19. GENETICS OF DEPRESSION IN HALF A MILLION CASES: UPDATE FROM THE MAJOR DEPRESSIVE DISORDER WORKING GROUP OF THE PSYCHIATRIC GENOMICS CONSORTIUM

The PGC and collaborators have conducted an updated genome-wide association study of major depressive disorder in 70+ cohorts totalling over half a million cases and three million controls. The discovery meta-analysis in European ancestry cohorts consisted of 525k cases and 3.36M controls. We conducted a fixed-effects meta-analyses and a phenotyping-based common factor meta-analysis. We combined functionally-informed finemapping, expression and protein quantitative trait loci, and other datasets to gain insight into the variants, genes, and pathways underlying the associated loci. We used single cell gene expression data to analyze enrichment of causal neural cell types. We tested cross-ancestry polygenic prediction in East Asian, South Asian, African and Admixed American ancestries cohorts (total N cases = 15k, N controls = 117k). The discovery meta-analysis found 570 associated genomic regions, including 274 that were novel, with a SNP-based heritability of 8.4%. Major depression diagnosis based on different approaches (clinical assessment or interview, health records, questionnaire, and self-report of diagnosis) were genetically correlated (rg = 0.78-0.88), explained by a common factor, and showed little evidence of heterogeneity in association signals. By combining fine-mapping results with expression and protein quantitative trait data, we pinpointed 308 high-confidence associations. Genes implicated by these associations showed enrichment of postsynaptic density and receptor clustering while cell-type enrichment implicated excitatory and inhibitory midbrain and forebrain neurons, peptidergic neurons, and medium spiny neurons. Polygenic scores (PGS) from these data explained 5.7% of the variance in liability to MD in European samples and predicted case control status across diverse ancestries. Increasing sample size in genetic analysis of major depressive disorder continues to reveal biology and aetiology.