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Use of multiple polygenic risk scores for distinguishing schizophrenia-spectrum disorder and affective psychosis categories in a first-episode sample; the EU-GEI study.

Authors :
Rodriguez V
Alameda L
Quattrone D
Tripoli G
Gayer-Anderson C
Spinazzola E
Trotta G
Jongsma HE
Stilo S
La Cascia C
Ferraro L
La Barbera D
Lasalvia A
Tosato S
Tarricone I
Bonora E
Jamain S
Selten JP
Velthorst E
de Haan L
Llorca PM
Arrojo M
Bobes J
Bernardo M
Arango C
Kirkbride J
Jones PB
Rutten BP
Richards A
Sham PC
O'Donovan M
Van Os J
Morgan C
Di Forti M
Murray RM
Vassos E
Source :
Psychological medicine [Psychol Med] 2023 Jun; Vol. 53 (8), pp. 3396-3405. Date of Electronic Publication: 2022 Jan 25.
Publication Year :
2023

Abstract

Background: Schizophrenia (SZ), bipolar disorder (BD) and depression (D) run in families. This susceptibility is partly due to hundreds or thousands of common genetic variants, each conferring a fractional risk. The cumulative effects of the associated variants can be summarised as a polygenic risk score (PRS). Using data from the EUropean Network of national schizophrenia networks studying Gene-Environment Interactions (EU-GEI) first episode case-control study, we aimed to test whether PRSs for three major psychiatric disorders (SZ, BD, D) and for intelligent quotient (IQ) as a neurodevelopmental proxy, can discriminate affective psychosis (AP) from schizophrenia-spectrum disorder (SSD).<br />Methods: Participants (842 cases, 1284 controls) from 16 European EU-GEI sites were successfully genotyped following standard quality control procedures. The sample was stratified based on genomic ancestry and analyses were done only on the subsample representing the European population (573 cases, 1005 controls). Using PRS for SZ, BD, D, and IQ built from the latest available summary statistics, we performed simple or multinomial logistic regression models adjusted for 10 principal components for the different clinical comparisons.<br />Results: In case-control comparisons PRS-SZ, PRS-BD and PRS-D distributed differentially across psychotic subcategories. In case-case comparisons, both PRS-SZ [odds ratio (OR) = 0.7, 95% confidence interval (CI) 0.54-0.92] and PRS-D (OR = 1.31, 95% CI 1.06-1.61) differentiated AP from SSD; and within AP categories, only PRS-SZ differentiated BD from psychotic depression (OR = 2.14, 95% CI 1.23-3.74).<br />Conclusions: Combining PRS for severe psychiatric disorders in prediction models for psychosis phenotypes can increase discriminative ability and improve our understanding of these phenotypes. Our results point towards the potential usefulness of PRSs in specific populations such as high-risk or early psychosis phases.

Details

Language :
English
ISSN :
1469-8978
Volume :
53
Issue :
8
Database :
MEDLINE
Journal :
Psychological medicine
Publication Type :
Academic Journal
Accession number :
35076361
Full Text :
https://doi.org/10.1017/S0033291721005456