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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
Nature communications | 2019

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.

Pubmed ID: 31636271

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Associated grants

  • Agency: NCI NIH HHS, United States
    Id: R01 CA227237
  • Agency: NIDCR NIH HHS, United States
    Id: R03 DE025665
  • Agency: NHGRI NIH HHS, United States
    Id: R01 HG006399
  • Agency: NHLBI NIH HHS, United States
    Id: P01 HL028481
  • Agency: NIDDK NIH HHS, United States
    Id: U01 DK105561
  • Agency: NHLBI NIH HHS, United States
    Id: R01 HL095056
  • Agency: NHGRI NIH HHS, United States
    Id: R21 HG007687
  • Agency: NHLBI NIH HHS, United States
    Id: K25 HL121295

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R Project for Statistical Computing (tool)

RRID:SCR_001905

Software environment and programming language for statistical computing and graphics. R is integrated suite of software facilities for data manipulation, calculation and graphical display. Can be extended via packages. Some packages are supplied with the R distribution and more are available through CRAN family.It compiles and runs on wide variety of UNIX platforms, Windows and MacOS.

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Cytoscape (tool)

RRID:SCR_003032

Software platform for complex network analysis and visualization. Used for visualization of molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data.

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