A polygenic score for schizophrenia predicts glycemic control

• Verfasst von: Cao, Han [VerfasserIn]
• Verfasst von: Chen, Junfang [VerfasserIn]
• Verfasst von: Meyer-Lindenberg, Andreas [VerfasserIn]
• Verfasst von: Schwarz, Emanuel [VerfasserIn]
• Titel: A polygenic score for schizophrenia predicts glycemic control
• Verf.angabe: Han Cao, Junfang Chen, Andreas Meyer-Lindenberg, Emanuel Schwarz
• E-Jahr: 2017
• Jahr: 18 December 2017
• Umfang: 9 S.
• Fussnoten: Gesehen am 16.04.2018
• Titel Quelle: Enthalten in: Translational Psychiatry
• Ort Quelle: London : Nature Publishing Group, 2011
• Jahr Quelle: 2017
• Band/Heft Quelle: 7(2017), 12, Artikel-ID 1295, Seite 1-9
• ISSN Quelle: 2158-3188
• DOI: doi:10.1038/s41398-017-0044-z
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1572028165

Abstract

Schizophrenia is substantially comorbid with type 2 diabetes (T2D), but the molecular basis of this effect is incompletely understood. Here, we show that a cortical schizophrenia expression score predicts glycemic control from pancreatic islet cell expression. We used machine learning to identify a cortical expression signature in 212 schizophrenia patients and controls, which explained ~25% of the illness-associated variance. The algorithm was predicted in expression data from 51 subjects (9 with T2D), explained up to 26.3% of the variance in the glycemic control indicator HbA1c and could significantly differentiate T2D patients from controls. The cross-tissue prediction was driven by processes previously linked to diabetes. Genes contributing to this prediction were involved in the electron transport chain as well as kidney development and support oxidative stress as a molecular process underlying the comorbidity between both conditions. Together, the present results suggest a molecular commonality between schizophrenia and glycemic markers of type 2 diabetes.