Genetic Architecture of Parkinson's Disease in African-American and Latino Veterans

Parkinson’s disease (PD) is the fastest growing neurological disorder and its worldwide prevalence is expected to double by the year 2040, a trend that some have labeled the “PD pandemic.” Disease disease-modifying therapies and better methods of detection in early or pre-symptomatic phases are desperately needed and

data from human genetic studies have moved us much closer to those goals. Unfortunately, such studies have largely excluded individuals of non-European origin which risks further worsening existing health disparities for minority populations. The project seeks to address this gap in knowledge by studying the genetic architecture

of PD in African American and Latino participants in the Million Veteran Program (MVP) and other cohorts. The research team assembled for this project has extensive expertise in clinical movement disorders, bioinformatics, molecular genetics, and statistical genetics with specialized knowledge in mapping disease

genes in “admixed” (mixed ancestry) populations. This same group of investigators recently published the first and only admixture mapping analysis and genome-wide association study (GWAS) of PD ever conducted in a Latino population (based on a cohort from the Latin American Research Consortium on the Genetics of

Parkinson’s Disease [LARGE-PD]). The fundamental approach will be to perform two complementary techniques (1) admixture mapping, a technique that leverages local ancestry to identify regions of the genome where ancestry from a particular ancestral population is inherited more frequently in cases vs controls, and (2) Tractor GWAS, a new analytical

approach that unlike traditional GWAS methods is designed to accommodate admixed individuals. A Discovery sample will be created using cohorts from MVP and the Veterans Parkinson’s Disease Genetics Initiative (Vet- PD) and a Replication sample will be assembled from LARGE-PD and several publicly available datasets.

Admixture mapping and Tractor GWAS will first be performed on the Discovery Sample, analyzing each ancestry group separately and all groups combined. We will also perform the “variant-set test for association using annotation information” (STAAR) to perform gene-centric association tests of rare variants that are not

suitable for single-marker analyses (such as GWAS). These processes will be repeated in the Replication sample to validate results. Prioritization of candidate regions discovered will be performed using a combination of (1) physical position on the genome (positional mapping), (2) expression quantitative trait locus (eQTL)

mapping, and (3) chromatin interaction mapping. In addition, polygenic risk scores (PRS) will be calculated. A PRS is an estimate of an individual’s genetic liability to a trait or disease, calculated according to their genotype profile and relevant GWAS data. These scores have been applied to an increasing number of diseases with the eventual goal of risk stratification

followed by clinical interventions. But PRS models based on GWAS results from individuals of European origin are often less accurate when applied to non-European populations. Therefore, PRS models will be constructed from the European, African, and Latino components of the Discovery sample and their

performance will be compared across all three subgroups (e.g., Latino to African American and Latino to European American). Finally, findings from this project will be cross-validated with results from any other suitable studies that become available in future years. Results from this project will provide a better understanding of the genetic architecture of PD in African

Americans and Latinos which is important for two reasons. First it moves the field closer to a more equitable balance in the application of genetic information to clinical decisions in future years (e.g., PRS models). Second, it begins to unlock the potential for new PD gene discovery in non-European populations which will

further our understanding of PD pathophysiology.