Chronicity and Sex Affect Genetic Risk Prediction in Schizophrenia
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- Schizophrenia (SCZ) is a severe mental disorder with immense personal and societal costs; identifying individuals at risk is therefore of utmost importance. Genomic risk profile scores (GRPS) have been shown to significantly predict cases-control status. Making use of a large-population based sample from Sweden, we replicate a previous finding demonstrating that the GRPS is strongly associated with admission frequency and chronicity of SCZ. Furthermore, we were able to show a substantial gap in prediction accuracy between males and females. InSchizophrenia (SCZ) is a severe mental disorder with immense personal and societal costs; identifying individuals at risk is therefore of utmost importance. Genomic risk profile scores (GRPS) have been shown to significantly predict cases-control status. Making use of a large-population based sample from Sweden, we replicate a previous finding demonstrating that the GRPS is strongly associated with admission frequency and chronicity of SCZ. Furthermore, we were able to show a substantial gap in prediction accuracy between males and females. In sum, our results indicate that prediction accuracy by GRPS depends on clinical and demographic characteristics.…
Autor(en): | Sandra M. Meier, Anna K. Kähler, Sarah E. Bergen, Patrick F. Sullivan, Christina M. Hultman, Manuel Mattheisen |
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URN: | urn:nbn:de:bvb:20-opus-205677 |
Dokumentart: | Artikel / Aufsatz in einer Zeitschrift |
Institute der Universität: | Medizinische Fakultät / Klinik und Poliklinik für Psychiatrie, Psychosomatik und Psychotherapie |
Sprache der Veröffentlichung: | Englisch |
Titel des übergeordneten Werkes / der Zeitschrift (Englisch): | Frontiers in Psychiatry |
ISSN: | 1664-0640 |
Erscheinungsjahr: | 2020 |
Band / Jahrgang: | 11 |
Aufsatznummer: | 313 |
Originalveröffentlichung / Quelle: | Frontiers in Psychiatry 2020, 11:313. doi: 10.3389/fpsyt.2020.00313 |
DOI: | https://doi.org/10.3389/fpsyt.2020.00313 |
Allgemeine fachliche Zuordnung (DDC-Klassifikation): | 6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit |
Freie Schlagwort(e): | course; polygenic risk score; prediction; schizophrenia; sex |
Datum der Freischaltung: | 03.03.2021 |
Datum der Erstveröffentlichung: | 09.06.2020 |
EU-Projektnummer / Contract (GA) number: | 610307 |
OpenAIRE: | OpenAIRE |
Open-Access-Publikationsfonds / Förderzeitraum 2020 | |
Lizenz (Deutsch): | CC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International |