Derivation and utility of schizophrenia polygenic risk associated multimodal MRI frontotemporal network
Shile Qi, Jing Sui （Beijing Normal University）， my correct affiliation is beijing normal university, not Qingdao University of Science and Technology, please correct the current affiliation. Thank you, Godfrey D. Pearlson, Juan Bustillo, Nora I. Perrone‐Bizzozero, Peter Kochunov, Jessica A. Turner, Zening Fu, Wei Shao, Rongtao Jiang, Xiao Yang, Jingyu Liu, Yuhui Du, Jiayu Chen, Daoqiang Zhang, Vince D. Calhoun
Abstract
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.