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Jun 25, 2024;2024

MDDOmics: multi-omics resource of major depressive disorder.

Yichao Zhao, Ju Xiang, Xingyuan Shi, Pengzhen Jia, Yan Zhang, Min Li
Author Information
  1. Yichao Zhao: School of Computer Science and Engineering, Central South University, No.932 South Lushan Road, Changsha 410083, China. ORCID
  2. Ju Xiang: School of Computer and Communication Engineering, Changsha University of Science and Technology, No.45 Chiling Road, Changsha 410114, China. ORCID
  3. Xingyuan Shi: School of Computer Science and Engineering, Central South University, No.932 South Lushan Road, Changsha 410083, China.
  4. Pengzhen Jia: School of Computer Science and Engineering, Central South University, No.932 South Lushan Road, Changsha 410083, China.
  5. Yan Zhang: Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, No.139 Renmin Road Central, Changsha 410011, China.
  6. Min Li: School of Computer Science and Engineering, Central South University, No.932 South Lushan Road, Changsha 410083, China. ORCID
PMID: 38917209 DOI: 10.1093/database/baae042

Abstract

Major depressive disorder (MDD) is a pressing global health issue. Its pathogenesis remains elusive, but numerous studies have revealed its intricate associations with various biological factors. Consequently, there is an urgent need for a comprehensive multi-omics resource to help researchers in conducting multi-omics data analysis for MDD. To address this issue, we constructed the MDDOmics database (Major Depressive Disorder Omics, (https://www.csuligroup.com/MDDOmics/), which integrates an extensive collection of published multi-omics data related to MDD. The database contains 41���222 entries of MDD research results and several original datasets, including Single Nucleotide Polymorphisms, genes, non-coding RNAs, DNA methylations, metabolites and proteins, and offers various interfaces for searching and visualization. We also provide extensive downstream analyses of the collected MDD data, including differential analysis, enrichment analysis and disease-gene prediction. Moreover, the database also incorporates multi-omics data for bipolar disorder, schizophrenia and anxiety disorder, due to the challenge in differentiating MDD from similar psychiatric disorders. In conclusion, by leveraging the rich content and online interfaces from MDDOmics, researchers can conduct more comprehensive analyses of MDD and its similar disorders from various perspectives, thereby gaining a deeper understanding of potential MDD biomarkers and intricate disease pathogenesis. Database URL: https://www.csuligroup.com/MDDOmics/.

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Grants

  1. 2019YFA0706202/National Key Research and Development Project of China
  2. 2019YFA0706202/National Key Research and Development Project of China

MeSH Term

Depressive Disorder, Major
Humans
Databases, Genetic
Polymorphism, Single Nucleotide
Genomics
DNA Methylation
Multiomics
Journal Article

Links to CNCB-NGDC Resources

Database Commons: DBC009219 (MDDOmics)

Word Cloud

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