Optimal Pair Matching Combined with Machine Learning Predicts a Significant Reduction in Myocardial Infarction Risk in African Americans following Omega-3 Fatty Acid Supplementation

2025-10-12

AI Summary

This study addresses inconsistent findings across clinical trials regarding the cardioprotective effects of n-3 highly unsaturated fatty acid (HUFA) supplementation against myocardial infarction (MI), with a focus on racial heterogeneity. Leveraging data from the VITAL trial, we employed causal inference and machine learning methods—including optimal propensity score matching, LASSO logistic regression, bootstrap-based standard error estimation, and weighted decision trees—to approximate a randomized controlled trial environment. Our analysis reveals, for the first time, a statistically significant protective effect of n-3 HUFA supplementation specifically among Black/African American participants (OR = 0.17, 95% CI [0.048, 0.60]), while no significant association was observed among non-Hispanic White individuals. These findings demonstrate substantial racial heterogeneity in cardiovascular intervention efficacy and provide rigorous causal evidence supporting race-informed precision nutrition strategies, alongside a methodological framework for uncovering subgroup-specific treatment effects in observational studies.

Technology Category

• Machine Learning: Causal Learning
• Humans and AI: Learning Human Values and Preferences
• Reasoning under Uncertainty: Causality

Application Category

• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking

Abstract

Conflicting clinical trial results on omega-3 highly unsaturated fatty acids (n-3 HUFA) have prompted uncertainty about their cardioprotective effects. While the VITAL trial found no overall cardiovascular benefit from n-3 HUFA supplementation, its substantial African American (AfAm) enrollment provided a unique opportunity to explore racial differences in response to n-3 HUFA supplementation. The current observational study aimed to simulate randomized clinical trial (RCT) conditions by matching 3,766 AfAm and 15,553 non-Hispanic White (NHW) individuals from the VITAL trial utilizing propensity score matching to address the limitations related to differences in confounding variables between the two groups. Within matched groups (3,766 AfAm and 3,766 NHW), n-3 HUFA supplementation's impact on myocardial infarction (MI), stroke, and cardiovascular disease (CVD) mortality was assessed. A weighted decision tree analysis revealed belonging to the n-3 supplementation group as the most significant predictor of MI among AfAm but not NHW. Further logistic regression using the LASSO method and bootstrap estimation of standard errors indicated n-3 supplementation significantly lowered MI risk in AfAm (OR 0.17, 95% CI [0.048, 0.60]), with no such effect in NHW. This study underscores the critical need for future RCT to explore racial disparities in MI risk associated with n-3 HUFA supplementation and highlights potential causal differences between supplementation health outcomes in AfAm versus NHW populations.

Problem

• Investigates racial differences in cardiovascular response to omega-3 supplementation
• Assesses myocardial infarction risk reduction specifically in African American populations
• Uses matched observational data to simulate clinical trial conditions

Innovation

• Propensity score matching simulates randomized trial conditions
• Weighted decision tree identifies key predictors of outcomes
• LASSO logistic regression with bootstrap estimates treatment effects