיות המאפשרות מעקב אחר מצב הרוח‬ ‫והאנרגיה במהלך טיפול‪ .‬סקירה זו מתייחסת באופן ביקורתי‬ ‫לכמה תחומים בהערכה מסוג זה‪( :‬א) הצורך בהערכה של‬ ‫מחלות דו–קוטביות כחלק בלתי נפרד מטיפול קליני רגיל‪.‬‬ ‫(ב) מצבים שמעלים את הצורך בהערכה של המחלה‪( .‬ג)‬ ‫מתי במהלך האבחנה והטיפול הכי מתאים להפעיל את‬ ‫‪1‬השיטות השונות‪( .‬ד) שיטות הערכה חדשות ומבטיחות‪.‬‬ ‫מוצגת מסגרת לקבלת החלטות‪ ,‬הלקוחה משיטות מבוססות‬ ‫ראיות‪ ,‬שנועדה לסייע בבחירת סדר הפעלת השיטות השונות‬ ‫בגישה ממוקדת מטופל‪ .‬מודגשות השיטות בעלות התקפות‬ ‫וההיתכנות הגבוהות ביותר ברוב המצבים הקליניים‪ .‬שיטות‬ ‫אלו מגבירות את הדיוק ונוגעות בנושאים רבים‪ ,‬שיש לגביהם‬ ‫חילוקי דעות‪ ,‬הקשורים לאבחנת דו–קוטביות בקרב ילדים‪.‬‬ ‫עדות ביולוגית לקיום מודל נוירו־התפתחותי‬ ‫של הפרעה דו־קוטבית בקרב ילדים‬ ‫ד‪.‬ג'‪ .‬רויבל‪ ,‬מ‪.‬ק‪ .‬סינג'‪ ,‬ו‪.‬א‪ .‬קוסגרוב‪ ,‬מ‪ .‬האווי‪ ,‬ר‪ .‬קלי‪,‬‬ ‫נ‪ .‬ברנע־גורלי וק‪.‬ד‪ .‬צ'נג‪ ,‬סטנפורד‪ ,‬ארה"ב‬

‫הפרעה דו–קוטבית היא מחלה כרונית שהלוקים בה סובלים‬ ‫גם מתחלואה נלווית ומשיעורי תמותה גבוהים‪ .‬מהלך המחלה‬ ‫של הפרעה דו–קוטבית המתחילה בגיל הילדות הוא קשה יותר‬ ‫ובמקרים אלו נראות חזרות רבות יותר של התקפים ומאובחנת‬ ‫הפרעה פסיכו–סוציאלית‪ .‬מציאת דרכי התערבות בשלבים‬ ‫המוקדמים של המחלה בקרב צעירים חשובה ביותר למניעת‬ ‫התבטאות המחלה במלואה ולשיפור התפקוד במהלך החיים‪.‬‬ ‫חשוב מאוד להבין את מנגנון התפתחות המחלה על מנת לאתר‬ ‫את הצעירים שנמצאים בסיכון גבוה להתפתחות המחלה‪,‬‬ ‫ולזהות סמנים ביולוגיים לשם התערבות מוקדמת‪.‬‬ ‫לצורך זה מוצע מודל נוירו–התפתחותי להפרעה דו–‬ ‫קוטבית בקרב ילדים‪ ,‬המבוסס על מידע קיים המצביע על‬ ‫פגיעה תפקודית במארג הפרה–פרונטלי–סבקורטיקלי שנגרמת‬ ‫בעקבות רגישות גנטית קיימת המופעלת בתגובה פתולוגית‬ ‫לעקה ולתהליכים דלקתיים כרוניים‪.‬‬ ‫השלכות אבחנתיות במקרים של אי‬ ‫הסכמה בדיווח על התפרצויות זעם‪:‬‬ ‫הפרעה דו־קוטבית או מצבים אחרים?‬ ‫ג‪.‬א‪ .‬קרלסון ומ‪ .‬דייסון‪ ,‬סטוני ברוק‪ ,‬ארה"ב‬

‫רקע‪ :‬הסכמה חלקית בין הורים למורים בנוגע להתנהגות הילד‬ ‫היא ממצא נפוץ‪ .‬מחקר זה בחן את האבחנה של ילדים שנמצאו‬ ‫לגביהם פערים גדולים בין דיווח ההורים לזה של המורים בנוגע‬ ‫‪72‬‬