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  • Review Article
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Integrative omics of schizophrenia: from genetic determinants to clinical classification and risk prediction

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.

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Fig. 1: Overall strategy for Schizophrenia Omics research.
Fig. 2: Examples of integrative Omics studies on Schizophrenia.

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Acknowledgements

This work was supported by the Natural Science Foundation of China, Shaanxi Province Innovation Capability Support Project (81772033 and 2020KJXX-039 to FG), National Heart, Lung, and Blood Institute (R01HL141845 to LKW), National Natural Science Foundation of China/Research Grants Council of Hong Kong Joint Research Scheme (8141101084 to PCS), Hong Kong Innovation and Technology Bureau Funding to State Key Laboratories, and Henry Ford Hospital Mentored Scientist grant (A20067 to HG). We thank Mr. Yang Cao and Ms. Dongru Chen for their help about the figures.

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Guan, F., Ni, T., Zhu, W. et al. Integrative omics of schizophrenia: from genetic determinants to clinical classification and risk prediction. Mol Psychiatry 27, 113–126 (2022). https://doi.org/10.1038/s41380-021-01201-2

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