BACKGROUND: Polygenic scores (PGSs) hold the potential to identify patients who respond favorably to specific psychiatric treatments. However, their biological interpretation remains unclear. In this study, we developed pathway-specific PGSs (PSPGSs) for lithium response and assessed their association with clinical lithium response in patients with bipolar disorder. METHODS: Using sets of genes involved in pathways affected by lithium, we developed 9 PSPGSs and evaluated their associations with lithium response in the International Consortium on Lithium Genetics (ConLi+Gen) (N = 2367), with validation in combined PsyCourse (Pathomechanisms and Signatures in the Longitudinal Course of Psychosis) (N = 105) and BipoLife (N = 102) cohorts. The association between each PSPGS and lithium response-defined both as a continuous ALDA score and a categorical outcome (good vs. poor responses)-was evaluated using regression models, with adjustment for confounders. The cutoff for a significant association was p < .05 after multiple testing correction. RESULTS: The PGSs for acetylcholine, GABA (gamma-aminobutyric acid), and mitochondria were associated with response to lithium in both categorical and continuous outcomes. However, the PGSs for calcium channel, circadian rhythm, and GSK (glycogen synthase kinase) were associated only with the continuous outcome. Each score explained 0.29% to 1.91% of the variance in the categorical and 0.30% to 1.54% of the variance in the continuous outcomes. A multivariate model combining PSPGSs that showed significant associations in the univariate analysis (combined PSPGS) increased the percentage of variance explained (R 2) to 3.71% and 3.18% for the categorical and continuous outcomes, respectively. Associations for PGSs for GABA and circadian rhythm were replicated. Patients with the highest genetic loading (10th decile) for acetylcholine variants were 3.03 times more likely (95% CI, 1.95 to 4.69) to show a good lithium response (categorical outcome) than patients with the lowest genetic loading (1st decile). CONCLUSIONS: PSPGSs achieved predictive performance comparable to the conventional genome-wide PGSs, with the added advantage of biological interpretability using a smaller list of genetic variants.

Polygenic scores (PGSs) have the potential to identify patients likely to respond to specific psychiatric treatments, but their biological interpretation remains unclear. In this study, we developed 9 pathway-specific PGSs (PSPGSs) for lithium response by aggregating genetic variants involved in pathways affected by lithium. We assessed their associations with lithium response in the International Consortium on Lithium Genetics (ConLi+Gen) (N = 2367) cohort and validated the findings in the PsyCourse (N = 105) and BipoLife (N = 102) cohorts. Clinical response to lithium treatment was significantly associated with PSPGSs for acetylcholine, GABA (gamma-aminobutyric acid), calcium channel signaling, mitochondria, circadian rhythm, and GSK pathways, with explained variance (R 2) ranging from 0.29% to 1.91%. The combined PSPGS explained up to 3.71% of the variability. Associations for GABA and circadian rhythm PGSs were successfully replicated. In a decile-based analysis, patients with the highest genetic load (10th decile) for acetylcholine pathway variants were 3.03 times more likely to respond well to lithium compared with those in the lowest decile (1st decile). PSPGSs achieved predictive performance comparable to conventional genome-wide PGSs, with better biological interpretability and a more focused set of genetic variants.

• Keywords
• Bipolar disorder, Lithium, Pharmacogenomics, Polygenic score, Psychiatry,
• Publication type
• Journal Article MeSH