58 - GENOMIC DISSECTION OF BIPOLAR DISORDER AND SCHIZOPHRENIA IN 50K CASES, 50K CONTROLS AND 28 SUBPHENOTYPES

Abstract

Background Schizophrenia (SCZ) and Bipolar Disorder (BD) are heritable disorders (h2 ~ 0.8) that share a significant proportion of common genetic factors (genetic correlation (rg) ~ 0.6). Understanding the genetic factors underlying the specific symptoms will be crucial for improving diagnosis, intervention and treatment. We previously demonstrated that a polygenic score could distinguish these two disorders. However, no particular locus reached genome-wide significance in a direct case-case Genome-Wide Association (GWA) study. Since that study, sample size and number of subphenotypes have greatly increased, providing improved power to identify disease and subphenotype specific genomic factors. Methods In case-control data consisting of 52,555 cases (20,129 BD, 32,541 SCZ) and 54,065 controls we performed GWA on a combined phenotype (BD+SCZ vs controls), disease specific phenotypes and a comparison phenotype (SCZ vs BD). We incorporated expression data from blood and brain to identify significantly associated regulatory variants using Summary-data-based Mendelian Randomization (SMR). Disease specific genomic regions were assessed using a regional joint association approach and regional heritability estimation. Finally, we tested if there was significant correlation between 28 subphenotypes (4 in SCZ, 24 in BD) and polygenic risk scores from both BD and SCZ. Results We identified 114 genome-wide significant loci (GWS) from all cases vs controls where 37 were novel. Two GWS were identified when comparing SCZ vs BD with a third discovered by including expression using SMR. We performed regional joint association identifying a genomic region of overlapping association in BD and SCZ, which was, however, contributed from independent variants. Regional heritability analyses showed that estimated heritability of BD based on SCZ GWS regions was significantly higher than the average genomic region (N=82, p = 1.1×10-6). However, heritability of SCZ based on BD GWS regions was not significantly different from the average (N=10, p = 0.56). We identified significant correlations between BD and SCZ polygenic risk scores: 1) SCZ subphenotypes: negative symptoms (SCZ, 3.6×10-6) and manic symptoms (BD, p=2×10-5), 2) BD subphenotypes: psychotic features (SCZ 1.2×10-10, BD 5.3×10-5) and age of onset (SCZ 7.9×10-4). Finally, GWAS of psychotic features in BD has significant heritability (h2=0.15, SE=0.06), significant genetic correlation with SCZ (rg=0.34) and significant sign test with SCZ GWAS (p=0.0038, one-side binomial test). Discussion For the first time, we identified specific loci pointing to a potential role of 4 genes (DARS2, ARFGEF2, DCAKD and GATAD2A) that distinguish between BD and SCZ providing an opportunity to understand the biology contributing to differing symptoms of these disorders. Our results suggest a direction of genomic sharing with SCZ GWS loci contributing to BD but not the other way around. Finally, we present polygenic analyses of 28 different subphenotypes demonstrating underlying genomic components contributing to symptom dimensions such as psychotic features in BD, negative and manic symptoms in SCZ and measures of severity including number of hospitalizations and age of onset. We show that psychotic features in BD has a strong genetic component shared with SCZ for both genome-wide and at the most significant SCZ loci. Our results provide the best evidence so far of genomic components divergent between BD and SCZ contributing directly to specific symptom dimensions.