Integrative analysis of metabolite GWAS illuminates the molecular basis of pleiotropy and genetic correlation
- Stanford University, United States
- Fred Hutchinson Cancer Research Center, United States
- Nightingale Health Plc, Finland
- Pfizer, United States
Abstract
Pleiotropy and genetic correlation are widespread features in GWAS, but they are often difficult to interpret at the molecular level. Here, we perform GWAS of 16 metabolites clustered at the intersection of amino acid catabolism, glycolysis, and ketone body metabolism in a subset of UK Biobank. We utilize the well-documented biochemistry jointly impacting these metabolites to analyze pleiotropic effects in the context of their pathways. Among the 213 lead GWAS hits, we find a strong enrichment for genes encoding pathway-relevant enzymes and transporters. We demonstrate that the effect directions of variants acting on biology between metabolite pairs often contrast with those of upstream or downstream variants as well as the polygenic background. Thus, we find that these outlier variants often reflect biology local to the traits. Finally, we explore the implications for interpreting disease GWAS, underscoring the potential of unifying biochemistry with dense metabolomics data to understand the molecular basis of pleiotropy in complex traits and diseases.
Data availability
The source data and analyzed data have been deposited in Dryad. Code are available at the github link (https://github.com/courtrun/Pleiotropy-of-UKB-Metabolites). The raw individual level data are available through application to UK Biobank.
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Pleiotropy of UK Biobank Metabolites [preliminary]Dryad Digital Repository, doi:10.5061/dryad.79cnp5hxs.
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The UK Biobank resource with deep phenotyping and genomic dataUK Biobank http://www.ukbiobank.ac.uk/register-apply/.
Article and author information
Author details
Jonathan K Pritchard
Funding
Stanford Knight-Hennessy Scholars Program (Graduate Student Fellowship)
- Courtney J Smith
National Science Foundation (Graduate Student Fellowship)
- Courtney J Smith
National Institute of Health (5R01HG011432 and 5R01AG066490)
- Jonathan K Pritchard
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: All participants provided written informed consent and ethical approval was obtained from the North West Multi-Center Research Ethics Committee (11/NW/0382). The current analysis was approved under UK Biobank Project 24983 and 30418.
Copyright
© 2022, Smith et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Integrative analysis of metabolite GWAS illuminates the molecular basis of pleiotropy and genetic correlation
eLife 11:e79348.
https://doi.org/10.7554/eLife.79348
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