Incorporating genetic data improves target trial emulations and informs the use of polygenic scores in randomized controlled trial design

Abstract

Randomized controlled trials (RCTs) remain the gold standard for evaluating medical interventions, yet ethical, practical and financial constraints often necessitate reliance on observational data and trial emulations. This study explores how integrating genetic data can enhance both emulated and traditional trial designs. Using FinnGen (n = 425,483), we emulated four major cardiometabolic RCTs and showed how reduced differences in polygenic scores (PGS) between trial arms track improvement in study design. Simulation studies reveal that PGS alone cannot fully adjust for unmeasured confounding. Instead, Mendelian randomization analyses can be used to detect likely confounders. Finally, trial emulations provide a platform to assess and refine PGS implementation for genetic enrichment strategies. By comparing associations of PGS with trial outcomes in the general population and emulated trial cohorts, we highlight the need to validate prognostic enrichment approaches in trial-relevant populations. These results highlight the growing potential of incorporating genetic information to optimize clinical trial design.