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Heritability estimates for 361 blood metabolites across 40 genome-wide association studies.

Authors :
Hagenbeek, Fiona A.
Pool, René
van Dongen, Jenny
Draisma, Harmen H. M.
Jan Hottenga, Jouke
Willemsen, Gonneke
Abdellaoui, Abdel
Fedko, Iryna O.
den Braber, Anouk
Visser, Pieter Jelle
de Geus, Eco J. C. N.
Willems van Dijk, Ko
Verhoeven, Aswin
Suchiman, H. Eka
Beekman, Marian
Slagboom, P. Eline
van Duijn, Cornelia M.
BBMRI Metabolomics Consortium
Barkey Wolf, J. J. H.
Cats, D.
Source :
Nature Communications; 1/7/2020, Vol. 11 Issue 1, p1-11, 11p
Publication Year :
2020

Abstract

Metabolomics examines the small molecules involved in cellular metabolism. Approximately 50% of total phenotypic differences in metabolite levels is due to genetic variance, but heritability estimates differ across metabolite classes. We perform a review of all genome-wide association and (exome-) sequencing studies published between November 2008 and October 2018, and identify >800 class-specific metabolite loci associated with metabolite levels. In a twin-family cohort (N = 5117), these metabolite loci are leveraged to simultaneously estimate total heritability (h<superscript>2</superscript><subscript>total</subscript>), and the proportion of heritability captured by known metabolite loci (h<superscript>2</superscript><subscript>Metabolite-hits</subscript>) for 309 lipids and 52 organic acids. Our study reveals significant differences in h<superscript>2</superscript><subscript>Metabolite-hits</subscript> among different classes of lipids and organic acids. Furthermore, phosphatidylcholines with a high degree of unsaturation have higher h<superscript>2</superscript><subscript>Metabolite-hits</subscript> estimates than phosphatidylcholines with low degrees of unsaturation. This study highlights the importance of common genetic variants for metabolite levels, and elucidates the genetic architecture of metabolite classes. Blood metabolite levels are under the influence of environmental and genetic factors. Here, Hagenbeek et al. perform heritability estimations for metabolite measures and determine the contribution of known metabolite loci to metabolite levels using data from 40 genome-wide association studies. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20411723
Volume :
11
Issue :
1
Database :
Complementary Index
Journal :
Nature Communications
Publication Type :
Academic Journal
Accession number :
141099454
Full Text :
https://doi.org/10.1038/s41467-019-13770-6