245-OR: Comprehensive Genome-Wide Association Study (GWAS) Meta-analysis Using TOPMed Imputation in Latinos Identifies Rare Variation Associated with Type 2 Diabetes (T2D)

The high prevalence of T2D among Latino individuals emphasizes the importance of studying both environmental and genetic factors that influence disease in this population. However, Latino is a recently admixed population with complex linkage disequilibrium patterns that impose methodological challenges, especially when using genotype imputation to test association with rare variation. The recent release of the multi-ethnic NHLBI Trans-Omics for Precision Medicine (TOPMed) reference panel, comprising more than 100,000 samples (~10% are Latinos), represents a unique opportunity to explore rare genetic variation in this population.

We performed the largest T2D GWAS meta-analysis in the Latino population imputed to the TOPMed panel. Our analysis includes 18,294 individuals (7,556 cases and 10,738 controls) with genotyping array and whole-exome sequencing data. We were able to impute 38M high-quality variants (rsq>0.8) with TOPMed (5M with minor allele frequency [MAF] 0.001-0.0005) compared to 16M with 1000G Phase 3 panel (1.6M with [MAF] 0.001-0.0005). This allowed us to replicate previously reported T2D-associated common variants, and to identify a novel genome-wide significant variant (MAF=0.016, OR=2.06, P=1.7×10^-9) near ORC5, a gene implicated in familial hyperinsulinemic hypoglycemia 2. Two additional suggestive novel signals merit further research: a variant in ROR2 (MAF=0.066, OR=1.3, P=8.8×10^-8) and a Latino specific variant in HDAC2 only identified with the use of TOPMed (MAF=0.013, OR=1.82, P=3.2×10^-7) and associated with insulin secretion in individuals without diabetes in this study.

Our results demonstrate the utility of the TOPMed imputation for the identification of novel and population-specific rare variation associated with T2D in understudied populations, which could lead to the identification of novel therapeutic targets and the improvement of polygenic risk scores.