A cross-platform approach identifies genetic regulators of human metabolism and health.
Accepted version
Peer-reviewed
Repository URI
Repository DOI
Change log
Authors
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.
Description
Keywords
Journal Title
Conference Name
Journal ISSN
1546-1718
Volume Title
Publisher
Publisher DOI
Rights
Sponsorship
Medical Research Council (MC_UU_12012/3)
Medical Research Council (MR/N003284/1)
Medical Research Council (MR/P011705/1)
Medical Research Council (MR/P01836X/1)
Medical Research Council (MR/S003746/1)
Medical Research Council (MC_PC_13030)
MRC (MC_UU_00006/1)
Medical Research Council (MR/L003120/1)
British Heart Foundation (None)
British Heart Foundation (RG/18/13/33946)
Department of Health (via National Institute for Health Research (NIHR)) (NF-SI-0617-10149)
Medical Research Council (G1000143)
Medical Research Council (G0500300)
Medical Research Council (G0401527)
Medical Research Council (MC_UU_00002/7)
MRC (MC_UU_00014/3)
MRC (MC_UU_00014/5)
Wellcome Trust (204623/Z/16/Z)
British Heart Foundation (CH/12/2/29428)
Medical Research Council (MC_UU_12012/5)
Medical Research Council (MC_PC_12012)