The Genetic Drivers of Juvenile, Young, and Early-Onset Parkinson's Disease in India.

BACKGROUND: Recent studies have advanced our understanding of the genetic drivers of Parkinson's disease (PD). Rare variants in more than 20 genes are considered causal for PD, and the latest PD genome-wide association study (GWAS) identified 90 independent risk loci. However, there remains a gap in our understanding of PD genetics outside of the European populations in which the vast majority of these studies were focused. OBJECTIVE: The aim was to identify genetic risk factors for PD in a South Asian population. METHODS: A total of 674 PD subjects predominantly with age of onset (AoO) ≤50 years (encompassing juvenile, young, or early-onset PD) were recruited from 10 specialty movement disorder centers across India over a 2-year period; 1376 control subjects were selected from the reference population GenomeAsia, Phase 2. We performed various case-only and case-control genetic analyses for PD diagnosis and AoO. RESULTS: A genome-wide significant signal for PD diagnosis was identified in the SNCA region, strongly colocalizing with SNCA region signal from European PD GWAS. PD cases with pathogenic mutations in PD genes exhibited, on average, lower PD polygenic risk scores than PD cases lacking any PD gene mutations. Gene burden studies of rare, predicted deleterious variants identified BSN, encoding the presynaptic protein Bassoon that has been previously associated with neurodegenerative disease. CONCLUSIONS: This study constitutes the largest genetic investigation of PD in a South Asian population to date. Future work should seek to expand sample numbers in this population to enable improved statistical power to detect PD genes in this understudied group. © 2023 Denali Therapeutics and The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

South Asian medical cohorts reveal strong founder effects and high rates of homozygosity.

The benefits of large-scale genetic studies for healthcare of the populations studied are well documented, but these genetic studies have traditionally ignored people from some parts of the world, such as South Asia. Here we describe whole genome sequence (WGS) data from 4806 individuals recruited from the healthcare delivery systems of Pakistan, India and Bangladesh, combined with WGS from 927 individuals from isolated South Asian populations. We characterize population structure in South Asia and describe a genotyping array (SARGAM) and imputation reference panel that are optimized for South Asian genomes. We find evidence for high rates of reproductive isolation, endogamy and consanguinity that vary across the subcontinent and that lead to levels of rare homozygotes that reach 100 times that seen in outbred populations. Founder effects increase the power to associate functional variants with disease processes and make South Asia a uniquely powerful place for population-scale genetic studies.

Validation of a Genome-Wide Polygenic Score for Coronary Artery Disease in South Asians.

BACKGROUND: Genome-wide polygenic scores (GPS) integrate information from many common DNA variants into a single number. Because rates of coronary artery disease (CAD) are substantially higher among South Asians, a GPS to identify high-risk individuals may be particularly useful in this population. OBJECTIVES: This analysis used summary statistics from a prior genome-wide association study to derive a new GPSCAD for South Asians. METHODS: This GPSCAD was validated in 7,244 South Asian UK Biobank participants and tested in 491 individuals from a case-control study in Bangladesh. Next, a static ancestry and GPSCAD reference distribution was built using whole-genome sequencing from 1,522 Indian individuals, and a framework was tested for projecting individuals onto this static ancestry and GPSCAD reference distribution using 1,800 CAD cases and 1,163 control subjects newly recruited in India. RESULTS: The GPSCAD, containing 6,630,150 common DNA variants, had an odds ratio (OR) per SD of 1.58 in South Asian UK Biobank participants and 1.60 in the Bangladeshi study (p < 0.001 for each). Next, individuals of the Indian case-control study were projected onto static reference distributions, observing an OR/SD of 1.66 (p < 0.001). Compared with the middle quintile, risk for CAD was most pronounced for those in the top 5% of the GPSCAD distribution-ORs of 4.16, 2.46, and 3.22 in the South Asian UK Biobank, Bangladeshi, and Indian studies, respectively (p < 0.05 for each). CONCLUSIONS: The new GPSCAD has been developed and tested using 3 distinct South Asian studies, and provides a generalizable framework for ancestry-specific GPS assessment.