An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans

Abstract

To characterise type 2 diabetes (T2D) associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D cases and 132,532 controls of European ancestry after imputation using the 1000 Genomes multi-ethnic reference panel. Promising association signals were followed-up in additional data sets (of 14,545 or 7,397 T2D cases and 38,994 or 71,604 controls). We identified 13 novel T2D-associated loci (p<5×10-8), including variants near the GLP2R, GIP, and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common SNVs. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion, and in adipocytes, monocytes and hepatocytes for insulin action-associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology.

Patterns of differential gene expression in a cellular model of human islet development, and relationship to type 2 diabetes predisposition

“…Credible intervals were defined by the boundaries of the 99% credible sets of variants [24] from DIAGRAM (96 loci) [25] and ENGAGE (16 loci) [26] consortium data, respectively (ESM Table 10). A subset of 15 loci was considered to influence type 2 diabetes via beta cell dysfunction; these loci included ones causing hyperglycaemia, reduced insulin processing and secretion, and reduced fasting proinsulin levels [27,28] (ESM Table 11, ESM Methods).…”

Precision medicine in diabetes: an opportunity for clinical translation

“…45 To date, well over 100 genetic loci have been identified in successive waves of GWAS metaanalyses as robustly associated with T2D and/or related traits. [46][47][48][49][50][51][52] Comprehensive sequencing studies that capture both common and rare variation suggest that most genetic variation influencing T2D appears to reside at common variant sites. 11 Although genetic risk variants at these loci have modest effects on disease predisposition (collectively accounting for 10-15% of overall disease risk), 11,50 the knowledge gained has paved the way to elucidate the molecular taxonomy of the disease and the potential identification of novel therapeutic approaches.…”

A Decade of Genetic and Metabolomic Contributions to Type 2 Diabetes Risk Prediction

“…In contrast to candidate gene studies, GWAS offer an “hypothesis-free” approach and rapidly led to the discovery of dozens of new genetic loci associated with T2D [14••]. Including multi-ethnic populations in GWAS, meta-analyzing multiple GWAS to increase sample size, and performing imputation against reference sequences, all further expanded the number of loci to just over 100 [15•, 16, 17••, 18, 19]. The variants identified through GWAS thus far individually confer small increased risks of T2D (odds ratios generally less than 1.3) and, combined, they explain about an estimated 10–20% of the familial aggregation of the disease [15•, 17••, 20, 21].…”

“…Increasing sample sizes of genetic association studies will likely enable discovery of hundreds of additional loci. While such additional loci are expected to have decreasing magnitudes of effect sizes [15•, 24••], in aggregate, they may still facilitate improved T2D risk prediction.…”