A comprehensive study of metabolite genetics reveals strong pleiotropy and heterogeneity across time and context

Apolline Gallois; Joel Mefford; Arthur Ko; Amaury Vaysse; Hanna Julienne; Mika Ala-Korpela; Markku Laakso; Noah Zaitlen; Päivi Pajukanta; Hugues Aschard

doi:10.1038/s41467-019-12703-7

Nature Communications (Oct 2019)

A comprehensive study of metabolite genetics reveals strong pleiotropy and heterogeneity across time and context

Apolline Gallois,
Joel Mefford,
Arthur Ko,
Amaury Vaysse,
Hanna Julienne,
Mika Ala-Korpela,
Markku Laakso,
Noah Zaitlen,
Päivi Pajukanta,
Hugues Aschard

Affiliations

Apolline Gallois: Department of Computational Biology - USR 3756 CNRS, Institut Pasteur
Joel Mefford: Department of Medicine, University of California
Arthur Ko: Department of Human Genetics, University of California
Amaury Vaysse: Department of Computational Biology - USR 3756 CNRS, Institut Pasteur
Hanna Julienne: Department of Computational Biology - USR 3756 CNRS, Institut Pasteur
Mika Ala-Korpela: Systems Epidemiology, Baker Heart and Diabetes Institute
Markku Laakso: Department of Medicine, University of Eastern Finland and Kuopio University Hospital
Noah Zaitlen: Department of Medicine, University of California
Päivi Pajukanta: Department of Human Genetics, University of California
Hugues Aschard: Department of Computational Biology - USR 3756 CNRS, Institut Pasteur

DOI: https://doi.org/10.1038/s41467-019-12703-7
Journal volume & issue: Vol. 10, no. 1
pp. 1 – 13

Abstract

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Genome-wide association studies of metabolites have revealed hundreds of genetic associations using univariate analyses. Here, the authors use a multivariate approach to perform association analyses for 158 serum metabolites, followed by fine mapping and GxE interaction tests with statin use and age.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

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