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Polygenic effects of schizophrenia on hippocampal grey matter volume and hippocampus-medial prefrontal cortex functional connectivity.
Liu, Shu; Li, Ang; Liu, Yong; Yan, Hao; Wang, Meng; Sun, Yuqing; Fan, Lingzhong; Song, Ming; Xu, Kaibin; Chen, Jun; Chen, Yunchun; Wang, Huaning; Guo, Hua; Wan, Ping; Lv, Luxian; Yang, Yongfeng; Li, Peng; Lu, Lin; Yan, Jun; Wang, Huiling; Zhang, Hongxing; Wu, Huawang; Ning, Yuping; Zhang, Dai; Jiang, Tianzi; Liu, Bing.
Afiliação
  • Liu S; MSc Student, Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences.
  • Li A; School of Artificial Intelligence, University of Chinese Academy of Sciences, China.
  • Liu Y; School of Artificial Intelligence, University of Chinese Academy of Sciences, China.
  • Yan H; PhD Student, Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences.
  • Wang M; School of Artificial Intelligence, University of Chinese Academy of Sciences, China.
  • Sun Y; Professor, Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences.
  • Fan L; Associate Professor, Peking University Sixth Hospital, Institute of Mental Health.
  • Song M; Key Laboratory of Mental Health, Ministry of Health (Peking University), China.
  • Xu K; School of Artificial Intelligence, University of Chinese Academy of Sciences, China.
  • Chen J; PhD Student, Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences.
  • Chen Y; School of Artificial Intelligence, University of Chinese Academy of Sciences, China.
  • Wang H; PhD Student, Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences.
  • Guo H; School of Artificial Intelligence, University of Chinese Academy of Sciences, China.
  • Wan P; Professor, Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences.
  • Lv L; School of Artificial Intelligence, University of Chinese Academy of Sciences, China.
  • Yang Y; Associate Professor, Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences.
  • Li P; School of Artificial Intelligence, University of Chinese Academy of Sciences, China.
  • Lu L; PhD Student, Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences.
  • Yan J; Associate Professor, Department of Radiology, Renmin Hospital of Wuhan University, China.
  • Wang H; Associate Professor, Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, China.
  • Zhang H; Associate Professor, Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, China.
  • Wu H; Professor, Zhumadian Psychiatric Hospital, China.
  • Ning Y; Professor, Zhumadian Psychiatric Hospital, China.
  • Zhang D; Professor, Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University.
  • Jiang T; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, China.
  • Liu B; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, China.
Br J Psychiatry ; 216(5): 267-274, 2020 05.
Article em En | MEDLINE | ID: mdl-31169117
ABSTRACT

BACKGROUND:

Schizophrenia is a complex mental disorder with high heritability and polygenic inheritance. Multimodal neuroimaging studies have also indicated that abnormalities of brain structure and function are a plausible neurobiological characterisation of schizophrenia. However, the polygenic effects of schizophrenia on these imaging endophenotypes have not yet been fully elucidated.

AIMS:

To investigate the effects of polygenic risk for schizophrenia on the brain grey matter volume and functional connectivity, which are disrupted in schizophrenia.

METHOD:

Genomic and neuroimaging data from a large sample of Han Chinese patients with schizophrenia (N = 509) and healthy controls (N = 502) were included in this study. We examined grey matter volume and functional connectivity via structural and functional magnetic resonance imaging, respectively. Using the data from a recent meta-analysis of a genome-wide association study that comprised a large number of Chinese people, we calculated a polygenic risk score (PGRS) for each participant.

RESULTS:

The imaging genetic analysis revealed that the individual PGRS showed a significantly negative correlation with the hippocampal grey matter volume and hippocampus-medial prefrontal cortex functional connectivity, both of which were lower in the people with schizophrenia than in the controls. We also found that the observed neuroimaging measures showed weak but similar changes in unaffected first-degree relatives of patients with schizophrenia.

CONCLUSIONS:

These findings suggested that genetically influenced brain grey matter volume and functional connectivity may provide important clues for understanding the pathological mechanisms of schizophrenia and for the early diagnosis of schizophrenia.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Esquizofrenia / Córtex Pré-Frontal / Herança Multifatorial / Substância Cinzenta / Hipocampo Tipo de estudo: Diagnostic_studies / Screening_studies Limite: Adolescent / Adult / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Esquizofrenia / Córtex Pré-Frontal / Herança Multifatorial / Substância Cinzenta / Hipocampo Tipo de estudo: Diagnostic_studies / Screening_studies Limite: Adolescent / Adult / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2020 Tipo de documento: Article