Type 2 diabetes: genetic data sharing to advance complex disease research

Abstract

As with other complex diseases, unbiased association studies followed by physiological and experimental characterization have for years formed a paradigm for identifying genes or processes of relevance to type 2 diabetes mellitus (T2D). Recent large-scale common and rare variant genome-wide association studies (GWAS) suggest that substantially larger association studies are needed to identify most T2D loci in the population. To hasten clinical translation of genetic discoveries, new paradigms are also required to aid specialized investigation of nascent hypotheses. We argue for an integrated T2D knowledgebase, designed for a worldwide community to access aggregated large-scale genetic data sets, as one paradigm to catalyse convergence of these efforts.