Causal associations between hormone replacement therapy and brain structure: Evidence from large-scale Mendelian randomization and double machine learning.

BACKGROUND: Hormone replacement therapy (HRT) is widely prescribed for the management of hormone deficiency, particularly during menopause, yet its causal effects on human brain structure remain incompletely understood. Observational studies have reported heterogeneous associations, underscoring the need for robust causal inference. METHODS: We applied an integrated causal framework combining two-sample Mendelian Randomization (MR) and Double Machine Learning (DML) to evaluate the effects of four HRT-related exposures-age at initiation, age at cessation, ever-use of HRT, and a composite medication-based phenotype-on 1366 brain imaging-derived phenotypes from the UK Biobank. Genetic instruments were derived from large-scale GWAS summary statistics, and causal estimates were validated using non-parametric DML models with cross-fitting and performance evaluation. RESULTS: Genetic instruments for age at HRT initiation, age at cessation, and ever-use of HRT were strong (median F-statistics 16.29-36.66). MR analyses identified a causal association between later initiation of HRT and lower orientation dispersion in the right inferior cerebellar peduncle (ubm-a-542; primary finding, no pleiotropy detected). An additional association with the left tapetum FA (ubm-a-243) was identified but exhibited significant directional horizontal pleiotropy (MR-Egger intercept P = 0.001) and is excluded from primary conclusions (Supplementary Note S2). Later cessation of HRT was associated with increased cortical thickness in the left middle occipital gyrus, reduced surface area in the left frontopolar cortex, and increased orientation dispersion in the splenium of the corpus callosum. Ever-use of HRT was causally linked to larger volumes of the right inferior frontal gyrus and right nucleus accumbens. These associations were corroborated by independent DML validation, which provided causally debiased estimates robust to high-dimensional confounding. Results for ukb-b-8080 (median F = 1.45) are provided in Supplementary Note S1 only; weak-instrument bias precludes causal inference. CONCLUSIONS: This study provides genetic-instrument-based and machine-learning-validated evidence for causal associations between HRT exposure-particularly its timing and lifetime use-and specific features of human brain structure, including white-matter microarchitecture, cortical thickness, and regional brain volume. These findings are FDR-controlled within exposures and independently replicated by DML, but require replication in external neuroimaging GWAS cohorts to establish definitive causal conclusions. They highlight the neurobiological relevance of sex steroid exposure and inform future research on brain aging and personalized hormone-based interventions.