Evidence map›Paper›PMID 33392005›Full record

ArticleWorld journal of psychiatry2020

Identification of key genes involved in post-traumatic stress disorder: Evidence from bioinformatics analysis.

Yao-Yao Bian, Li-Li Yang, Bin Zhang, Wen Li, Zheng-Jun Li, Wen-Lin Li, Li Zeng

Abstract read
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Article in World journal of psychiatry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
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2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Yao-Yao BianSchool of Nursing, Nanjing University of Chinese Medicine, Nanjing 210023, Jiangsu Province, China.
Li-Li YangSchool of First Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, Jiangsu Province, China.
Bin ZhangDigestive Department, Ningbo Hospital of Traditional Chinese Medicine, Ningbo 315200, Zhejiang Province, China.
Wen LiSchool of Preclinical Medicine, Guizhou University of Traditional Chinese Medicine, Guiyang 550025, Guizhou Province, China.
Zheng-Jun LiManagement School, University of St Andrews, St Andrews KY16 9AJ, United Kingdom.
Wen-Lin LiJingwen Library, Nanjing University of Chinese Medicine, Nanjing 210023, Jiangsu Province, China.
Li ZengSchool of First Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, Jiangsu Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPost-traumatic stress disorder (PTSD) is a serious stress-related disorder.

aimTo identify the key genes and pathways to uncover the potential mechanisms of PTSD using bioinformatics methods.

methodsGene expression profiles were obtained from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were identified by using GEO2R. Gene functional annotation and pathway enrichment were then conducted. The gene-pathway network was constructed with Cytoscape software. Quantitative real-time polymerase chain reaction (qRT-PCR) analysis was applied for validation, and text mining by Coremine Medical was used to confirm the connections among genes and pathways.

resultsWe identified 973 DEGs including 358 upregulated genes and 615 downregulated genes in PTSD. A group of centrality hub genes and significantly enriched pathways (MAPK, Ras, and ErbB signaling pathways) were identified by using gene functional assignment and enrichment analyses. Six genes (

conclusionThe current study identified a panel of candidate genes and important pathways, which might help us deepen our understanding of the underlying mechanism of PTSD at the molecular level. However, further studies are warranted to discover the critical regulatory mechanism of these genes

Indexed as

Bioinformatics analysisDifferentially expressed genesGene-pathway co-expressionKey pathwayMicroarrayPost-traumatic stress disorder

Identifiers

PMID33392005
PMCPMC7754529

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