Derivation and utility of schizophrenia polygenic risk associated multimodal MRI frontotemporal network

• Authors: Shile Qi, Nanjing University of Aeronautics & Astronautics; Jing Sui, Beijing Normal University; Godfrey Pearlson, Yale School of Medicine; Juan Bustillo, University of New Mexico; Nora I Perrone-Bizzozero, University of New Mexico; Peter Kochunov, Univ Maryland; Jessica A Turner, Georgia State University; Zening Fu, Emory University; Wei Shao, Nanjing University of Aeronautics & Astronautics; Rongtao Jiang, Yale University; Xiao Yang, Sichuan University; Jingyu Liu, Emory University; Yuhui Du, Shanxi University; Jiayu Chen, Emory University; Daoqiang Zhang, Nanjing University of Aeronautics & Astronautics; Vince Calhoun, Emory University
• Journal Title: NATURE COMMUNICATIONS
• Volume: Volume 13, Number 1
• Publisher: NATURE PORTFOLIO | 2022-08-22, Pages 4929-4929
• Type of Work: Article | Final Publisher PDF
• Publisher DOI: http://doi.org/10.1038/s41467-022-32513-8
• Subjects: Health Sciences, Mental Health
• Keywords: Science & Technology; Multidisciplinary Sciences; Science & Technology - Other Topics; CONFOUND REGRESSION; MOTION ARTIFACT; BRAIN; SYMPTOMS; GENETICS; GENOMICS; SCORE

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.