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Multi-scale analysis of schizophrenia risk genes, brain structure, and clinical symptoms reveals integrative clues for subtyping schizophrenia patients
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Ma, Liang, Rolls, Edmund T., Liu, Xiuqin, Liu, Yuting, Jiao, Zeyu, Wang, Yue, Gong, Weikang, Ma, Zhiming, Gong, Fuzhou and Wan, Lin (2018) Multi-scale analysis of schizophrenia risk genes, brain structure, and clinical symptoms reveals integrative clues for subtyping schizophrenia patients. Journal of Molecular Cell Biology . doi:10.1093/jmcb/mjy071 ISSN 1674-2788.
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Official URL: https://doi.org/10.1093/jmcb/mjy071
Abstract
Analysis linking directly genomics, neuroimaging phenotypes and clinical measurements is crucial for understanding psychiatric disorders, but remains rare. Here, we describe a multi-scale analysis using genome-wide SNPs, gene-expression, grey matter volume (GMV) and the Positive and Negative Syndrome Scale scores (PANSS) to explore the etiology of schizophrenia. With 72 drug-naive schizophrenic first episode patients (FEPs) and 73 matched heathy controls, we identified 108 genes, from schizophrenia risk genes, that correlated significantly with GMV, which are highly co-expressed in the brain during development. Among these 108 candidates, 19 distinct genes were found associated with 16 brain regions referred to as hot clusters (HCs), primarily in the frontal cortex, sensory-motor regions and temporal and parietal regions. The patients were subtyped into three groups with distinguishable PANSS scores by the GMV of the identified HCs. Furthermore, we found that HCs with common GMV among patient groups are related to genes that mostly mapped to pathways relevant to neural signaling, which are associated with the risk for schizophrenia. Our results provide an integrated view of how genetic variants may affect brain structures that lead to distinct disease phenotypes. The method of multi-scale analysis that was described in this research, may help to advance the understanding of the etiology of schizophrenia.
Item Type: | Journal Article | ||||||||||||||||||||||||
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Subjects: | R Medicine > RC Internal medicine | ||||||||||||||||||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||||||||||||||||||||
SWORD Depositor: | Library Publications Router | ||||||||||||||||||||||||
Library of Congress Subject Headings (LCSH): | Schizophrenia -- Genetics | ||||||||||||||||||||||||
Journal or Publication Title: | Journal of Molecular Cell Biology | ||||||||||||||||||||||||
Publisher: | Oxford University Press | ||||||||||||||||||||||||
ISSN: | 1674-2788 | ||||||||||||||||||||||||
Official Date: | 3 December 2018 | ||||||||||||||||||||||||
Dates: |
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DOI: | 10.1093/jmcb/mjy071 | ||||||||||||||||||||||||
Status: | Peer Reviewed | ||||||||||||||||||||||||
Publication Status: | Published | ||||||||||||||||||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||||||||||||||||||
Date of first compliant deposit: | 22 January 2019 | ||||||||||||||||||||||||
Date of first compliant Open Access: | 22 January 2019 | ||||||||||||||||||||||||
RIOXX Funder/Project Grant: |
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