1. Genetics and Genomics

Integrative analysis of metabolite GWAS illuminates the molecular basis of pleiotropy and genetic correlation

  1. Courtney J Smith  Is a corresponding author
  2. Nasa Sinnott-Armstrong  Is a corresponding author
  3. Anna Cichońska
  4. Heli Julkunen
  5. Eric B Fauman
  6. Peter Würtz
  7. Jonathan K Pritchard  Is a corresponding author
  1. Stanford University, United States
  2. Fred Hutchinson Cancer Research Center, United States
  3. Nightingale Health Plc, Finland
  4. Pfizer, United States
https://doi.org/10.7554/eLife.79348
Share this article
Cite this article
  1. Courtney J Smith
  2. Nasa Sinnott-Armstrong
  3. Anna Cichońska
  4. Heli Julkunen
  5. Eric B Fauman
  6. Peter Würtz
  7. Jonathan K Pritchard
(2022)
Integrative analysis of metabolite GWAS illuminates the molecular basis of pleiotropy and genetic correlation
eLife 11:e79348.
https://doi.org/10.7554/eLife.79348
  2. Download BibTeX
  3. Download .RIS

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.

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Courtney J Smith

    Department of Genetics, Stanford University, Stanford, United States
    For correspondence
    courtrun@stanford.edu
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7812-0083

  2. Nasa Sinnott-Armstrong

    Herbold Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, United States
    For correspondence
    nasa@fredhutch.org
    Competing interests
    No competing interests declared.

  3. Anna Cichońska

    Nightingale Health Plc, Helsinki, Finland
    Competing interests
    Anna Cichońska, is a former employee and holds stock options with Nightingale Health Plc..

  4. Heli Julkunen

    Nightingale Health Plc, Helsinki, Finland
    Competing interests
    Heli Julkunen, is an employee and holds stock options with Nightingale Health Plc..
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4282-0248

  5. Eric B Fauman

    Internal Medicine Research Unit, Pfizer, Cambridge, United States
    Competing interests
    Eric B Fauman, is affiliated with Pfizer Worldwide Research, has no financial interests to declare, contributed as an individual and the work was not part of a Pfizer collaboration nor was it funded by Pfizer..

  6. Peter Würtz

    Nightingale Health Plc, Helsinki, Finland
    Competing interests
    Peter Würtz, is an employee and shareholder of Nightingale Health Plc..
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5832-0221

  7. Jonathan K Pritchard

    Departments of Genetics and Biology, Stanford University, Stanford, United States
    For correspondence
    pritch@stanford.edu
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8828-5236

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.

Metrics

  • 3,974
    views
  • 700
    downloads
  • 23
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Courtney J Smith
  2. Nasa Sinnott-Armstrong
  3. Anna Cichońska
  4. Heli Julkunen
  5. Eric B Fauman
  6. Peter Würtz
  7. Jonathan K Pritchard
(2022)
Integrative analysis of metabolite GWAS illuminates the molecular basis of pleiotropy and genetic correlation
eLife 11:e79348.
https://doi.org/10.7554/eLife.79348

Share this article

https://doi.org/10.7554/eLife.79348

Categories and tags

Research organism

Further reading

    1. Epidemiology and Global Health
    2. Genetics and Genomics

    Ethnic and region-specific genetic risk variants of stroke and its comorbid conditions can define the variations in the burden of stroke and its phenotypic traits

    Rashmi Sukumaran, Achuthsankar S Nair, Moinak Banerjee
    Research Article

    Burden of stroke differs by region, which could be attributed to differences in comorbid conditions and ethnicity. Genomewide variation acts as a proxy marker for ethnicity, and comorbid conditions. We present an integrated approach to understand this variation by considering prevalence and mortality rates of stroke and its comorbid risk for 204 countries from 2009 to 2019, and Genome-wide association studies (GWAS) risk variant for all these conditions. Global and regional trend analysis of rates using linear regression, correlation, and proportion analysis, signifies ethnogeographic differences. Interestingly, the comorbid conditions that act as risk drivers for stroke differed by regions, with more of metabolic risk in America and Europe, in contrast to high systolic blood pressure in Asian and African regions. GWAS risk loci of stroke and its comorbid conditions indicate distinct population stratification for each of these conditions, signifying for population-specific risk. Unique and shared genetic risk variants for stroke, and its comorbid and followed up with ethnic-specific variation can help in determining regional risk drivers for stroke. Unique ethnic-specific risk variants and their distinct patterns of linkage disequilibrium further uncover the drivers for phenotypic variation. Therefore, identifying population- and comorbidity-specific risk variants might help in defining the threshold for risk, and aid in developing population-specific prevention strategies for stroke.

    1. Genetics and Genomics

    Dysfunction of Calcyphosine-Like gene impairs retinal angiogenesis through the MYC axis and is associated with familial exudative vitreoretinopathy

    Wenjing Liu, Shujin Li ... Xianjun Zhu
    Research Article

    Familial exudative vitreoretinopathy (FEVR) is a severe genetic disorder characterized by incomplete vascularization of the peripheral retina and associated symptoms that can lead to vision loss. However, the underlying genetic causes of approximately 50% of FEVR cases remain unknown. Here, we report two heterozygous variants in calcyphosine-like gene (CAPSL) that is associated with FEVR. Both variants exhibited compromised CAPSL protein expression. Vascular endothelial cell (EC)-specific inactivation of Capsl resulted in delayed radial/vertical vascular progression, compromised endothelial proliferation/migration, recapitulating the human FEVR phenotypes. CAPSL-depleted human retinal microvascular endothelial cells (HRECs) exhibited impaired tube formation, decreased cell proliferation, disrupted cell polarity establishment, and filopodia/lamellipodia formation, as well as disrupted collective cell migration. Transcriptomic and proteomic profiling revealed that CAPSL abolition inhibited the MYC signaling axis, in which the expression of core MYC targeted genes were profoundly decreased. Furthermore, a combined analysis of CAPSL-depleted HRECs and c-MYC-depleted human umbilical vein endothelial cells uncovered similar transcription patterns. Collectively, this study reports a novel FEVR-associated candidate gene, CAPSL, which provides valuable information for genetic counseling of FEVR. This study also reveals that compromised CAPSL function may cause FEVR through MYC axis, shedding light on the potential involvement of MYC signaling in the pathogenesis of FEVR.

    1. Developmental Biology
    2. Genetics and Genomics

    Early moderate prenatal alcohol exposure and maternal diet impact offspring DNA methylation across species

    Mitchell Bestry, Alexander N Larcombe ... David Martino
    Research Article

    Alcohol consumption in pregnancy can affect genome regulation in the developing offspring but results have been contradictory. We employed a physiologically relevant murine model of short-term moderate prenatal alcohol exposure (PAE) resembling common patterns of alcohol consumption in pregnancy in humans. Early moderate PAE was sufficient to affect site-specific DNA methylation in newborn pups without altering behavioural outcomes in adult littermates. Whole-genome bisulfite sequencing of neonatal brain and liver revealed stochastic influence on DNA methylation that was mostly tissue-specific, with some perturbations likely originating as early as gastrulation. DNA methylation differences were enriched in non-coding genomic regions with regulatory potential indicative of broad effects of alcohol on genome regulation. Replication studies in human cohorts with fetal alcohol spectrum disorder suggested some effects were metastable at genes linked to disease-relevant traits including facial morphology, intelligence, educational attainment, autism, and schizophrenia. In our murine model, a maternal diet high in folate and choline protected against some of the damaging effects of early moderate PAE on DNA methylation. Our studies demonstrate that early moderate exposure is sufficient to affect fetal genome regulation even in the absence of overt phenotypic changes and highlight a role for preventative maternal dietary interventions.