Optimal Pair Matching Combined with Machine Learning Predicts that Omega-3 Fatty Acid Supplementation Markedly Reduces the Risk of Myocardial Infarction in African Americans

Abstract

AbstractConflicting results from clinical trials have contributed to a lack of consensus about cardioprotective effects of omega-3 (n-3) highly unsaturated fatty acids (HUFA). Although the VITAL trial did not demonstrate an overall benefit of n-3 HUFA supplementation on composite cardiovascular disease (CVD) and cancer outcomes, the substantial enrollment of African Americans (AfAm) afforded a unique opportunity for a post-hoc analysis of racial differences in the supplementation response. We employed propensity score matching to address potential covariate imbalances between AfAm and European American (EuAm) participants in VITAL (N=3,766 participants). Using Kaplan-Meier curves and two machine learning methodologies, we found that n-3 HUFA supplementation was significantly associated with a reduced risk of myocardial infarction (MI) exclusively in the AfAm subgroup, as evidenced by an odds ratio of 0.17 (95% CI [0.048, 0.59]). These findings indicate a potential cardioprotective benefit of n-3 supplementation in AfAm, specifically in reducing MI risks; a risk not identified in EuAm. Further investigation of n-3 HUFA effects through a hypothesis-driven randomized clinical trial among AfAm is needed to test a race-specific response that may inform recommendations for n-3 HUFA supplementation.