Disorder-specific and shared genetic architecture underlying schizophrenia and bipolar disorder

Abstract

Schizophrenia (SCZ) and bipolar disorder (BIP) share substantial common-variant liability but differ in cognition, medical comorbidity, and treatment response. Here we decomposed this overlap into schizophrenia-predominant, bipolar-predominant, and shared psychosis dimensions to test whether these components show distinct pleiotropic and biological profiles. Using the largest available SCZ and BIP GWAS, we applied bidirectional mtCOJO and Genomic SEM to derive SCZcondBIP, BIPcondSCZ, and PSY-shared and validated them using inter-component genetic correlations, FinnGen psychiatric endpoints, and Genomic SEM latent factors. We then characterized each component across cognitive, cardiometabolic, and immune traits, followed by genomic risk-locus discovery, pathway analysis, developmental expression profiling, and drug-target enrichment. The three components showed marked divergence. SCZcondBIP was negatively genetically correlated with cognition, education, metabolic syndrome, C-reactive protein, and neutrophil percentage, whereas BIPcondSCZ showed the opposite cognitive profile and shifted toward positive cardiometabolic and immune correlations. PSY-shared retained the mixed cognitive pattern seen at the disorder level and intermediate peripheral correlations, indicating that shared psychosis liability masks stronger disorder-specific differences. Between-component contrasts were approximately twice the magnitude of the corresponding SCZ-versus-BIP contrasts. We identified 248 consensus genomic risk loci, including 81 not detected in the input disorder GWAS. Biologically, PSY-shared was enriched for synaptic signalling, ion-channel, and neurodevelopmental pathways; SCZcondBIP primarily implicated synaptic-signalling and cellular-homeostasis pathways; and BIPcondSCZ showed weaker but distinct enrichment for synaptic-vesicular biology. Drug-target enrichment further separated the components, with strong antipsychotic enrichment for PSY-shared and distinct non-antipsychotic signals for the conditional factors. These findings show that SCZ and BIP genetic risk is best understood as biologically distinguishable shared and disorder-predominant dimensions that differentially map onto cognitive, cardiometabolic, immune, and molecular architecture. These findings provide a framework for evaluating whether component-specific polygenic scores improve stratification of cognitive, cardiometabolic, and inflammatory heterogeneity across severe psychiatric illness.