Mood disorders polygenic scores influence clinical outcomes of major psychiatric disorders

Polygenic scores (PGS), summarizing the cumulative contribution of common genetic variants to psychiatric phenotypes, are increasingly investigated as putative predictors of treatment response and illness course. In major depressive disorder (MDD), several studies have associated higher MDD PGS with a modestly increased risk of nonresponse, lower remission rates, and treatment resistance. Conversely, bipolar disorder (BD) PGS have yielded more heterogeneous findings, with largely null or weak associations in unipolar depression but a possible on lithium response in BD cohorts, while lower MDD PGS showed a more consistent beneficial effect on lithium response in BD. MDD PGS may also have a modulating effect on clinical features of schizophrenia and a range of other psychiatric disorders. Nonetheless, the variance explained remains limited and predictive power improves only marginally when PGS are used in isolation. Integrative approaches that combine clinical predictors, environmental measures, and biomarker data appear to enhance prediction over genetics alone, which is increasing due to the most recent large genomewide studies. However, ancestral diversity remains limited, with most research conducted in Caucasian samples. Taken together, current evidence supports the incremental value of MDD and BD PGS in informing prognosis and treatment response, though clinical implementation remains premature. Replication in ancestrally diverse samples, integration with dimensional phenotypes, and improved modeling strategies will be essential to translate genetic liability into clinically actionable insights in precision psychiatry.