Genetic evidence for the psychosis continuum: polygenic score analysis.
The psychosis continuum conceptualises psychotic phenomena as existing on a spectrum from subclinical experiences to psychotic disorders. Despite epidemiological and clinical evidence in support of this model, few studies have examined polygenic liability across the severity continuum: from subclinical experiences to first-episode psychosis (FEP).
To map polygenic liability for schizophrenia (SCZ), bipolar disorder and major depressive disorder (MDD) across the psychosis continuum. We hypothesised that schizophrenia polygenic scores (SCZ-PGS) would track phenotypic severity most closely across this continuum.
We harmonised data from 5 south-east London cohorts (N = 1315; 860 European, 455 African ancestries) across 4 ordered groups indicative of different levels of phenotypic severity: controls (n = 647), individuals with self-reported psychotic experiences (n = 89), individuals at clinical high risk (CHR) that did not convert to psychosis (n = 124) and individuals with FEP (n = 455). We computed ancestry-specific PGS for SCZ, bipolar disorder and MDD and compared these across groups using ordinal logistic regression.
In European ancestry participants, elevated SCZ-PGS (odds ratio 1.72, p = 4.57 × 10-15), bipolar disorder-PGS (odds ratio 1.56, p = 1.03 × 10-10) and MDD-PGS (odds ratio 1.44, p = 4.86 × 10-8) were individually associated with increasing phenotypic severity. SCZ-PGS explained the largest variance (R2 = 0.084) across the psychosis continuum and showed pairwise differences between CHR and controls (β = 0.32, p = 0.027), and between FEP and CHR (β = 0.38, p = 0.017). Multivariable models, combining three PGS, outperformed univariable models (R2 = 0.105). Similar trends in SCZ-PGS across the psychosis continuum phenotype were seen in African ancestry participants, but only controls and FEP groups differed significantly (β = 0.27, p = 0.037).
Our findings provide biological evidence supporting the psychosis continuum framework. In European ancestry, SCZ-PGS differences suggest that CHR who do not transition to psychosis have intermediate genetic vulnerability. Multivariable models, utilising all three PGS, explained additional variance compared with univariable ones, supporting transdiagnostic genetic liability. Improving PGS predictive power in African ancestry remains a priority.
To map polygenic liability for schizophrenia (SCZ), bipolar disorder and major depressive disorder (MDD) across the psychosis continuum. We hypothesised that schizophrenia polygenic scores (SCZ-PGS) would track phenotypic severity most closely across this continuum.
We harmonised data from 5 south-east London cohorts (N = 1315; 860 European, 455 African ancestries) across 4 ordered groups indicative of different levels of phenotypic severity: controls (n = 647), individuals with self-reported psychotic experiences (n = 89), individuals at clinical high risk (CHR) that did not convert to psychosis (n = 124) and individuals with FEP (n = 455). We computed ancestry-specific PGS for SCZ, bipolar disorder and MDD and compared these across groups using ordinal logistic regression.
In European ancestry participants, elevated SCZ-PGS (odds ratio 1.72, p = 4.57 × 10-15), bipolar disorder-PGS (odds ratio 1.56, p = 1.03 × 10-10) and MDD-PGS (odds ratio 1.44, p = 4.86 × 10-8) were individually associated with increasing phenotypic severity. SCZ-PGS explained the largest variance (R2 = 0.084) across the psychosis continuum and showed pairwise differences between CHR and controls (β = 0.32, p = 0.027), and between FEP and CHR (β = 0.38, p = 0.017). Multivariable models, combining three PGS, outperformed univariable models (R2 = 0.105). Similar trends in SCZ-PGS across the psychosis continuum phenotype were seen in African ancestry participants, but only controls and FEP groups differed significantly (β = 0.27, p = 0.037).
Our findings provide biological evidence supporting the psychosis continuum framework. In European ancestry, SCZ-PGS differences suggest that CHR who do not transition to psychosis have intermediate genetic vulnerability. Multivariable models, utilising all three PGS, explained additional variance compared with univariable ones, supporting transdiagnostic genetic liability. Improving PGS predictive power in African ancestry remains a priority.
Authors
Haussler Haussler, Prata Prata, Kempton Kempton, Bhavsar Bhavsar, Arathimos Arathimos, Coleman Coleman, Valmaggia Valmaggia, Tognin Tognin, Modinos Modinos, Fusar-Poli Fusar-Poli, Quattrone Quattrone, van Os van Os, Rutten Rutten, Breen Breen, Di Forti Di Forti, Morgan Morgan, Lewis Lewis, Hotopf Hotopf, McGuire McGuire, Murray Murray, Vassos Vassos
View on Pubmed