Gallois, A., Mefford, J., Ko, A. et al. A comprehensive study of metabolite genetics reveals strong pleiotropy and heterogeneity across time and context. Nat Commun 10, 4788 (2019). https://doi.org/10.1038/s41467-019-12703-7
A comprehensive study of metabolite genetics reveals strong pleiotropy and heterogeneity across time and context
|Author:||Gallois, Apolline1; Mefford, Joel2; Ko, Arthur3;|
1Department of Computational Biology - USR 3756 CNRS, Institut Pasteur, Paris, France
2Department of Medicine, University of California, San Francisco, CA, USA
3Department of Human Genetics, University of California, Los Angeles, CA, USA
4Systems Epidemiology, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
5Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland
6NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland
7Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
8Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
9Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, The Alfred Hospital, Monash University, Melbourne, VIC, Australia
10Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
11Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
|Online Access:||PDF Full Text (PDF, 2.8 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe202003057324
|Publish Date:|| 2020-03-05
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.
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
1184 Genetics, developmental biology, physiology
This study was funded by National Institutes of Health (NIH) grants R03DE025665, R21HG007687, HL-095056, HL-28481, and U01 DK105561.
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