Cargando…

Identification of Key Genes and the Pathophysiology Associated With Major Depressive Disorder Patients Based on Integrated Bioinformatics Analysis

Background: At present, laboratory blood tests to support major depressive disorder (MDD) diagnosis are not available. This study aimed to screen potential mRNAs for peripheral blood biomarkers and novel pathophysiology of MDD. Methods: The present study utilized public data from two mRNA microarray...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Guangyin, Xu, Shixin, Zhang, Zhenqing, Zhang, Yu, Wu, Yankun, An, Jing, Lin, Jinyu, Yuan, Zhuo, Shen, Li, Si, Tianmei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7146847/
https://www.ncbi.nlm.nih.gov/pubmed/32317989
http://dx.doi.org/10.3389/fpsyt.2020.00192
_version_ 1783520296058224640
author Zhang, Guangyin
Xu, Shixin
Zhang, Zhenqing
Zhang, Yu
Wu, Yankun
An, Jing
Lin, Jinyu
Yuan, Zhuo
Shen, Li
Si, Tianmei
author_facet Zhang, Guangyin
Xu, Shixin
Zhang, Zhenqing
Zhang, Yu
Wu, Yankun
An, Jing
Lin, Jinyu
Yuan, Zhuo
Shen, Li
Si, Tianmei
author_sort Zhang, Guangyin
collection PubMed
description Background: At present, laboratory blood tests to support major depressive disorder (MDD) diagnosis are not available. This study aimed to screen potential mRNAs for peripheral blood biomarkers and novel pathophysiology of MDD. Methods: The present study utilized public data from two mRNA microarray datasets to analyze the hub genes changes related to MDD. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of differentially expressed genes (DEGs) were performed. Finally, some potential mRNA quality biomarkers for hub gene expression in blood were identified. Results: A total of 25 significantly co-upregulated DEGs and 98 co-downregulated DEGs were obtained from two datasets. The pathway enrichment analyses showed that co-upregulated genes were significantly enriched in the regulation of cell-matrix adhesion and mitochondrial membrane permeability which were involved in the apoptotic process. Co-downregulated genes were mainly involved in the neutrophil activation which in turn was involved in the immune response, degranulation and cell-mediated immunity, positive regulation of immune response, the Toll-like receptor signaling pathway, and the NOD-like receptor signaling pathway. From the PPI network, 14 hub genes were obtained. Among them, the subnetworks of PLCG1, BCL2A1, TLR8, FADD, and TLR4 screened out from our study have been shown to play a role in immune and inflammation responses. Discussion: The potential molecular mechanisms that have been identified simultaneously include innate immunity, neuroinflammation, and neurotrophic factors for synapse function and development.
format Online
Article
Text
id pubmed-7146847
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-71468472020-04-21 Identification of Key Genes and the Pathophysiology Associated With Major Depressive Disorder Patients Based on Integrated Bioinformatics Analysis Zhang, Guangyin Xu, Shixin Zhang, Zhenqing Zhang, Yu Wu, Yankun An, Jing Lin, Jinyu Yuan, Zhuo Shen, Li Si, Tianmei Front Psychiatry Psychiatry Background: At present, laboratory blood tests to support major depressive disorder (MDD) diagnosis are not available. This study aimed to screen potential mRNAs for peripheral blood biomarkers and novel pathophysiology of MDD. Methods: The present study utilized public data from two mRNA microarray datasets to analyze the hub genes changes related to MDD. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of differentially expressed genes (DEGs) were performed. Finally, some potential mRNA quality biomarkers for hub gene expression in blood were identified. Results: A total of 25 significantly co-upregulated DEGs and 98 co-downregulated DEGs were obtained from two datasets. The pathway enrichment analyses showed that co-upregulated genes were significantly enriched in the regulation of cell-matrix adhesion and mitochondrial membrane permeability which were involved in the apoptotic process. Co-downregulated genes were mainly involved in the neutrophil activation which in turn was involved in the immune response, degranulation and cell-mediated immunity, positive regulation of immune response, the Toll-like receptor signaling pathway, and the NOD-like receptor signaling pathway. From the PPI network, 14 hub genes were obtained. Among them, the subnetworks of PLCG1, BCL2A1, TLR8, FADD, and TLR4 screened out from our study have been shown to play a role in immune and inflammation responses. Discussion: The potential molecular mechanisms that have been identified simultaneously include innate immunity, neuroinflammation, and neurotrophic factors for synapse function and development. Frontiers Media S.A. 2020-04-03 /pmc/articles/PMC7146847/ /pubmed/32317989 http://dx.doi.org/10.3389/fpsyt.2020.00192 Text en Copyright © 2020 Zhang, Xu, Zhang, Zhang, Wu, An, Lin, Yuan, Shen and Si. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychiatry
Zhang, Guangyin
Xu, Shixin
Zhang, Zhenqing
Zhang, Yu
Wu, Yankun
An, Jing
Lin, Jinyu
Yuan, Zhuo
Shen, Li
Si, Tianmei
Identification of Key Genes and the Pathophysiology Associated With Major Depressive Disorder Patients Based on Integrated Bioinformatics Analysis
title Identification of Key Genes and the Pathophysiology Associated With Major Depressive Disorder Patients Based on Integrated Bioinformatics Analysis
title_full Identification of Key Genes and the Pathophysiology Associated With Major Depressive Disorder Patients Based on Integrated Bioinformatics Analysis
title_fullStr Identification of Key Genes and the Pathophysiology Associated With Major Depressive Disorder Patients Based on Integrated Bioinformatics Analysis
title_full_unstemmed Identification of Key Genes and the Pathophysiology Associated With Major Depressive Disorder Patients Based on Integrated Bioinformatics Analysis
title_short Identification of Key Genes and the Pathophysiology Associated With Major Depressive Disorder Patients Based on Integrated Bioinformatics Analysis
title_sort identification of key genes and the pathophysiology associated with major depressive disorder patients based on integrated bioinformatics analysis
topic Psychiatry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7146847/
https://www.ncbi.nlm.nih.gov/pubmed/32317989
http://dx.doi.org/10.3389/fpsyt.2020.00192
work_keys_str_mv AT zhangguangyin identificationofkeygenesandthepathophysiologyassociatedwithmajordepressivedisorderpatientsbasedonintegratedbioinformaticsanalysis
AT xushixin identificationofkeygenesandthepathophysiologyassociatedwithmajordepressivedisorderpatientsbasedonintegratedbioinformaticsanalysis
AT zhangzhenqing identificationofkeygenesandthepathophysiologyassociatedwithmajordepressivedisorderpatientsbasedonintegratedbioinformaticsanalysis
AT zhangyu identificationofkeygenesandthepathophysiologyassociatedwithmajordepressivedisorderpatientsbasedonintegratedbioinformaticsanalysis
AT wuyankun identificationofkeygenesandthepathophysiologyassociatedwithmajordepressivedisorderpatientsbasedonintegratedbioinformaticsanalysis
AT anjing identificationofkeygenesandthepathophysiologyassociatedwithmajordepressivedisorderpatientsbasedonintegratedbioinformaticsanalysis
AT linjinyu identificationofkeygenesandthepathophysiologyassociatedwithmajordepressivedisorderpatientsbasedonintegratedbioinformaticsanalysis
AT yuanzhuo identificationofkeygenesandthepathophysiologyassociatedwithmajordepressivedisorderpatientsbasedonintegratedbioinformaticsanalysis
AT shenli identificationofkeygenesandthepathophysiologyassociatedwithmajordepressivedisorderpatientsbasedonintegratedbioinformaticsanalysis
AT sitianmei identificationofkeygenesandthepathophysiologyassociatedwithmajordepressivedisorderpatientsbasedonintegratedbioinformaticsanalysis