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eLifeGenetic & Genomic MedicinePeer-reviewed journal article

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

Joshua K. ParkiD, Shantanu BafnaiD, Iain S. ForrestiD, Áine DuffyiD, Carla Márquez‐LunaiD, Ben Omega PetrazziniiD, Ha My T. VyiD, Daniel M. JordaniD, Marie VerbanckiD, Jagat NarulaiD, Robert S. RosensoniD, Ghislain RocheleauiD, Ron DoiD

PDFDOIPreprint

Abstract

BackgroundCausality 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. MethodsHere, 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. ResultsOur results identified 7 disease traits reaching Bonferroni-corrected significance in both the discovery (p < 1.92 x 10-5) and replication analyses (p < 2.26 x 10-4), supporting 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 x 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 risk factor for 9 non-ASCVD diseases, including uterine leiomyoma (OR 1.19, 95% CI 1.10-1.29, p = 1.17 x 10-5). ConclusionsTaking 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 study.

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