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

Victoria Rodriguez; Luis Alameda; Diego Quattrone; Giada Tripoli; Charlotte Gayer-Anderson; Edoardo Spinazzola; Giulia Trotta; Hannah E Jongsma; Simona Stilo; Caterina La Cascia; Laura Ferraro; Daniele La Barbera; Antonio Lasalvia; Sarah Tosato; Ilaria Tarricone; Elena Bonora; Stéphane Jamain; Jean-Paul Selten; Eva Velthorst; Lieuwe de Haan; Pierre-Michel Llorca; Manuel Arrojo; Julio Bobes; Miguel Bernardo; Celso Arango; James Kirkbride; Peter B Jones; Bart P Rutten; Alexander Richards; Pak C Sham; Michael O'Donovan; Jim Van Os; Craig Morgan; Marta Di Forti; Robin M Murray; Evangelos Vassos

doi:10.1017/S0033291721005456

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

Victoria Rodriguez, Luis Alameda, Diego Quattrone, Giada Tripoli, Charlotte Gayer-Anderson, Edoardo Spinazzola, Giulia Trotta, Hannah E Jongsma, Simona Stilo, Caterina La Cascia, Laura Ferraro, Daniele La Barbera, Antonio Lasalvia, Sarah Tosato, Ilaria Tarricone, Elena Bonora, Stéphane Jamain, Jean-Paul Selten, Eva Velthorst, Lieuwe de HaanPierre-Michel Llorca, Manuel Arrojo, Julio Bobes, Miguel Bernardo, Celso Arango, James Kirkbride, Peter B Jones, Bart P Rutten, Alexander Richards, Pak C Sham, Michael O'Donovan, Jim Van Os, Craig Morgan, Marta Di Forti, Robin M Murray^*, Evangelos Vassos^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

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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).

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.

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).

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.

Original language	English
Pages (from-to)	3396-3405
Number of pages	10
Journal	Psychological medicine
Volume	53
Issue number	8
Early online date	25 Jan 2022
DOIs	https://doi.org/10.1017/S0033291721005456
Publication status	Published - Jun 2023

Keywords

Affective psychosis
bipolar disorder
diagnosis
genetics
polygenic score
psychosis
psychotic depression
schizophrenia-spectrum disorder

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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-studyFinal published version, 485 KBLicence: CC BY

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Rodriguez, V., Alameda, L., Quattrone, D., Tripoli, G., Gayer-Anderson, C., Spinazzola, E., Trotta, G., Jongsma, H. E., Stilo, S., La Cascia, C., Ferraro, L., La Barbera, D., Lasalvia, A., Tosato, S., Tarricone, I., Bonora, E., Jamain, S., Selten, J.-P., Velthorst, E., ... Vassos, E. (2023). Use of multiple polygenic risk scores for distinguishing schizophrenia-spectrum disorder and affective psychosis categories in a first-episode sample; the EU-GEI study. Psychological medicine, 53(8), 3396-3405. https://doi.org/10.1017/S0033291721005456

@article{c6dd63bda3fe44e8b428dbf45f03e2a0,

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

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).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.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).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.",

keywords = "Affective psychosis, bipolar disorder, diagnosis, genetics, polygenic score, psychosis, psychotic depression, schizophrenia-spectrum disorder",

author = "Victoria Rodriguez and Luis Alameda and Diego Quattrone and Giada Tripoli and Charlotte Gayer-Anderson and Edoardo Spinazzola and Giulia Trotta and Jongsma, {Hannah E} and Simona Stilo and {La Cascia}, Caterina and Laura Ferraro and {La Barbera}, Daniele and Antonio Lasalvia and Sarah Tosato and Ilaria Tarricone and Elena Bonora and St{\'e}phane Jamain and Jean-Paul Selten and Eva Velthorst and {de Haan}, Lieuwe and Pierre-Michel Llorca and Manuel Arrojo and Julio Bobes and Miguel Bernardo and Celso Arango and James Kirkbride and Jones, {Peter B} and Rutten, {Bart P} and Alexander Richards and Sham, {Pak C} and Michael O'Donovan and {Van Os}, Jim and Craig Morgan and {Di Forti}, Marta and Murray, {Robin M} and Evangelos Vassos",

note = "Funding Information: This work was supported by funding from the European Community's Seventh Framework Programme under grant agreement No. HEALTH-F2-2010-241909 (Project EU-GEI). VR was funded by a PhD scholarship supported by Lord Leverhulme's Charitable Trust and the Velvet Foundation. EV is funded by the National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. CA was supported by the Spanish Ministry of Science and Innovation; Instituto de Salud Carlos III (SAM16PE07CP1, PI16/02012, PI19/024), co-financed by ERDF Funds from the European Commission, {\textquoteleft}A way of making Europe{\textquoteright}, CIBERSAM. Madrid Regional Government (B2017/BMD-3740 AGES-CM-2), Fundaci{\'o}n Familia Alonso and Fundaci{\'o}n Alicia Koplowitz. MB was supported by the Ministry od Economy and Competitivity (PI08/0208; PI11/00325; PI14/00612), Instituto de Salud Carlos III – ERDF Funds from the European Commission, {\textquoteleft}A way of making Europe{\textquoteright}, CIBERSAM, by the CERCA Programme/Generalitat de Catalunya and Secretaria d'Universitats i Recerca del Departament d'Economia I Coneixement (2017SGR1355). Departament de Salut de la Generalitat de Catalunya, en la convocatoria corresponent a l'any 2017 de concessi{\'o} de subvencions del PERIS 2016-2020, modalitat Projectes de recerca orientats a l'atenci{\'o} prim{\`a}ria, amb el codi d'expedient SLT006/17/00345; and grateful for the support of the Institut de Neuroci{\`e}ncies, Universitat de Barcelona. Publisher Copyright: Copyright {\textcopyright} The Author(s), 2022. Published by Cambridge University Press.",

year = "2023",

month = jun,

doi = "10.1017/S0033291721005456",

language = "English",

volume = "53",

pages = "3396--3405",

journal = "Psychological medicine",

issn = "0033-2917",

publisher = "Cambridge University Press",

number = "8",

}

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, J-P, Velthorst, E, de Haan, L, Llorca, P-M, 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 2023, 'Use of multiple polygenic risk scores for distinguishing schizophrenia-spectrum disorder and affective psychosis categories in a first-episode sample; the EU-GEI study', Psychological medicine, vol. 53, no. 8, pp. 3396-3405. https://doi.org/10.1017/S0033291721005456

Use of multiple polygenic risk scores for distinguishing schizophrenia-spectrum disorder and affective psychosis categories in a first-episode sample; the EU-GEI study. / Rodriguez, Victoria; Alameda, Luis; Quattrone, Diego et al.
In: Psychological medicine, Vol. 53, No. 8, 06.2023, p. 3396-3405.

Research output: Contribution to journal › Article › Academic › peer-review

TY - JOUR

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

AU - Rodriguez, Victoria

AU - Alameda, Luis

AU - Quattrone, Diego

AU - Tripoli, Giada

AU - Gayer-Anderson, Charlotte

AU - Spinazzola, Edoardo

AU - Trotta, Giulia

AU - Jongsma, Hannah E

AU - Stilo, Simona

AU - La Cascia, Caterina

AU - Ferraro, Laura

AU - La Barbera, Daniele

AU - Lasalvia, Antonio

AU - Tosato, Sarah

AU - Tarricone, Ilaria

AU - Bonora, Elena

AU - Jamain, Stéphane

AU - Selten, Jean-Paul

AU - Velthorst, Eva

AU - de Haan, Lieuwe

AU - Llorca, Pierre-Michel

AU - Arrojo, Manuel

AU - Bobes, Julio

AU - Bernardo, Miguel

AU - Arango, Celso

AU - Kirkbride, James

AU - Jones, Peter B

AU - Rutten, Bart P

AU - Richards, Alexander

AU - Sham, Pak C

AU - O'Donovan, Michael

AU - Van Os, Jim

AU - Morgan, Craig

AU - Di Forti, Marta

AU - Murray, Robin M

AU - Vassos, Evangelos

N1 - Funding Information: This work was supported by funding from the European Community's Seventh Framework Programme under grant agreement No. HEALTH-F2-2010-241909 (Project EU-GEI). VR was funded by a PhD scholarship supported by Lord Leverhulme's Charitable Trust and the Velvet Foundation. EV is funded by the National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. CA was supported by the Spanish Ministry of Science and Innovation; Instituto de Salud Carlos III (SAM16PE07CP1, PI16/02012, PI19/024), co-financed by ERDF Funds from the European Commission, ‘A way of making Europe’, CIBERSAM. Madrid Regional Government (B2017/BMD-3740 AGES-CM-2), Fundación Familia Alonso and Fundación Alicia Koplowitz. MB was supported by the Ministry od Economy and Competitivity (PI08/0208; PI11/00325; PI14/00612), Instituto de Salud Carlos III – ERDF Funds from the European Commission, ‘A way of making Europe’, CIBERSAM, by the CERCA Programme/Generalitat de Catalunya and Secretaria d'Universitats i Recerca del Departament d'Economia I Coneixement (2017SGR1355). Departament de Salut de la Generalitat de Catalunya, en la convocatoria corresponent a l'any 2017 de concessió de subvencions del PERIS 2016-2020, modalitat Projectes de recerca orientats a l'atenció primària, amb el codi d'expedient SLT006/17/00345; and grateful for the support of the Institut de Neurociències, Universitat de Barcelona. Publisher Copyright: Copyright © The Author(s), 2022. Published by Cambridge University Press.

PY - 2023/6

Y1 - 2023/6

N2 - 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).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.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).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.

AB - 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).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.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).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.

KW - Affective psychosis

KW - bipolar disorder

KW - diagnosis

KW - genetics

KW - polygenic score

KW - psychosis

KW - psychotic depression

KW - schizophrenia-spectrum disorder

UR - http://www.scopus.com/inward/record.url?scp=85124036312&partnerID=8YFLogxK

U2 - 10.1017/S0033291721005456

DO - 10.1017/S0033291721005456

M3 - Article

C2 - 35076361

SN - 0033-2917

VL - 53

SP - 3396

EP - 3405

JO - Psychological medicine

JF - Psychological medicine

IS - 8

ER -

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

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