Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes

Dorret Boomsma, Michel G. Nivard, eQTLGen Consortium

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Type 2 diabetes (T2D) is a very common disease in humans. Here we conduct a meta-analysis of genome-wide association studies (GWAS) with ~16 million genetic variants in 62,892 T2D cases and 596,424 controls of European ancestry. We identify 139 common and 4 rare variants associated with T2D, 42 of which (39 common and 3 rare variants) are independent of the known variants. Integration of the gene expression data from blood (n = 14,115 and 2765) with the GWAS results identifies 33 putative functional genes for T2D, 3 of which were targeted by approved drugs. A further integration of DNA methylation (n = 1980) and epigenomic annotation data highlight 3 genes (CAMK1D, TP53INP1, and ATP5G1) with plausible regulatory mechanisms, whereby a genetic variant exerts an effect on T2D through epigenetic regulation of gene expression. Our study uncovers additional loci, proposes putative genetic regulatory mechanisms for T2D, and provides evidence of purifying selection for T2D-associated variants.

Original languageEnglish
Article number2941
Number of pages14
JournalNature Communications
Volume9
Issue number1
DOIs
Publication statusPublished - 27 Jul 2018

Funding

This research was supported by the Australian National Health and Medical Research Council (1107258, 1083656, 1078037, and 1113400), Australian Research Council grants (DP160101056, DP160103860, and DP160102400), the US National Institutes of Health (R01 MH100141, P01 GM099568, R01 GM075091, R01 AG042568, and R21 ES025052), and the Sylvia & Charles Viertel Charitable Foundation. Yeda Wu is supported by the F.G. Meade Scholarship and UQ Research Training Scholarship from the University of Queensland. This study makes use of data from dbGaP (accession: phs000674.v2.p2) and UK Biobank (project ID: 12505). A full list of acknowledgments of these data sets can be found in Supplementary Note 13.

FundersFunder number
Australian National Health and Medical Research Council1107258, 1083656, 1113400, 1078037
US National Institutes of HealthR21 ES025052, R01 AG042568, P01 GM099568, R01 GM075091, R01 MH100141
National Institute on AgingR01AG042568
Sylvia and Charles Viertel Charitable Foundation
Australian Research CouncilDP160102400, DP160101056, DP160103860
University of Queensland

    Cohort Studies

    • Netherlands Twin Register (NTR)

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