Association of schizophrenia polygenic risk score with data-driven cognitive subtypes:: A six-year longitudinal study in patients, siblings and controls

Tesfa Dejenie Habtewold; Edith J  Liemburg; Md Atiqul  Islam; Sonja de Zwarte; H Marike  Boezen; GROUP investigators; Richard Bruggeman; Behrooz Z Alizadeh

doi:10.1016/j.schres.2020.05.020

Association of schizophrenia polygenic risk score with data-driven cognitive subtypes: A six-year longitudinal study in patients, siblings and controls

Tesfa Dejenie Habtewold
, Edith J Liemburg
, Md Atiqul Islam
, Sonja de Zwarte
, H Marike Boezen
, GROUP investigators
, Richard Bruggeman
, Behrooz Z Alizadeh

University Medical Center Groningen
Shahjalal University of Science and Technology
University Medical Center Utrecht
Icahn School of Medicine at Mount Sinai
Maastricht University Medical Centre
KU Leuven
Altrecht Institute for Mental Health Care
Amsterdam University Medical Center
Arkin Mental Health Care
GGzE Centre for Child and Adolescent Psychiatry
Kings College London, University of London
University of Groningen

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

Abstract

Cross-sectional studies have shown that the polygenic risk score for schizophrenia (PRSSCZ) may influence heterogeneity in cognitive performance although evidence from family-based longitudinal study is limited. This study aimed to identify trajectories of cognitive function and assess whether the PRSSCZ is associated with baseline cognitive performance and predicted six-year trajectories. We included 1119 patients with a schizophrenia spectrum disorder, and 1059 unaffected siblings and 586 unrelated controls who are eligible at baseline. Genotype data were collected at baseline, whereas clinical and sociodemographic data were collected at baseline, three and six years. Group-based trajectory modeling was applied on a weighted standardized composite score of general cognition to unravel cognitive subtypes and explore trajectories over time. We followed a standard procedure to calculate the polygenic risk score. A random-effects ordinal regression model was used to investigate the association between PRSSCZ and cognitive subtypes. Five cognitive subtypes with variable trajectories were found in patients, four in siblings and controls, and six in all combined samples. PRSSCZ significantly predicted poor cognitive trajectories in patients, siblings and all samples. After Bonferroni correction and adjustment for non-genetic factors, only the results in all combined sample remained significant. Cognitive impairment in schizophrenia is heterogeneous and may be linked with high PRSSCZ. Our finding confirmed at least in all combined samples the presence of genetic overlap between schizophrenia and cognitive function and can give insight into the mechanisms of cognitive deficits.

Original language	English
Pages (from-to)	135-147
Number of pages	13
Journal	Schizophrenia Research
Volume	223
DOIs	https://doi.org/10.1016/j.schres.2020.05.020
Publication status	Published - Sept 2020
Externally published	Yes

Funding

Tesfa Dejenie is supported by the scholarship for a PhD from the University of Groningen, Groningen, the Netherlands. This research was supported by Geestkracht programme of the Dutch Health Research Council (Zon-Mw) (10-000-1001), and matching funds from participating pharmaceutical companies (Lundbeck; AstraZeneca; Eli Lilly and Janssen Cilag) and, universities and mental health care organizations (Amsterdam: Academic Psychiatric Centre of the Academic Medical Center and the mental health institutions: GGZ Ingeest; Arkin, Dijk en Duin; GGZ Rivierduinen; Erasmus Medical Centre and GGZ Noord Holland Noord. Groningen: University Medical Center Groningen and the mental health institutions: Lentis, GGZ Friesland; GGZ Drenthe; Dimence; Mediant; GGNet Warnsveld; Yulius Dordrecht and Parnassia psycho-medical center The Hague. Maastricht: Maastricht University Medical Centre and the mental health institutions: GGZ Eindhoven en De Kempen; GGZ Breburg; GGZ Oost-Brabant; Vincent van Gogh voor Geestelijke Gezondheid; Mondriaan; Virenze riagg; Zuyderland GGZ; MET ggz; Universitair Centrum Sint-Jozef Kortenberg; CAPRI University of Antwerp; PC Ziekeren Sint-Truiden; PZ Sancta Maria Sint-Truiden; GGZ Overpelt and OPZ Rekem. Utrecht: University Medical Center Utrecht and the mental health institutions: Altrecht; GGZ Centraal and Delta). The sponsors have no role in designing of the study, the collection, analysis, and interpretation of data, the writing of the report and the decision to submit the paper for publication.

Keywords

Cognition
Cognitive trajectory
Heterogeneity
Polygenic risk score
Psychosis
Schizophrenia

Access to Document

10.1016/j.schres.2020.05.020Licence: CC BY

Cite this

Habtewold, T. D., Liemburg, E. J., Islam, M. A., de Zwarte, S., Boezen, H. M., GROUP investigators, Bruggeman, R., & Alizadeh, B. Z. (2020). Association of schizophrenia polygenic risk score with data-driven cognitive subtypes: A six-year longitudinal study in patients, siblings and controls. Schizophrenia Research, 223, 135-147. https://doi.org/10.1016/j.schres.2020.05.020

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AU - Boezen, H Marike

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