RT Journal Article
T1 Use of multiple polygenic risk scores for distinguishing schizophrenia-spectrum disorder and affective psychosis categories in a first-episode sample; the EU-GEI study.
A1 Rodriguez, Victoria
A1 Alameda, Luis
A1 Quattrone, Diego
A1 Tripoli, Giada
A1 Gayer-Anderson, Charlotte
A1 Spinazzola, Edoardo
A1 Trotta, Giulia
A1 Jongsma, Hannah E
A1 Stilo, Simona
A1 La Cascia, Caterina
A1 Ferraro, Laura
A1 La Barbera, Daniele
A1 Lasalvia, Antonio
A1 Tosato, Sarah
A1 Tarricone, Ilaria
A1 Bonora, Elena
A1 Jamain, Stéphane
A1 Selten, Jean-Paul
A1 Velthorst, Eva
A1 de Haan, Lieuwe
A1 Llorca, Pierre-Michel
A1 Arrojo, Manuel
A1 Bobes, Julio
A1 Bernardo, Miguel
A1 Arango, Celso
A1 Kirkbride, James
A1 Jones, Peter B
A1 Rutten, Bart P
A1 Richards, Alexander
A1 Sham, Pak C
A1 O'Donovan, Michael
A1 Van Os, Jim
A1 Morgan, Craig
A1 Di Forti, Marta
A1 Murray, Robin M
A1 Vassos, Evangelos
K1 Affective psychosis
K1 bipolar disorder
K1 diagnosis
K1 genetics
K1 polygenic score
K1 psychosis
K1 psychotic depression
K1 schizophrenia-spectrum disorder
AB 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). 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. 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). 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.
YR 2022
FD 2022-01-25
LK http://hdl.handle.net/10668/22574
UL http://hdl.handle.net/10668/22574
LA en
DS RISalud
RD Apr 11, 2025