Genetic architecture and polygenic prediction of self-reported response to selective serotonin reuptake inhibitors in individuals with depression: a genome-wide meta-analysis

Selective serotonin reuptake inhibitors (SSRIs) are first-line treatments for depression, but response is highly variable, and no robust genetic predictors have been identified. We conducted a genome-wide association meta-analysis of self-reported SSRI response in 62,879 individuals of European ancestry with depression (72.6% responders) across six cohorts (seven datasets), followed by gene-set, transcriptomic, proteomic, drug-target and polygenic score (PGS) analyses. SNP-based heritability was modest but significant (h2 = 3.1%, SE = 1.4%) with no genome-wide significant variants detected. Gene-set analyses implicated gamma-aminobutyric acid (GABA)ergic and glutamatergic neurotransmission, and a gene involved in glutamate transport (SLC17A6) showed consistent sub-threshold evidence across pathway, transcriptomic and proteomic analyses. Drug-target enrichment for hypnotics, anxiolytics and general anesthetics further supported the GABAergic signal. A leave-one-out PGS from the discovery meta-analysis was associated with self-reported SSRI response in independent cohorts (meta-analysis OR = 1.05, 95% CI 1.02--1.08, p = 0.002). Higher PGS for depression, attention-deficit/hyperactivity disorder (ADHD), anxiety, post-traumatic stress disorder (PTSD), autism, addiction and schizophrenia were associated with lower odds of reported SSRI response, with ADHD, PTSD, autism and addiction remaining after adjustment for depression PGS. In contrast, educational attainment PGS was associated with better SSRI response. Self-reported SSRI response captures genetic insights relevant to antidepressant response, implicating GABAergic and glutamatergic neurotransmission. Individuals with higher genetic loading for psychiatric conditions report poorer response, and higher genetic loading for educational attainment PGS a better reported response. Although larger studies are needed to identify specific variants, self-report offers a practical, patient-centered and scalable route to collect the larger samples required.