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

Fiona A. Hagenbeek (), René Pool, Jenny Dongen, Harmen H. M. Draisma, Jouke Hottenga, Gonneke Willemsen, Abdel Abdellaoui, Iryna O. Fedko, Anouk Braber, Pieter Jelle Visser, Eco J. C. N. Geus, Ko Willems van Dijk, Aswin Verhoeven, H. Eka Suchiman, Marian Beekman, P. Eline Slagboom, Cornelia M. Duijn, Amy C. Harms, Thomas Hankemeier, Meike Bartels, Michel G. Nivard () and Dorret I. Boomsma ()
Additional contact information
Fiona A. Hagenbeek: Vrije Universiteit Amsterdam
René Pool: Vrije Universiteit Amsterdam
Jenny Dongen: Vrije Universiteit Amsterdam
Harmen H. M. Draisma: Vrije Universiteit Amsterdam
Jouke Hottenga: Vrije Universiteit Amsterdam
Gonneke Willemsen: Vrije Universiteit Amsterdam
Abdel Abdellaoui: Vrije Universiteit Amsterdam
Iryna O. Fedko: Vrije Universiteit Amsterdam
Anouk Braber: Vrije Universiteit Amsterdam
Pieter Jelle Visser: Alzheimer Center Amsterdam, Department of Neurology, VU Amsterdam, Amsterdam UMC
Eco J. C. N. Geus: Vrije Universiteit Amsterdam
Ko Willems van Dijk: Leiden University Medical Center
Aswin Verhoeven: Leiden University Medical Center
H. Eka Suchiman: Leiden University Medical Center
Marian Beekman: Leiden University Medical Center
P. Eline Slagboom: Leiden University Medical Center
Cornelia M. Duijn: Erasmus Medical Center
Amy C. Harms: Leiden Academic Center for Drug Research, Leiden University and The Netherlands Metabolomics Centre
Thomas Hankemeier: Leiden Academic Center for Drug Research, Leiden University and The Netherlands Metabolomics Centre
Meike Bartels: Vrije Universiteit Amsterdam
Michel G. Nivard: Vrije Universiteit Amsterdam
Dorret I. Boomsma: Vrije Universiteit Amsterdam

Nature Communications, 2020, vol. 11, issue 1, 1-11

Abstract: 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 (h2total), and the proportion of heritability captured by known metabolite loci (h2Metabolite-hits) for 309 lipids and 52 organic acids. Our study reveals significant differences in h2Metabolite-hits among different classes of lipids and organic acids. Furthermore, phosphatidylcholines with a high degree of unsaturation have higher h2Metabolite-hits 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.

Date: 2020
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DOI: 10.1038/s41467-019-13770-6

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