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Integrative omics of schizophrenia: from genetic determinants to clinical classification and risk prediction.
Guan, Fanglin; Ni, Tong; Zhu, Weili; Williams, L Keoki; Cui, Long-Biao; Li, Ming; Tubbs, Justin; Sham, Pak-Chung; Gui, Hongsheng.
Affiliation
  • Guan F; Department of Forensic Psychiatry, School of Medicine & Forensics, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.
  • Ni T; Department of Forensic Psychiatry, School of Medicine & Forensics, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.
  • Zhu W; National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China.
  • Williams LK; Center for Individualized and Genomic Medicine Research, Department of Internal Medicine, Henry Ford Health System, Detroit, MI, USA.
  • Cui LB; Department of Clinical Psychology, School of Medical Psychology, Air Force Medical University, Xi'an, Shaanxi, China.
  • Li M; Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.
  • Tubbs J; Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
  • Sham PC; Centre for PanorOmic Sciences, The University of Hong Kong, Hong Kong SAR, China.
  • Gui H; Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China. pcsham@hku.hk.
Mol Psychiatry ; 27(1): 113-126, 2022 01.
Article in En | MEDLINE | ID: mdl-34193973
ABSTRACT
Schizophrenia (SCZ) is a debilitating neuropsychiatric disorder with high heritability and complex inheritance. In the past decade, successful identification of numerous susceptibility loci has provided useful insights into the molecular etiology of SCZ. However, applications of these findings to clinical classification and diagnosis, risk prediction, or intervention for SCZ have been limited, and elucidating the underlying genomic and molecular mechanisms of SCZ is still challenging. More recently, multiple Omics technologies - genomics, transcriptomics, epigenomics, proteomics, metabolomics, connectomics, and gut microbiomics - have all been applied to examine different aspects of SCZ pathogenesis. Integration of multi-Omics data has thus emerged as an approach to provide a more comprehensive view of biological complexity, which is vital to enable translation into assessments and interventions of clinical benefit to individuals with SCZ. In this review, we provide a broad survey of the single-omics studies of SCZ, summarize the advantages and challenges of different Omics technologies, and then focus on studies in which multiple omics data are integrated to unravel the complex pathophysiology of SCZ. We believe that integration of multi-Omics technologies would provide a roadmap to create a more comprehensive picture of interactions involved in the complex pathogenesis of SCZ, constitute a rich resource for elucidating the potential molecular mechanisms of the illness, and eventually improve clinical assessments and interventions of SCZ to address clinical translational questions from bench to bedside.
Subject(s)

Full text: 1 Database: MEDLINE Main subject: Schizophrenia Type of study: Etiology_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Year: 2022 Type: Article

Full text: 1 Database: MEDLINE Main subject: Schizophrenia Type of study: Etiology_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Year: 2022 Type: Article