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Phenome-wide Mendelian randomization study of plasma triglyceride levels and 2600 disease traits. | LitMetric

AI Article Synopsis

  • - The study analyzed the causal relationship between plasma triglyceride (TG) levels and various disease traits using a two-sample Mendelian randomization approach with data from the UK Biobank and FinnGen, highlighting ongoing controversy around TG's impact on cardiovascular diseases.
  • - Results showed significant associations between plasma TG levels and 19 disease traits, including a clear link to atherosclerotic cardiovascular diseases (ASCVD) like coronary artery disease and non-ASCVD diseases like uterine leiomyoma.
  • - The research provides evidence that plasma TG levels could be a risk factor across multiple diseases, emphasizing the importance of further understanding its role in health outcomes.

Article 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 2600 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 (MVMR) controlling for correlated lipid fractions to distinguish the independent effect of plasma TG levels.

Results: Our results identified seven disease traits reaching Bonferroni-corrected significance in both the discovery (p<1.92 × 10) and replication analyses (p<2.26 × 10), 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). 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 nine non-ASCVD diseases, including uterine leiomyoma (OR 1.19, 95% CI 1.10-1.29, p=1.17 × 10).

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).

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10079290PMC
http://dx.doi.org/10.7554/eLife.80560DOI Listing

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