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

Author

Listed:
  • 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
    University of Oulu and Biocenter Oulu
    University of Eastern Finland
    University of Bristol)

  • Markku Laakso

    (University of Eastern Finland and Kuopio University Hospital)

  • Noah Zaitlen

    (University of California)

  • Päivi Pajukanta

    (University of California)

  • Hugues Aschard

    (Institut Pasteur
    Harvard T.H. Chan School of Public Health)

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.

Suggested Citation

  • Apolline Gallois & Joel Mefford & Arthur Ko & Amaury Vaysse & Hanna Julienne & Mika Ala-Korpela & Markku Laakso & Noah Zaitlen & Päivi Pajukanta & Hugues Aschard, 2019. "A comprehensive study of metabolite genetics reveals strong pleiotropy and heterogeneity across time and context," Nature Communications, Nature, vol. 10(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-12703-7
    DOI: 10.1038/s41467-019-12703-7
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    Cited by:

    1. Linda Ottensmann & Rubina Tabassum & Sanni E. Ruotsalainen & Mathias J. Gerl & Christian Klose & Elisabeth Widén & Kai Simons & Samuli Ripatti & Matti Pirinen, 2023. "Genome-wide association analysis of plasma lipidome identifies 495 genetic associations," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    2. Andrew A. Brown & Juan J. Fernandez-Tajes & Mun-gwan Hong & Caroline A. Brorsson & Robert W. Koivula & David Davtian & Théo Dupuis & Ambra Sartori & Theodora-Dafni Michalettou & Ian M. Forgie & Jonath, 2023. "Genetic analysis of blood molecular phenotypes reveals common properties in the regulatory networks affecting complex traits," Nature Communications, Nature, vol. 14(1), pages 1-17, December.

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