Derivation and utility of schizophrenia polygenic risk associated multimodal MRI frontotemporal network
Author
Qi, ShileSui, Jing
Pearlson, Godfrey
Bustillo, Juan
Perrone-Bizzozero, Nora I.
Kochunov, Peter
Turner, Jessica A.
Fu, Zening
Shao, Wei
Jiang, Rongtao
Yang, Xiao
Liu, Jingyu
Du, Yuhui
Chen, Jiayu
Zhang, Daoqiang
Calhoun, Vince D.
Date
2022-08-22Journal
Nature CommunicationsPublisher
Springer Science and Business Media LLCType
Article
Metadata
Show full item recordAbstract
Schizophrenia is a highly heritable psychiatric disorder characterized by widespread functional and structural brain abnormalities. However, previous association studies between MRI and polygenic risk were mostly ROI-based single modality analyses, rather than identifying brain-based multimodal predictive biomarkers. Based on schizophrenia polygenic risk scores (PRS) from healthy white people within the UK Biobank dataset (N = 22,459), we discovered a robust PRS-associated brain pattern with smaller gray matter volume and decreased functional activation in frontotemporal cortex, which distinguished schizophrenia from controls with >83% accuracy, and predicted cognition and symptoms across 4 independent schizophrenia cohorts. Further multi-disease comparisons demonstrated that these identified frontotemporal alterations were most severe in schizophrenia and schizo-affective patients, milder in bipolar disorder, and indistinguishable from controls in autism, depression and attention-deficit hyperactivity disorder. These findings indicate the potential of the identified PRS-associated multimodal frontotemporal network to serve as a trans-diagnostic gene intermediated brain biomarker specific to schizophrenia.Identifier to cite or link to this item
http://hdl.handle.net/10713/19613ae974a485f413a2113503eed53cd6c53
10.1038/s41467-022-32513-8
Scopus Count
Collections
Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by/4.0