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

Hagenbeek, FA; Pool, R; van Dongen, J; Draisma, HHM; Jan Hottenga, J; Willemsen, G; Abdellaoui, A; ... Boomsma, DI; + view all (2020) Heritability estimates for 361 blood metabolites across 40 genome-wide association studies. Nature Communications , 11 (1) , Article 39. 10.1038/s41467-019-13770-6. Green open access

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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 (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.

Type: Article
Title: Heritability estimates for 361 blood metabolites across 40 genome-wide association studies
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1038/s41467-019-13770-6
Publisher version: https://doi.org/10.1038/s41467-019-13770-6
Language: English
Additional information: This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. - Correction issued 31/3/20
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics
URI: https://discovery.ucl.ac.uk/id/eprint/10091640
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