Unraveling the Mysteries of Neurodegenerative Disease: One Terabyte at a Time by Brad Racette, MD

Unraveling the Mysteries of Neurodegenerative Disease: One Terabyte at a Time

Brad A. Racette, M.D.

Kemper and Ethel Marley Professor and Chairman of Neurology Senior Vice President

Barrow Neurological Institute

Outline

1. Introduction to administrative data

2. Research themes

a) Predictive modeling

b) Association Studies (including Pharmacoepidemiology)

c) Health Services

3. The Future

What is Big Data?

Source: Cloud Computing

Neuroepidemiology Using Medicare Data

 Medicare is the only “national” health insurance in the U.S.

 Complete demographic (race, age, sex) data, diagnoses, and date of death.

 Data purchased by primary diagnosis of interest (e.g., 332 and 332.0).

 Each subject identified by a unique beneficiary identification number.

 Spatial distribution (ARC GISTM ).

 Variety of research: Descriptive epidemiology, spatial epidemiology, health services, disease outcome.

 Use for research assumes competent diagnosis and administrative filing.

 Medicare Advantage.

 DRG’s.

 Not randomized.

 Expensive.

Crowd Sourced PD Research

Racette Lab Medicare Datasets

 Complete PD Case Dataset - All incident and prevalent PD 1995, 2000-2014

 Prodromal PD and ALS Case-Control Studies

• All 2009 incident PD (≈ 90,000)

• ALS (≈ 4000)

• AD (≈ 11,000)

• Population-based controls (≈ 120,000)

* Medicare Part D coverage

 Prodromal PD and AD Case-Control Studies

• All 2015-19 incident PD (≈ 500,000)

• AD (≈ 30,000)

• Population-based controls (≈ 4.5 million)

Predicting Neurological Disease

Developing a Predictive Model for Prodromal PD

Subjects

• 89,790 incident PD cases from 2009 (ICD9 332.0, 332); 118,095 population-based controls, age 66-90.

• All ICD9 and CPT codes from 2004-2009 (diagnosis).

Data Analysis

• Identified codes significantly associated with PD from 11,063 ICD9 and 15,405 CPT codes, Bonferroni corrected (1.889E-6).

• Covariates: Use of care, sex, race, age, smoking*.

• Used elastic net algorithm to select final ICD9/CPT codes.

• Cross-validation.

• Model quality: ROC AUC, sensitivity, specificity.

• Final model had 536 ICD9/CPT codes.

Categories of ICD9/CPT Codes Positively Associated with PD

Categories of ICD9/CPT Codes Inversely Associated with PD

Activity (77 codes: Knee OA, upper extremity overuse injuries, trigger finger, CTS, bursitis)

Cardiovascular (57 codes: Heart, stroke, PVD)

Cancer (48 codes: Various cancers, chemotherapy, and related procedures)

Tobacco (21 codes)

Inflammatory diseases/Allergy (8 and 10 codes respectively)

Obesity Gout

Probability of Developing PD Based upon Predictive Model

Basic model

Full predictive model

AUC: 0.86

Sensitivity: 73.2%

Specificity: 83.5%

TBI, Fractures, and Prodromal PD

Camacho-Soto A, et al., Ann Neurol, 2017.

Camacho-Soto A, et al., Neurology, 2020

Association Studies

Geographic Clusters

PD Non-randomly Distributed in U.S.

z test statistic for non-random clustering p<0.00001

Willis AW, et al. Neuroepidemiology, 2010.

Willis AW, et al. Am J Epi, 2011.

PD Risk and Air Pollution

BiLISA cluster map showing how PD hot and cold spots overlay with PM2.5 hot and cold spots

Pharmacoepidemiology

The study of the use and effect of medicine in large populations

Examples:

 Harm - Antipsychotics in Alzheimer dementia

 Benefits - Urate lowering medications

 Health Services - Sinemet in PD

Immunosuppression and Risk of PD

Transplant and risk of PD (Fan et al. 2019)

• All solid organ OR = 0.63 (0.53-0.75)

• Bone marrow OR = 0.57 (0.38-0.83)

Inflammatory Bowel Disease and risk of PD (Camacho-Soto et al. 2018)

• Ulcerative colitis OR = 0.88 (0.82-0.96)

• Crohn’s disease OR = 0.83 (0.74-0.93)

Immunosuppressant use and risk of PD (Racette et al. 2018)

• IMDH inhibitors RR = 0.64 (0.51-0.79)

• Corticosteroids RR = 0.80 (0.77-0.83)

• IMDH inhibitors + corticosteroid RR = 0.53 (0.40-0.70)

ALS: Bedside to Bench and Back

Lovastatin delays onset of weakness and extends survival in SOD-1 mice.

 149 medications inversely associated with ALS risk (OR<0.90)

• 8 significant after adjustment

 198 greater survival (HR<0.90)

• 21 significant after adjustment

Selected lovastatin, sulfasalazine, telmisartan for mouse studies

Lovastatin reduces activated microglia and delays motor neuron loss.

Kreple C, et al, in review

Administrative Data and Health Services Utilization

Neurologist Use in Medicare Beneficiaries with PD

Disparities in Neurologist Referral

Improved Survival and Reduced Hospitalizations with Neurologists’ Care

Willis AW, et al. Neurology, 2012

The Future…

Beam AL and Kohane IS. JAMA; 2018.

Neurologic Disease Data Science

Where we have been…

Grants/Gifts

 WUSM Diversity Scholars (3)

 MJFF-000939

 MJFF-020718

 PD190057, DoD

 Cure Alzheimer’s Fund

 Hope Center for Neurologic Disorders

 K01ES028295

 Grant # 10289, MJFF

 K23NS081087

 KL2RR024994

 5T32NS007205

 APDA (multiple)

 R01ES034373

 AL220032 (DoD)

 ARPA

Where we are going…

Publications

28 peer-reviewed, including:

 8 in Neurology

 3 in Annals of Neurology

 2 PLOS1

 JAMA Neurology

 American Journal of Epidemiology

 JBJS

 Barrow Data Science Center

 Expanding to other neurologic diseases (subarachnoid hemorrhage, GBM)

 Geospatial neurology

 Health economics

 Environment

Our Medicare Research Future

Health disparities and PD

Environment and neurodegeneration

GIS and neurodegeneration

Health disparities and epilepsy

Climate change and stroke care