Heritability estimates for 361 blood metabolites across 40 genome-wide association studies
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-) s...
Saved in:
Published in | Nature communications Vol. 11; no. 1; pp. 39 - 11 |
---|---|
Main Authors | , , , , , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
London
Nature Publishing Group UK
07.01.2020
Nature Publishing Group Nature Portfolio |
Subjects | |
Online Access | Get full text |
ISSN | 2041-1723 2041-1723 |
DOI | 10.1038/s41467-019-13770-6 |
Cover
Summary: | 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
2
total
), and the proportion of heritability captured by known metabolite loci (h
2
Metabolite-hits
) for 309 lipids and 52 organic acids. Our study reveals significant differences in h
2
Metabolite-hits
among different classes of lipids and organic acids. Furthermore, phosphatidylcholines with a high degree of unsaturation have higher h
2
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.
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. |
---|---|
Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Review-3 content type line 23 |
ISSN: | 2041-1723 2041-1723 |
DOI: | 10.1038/s41467-019-13770-6 |