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 () and Hugues Aschard ()
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Apolline Gallois: Institut Pasteur
Joel Mefford: University of California
Arthur Ko: University of California
Amaury Vaysse: Institut Pasteur
Hanna Julienne: Institut Pasteur
Mika Ala-Korpela: Baker Heart and Diabetes Institute
Markku Laakso: University of Eastern Finland and Kuopio University Hospital
Noah Zaitlen: University of California
Päivi Pajukanta: University of California
Hugues Aschard: Institut Pasteur

Nature Communications, 2019, vol. 10, issue 1, 1-13

Abstract: Abstract Genetic studies of metabolites have identified thousands of variants, many of which are associated with downstream metabolic and obesogenic disorders. However, these studies have relied on univariate analyses, reducing power and limiting context-specific understanding. Here we aim to provide an integrated perspective of the genetic basis of metabolites by leveraging the Finnish Metabolic Syndrome In Men (METSIM) cohort, a unique genetic resource which contains metabolic measurements, mostly lipids, across distinct time points as well as information on statin usage. We increase effective sample size by an average of two-fold by applying the Covariates for Multi-phenotype Studies (CMS) approach, identifying 588 significant SNP-metabolite associations, including 228 new associations. Our analysis pinpoints a small number of master metabolic regulator genes, balancing the relative proportion of dozens of metabolite levels. We further identify associations to changes in metabolic levels across time as well as genetic interactions with statin at both the master metabolic regulator and genome-wide level.

Date: 2019
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DOI: 10.1038/s41467-019-12703-7

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