MENDA: a comprehensive curated resource of metabolic characterization in depression

Pu, Juncai; Yu, Yue; Liu, Yiyun; Tian, Lu; Gui, Siwen; Zhong, Xiaogang; Fan, Chu; Xu, Shaohua; Song, Xuemian; Liu, Lanxiang; Yang, Lining; Zheng, Peng; Chen, Jianjun; Cheng, Ke; Zhou, Chanjuan; Wang, Haiyang; Xie, Peng

doi:10.1093/bib/bbz055

Cited by 35 publications

(29 citation statements)

References 47 publications

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“…cn:8080/index.php), our online database of existing metabolic characterization studies associated with depression. We updated our search up to January 2019, using our previously reported search terms [24]. In this study, we narrowed our selection according to the following steps.…”

Section: Identification Of Relevant Studiesmentioning

confidence: 99%

An integrated meta-analysis of peripheral blood metabolites and biological functions in major depressive disorder

et al. 2020

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Major depressive disorder (MDD) is a serious mental illness, characterized by high morbidity, which has increased in recent decades. However, the molecular mechanisms underlying MDD remain unclear. Previous studies have identified altered metabolic profiles in peripheral tissues associated with MDD. Using curated metabolic characterization data from a large sample of MDD patients, we meta-analyzed the results of metabolites in peripheral blood. Pathway and network analyses were then performed to elucidate the biological themes within these altered metabolites. We identified 23 differentially expressed metabolites between MDD patients and controls from 46 studies. MDD patients were characterized by higher levels of asymmetric dimethylarginine, tyramine, 2-hydroxybutyric acid, phosphatidylcholine (32:1), and taurochenodesoxycholic acid and lower levels of L-acetylcarnitine, creatinine, L-asparagine, L-glutamine, linoleic acid, pyruvic acid, palmitoleic acid, L-serine, oleic acid, myo-inositol, dodecanoic acid, L-methionine, hypoxanthine, palmitic acid, L-tryptophan, kynurenic acid, taurine, and 25-hydroxyvitamin D compared with controls. L-tryptophan and kynurenic acid were consistently downregulated in MDD patients, regardless of antidepressant exposure. Depression rating scores were negatively associated with decreased levels of L-tryptophan. Pathway and network analyses revealed altered amino acid metabolism and lipid metabolism, especially for the tryptophan-kynurenine pathway and fatty acid metabolism, in the peripheral system of MDD patients. Taken together, our integrated results revealed that metabolic changes in the peripheral blood were associated with MDD, particularly decreased L-tryptophan and kynurenic acid levels, and alterations in the tryptophan-kynurenine and fatty acid metabolism pathways. Our findings may facilitate biomarker development and the elucidation of the molecular mechanisms that underly MDD.

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Section: Identification Of Relevant Studiesmentioning

confidence: 99%

An integrated meta-analysis of peripheral blood metabolites and biological functions in major depressive disorder

et al. 2020

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“…The API has been available since April 2017 and a few internal and external applications are already making use of the new functionality: DataMed (https://datamed.org/) (7) or MENDA (http://menda.cqmu.edu.cn:8080/index.php) (8). Since the first release, the OmicsDI datasets has have been visited in the OmicsDI web site 1,233,388, 253,428, 435,859, 860,092, 1,417,107, 14,793,937 times for genomics, metabolomics, models, multiomics, proteomics and transcriptomics, respectively.…”

Section: Discussionmentioning

confidence: 99%

“…In addition, it allows to perform search and filters on the datasets by different properties such as tissue, cell type, or organisms. This API is used by different external resources, such as DataMed (https://datamed.org/) (7) or MENDA (http://menda.cqmu.edu.cn:8080/index.php) (8). Finally, we introduce two new client libraries in R (ddiR -https://github.com/OmicsDI/ddiR) and python (ddipy -https://github.com/OmicsDI/ddipy ) to enable bioinformaticians and developers to develop new tools and packages that interact with OmicsDI.…”

Section: Introductionmentioning

confidence: 99%

The Omics Discovery REST interface

Dass

et al. 2020

Preprint

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AbstractThe Omics Discovery Index is an open source platform that can be used to access, discover and disseminate omics datasets. OmicsDI integrates proteomics, genomics, metabolomics, models and transcriptomics datasets. Using an efficient indexing system, OmicsDI integrates different biological entities including genes, transcripts, proteins, metabolites and the corresponding publications from PubMed. In addition, it implements a group of pipelines to estimate the impact of each dataset by tracing the number of citations, reanalysis and biological entities reported by each dataset. Here, we present the OmicsDI REST interface to enable programmatic access to any dataset in OmicsDI or all the datasets for a specific provider (database). Clients can perform queries on the API using different metadata information such as sample details (species, tissues, etc), instrumentation (mass spectrometer, sequencer), keywords and other provided annotations. In addition, we present two different libraries in R and Python to facilitate the development of tools that can programmatically interact with the OmicsDI REST interface.

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“…We manually collected candidate genes and proteins associated with VKH disease by a thorough review of the literature in any language published from May 1981 to November 2019, using a similar approach used earlier by others (9,10). We used the following terms to search the PubMed database: "idiopathic uveoencephalitis" OR uveoencephalitis OR "uveomeningitic syndrome" OR Vogt-Koyanagi-Harada.…”

Section: Identifying Candidate Genes and Proteins Associated With Vkhmentioning

confidence: 99%

Integrated Analysis of Key Pathways and Drug Targets Associated With Vogt-Koyanagi-Harada Disease

et al. 2020

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BackgroundVogt-Koyanagi-Harada (VKH) disease is a complex disease associated with multiple molecular immunological mechanisms. As the underlying mechanism for VKH disease is unclear, we hope to utilize an integrated analysis of key pathways and drug targets to develop novel therapeutic strategies.MethodsCandidate genes and proteins involved in VKH disease were identified through text-mining in the PubMed database. The GO and KEGG pathway analyses were used to examine the biological functions of the involved pathways associated with this disease. Molecule-related drugs were predicted through Drug-Gene Interaction Database (DGIdb) analysis.ResultsA total of 48 genes and 54 proteins were associated with VKH disease. Forty-two significantly altered pathways were identified through pathway analysis and were mainly related to immune and inflammatory responses. The top five of significantly altered pathways were termed as “inflammatory bowel disease,” “cytokine-cytokine receptor interaction,” “allograft rejection,” “antigen processing,” and “presentation and Herpes simplex infection” in the KEGG database. IFN-γ and IL-6 were identified as the key genes through network analysis. The DGIdb analysis predicted 48 medicines as possible drugs for VKH disease, among which Interferon Alfa-2B was co-associated both with IFN-γ and IL-6.ConclusionsIn this study, systematic analyses were utilized to detect key pathways and drug targets in VKH disease via bioinformatics analysis. IFN-γ and IL-6 were identified as the key mediators and possible drug targets in VKH disease. Interferon Alfa-2B was predicted to be a potentially effective drug for VKH disease treatment by targeting IFN-γ and IL-6, which warrants further experimental and clinical investigations.

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MENDA: a comprehensive curated resource of metabolic characterization in depression

Cited by 35 publications

References 47 publications

An integrated meta-analysis of peripheral blood metabolites and biological functions in major depressive disorder

An integrated meta-analysis of peripheral blood metabolites and biological functions in major depressive disorder

The Omics Discovery REST interface

Integrated Analysis of Key Pathways and Drug Targets Associated With Vogt-Koyanagi-Harada Disease

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