Cross-platform genetic discovery of small molecule products of metabolism and application to clinical outcomes
By
Luca A Lotta,
Maik Pietzner,
Isobel D Stewart,
Laura BL. Wittemans,
Chen Li,
Roberto Bonelli,
Johannes Raffler,
Emma K. Biggs,
Clare Oliver-Williams,
Victoria P.W. Auyeung,
Jian’an Luan,
Eleanor Wheeler,
Ellie Paige,
Praveen Surendran,
Gregory A Michelotti,
Robert A Scott,
Stephen Burgess,
Verena Zuber,
Eleanor N Sanderson,
Albert Koulman,
Fumiaki Imamura,
Nita G Forouhi,
Kay-Tee Khaw,
MacTel Consortium,
Julian L. Griffin,
Angela M. Wood,
Gabi Kastenmüller,
John Danesh,
Adam S. Butterworth,
Fiona M. Gribble,
Frank Reimann,
Melanie Bahlo,
Eric B. Fauman,
Nicholas J. Wareham,
Claudia Langenberg
Posted 04 Feb 2020
bioRxiv DOI: 10.1101/2020.02.03.932541
Circulating levels of small molecules or metabolites are highly heritable, but the impact of genetic differences in metabolism on human health is not well understood. In this cross-platform, genome-wide meta-analysis of 174 metabolite levels across six cohorts including up to 86,507 participants (70% unpublished data), we identify 499 (362 novel) genome-wide significant associations (p<4.9×10-10) at 144 (94 novel) genomic regions. We show that inheritance of blood metabolite levels in the general population is characterized by pleiotropy, allelic heterogeneity, rare and common variants with large effects, non-linear associations, and enrichment for nonsynonymous variation in transporter and enzyme encoding genes. The majority of identified genes are known to be involved in biochemical processes regulating metabolite levels and to cause monogenic inborn errors of metabolism linked to specific metabolites, such as ASNS (rs17345286, MAF=0.27) and asparagine levels. We illustrate the influence of metabolite-associated variants on human health including a shared signal at GLP2R (p.Asp470Asn) associated with higher citrulline levels, body mass index, fasting glucose-dependent insulinotropic peptide and type 2 diabetes risk, and demonstrate beta-arrestin signalling as the underlying mechanism in cellular models. We link genetically-higher serine levels to a 95% reduction in the likelihood of developing macular telangiectasia type 2 [odds ratio (95% confidence interval) per standard deviation higher levels 0.05 (0.03-0.08; p=9.5×10-30)]. We further demonstrate the predictive value of genetic variants identified for serine or glycine levels for this rare and difficult to diagnose degenerative retinal disease [area under the receiver operating characteristic curve: 0.73 (95% confidence interval: 0.70-0.75)], for which low serine availability, through generation of deoxysphingolipids, has recently been shown to be causally relevant. These results show that integration of human genomic variation with circulating small molecule data obtained across different measurement platforms enables efficient discovery of genetic regulators of human metabolism and translation into clinical insights. ### Competing Interest Statement A.S.B. has received grants from AstraZeneca, Biogen, Bioverativ, Merck, Novartis, and Sanofi. J. D. sits on the International Cardiovascular and Metabolic Advisory Board for Novartis (since 2010), the Steering Committee of UK Biobank (since 2011), the MRC International Advisory Group (ING) member, London (since 2013), the MRC High Throughput Science Omics Panel Member, London (since 2013), the Scientific Advisory Committee for Sanofi (since 2013), the International Cardiovascular and Metabolism Research and Development Portfolio Committee for Novartis and the Astra Zeneca Genomics Advisory Board (2018). E.B.F. is an employee and stock holder of Pfizer.
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