Brain signatures of childhood trauma and polygenic scores for mental health drive clinical subtypes in depression: a UK Biobank study.

Gene-environment correlations (rGE) may drive the clinical heterogeneity of major depressive disorder (MDD) through their effects on brain structure. However, previous literature focused on isolated components of these interplays. Here, we jointly investigate how rGE shape neurobiological profiles in MDD, and whether rGE-driven brain signatures can disentangle depression subtypes. In 5951 MDD patients with genetic, trauma-related and neuroimaging data from the UK Biobank, cross-validated sparse canonical correlation analysis was employed to assess multivariate associations between polygenic scores (PGSs) for mental health conditions and adverse childhood experiences (ACEs). Linear regressions tested the impact of the shared PGSs-ACEs dimensions on gray matter (GM) measures. Consensus clustering was applied to the neuroimaging features significantly associated with PGSs or ACEs to identify latent biotypes of MDD, and the emerged clusters were compared for depressive symptomatology and organic comorbidities. We found a significant canonical correlation between PGSs and ACEs (r = 0.11, p < 0.001). The most contributing PGSs were schizophrenia, attention deficit-hyperactivity disorder, autism (positive weights) and education (negative weight). Canonical variates of PGSs and ACEs associated with reduced GM in frontal, temporal, cingulate, parietal and subcortical regions (b = [-0.041; -0.021], pFDR<0.05). Such rGE-sensitive brain regions underpinned two clusters of patients, with one showing higher genetic/environmental risk, reduced GM integrity, and a worse clinical profile, including atypical symptoms, anhedonia, lethargy, sleep alterations and diabetes comorbidity. These findings indicate that rGE-driven neurobiological signatures contribute to the clinical heterogeneity of depression, supporting biologically informed subtyping in MDD.