Back

Polygenic associations with phenotypic classes across the psychosis-affective spectrum

Dennison, C. A.; Legge, S. E.; Cardno, A. G.; Quattrone, D.; Holmans, P.; Di Florio, A.; Gordon-Smith, K.; Jones, I.; Jones, L.; Owen, M. J.; O'Donovan, M.; Walters, J. T.

2026-07-14 psychiatry and clinical psychology
10.64898/2026.07.10.26357470 medRxiv
Show abstract

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.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
Psychological Medicine
88 papers in training set
Top 0.1%
14.4%
2
The British Journal of Psychiatry
23 papers in training set
Top 0.1%
12.1%
3
Schizophrenia Bulletin
32 papers in training set
Top 0.1%
7.6%
4
Molecular Psychiatry
282 papers in training set
Top 1.0%
6.5%
5
Biological Psychiatry
137 papers in training set
Top 0.5%
6.1%
6
Schizophrenia Research
35 papers in training set
Top 0.1%
5.4%
50% of probability mass above
7
Translational Psychiatry
260 papers in training set
Top 1%
4.2%
8
American Journal of Psychiatry
24 papers in training set
Top 0.1%
3.3%
9
BJPsych Open
29 papers in training set
Top 0.2%
3.1%
10
JAMA Psychiatry
15 papers in training set
Top 0.1%
3.0%
11
BMC Psychiatry
25 papers in training set
Top 0.3%
2.6%
12
Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
71 papers in training set
Top 0.8%
2.1%
13
Schizophrenia
21 papers in training set
Top 0.2%
1.9%
14
Journal of Affective Disorders
92 papers in training set
Top 1%
1.7%
15
Psychiatry Research
41 papers in training set
Top 0.7%
1.7%
16
BMJ Mental Health
15 papers in training set
Top 0.3%
1.5%
17
Computational Psychiatry
12 papers in training set
Top 0.1%
1.5%
18
European Psychiatry
11 papers in training set
Top 0.2%
1.4%
19
Neuropsychopharmacology
153 papers in training set
Top 2%
1.4%
20
Psychiatry Research: Neuroimaging
18 papers in training set
Top 0.2%
1.3%
21
Acta Psychiatrica Scandinavica
10 papers in training set
Top 0.1%
1.3%
22
PLOS ONE
5266 papers in training set
Top 56%
1.1%
23
Biological Psychiatry Global Open Science
60 papers in training set
Top 1%
1.1%
24
American Journal of Medical Genetics Part B: Neuropsychiatric Genetics
26 papers in training set
Top 0.3%
1.1%
25
Neuroscience & Biobehavioral Reviews
43 papers in training set
Top 0.8%
0.8%
26
Acta Neuropsychiatrica
14 papers in training set
Top 0.6%
0.8%
27
Progress in Neuro-Psychopharmacology and Biological Psychiatry
48 papers in training set
Top 1%
0.6%