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Multi-scale analysis of schizophrenia risk genes, brain structure, and clinical symptoms reveals integrative clues for subtyping schizophrenia patients
Ma, Liang1,2; Rolls, Edmund T.3,4; Liu, Xiuqin5; Liu, Yuting6; Jiao, Zeyu7; Wang, Yue6; Gong, Weikang8,9; Ma, Zhiming2; Gong, Fuzhou2; Wan, Lin2,9
2019-08-01
Source PublicationJOURNAL OF MOLECULAR CELL BIOLOGY
ISSN1674-2788
Volume11Issue:8Pages:678-687
AbstractAnalysis 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.
KeywordSchizophrenia PANSS multi-scale analysis hot cluster grey matter volume pathway
DOI10.1093/jmcb/mjy071
Indexed BySCI
Language英语
Funding ProjectNSFC[81673833] ; NSFC[11571349] ; NSFC[91630314] ; Strategic Priority Research Program of Chinese Academy of Sciences (CAS)[XDB13050000] ; NCMIS of CAS ; LSC of CAS ; Youth Innovation Promotion Association of CAS
WOS Research AreaCell Biology
WOS SubjectCell Biology
WOS IDWOS:000493042300006
PublisherOXFORD UNIV PRESS
Citation statistics
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/50688
Collection中国科学院数学与系统科学研究院
Corresponding AuthorWan, Lin
Affiliation1.Chinese Acad Sci, Beijing Inst Genom, Key Lab Genom & Precis Med, Beijing 100101, Peoples R China
2.Chinese Acad Sci, Acad Math & Syst Sci, Natl Ctr Math & Interdisciplinary Sci, Beijing 100190, Peoples R China
3.Univ Warwick, Dept Comp Sci, Coventry CV4 7AL, W Midlands, England
4.Oxford Ctr Computat Neurosci, Oxford OX2 7JF, England
5.Univ Sci & Technol Beijing, Sch Math & Phys, Beijing 100083, Peoples R China
6.Beijing Jiaotong Univ, Sch Sci, Beijing 100044, Peoples R China
7.Fudan Univ, Sch Math Sci, Ctr Computat Syst Biol, Shanghai 200433, Peoples R China
8.Chinese Acad Sci, MPG Partner Inst Computat Biol, Shanghai Inst Biol Sci, Shanghai 200031, Peoples R China
9.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
Recommended Citation
GB/T 7714
Ma, Liang,Rolls, Edmund T.,Liu, Xiuqin,et al. Multi-scale analysis of schizophrenia risk genes, brain structure, and clinical symptoms reveals integrative clues for subtyping schizophrenia patients[J]. JOURNAL OF MOLECULAR CELL BIOLOGY,2019,11(8):678-687.
APA Ma, Liang.,Rolls, Edmund T..,Liu, Xiuqin.,Liu, Yuting.,Jiao, Zeyu.,...&Wan, Lin.(2019).Multi-scale analysis of schizophrenia risk genes, brain structure, and clinical symptoms reveals integrative clues for subtyping schizophrenia patients.JOURNAL OF MOLECULAR CELL BIOLOGY,11(8),678-687.
MLA Ma, Liang,et al."Multi-scale analysis of schizophrenia risk genes, brain structure, and clinical symptoms reveals integrative clues for subtyping schizophrenia patients".JOURNAL OF MOLECULAR CELL BIOLOGY 11.8(2019):678-687.
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