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Diverse type 2 diabetes genetic risk factors functionally converge in a phenotype-focused gene network

Sandor, Cynthia ORCID: https://orcid.org/0000-0002-8905-1052, Beer, Nicola L. and Webber, Caleb ORCID: https://orcid.org/0000-0001-8063-7674 2017. Diverse type 2 diabetes genetic risk factors functionally converge in a phenotype-focused gene network. PLoS Computational Biology 13 (10) , e1005816. 10.1371/journal.pcbi.1005816

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Abstract

Type 2 Diabetes (T2D) constitutes a global health burden. Efforts to uncover predisposing genetic variation have been considerable, yet detailed knowledge of the underlying pathogenesis remains poor. Here, we constructed a T2D phenotypic-linkage network (T2D-PLN), by integrating diverse gene functional information that highlight genes, which when disrupted in mice, elicit similar T2D-relevant phenotypes. Sensitising the network to T2D-relevant phenotypes enabled significant functional convergence to be detected between genes implicated in monogenic or syndromic diabetes and genes lying within genomic regions associated with T2D common risk. We extended these analyses to a recent multiethnic T2D case-control exome of 12,940 individuals that found no evidence of T2D risk association for rare frequency variants outside of previously known T2D risk loci. Examining associations involving protein-truncating variants (PTV), most at low population frequencies, the T2D-PLN was able to identify a convergent set of biological pathways that were perturbed within four of five independent T2D case/control ethnic sets of 2000 to 5000 exomes each. These same pathways were found to be over-represented among both known monogenic or syndromic diabetes genes and genes within T2D-associated common risk loci. Our study demonstrates convergent biology amongst variants representing different classes of T2D genetic risk. Although convergence was observed at the pathway level, few of the contributing genes were found in common between different cohorts or variant classes, most notably between the exome variant sets which suggests that future rare variant studies may be better focusing their power onto a single population of recent common ancestry.

Item Type: Article
Date Type: Published Online
Status: Published
Schools: Medicine
Publisher: Public Library of Science
ISSN: 1553-734X
Date of First Compliant Deposit: 21 October 2020
Date of Acceptance: 11 October 2017
Last Modified: 04 May 2023 06:30
URI: https://orca.cardiff.ac.uk/id/eprint/135794

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