Phenome-wide Mendelian randomization study of plasma triglyceride levels and 2,600 disease traits

Abstract

Background: Causality between plasma triglyceride (TG) levels and atherosclerotic cardiovascular disease (ASCVD) risk remains controversial despite more than four decades of study and two recent landmark trials, STRENGTH and REDUCE-IT. Further unclear is the association between TG levels and non-atherosclerotic diseases across organ systems.

Methods: Here, we conducted a phenome-wide, two-sample Mendelian randomization (MR) analysis using inverse-variance weighted (IVW) regression to systematically infer the causal effects of plasma TG levels on 2,600 disease traits in the European ancestry population of UK Biobank. For replication, we externally tested 221 nominally significant associations (p < 0.05) in an independent cohort from FinnGen. To account for potential horizontal pleiotropy and the influence of invalid instrumental variables, we performed sensitivity analyses using MR-Egger regression, weighted median estimator, and MR-PRESSO. Finally, we used multivariable MR controlling for correlated lipid fractions to distinguish the independent effect of plasma TG levels.

Results: Our results identified 7 disease traits reaching Bonferroni-corrected significance in both the discovery (p < 1.92 × 10-5) and replication analyses (p < 2.26 × 10-4), suggesting a causal relationship between plasma TG levels and ASCVDs, including coronary artery disease (OR 1.33, 95% CI 1.24-1.43, p = 2.47 × 10-13). We also identified 12 disease traits that were Bonferroni-significant in the discovery or replication analysis and at least nominally significant in the other analysis (p < 0.05), identifying plasma TG levels as a novel potential risk factor for 9 non-ASCVD diseases, including uterine leiomyoma (OR 1.19, 95% CI 1.10-1.29, p = 1.17 × 10-5).

Conclusions: Taking a phenome-wide, two-sample MR approach, we identified causal associations between plasma TG levels and 19 disease traits across organ systems. Our findings suggest unrealized drug repurposing opportunities or adverse effects related to approved and emerging TG-lowering agents, as well as mechanistic insights for future studies.

Funding: RD is supported by the National Institute of General Medical Sciences of the National Institutes of Health (NIH) (R35-GM124836) and the National Heart, Lung, and Blood Institute of the NIH (R01-HL139865 and R01-HL155915).

Data availability

All data generated in this study are included in the manuscript and supplementary tables. All analyses used publicly available data (UKB , FinnGen), including previously published GWAS (GLGC) (Willer et al., 2013). Obtaining access to UKB (Pan-UKB_Team, 2020) and FinnGen (FinnGen, 2020) GWAS summary statistics is detailed here (https://www.finngen.fi/en/access_results) and here (https://pan.ukbb.broadinstitute.org/downloads. Please note the summary statistics for FinnGen and Pan-UKB are made publicly available.

Article and author information

Author details

  1. Joshua K Park

    Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, United States
    Competing interests
    No competing interests declared.
  2. Shantanu Bafna

    Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, United States
    Competing interests
    No competing interests declared.
  3. Iain S Forrest

    Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, United States
    Competing interests
    No competing interests declared.
  4. Áine Duffy

    Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, United States
    Competing interests
    No competing interests declared.
  5. Carla Marquez-Luna

    Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, United States
    Competing interests
    No competing interests declared.
  6. Ben O Petrazzini

    Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, United States
    Competing interests
    No competing interests declared.
  7. Ha My Vy

    Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, United States
    Competing interests
    No competing interests declared.
  8. Daniel M Jordan

    Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, United States
    Competing interests
    No competing interests declared.
  9. Marie Verbanck

    Université Paris Cité, Paris, France
    Competing interests
    No competing interests declared.
  10. Jagat Narula

    Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, United States
    Competing interests
    No competing interests declared.
  11. Robert S Rosenson

    Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, United States
    Competing interests
    Robert S Rosenson, reports receiving grants from Amgen, Arrowhead, Lilly, Novartis and Regeneron; consulting fees from Amgen, Arrowhead, Lilly, Novartis and Regeneron; honoraria for non-promotional lectures from Amgen, Kowa and Regeneron, royalties from Wolters Kluwer (UpToDate); and stock holdings in MediMergent, LLC..
  12. Ghislain Rocheleau

    Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9989-7553
  13. Ron Do

    Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, United States
    For correspondence
    ron.do@mssm.edu
    Competing interests
    Ron Do, reports receiving grants from AstraZeneca; grants and non-financial support from Goldfinch Bio; being a scientific co-founder, consultant, and equity holder (pending) for Pensieve Health; and a consultant for Variant Bio, all unrelated to this work..
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3144-3627

Funding

National Institute of General Medical Sciences (R35-GM124836)

  • Ron Do

National Heart, Lung, and Blood Institute (R01-HL139865)

  • Ron Do

National Heart, Lung, and Blood Institute (R01-HL155915)

  • Ron Do

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Human subjects: UK Biobank has approval from the North West Multi Centre Research Ethics Committee (MREC) as a Research Tissue Bank (RTB) (11/NW/0382), and all participants of UKB provided written informed consent. More information is available at (https://www.ukbiobank.ac.uk/learn-more-about-uk-biobank/about-us/ethics). The work described in this study was approved by UKB under application number 16218. All participants of FinnGen provided written informed consent for biobank research, based on the Finnish Biobank Act. The Coordinating Ethics Committee of the Hospital District of Helsinki and Uusimaa (HUS) approved the FinnGen study protocol Nr HUS/990/2017. More information is available at (https://www.finngen.fi/en/code_of_conduct).

Copyright

© 2023, Park 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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  1. Joshua K Park
  2. Shantanu Bafna
  3. Iain S Forrest
  4. Áine Duffy
  5. Carla Marquez-Luna
  6. Ben O Petrazzini
  7. Ha My Vy
  8. Daniel M Jordan
  9. Marie Verbanck
  10. Jagat Narula
  11. Robert S Rosenson
  12. Ghislain Rocheleau
  13. Ron Do
(2023)
Phenome-wide Mendelian randomization study of plasma triglyceride levels and 2,600 disease traits
eLife 12:e80560.
https://doi.org/10.7554/eLife.80560

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https://doi.org/10.7554/eLife.80560

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