Decomposing type 2 diabetes genetics into population-specific features by 600,000 East-Asians

Background : Type 2 diabetes (T2D) is a highly heterogeneous metabolic trait, with a higher prevalence in East Asians. This study aims to elucidate the East Asian-specific genetic architecture underlying T2D. Methods : We conducted the largest single-ancestry GWAS to date (596,778 East Asians) and performed one-to-one comparative analyses at high-resolution and in polygenic levels with a European meta-analysis with comparable effective sample sizes. Findings : The East Asian meta-analysis identified 196 T2D-associated loci, comparable to the 199 loci in the EUR meta-analysis. We found 69 SNPs (p<5x10-8) unique to either population, including six East Asian-specific missense variants with stronger effect sizes. Genetic correlation analysis revealed a strong similarity of polygenic architecture between the populations, yet statistical fine-mapping analyses highlighted distinct variant-gene interactions, particularly in pancreatic cells. We found distinct associations between lipid-related traits and T2D susceptibility—pathway analysis of heterogeneous loci revealed higher enrichment of lipid-related gene pathways in Europeans with a stronger effect size of adipose tissue-related epigenetic markers in Europeans. While genetic predisposition to insulin resistance was associated with increased T2D risk in Europeans, East Asians showed minimal differences between cases and controls. Genetic predisposition to HDL-C and BMI-adjusted waist-hip ratio was significantly associated with T2D risk in Europeans. However, the associations were not observed or much weaker in East Asians. Interpretation : Fine-scale genetic differences between populations, especially in lipid-related traits, underlie T2D susceptibility. Associations between insulin resistance and T2D susceptibility are distinct between East Asians and Europeans, in contrast to insulin secretion. Our findings highlight the importance of expanding single-ancestry genetic studies to gain deeper insights into the biology of complex traits.