Introduction Limitations of current classifications of schizophrenia, schizoaffective disorder, and bipolar disorder are evident from their overlapping symptoms, aetiologies, treatments, and outcomes, and present a barrier to novel treatment discovery. Alternative conceptualisations are needed to address nosological validity, align diagnosis to aetiology, and improve prognostication and treatment choice. We aimed to identify latent classes across the psychosis spectrum based on premorbid functioning and outcomes, and assess these in relation to genetic liability and symptom dimensions. Method Participants with a diagnosis of schizophrenia, schizoaffective disorder, or bipolar disorder type 1, were ascertained from four UK clinical cohorts (total n=5,043). Latent class analysis was conducted using phenotypes not included within the diagnostic criteria, including premorbid functioning, age at illness onset, and measures of severity and course. Polygenic scores (PGS) for psychiatric disorders and behavioural traits were tested for associations with latent classes. We tested if diagnosis explained associations between PGS and classes. Results A three-class model provided the best fit. Class one had poorer premorbid functioning, lower rates of recovery, and higher PGS for schizophrenia and ADHD. Class three had the highest functioning, higher rates of psychosocial stressors before onset, higher intelligence PGS and lower PGS for psychiatric disorders. Class two was intermediate between classes one and three on measures of functioning, but was characterised by high levels of involuntary hospital admissions and high bipolar disorder PGS. Diagnosis only partially explained associations between PGS and class membership. Conclusions We identified classes across the psychosis spectrum characterised by different premorbid functioning and outcomes, that cut across diagnostic categories and captured genetic liability not explained by diagnosis. Our findings suggest alternative conceptualisations of psychotic disorders may complement diagnoses in mapping to the aetiology of these conditions, and could be useful to advance precision psychiatry.
Charlotte A. Dennison, S. Legge, A. Cardno et al.· medRxiv· 0 citations
Schizophrenia and bipolar disorder are diagnostically distinct categories that overlap substantially in clinical features and genetic aetiology. Understanding genetic variants that contribute liability specifically to each disorder can offer insights into biological processes that differentiate them. Here we used Case-Case GWAS (CC-GWAS) to identify common genetic variants differentially associated with schizophrenia and bipolar disorder, analysing 67,390 schizophrenia cases and 41,917 bipolar disorder cases. We identified 19 genome-wide significant loci, of which 16 (84%) demonstrated divergent genetic effects with risk alleles showing opposite directions of association between disorders. The CC-GWAS summary statistics had detectable disorder-differentiating heritability (10.27%, SE=0.01) and showed genetic correlations indicating that SCZ-differentiating alleles were associated with lower educational attainment, lower cognitive performance, and increased risk of ADHD, anorexia, autism, BD1 (though not BD2), cannabis use disorder, and OCD. Four loci showed divergent effects despite not reaching genome-wide significance in either individual disorder GWAS, demonstrating enhanced power to detect opposite-direction effects. Functional annotation identified 102 mapped genes significantly enriched for expression across all 13 tested brain regions, with no significant enrichment in peripheral tissues, and gene set enrichment analysis implicated neuronal projection and synaptic compartments as the strongest biological themes differentiating the two disorders. Polygenic risk scores derived from these disorder-differentiating variants were associated with earlier age at onset and more severe negative symptoms in schizophrenia, consistent with these variants marking neurodevelopmental dimensions of illness. Our findings provide targets for understanding pathogenic differences between schizophrenia and bipolar disorder and demonstrate that genuine divergent genetic effects exist beyond the substantial shared liability.
I. Willcocks, A. Richards, S. Legge et al.· medRxiv· 0 citations
