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

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 inte...

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Autores principales: Gallois, Apolline, Mefford, Joel, Ko, Arthur, Vaysse, Amaury, Julienne, Hanna, Ala-Korpela, Mika, Laakso, Markku, Zaitlen, Noah, Pajukanta, Päivi, Aschard, Hugues
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6803661/
https://www.ncbi.nlm.nih.gov/pubmed/31636271
http://dx.doi.org/10.1038/s41467-019-12703-7
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author Gallois, Apolline
Mefford, Joel
Ko, Arthur
Vaysse, Amaury
Julienne, Hanna
Ala-Korpela, Mika
Laakso, Markku
Zaitlen, Noah
Pajukanta, Päivi
Aschard, Hugues
author_facet Gallois, Apolline
Mefford, Joel
Ko, Arthur
Vaysse, Amaury
Julienne, Hanna
Ala-Korpela, Mika
Laakso, Markku
Zaitlen, Noah
Pajukanta, Päivi
Aschard, Hugues
author_sort Gallois, Apolline
collection PubMed
description 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.
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spelling pubmed-68036612019-10-23 A comprehensive study of metabolite genetics reveals strong pleiotropy and heterogeneity across time and context Gallois, Apolline Mefford, Joel Ko, Arthur Vaysse, Amaury Julienne, Hanna Ala-Korpela, Mika Laakso, Markku Zaitlen, Noah Pajukanta, Päivi Aschard, Hugues Nat Commun Article 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. Nature Publishing Group UK 2019-10-21 /pmc/articles/PMC6803661/ /pubmed/31636271 http://dx.doi.org/10.1038/s41467-019-12703-7 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Gallois, Apolline
Mefford, Joel
Ko, Arthur
Vaysse, Amaury
Julienne, Hanna
Ala-Korpela, Mika
Laakso, Markku
Zaitlen, Noah
Pajukanta, Päivi
Aschard, Hugues
A comprehensive study of metabolite genetics reveals strong pleiotropy and heterogeneity across time and context
title A comprehensive study of metabolite genetics reveals strong pleiotropy and heterogeneity across time and context
title_full A comprehensive study of metabolite genetics reveals strong pleiotropy and heterogeneity across time and context
title_fullStr A comprehensive study of metabolite genetics reveals strong pleiotropy and heterogeneity across time and context
title_full_unstemmed A comprehensive study of metabolite genetics reveals strong pleiotropy and heterogeneity across time and context
title_short A comprehensive study of metabolite genetics reveals strong pleiotropy and heterogeneity across time and context
title_sort comprehensive study of metabolite genetics reveals strong pleiotropy and heterogeneity across time and context
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6803661/
https://www.ncbi.nlm.nih.gov/pubmed/31636271
http://dx.doi.org/10.1038/s41467-019-12703-7
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