失智症
精神分裂症(面向对象编程)
神经科学
计算机科学
心理学
精神科
医学
多基因风险评分
疾病
计算生物学
生物信息学
痴呆
内科学
生物
遗传学
基因
基因型
单核苷酸多态性
作者
Shile Qi,Jing Sui,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
标识
DOI:10.1038/s41467-022-32513-8
摘要
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.
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