神经药理学报

神经药理学报 ›› 2018, Vol. 8 ›› Issue (5): 90-91.

• Session 6A: Basic and Clinical Research on Neuropsychiatric • 上一篇    下一篇

Integrative Omics Reveals Novel Genetic and Gene Regulatory Mechanisms Underpinning Schizophrenia

LUO Xiong-jian   

  1. Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province，Kunming Institute of Zoology，CAS，Kunming，China
  • 出版日期:2018-10-26 发布日期:2018-11-16
  • 作者简介:LUO Xiong-jian，E-mail：：luoxiongjian@mail.kiz.ac.cn

Integrative Omics Reveals Novel Genetic and Gene Regulatory Mechanisms Underpinning Schizophrenia

LUO Xiong-jian   

  1. Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province，Kunming Institute of Zoology，CAS，Kunming，China
  • Online:2018-10-26 Published:2018-11-16
  • About author:LUO Xiong-jian，E-mail：：luoxiongjian@mail.kiz.ac.cn

摘要： Schizophrenia is a debilitating brain disorder with a complex genetic architecture. Genetic studies，especially recent genome-wide association studies （GWAS），have identified multiple variants （loci） conferring risk to schizophrenia. However，how to efficiently extract meaningful biological information from bulk genetic findings of schizophrenia remains a major challenge and it is a daunting task to decipher the pathological role of these risk variants in schizophrenia. There is a pressing need to integrate multiple layers of data from various sources，e.g. genetic findings from GWAS，copy number variations （CNVs），association and linkage studies，gene expression，protein-protein interaction （PPI），co-expression，expression quantitative trait loci （eQTL），and Encyclopedia of DNA Elements （ENCODE） data，to provide a comprehensive resource to facilitate the translation of genetic findings into schizophrenia molecular diagnosis and mechanism study. To elucidate the genetic mechanisms of schizophrenia，we utilized integrative omics to systematically integrate multiple layers of data from diverse studies of schizophrenia. Several novel and pivotal schizophrenia risk genes have been identified
by using integrative omics，including CAMKK2，ZNF323，MKL1，GLT8D1 and etc. In addition， integrative omics also revealed the potential mechanisms of CNVs in schizophrenia susceptibility. Finally，based on comprehensive and systematic integration of multiple layers of data from various sources，we developed the SZDB database （http：//www.szdb.org/），a comprehensive resource for schizophrenia research. Schizophrenia genetic data，gene expression data，network-based data，brain eQTL data，and SNP function annotation information were systematically extracted， curated and deposited in SZDB. In-depth analyses and systematic integration were performed to identify top prioritized schizophrenia genes and enriched pathways. Multiple types of data from various layers of schizophrenia research were systematically integrated and deposited in SZDB. In-depth data analyses and integration identified top prioritized SZ genes and enriched pathways. We further showed that genes implicated in schizophrenia are highly co-expressed in human brain and proteins encoded by the prioritized schizophrenia risk genes are significantly interacted. The user-friendly SZDB provides high-confidence candidate variants and genes for further functional characterization. More important，SZDB provides convenient online tools for data search and browse，data integration，and customized data analyses.

Abstract: Schizophrenia is a debilitating brain disorder with a complex genetic architecture. Genetic studies，especially recent genome-wide association studies （GWAS），have identified multiple variants （loci） conferring risk to schizophrenia. However，how to efficiently extract meaningful biological information from bulk genetic findings of schizophrenia remains a major challenge and it is a daunting task to decipher the pathological role of these risk variants in schizophrenia. There is a pressing need to integrate multiple layers of data from various sources，e.g. genetic findings from GWAS，copy number variations （CNVs），association and linkage studies，gene expression，protein-protein interaction （PPI），co-expression，expression quantitative trait loci （eQTL），and Encyclopedia of DNA Elements （ENCODE） data，to provide a comprehensive resource to facilitate the translation of genetic findings into schizophrenia molecular diagnosis and mechanism study. To elucidate the genetic mechanisms of schizophrenia，we utilized integrative omics to systematically integrate multiple layers of data from diverse studies of schizophrenia. Several novel and pivotal schizophrenia risk genes have been identified
by using integrative omics，including CAMKK2，ZNF323，MKL1，GLT8D1 and etc. In addition， integrative omics also revealed the potential mechanisms of CNVs in schizophrenia susceptibility. Finally，based on comprehensive and systematic integration of multiple layers of data from various sources，we developed the SZDB database （http：//www.szdb.org/），a comprehensive resource for schizophrenia research. Schizophrenia genetic data，gene expression data，network-based data，brain eQTL data，and SNP function annotation information were systematically extracted， curated and deposited in SZDB. In-depth analyses and systematic integration were performed to identify top prioritized schizophrenia genes and enriched pathways. Multiple types of data from various layers of schizophrenia research were systematically integrated and deposited in SZDB. In-depth data analyses and integration identified top prioritized SZ genes and enriched pathways. We further showed that genes implicated in schizophrenia are highly co-expressed in human brain and proteins encoded by the prioritized schizophrenia risk genes are significantly interacted. The user-friendly SZDB provides high-confidence candidate variants and genes for further functional characterization. More important，SZDB provides convenient online tools for data search and browse，data integration，and customized data analyses.