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Cross-platform genetic discovery of small molecule products of metabolism and application to clinical outcomes

Luca A. Lotta, Maik Pietzner, Isobel D. Stewart, Laura B.L. 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 Sanderson, Albert Koulman, Fumiaki Imamura, Nita G. Forouhi, Kay-Tee Khaw, MacTel Consortium, Julian L. Griffin, Angela M. Wood, View ORCID ProfileGabi Kastenmüller, John Danesh, Adam S. Butterworth, Fiona M. Gribble, Frank Reimann, View ORCID ProfileMelanie Bahlo, Eric Fauman, Nicholas J. Wareham, Claudia Langenberg
doi: https://doi.org/10.1101/2020.02.03.932541
Luca A. Lotta
1MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
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Maik Pietzner
1MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
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Isobel D. Stewart
1MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
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Laura B.L. Wittemans
1MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
2The Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford
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Chen Li
1MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
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Roberto Bonelli
3Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Australia
4Department of Medical Biology, The University of Melbourne, Parkville, Australia
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Johannes Raffler
5Institute of Computational Biology, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
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Emma K. Biggs
6Metabolic Research Laboratories, University of Cambridge, Cambridge, United Kingdom
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Clare Oliver-Williams
7British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
8Homerton College, University of Cambridge, Cambridge, UK
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Victoria P.W. Auyeung
1MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
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Jian’an Luan
1MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
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Eleanor Wheeler
1MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
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Ellie Paige
9National Centre for Epidemiology and Population Health, The Australian National University, Canberra, Australia
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Praveen Surendran
7British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
10British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
11Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
12Rutherford Fund Fellow, Department of Public Health and Primary Care, University of Cambridge, UK
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Gregory A. Michelotti
13Metabolon Inc, Durham, North Carolina USA
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Robert A. Scott
1MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
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Stephen Burgess
14MRC Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom
15Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
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Verena Zuber
14MRC Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom
16Department of Epidemiology and Biostatistics, Imperial College London, UK
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Eleanor Sanderson
17MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, UK
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Albert Koulman
1MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
5Institute of Computational Biology, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
18NIHR BRC Nutritional Biomarker Laboratory, University of Cambridge, UK
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Fumiaki Imamura
1MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
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Nita G. Forouhi
1MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
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Kay-Tee Khaw
15Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
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Julian L. Griffin
19Biomolecular Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, UK
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Angela M. Wood
7British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
10British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
11Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
20National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
21The Alan Turing Institute, London, UK
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Gabi Kastenmüller
5Institute of Computational Biology, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
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  • ORCID record for Gabi Kastenmüller
John Danesh
7British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
10British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
11Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
20National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
22National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK
23Department of Human Genetics, Wellcome Sanger Institute, Hinxton, UK
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Adam S. Butterworth
7British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
10British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
11Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
20National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
22National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK
23Department of Human Genetics, Wellcome Sanger Institute, Hinxton, UK
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Fiona M. Gribble
6Metabolic Research Laboratories, University of Cambridge, Cambridge, United Kingdom
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Frank Reimann
6Metabolic Research Laboratories, University of Cambridge, Cambridge, United Kingdom
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Melanie Bahlo
3Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Australia
4Department of Medical Biology, The University of Melbourne, Parkville, Australia
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Eric Fauman
24Internal Medicine Research Unit, Pfizer Worldwide Research, Cambridge, MA 02142, USA
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Nicholas J. Wareham
1MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
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Claudia Langenberg
1MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
11Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
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  • For correspondence: claudia.langenberg@mrc-epid.cam.ac.uk
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Abstract

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.

Footnotes

  • We now include fine mapping of metabolite loci, multi-trait colocalization, network-based pleiotropy investigation, and extend statistical follow-up for the GLP2R missense variant. We extended methods sections and revised Figures 1 and 3. We upload Supplemental Material.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Cross-platform genetic discovery of small molecule products of metabolism and application to clinical outcomes
Luca A. Lotta, Maik Pietzner, Isobel D. Stewart, Laura B.L. 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 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 Fauman, Nicholas J. Wareham, Claudia Langenberg
bioRxiv 2020.02.03.932541; doi: https://doi.org/10.1101/2020.02.03.932541
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Cross-platform genetic discovery of small molecule products of metabolism and application to clinical outcomes
Luca A. Lotta, Maik Pietzner, Isobel D. Stewart, Laura B.L. 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 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 Fauman, Nicholas J. Wareham, Claudia Langenberg
bioRxiv 2020.02.03.932541; doi: https://doi.org/10.1101/2020.02.03.932541

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