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Large-scale analyses provide no evidence for gene-gene interactions influencing type 2 diabetes risk

Year: 2020

Type: other

Abstract: A growing number of genetic loci have been shown to influence individual predisposition to type 2 diabetes (T2D). Despite longstanding interest in understanding whether non-linear interactions between these risk-variants additionally influence T2D-risk, the ability to detect significant gene-gene interaction (GGI) effects has to date been limited. To increase power to detect GGI effects, we combined recent advances in the fine-mapping of causal T2D-risk variants with the increased sample size available within UK Biobank (375,736 unrelated European participants, including 16,430 T2D cases). In addition to conventional single variant-based analysis, we employed a complementary polygenic score-based approach which included partitioned T2D-risk scores that capture biological processes relevant to T2D pathophysiology. Nevertheless, we found no evidence in support of GGI effects influencing T2D-risk. The present study was powered to detect interactions between common variants with odds ratios >1.2, so these findings place limits on the contribution of GGIs to the overall heritability of T2D.

DOI: 10.2337/figshare.12827219.v1

Authors: Ada Admin, Abhishek Nag, Mark I McCarthy, Anubha Mahajan

Language: English

Topic: Genetic Associations and Epidemiology

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: gold

Funder: Medical Research Council

Award: Switching mammalian genes on and off during development, lineage specification, and differentiation, and its impact on human genetic disease

OpenAlex ID: W4252220310

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