The heterogeneous treatment effects of statins on dementia: a target trial emulation with causal machine learning using integrated genetic and real‐world data

INTRODUCTION: Given the complexity of dementia, the inconsistent evidence on statins and dementia highlights the need for robust methods to assess heterogeneous treatment effects (HTEs). METHODS: We emulated a target trial using UK Biobank comparing statin initiators and non-initiators aged ≥55 years. Marginal structural models were fitted to estimate 5-year adjusted risk difference (aRD). We used iterative causal forest, a causal machine learning subgrouping algorithm, to identify subgroups with HTEs. RESULTS: Among 18,366 participants, the overall aRD for all-cause dementia was -1.0‰ (95% CI: -4.2‰ to 2.3‰). We identified subgroups by polygenic risk score for Alzheimer's disease (AD) excluding apolipoprotein E (APOE) genotype ("non-APOE PRS"). Participants with high non-APOE PRS showed cognitive benefit (all-cause dementia: aRD -5.9‰, 95% CI: -8.1‰ to 1.2‰; AD: aRD -5.0‰, 95% CI: -8.2‰ to -0.2‰). DISCUSSION: Participants with high non-APOE PRS may benefit from statins, suggesting genetic susceptibility beyond APOE could modify statins' cognitive effects.