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

BBMRI Metabolomics Consortium, Fiona A. Hagenbeek*, Rene Pool, Jenny van Dongen, Harmen H. M. Draisma, Jouke Jan Hottenga, Gonneke Willemsen, Abdel Abdellaoui, Iryna O. Fedko, Anouk den Braber, Pieter Jelle Visser, Eco J. C. N. de Geus, Ko Willems van Dijk, Aswin Verhoeven, H. Eka Suchiman, Marian Beekman, P. Eline Slagboom, Cornelia M. van Duijn, Amy C. Harms, Thomas HankemeierMeike Bartels, Michel G. Nivard, Dorret I. Boomsma

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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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 (h2 total), and the proportion of heritability captured by known metabolite loci (h2 Metabolite-hits) for 309 lipids and 52 organic acids. Our study reveals significant differences in h2 Metabolite-hits among different classes of lipids and organic acids. Furthermore, phosphatidylcholines with a high degree of unsaturation have higher h2 Metabolite-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.

Original languageEnglish
Article number39
Number of pages11
JournalNature Communications
Volume11
Issue number1
DOIs
Publication statusPublished - 7-Jan-2020

Keywords

  • NETHERLANDS TWIN REGISTER
  • MISSING HERITABILITY
  • GENOTYPE IMPUTATION
  • VARIANCE-ESTIMATION
  • METABOLOMICS
  • SELECTION
  • DATABASE
  • BIOBANK

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