Genetic evidence for the psychosis continuum: polygenic score analysis

Background 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). Aims 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. Method 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. Results 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 ( R 2 = 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 ( R 2 = 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). Conclusions 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.

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Publication Details

Journal
The British Journal of Psychiatry
Published
2026-10-14
DOI
https://doi.org/10.1192/bjp.2026.10795
Primary Topic
Schizophrenia research and treatment
Type
article
Field-Weighted Citation Impact
0.00

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article

Genetic evidence for the psychosis continuum: polygenic score analysis

Matthew H. Hotopf, Gemma Modinos, Gerome D. Breen, Matthew J. Kempton et al.
The British Journal of Psychiatry
Schizophrenia research and treatment
article

Genetic evidence for the psychosis continuum: polygenic score analysis

Matthew H. Hotopf, Gemma Modinos, Gerome D. Breen, Matthew J. Kempton, Diana Pinto Prata, Diego Quattrone, Jim van Os, Robin M. Murray, Bart P. F. Rutten, Ryan Arathimos, Cathryn M. Lewis, Craig Morgan, Lucia Valmaggia, Paolo Fusar‐Poli, Vishal Bhavsar, Evangelos Vassos, Jonathan R. I. Coleman, Philip K. McGuire, Stefania Tognin, Marta Di Forti, Senta M. Haussler
article en

Abstract

Background 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). Aims 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. Method 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. Results 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 ( R 2 = 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 ( R 2 = 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). Conclusions 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.

The British Journal of Psychiatry
King's College London (GB), South London and Maudsley NHS Foundation Trust (GB), University of Pavia (IT), Maastricht University Medical Centre (NL), Oxford Health NHS Foundation Trust (GB), University Medical Center Utrecht (NL), University of Oxford (GB), Institute of Biophysics and Biomedical Engineering (BG), Orygen (AU)
South London and Maudsley NHS Foundation Trust, National Institute for Health and Care Research, King's College London, University of Oxford, European Commission, Universiteit Maastricht, Università degli Studi di Pavia, Universidade de Lisboa, Oxford Health NHS Foundation Trust, NIHR Maudsley Biomedical Research Centre, Medical Research Council, Economic and Social Research Council, Menzies Centre for Australian Studies, King's College London, University of London
Good health and well-being
Openalex Percentile: Top 13%
Schizophrenia research and treatment
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