Genetic discovery and translational decision support from exome sequencing of 20,791 type 2 diabetes cases and 24,440 controls from five ancestries

Abstract

Protein-coding genetic variants that strongly affect disease risk can provide important clues into disease pathogenesis. Here we report an exome sequence analysis of 20,791 type 2 diabetes (T2D) cases and 24,440 controls from five ancestries. We identify rare (minor allele frequency<0.5%) variant gene-level associations in (a) three genes at exome-wide significance, including a T2D-protective series of >30 SLC30A8 alleles, and (b) within 12 gene sets, including those corresponding to T2D drug targets (p=6.1×10⁻³) and candidate genes from knockout mice (p=5.2×10⁻³). Within our study, the strongest T2D rare variant gene-level signals explain at most 25% of the heritability of the strongest common single-variant signals, and the rare variant gene-level effect sizes we observe in established T2D drug targets will require 110K-180K sequenced cases to exceed exome-wide significance. To help prioritize genes using associations from current smaller sample sizes, we present a Bayesian framework to recalibrate association p-values as posterior probabilities of association, estimating that reaching p<0.05 (p<0.005) in our study increases the odds of causal T2D association for a nonsynonymous variant by a factor of 1.8 (5.3). To help guide target or gene prioritization efforts, our data are freely available for analysis at www.type2diabetesgenetics.org.