A cross-platform approach identifies genetic regulators of human metabolism and health
Date
2021
Authors
Lotta, Luca A.
Pietzner, Maik
Stewart, Isobel D.
Wittemans, Laura B. L.
Li, Chen
Bonelli, Roberto
Raffler, Johannes
Biggs, Emma K.
Oliver-Williams, Clare
Auyeung, Victoria P. W.
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Nature Publishing Group
Abstract
In cross-platform analyses of 174 metabolites, we identify 499 associations (P < 4.9 × 10−10) characterized by pleiotropy, allelic heterogeneity, large and nonlinear effects and enrichment for nonsynonymous variation. We identify a signal at GLP2R (p.Asp470Asn) shared among higher citrulline levels, body mass index, fasting glucose-dependent insulinotropic peptide and type 2 diabetes, with β-arrestin signaling as the underlying mechanism. Genetically higher serine levels are shown to reduce the likelihood (by 95%) and predict development of macular telangiectasia type 2, a rare degenerative retinal disease. Integration of genomic and small molecule data across platforms enables the discovery of regulators of human metabolism and translation into clinical insights.
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Nature Genetics
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Journal article
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2099-12-31
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