Type 2 diabetes is a chronic metabolic disease characterised by elevated levels of glucose in the blood, and presents a major and growing global public health challenge. While both genes and our environment influence the development of the disease, the underlying mechanisms are still not fully understood. The data provided by genome-wide association studies (GWAS) can help identify genetic risk factors and generate hypotheses to direct in-depth investigations that, in turn, help us better understand the biology of type 2 diabetes.

In a paper published today in Scientific Data, we describe the results from a GWAS examining  more than 8.9 million genetic variations and T2D risk among 22,326 individuals in the EPIC-InterAct study. A problem facing researchers undertaking genetic research on type 2 diabetes is that GWAS data is not publicly available for individual studies, so we decided to make the summary GWAS statistics for this study available on an open platform for researchers to use.

The EPIC-InterAct study, led by Professor Nick Wareham, is the world’s largest prospective case-cohort study of incident type 2 diabetes, established across 8 European countries and nested within the pan-European EPIC study. Volunteers provided extensive demographic, socio-economic and lifestyle information, as well as blood samples for genotyping and metabolic profiling. During almost 4 million person-years of follow-up time among 340,234 participants, researchers identified a total of 12,403 new cases of type 2 diabetes.

In this study, we have assessed the associations of more than 8.9 million genetic variants across the genome with type 2 diabetes in 22,326 individuals of European ancestry, which includes both individuals with incident type 2 diabetes and individuals randomly selected at the start of the study to be representative of the study population as a whole. Because the  EPIC-InterAct study followed participants not yet diagnosed with type 2 diabetes over time, we were also able to examine the associations of 370 previously established type 2 diabetes genetic variants with the risk of being diagnosed with type 2 diabetes. These are the first publicly available results for such incident diabetes risk.

With the publication of this study, we aim to provide a valuable resource for the research community to conduct further genetic investigations in diabetes aetiological studies. Therefore, we have shared the full genome-wide association results in free publicly available databases, including the Dryad Data Repository and the GWAS Catalog. We hope this will encourage and facilitate future use of this resource, promote an ‘open science’ culture and cultivate wider collaborations.

• Cai L, Wheeler E, Kerrison ND, Luan J, Deloukas P et al. Genome-wide association analysis of type 2 diabetes in the EPIC-InterAct study. Sci Data (2020) 7, 393. DOI: 10.1038/s41597-020-00716-7