Identification of Crucial Genes and Diagnostic Value Analysis in Major Depressive Disorder Using Bioinformatics Analysis

2020 ◽  
Vol 23 ◽  
Author(s):  
Yao Gao ◽  
Huiliang Zhao ◽  
Teng Xu ◽  
Junsheng Tian ◽  
Xuemei Qin
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Hub Genes ◽  
Major Depressive ◽  
Diagnostic Ability ◽  
Value Analysis

Aim and Objective:: Despite the prevalence and burden of major depressive disorder (MDD), our current understanding of the pathophysiology is still incomplete. Therefore, this paper aims to explore genes and evaluate their diagnostic ability in the pathogenesis of MDD. Methods:: Firstly, the expression profiles of mRNA and microRNA were downloaded from the gene expression database and analyzed by the GEO2R online tool to identify differentially expressed genes (DEGs) and differentially expressed microRNAs (DEMs). Then, the DAVID tool was used for functional enrichment analysis. Secondly, the comprehensive protein- protein interaction (PPI) network was analyzed using Cytoscape, and the network MCODE was applied to explore hub genes. Thirdly, the receiver operating characteristic (ROC) curve of the core gene was drawn to evaluate clinical diagnostic ability. Finally, mirecords was used to predict the target genes of DEMs. Results:: A total of 154 genes were identified as DEGs, and 14 microRNAs were identified as DEMs. Pathway enrichment analysis showed that DEGs were mainly involved in hematopoietic cell lineage, PI3K-Akt signaling pathway, cytokinecytokine receptor interaction, chemokine signaling pathway, and JAK-STAT signaling pathway. Three important modules are identified and selected by the MCODE clustering algorithm. The top 12 hub genes including CXCL16, CXCL1, GNB5, GNB4, OPRL1, SSTR2, IL7R, MYB, CSF1R, GSTM1, GSTM2, and GSTP1 were identified as important genes for subsequent analysis. Among these important hub genes, GSTM2, GNB4, GSTP1 and CXCL1 have good diagnostic ability. Finally, by combining these four genes, the diagnostic ability of MDD can be improved to 0.905, which is of great significance for the clinical diagnosis of MDD. Conclusion:: Our results indicate that GSTM2, GNB4, GSTP1 and CXCL1 have potential diagnostic markers and are of great significance in clinical research and diagnostic application of MDD. This result needs a large sample study to further confirm the pathogenesis of MDD.

scholarly journals Identification of Core Genes and Pathways in Major Depressive Disorder Applying Bioinformatics

2020 ◽  
Author(s):  
Wenshan Yang ◽  
Hong Yin ◽  
Yichen Wang ◽  
Ping Liu ◽  
Yuan Hu
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Signaling Pathway ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Ppi Network ◽  
Biological Mechanisms ◽  
Major Depressive ◽  
Kegg Pathway Analysis ◽  
Depressive Patients

Abstract Background: Although extensive study efforts on major depressive disorder (MDD), the pathogenesis related to the biological factors are not fully understood and present therapeutic regimen are ineffective in some depressive patients. This study aims to identify key genes and pathways associated with the molecular biological mechanisms of major depressive disorder through bioinformatics analysis in the Gene Expression Omnibus (GEO) public database of the National Center for Biotechnology Information (NCBI) website.Materials and methods: The whole-transcriptome brain expression profile dataset (GSE101521) was obtained from the GEO database. Differentially-expressed genes (DEGs) in normal group (non-psychiatric human) and MDD group (depressive patients) were identified applying Networkanalyst online database. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to function annotation and enrichment analysis. After that, STRING online database was conducted to protein–protein interaction (PPI) network, and Cytoscape.3.7.2 software was performed to module analysis. Results: Out of the 41 DEGs identified from normal tissue samples and MDD, 39 were upregulated and 2 were downregulated. GO enrichment analysis discovered that DEGs were primarily involved in inflammatory response, and KEGG pathway analysis suggested that the most chiefly pathway related to MDD were IL-17 signaling pathway, TNF signaling pathway and NOD-like receptor signaling pathway. Six hub genes (IL6, CXCL8, IL1B, FOS, CCL2 and CXCL2) were identified by PPI network and module analysis. Conclusion: Our current study detected novel markers and targets involved immune system, which are involved in pivotal biological mechanisms related to the pathogenesis of major depression. Looking forward, these findings still need to be validated in future experimental studies.

scholarly journals Identification of diagnostic markers for major depressive disorder by cross-validation of data from whole blood samples

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7171 ◽  
Author(s):  
Huimei Wang ◽  
Mingwei Zhang ◽  
Qiqi Xie ◽  
Jin Yu ◽  
Yan Qi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Signaling Pathway ◽  
Diagnostic Value ◽  
Ppi Network ◽  
Hub Genes ◽  
Major Depressive ◽  
Blood Samples ◽  
Whole Blood Samples

Background Major depressive disorder (MDD) is a severe disease characterized by multiple pathological changes. However, there are no reliable diagnostic biomarkers for MDD. The aim of the current study was to investigate the gene network and biomarkers underlying the pathophysiology of MDD. Methods In this study, we conducted a comprehensive analysis of the mRNA expression profile of MDD using data from Gene Expression Omnibus (GEO). The MDD dataset (GSE98793) with 128 MDD and 64 control whole blood samples was divided randomly into two non-overlapping groups for cross-validated differential gene expression analysis. The gene ontology (GO) enrichment and gene set enrichment analysis (GSEA) were performed for annotation, visualization, and integrated discovery. Protein–protein interaction (PPI) network was constructed by STRING database and hub genes were identified by the CytoHubba plugin. The gene expression difference and the functional similarity of hub genes were investigated for further gene expression and function exploration. Moreover, the receiver operating characteristic curve was performed to verify the diagnostic value of the hub genes. Results We identified 761 differentially expressed genes closely related to MDD. The Venn diagram and GO analyses indicated that changes in MDD are mainly enriched in ribonucleoprotein complex biogenesis, antigen receptor-mediated signaling pathway, catalytic activity (acting on RNA), structural constituent of ribosome, mitochondrial matrix, and mitochondrial protein complex. The GSEA suggested that tumor necrosis factor signaling pathway, Toll-like receptor signaling pathway, apoptosis pathway, and NF-kappa B signaling pathway are all crucial in the development of MDD. A total of 20 hub genes were selected via the PPI network. Additionally, the identified hub genes were downregulated and show high functional similarity and diagnostic value in MDD. Conclusions Our findings may provide novel insight into the functional characteristics of MDD through integrative analysis of GEO data, and suggest potential biomarkers and therapeutic targets for MDD.

scholarly journals Identification of novel genes and pathways in carotid atheroma using integrated bioinformatic methods

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Wenqing Nai ◽  
Diane Threapleton ◽  
Jingbo Lu ◽  
Kewei Zhang ◽  
Hongyuan Wu ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Transforming Growth Factor ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Transforming Growth Factor Β ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Atheromatous Plaques

Abstract Atherosclerosis is the primary cause of cardiovascular events and its molecular mechanism urgently needs to be clarified. In our study, atheromatous plaques (ATH) and macroscopically intact tissue (MIT) sampled from 32 patients were compared and an integrated series of bioinformatic microarray analyses were used to identify altered genes and pathways. Our work showed 816 genes were differentially expressed between ATH and MIT, including 443 that were up-regulated and 373 that were down-regulated in ATH tissues. GO functional-enrichment analysis for differentially expressed genes (DEGs) indicated that genes related to the “immune response” and “muscle contraction” were altered in ATHs. KEGG pathway-enrichment analysis showed that up-regulated DEGs were significantly enriched in the “FcεRI-mediated signaling pathway”, while down-regulated genes were significantly enriched in the “transforming growth factor-β signaling pathway”. Protein-protein interaction network and module analysis demonstrated that VAV1, SYK, LYN and PTPN6 may play critical roles in the network. Additionally, similar observations were seen in a validation study where SYK, LYN and PTPN6 were markedly elevated in ATH. All in all, identification of these genes and pathways not only provides new insights into the pathogenesis of atherosclerosis, but may also aid in the development of prognostic and therapeutic biomarkers for advanced atheroma.

scholarly journals Identification of Differentially Expressed Kinase and Screening Potential Anticancer Drugs in Papillary Thyroid Carcinoma

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Huairong Zhang ◽  
Bo Gao ◽  
Bingyin Shi
Keyword(s):  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Signaling Pathway ◽  
Protein Kinases ◽  
Molecular Mechanisms ◽  
Kinase Inhibitors ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Papillary Thyroid

Aim. We aim to identify protein kinases involved in the pathophysiology of papillary thyroid carcinoma (PTC) in order to provide potential therapeutic targets for kinase inhibitors and unfold possible molecular mechanisms.Materials and Methods. The gene expression profile of GSE27155 was analyzed to identify differentially expressed genes and mapped onto human protein kinases database. Correlation of kinases with PTC was addressed by systematic literature search, GO and KEGG pathway analysis.Results. The functional enrichment analysis indicated that “mitogen-activated protein kinases pathway” expression was extremely enriched, followed by “neurotrophin signaling pathway,” “focal adhesion,” and “GnRH signaling pathway.” MAPK, SRC, PDGFRa, ErbB, and EGFR were significantly regulated to correct these pathways. Kinases investigated by the literature on carcinoma were considered to be potential novel molecular therapeutic target in PTC and application of corresponding kinase inhibitors could be possible therapeutic tool.Conclusion. SRC, MAPK, and EGFR were the most important differentially expressed kinases in PTC. Combined inhibitors may have high efficacy in PTC treatment by targeting these kinases.

scholarly journals Identifying hub genes associated with clinical characteristicsin IgA nephropathy by Weighted Gene Co-expression Network Analysis

2019 ◽  
Author(s):  
Chengyu Yang ◽  
Chenyu Li ◽  
Long Zhao ◽  
Bin Zhou ◽  
Xiaofei Man ◽  
...  
Keyword(s):  
Iga Nephropathy ◽  
Signaling Pathway ◽  
Clinical Characteristics ◽  
Enrichment Analysis ◽  
Akt Signaling ◽  
Differentially Expressed ◽  
Akt Signaling Pathway ◽  
Hub Genes ◽  
Renal Interstitium ◽  
Healthy Control

Abstract Background: Clinically, IgA nephropathy has a variety of symptoms including paroxysmal gross hematuria, nephritic and nephrotic syndrome. This study aimed at investigating hub geneand genes modular related to IgA nephropathy clinical characteristics by using weighted gene co-expression network analysis combining clinical, microarray and network database parameters. Methods: We collected 32 human samples from the European Renal cDNA Bank and used RMA method to preprocess the data and utilize the limma package to obtain differentially expressed gene in renal interstitium and glomeruli. We used the WGCNA package to construct the gene co-expression of differential expression genes and identify hub genes associated with clinical characteristics in renal interstitium and glomeruli, respectively. Gene ontology enrichment analysis and KEGG analysis for hub genes which associated with clinical characteristics were performed by DAVID. PPI information was acquired from STRING. Results: For glomeruli, 1470 genes differentially expressed between IgA nephropathy patients and healthy control, containing 10 hub genes associated with age, 8 hub genes associated with sex, 48 hub genes associated with Bp enrichd in ERK1 and ERK2 cascade and Rap1 signaling pathway, 223 hub genes associated with BMI enrich in organic acid catabolic process and fatty acid degradation pathway, 136 hub genes associated GFR enriched in immune response and PI3K-Akt signaling pathway, 82 hub genes associated with proteinuria enriched in extracellular matrix organization and PI3K-Akt signaling pathway. In tubulointerstitium, there were 480 genes differentially expressed between IgA nephropathy patients and healthy control. Among 480 DEGs, 6 hub genes associated with age, 15 hub genes associated with sex, 35 hub genes associated with Bp enrichd in positive regulation of apoptotic process, 87 hub genes associated with GFR enriched in negative regulation of macromolecule metabolic process and RNA transport, 33 hub genes associated with proteinuria enriched in regulation of apoptotic process and FoxO signaling pathway. PPI enrichment analysis shown that all hub genes sets are biologically connected cluster. Conclusions: We made a preliminary investigation on molecular mechanisms of relationship between IgA nephropathy and clinical characteristics and identified hub genes and pathways closely related with BMI, GFR and Proteinuria in IgA nephropathy by a series of bioinformatics analysis.

scholarly journals Construction of Circular RNA–MicroRNA–Messenger RNA Regulatory Network of Recurrent Implantation Failure to Explore Its Potential Pathogenesis

2021 ◽  
Vol 11 ◽  
Author(s):  
Jiahuan Luo ◽  
Li Zhu ◽  
Ning Zhou ◽  
Yuanyuan Zhang ◽  
Lirong Zhang ◽  
...  
Keyword(s):  
Messenger Rna ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Implantation Failure ◽  
Ppi Network ◽  
Recurrent Implantation Failure ◽  
Hub Genes ◽  
Hub Gene ◽  
Gene Regulatory

Background: Many studies on circular RNAs (circRNAs) have recently been published. However, the function of circRNAs in recurrent implantation failure (RIF) is unknown and remains to be explored. This study aims to determine the regulatory mechanisms of circRNAs in RIF.Methods: Microarray data of RIF circRNA (GSE147442), microRNA (miRNA; GSE71332), and messenger RNA (mRNA; GSE103465) were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed circRNA, miRNA, and mRNA. The circRNA–miRNA–mRNA network was constructed by Cytoscape 3.8.0 software, then the protein–protein interaction (PPI) network was constructed by STRING database, and the hub genes were identified by cytoHubba plug-in. The circRNA–miRNA–hub gene regulatory subnetwork was formed to understand the regulatory axis of hub genes in RIF. Finally, the Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the hub genes were performed by clusterProfiler package of Rstudio software, and Reactome Functional Interaction (FI) plug-in was used for reactome analysis to comprehensively analyze the mechanism of hub genes in RIF.Results: A total of eight upregulated differentially expressed circRNAs (DECs), five downregulated DECs, 56 downregulated differentially expressed miRNAs (DEmiRs), 104 upregulated DEmiRs, 429 upregulated differentially expressed genes (DEGs), and 1,067 downregulated DEGs were identified regarding RIF. The miRNA response elements of 13 DECs were then predicted. Seven overlapping miRNAs were obtained by intersecting the predicted miRNA and DEmiRs. Then, 56 overlapping mRNAs were obtained by intersecting the predicted target mRNAs of seven miRNAs with 1,496 DEGs. The circRNA–miRNA–mRNA network and PPI network were constructed through six circRNAs, seven miRNAs, and 56 mRNAs; and four hub genes (YWHAZ, JAK2, MYH9, and RAP2C) were identified. The circRNA–miRNA–hub gene regulatory subnetwork with nine regulatory axes was formed in RIF. Functional enrichment analysis and reactome analysis showed that these four hub genes were closely related to the biological functions and pathways of RIF.Conclusion: The results of this study provide further understanding of the potential pathogenesis from the perspective of circRNA-related competitive endogenous RNA network in RIF.

scholarly journals SIGIRR and TNFAIP3 Are Differentially Expressed in Both PBMC and TNF-α Secreting Cells of Patients With Major Depressive Disorder

2021 ◽  
Vol 12 ◽  
Author(s):  
Chin-Chuen Lin ◽  
Tiao-Lai Huang
Keyword(s):  
Immune Response ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Innate Immune ◽  
Differentially Expressed ◽  
Mrna Levels ◽  
Healthy Controls ◽  
Negative Regulators ◽  
Major Depressive ◽  
Tnf Α

Background: Major depressive disorder (MDD) is associated with the activation of the immune/inflammatory system. TNF-α is associated with MDD and poor treatment response. Toll-like receptors (TLR) are responsible in innate immune response, and is associated with MDD and antidepressant response. Some negative regulators of TLR pathway such as SOCS1, TOLLIP, SIGIRR, TNFAIP3, and MyD88s, are reported to be differentially expressed in the peripheral blood samples of patients of MDD.Methods: We recruited patients with MDD and healthy controls, collect their demographic data, and measured their mRNA levels of negative TLR regulators, using peripheral blood mononuclear cells (PBMC) and isolated TNF-α secreting cells. Clinical symptoms were evaluated using Halmiton Depression Rating Scale (Ham-D). Some patients were evaluated again after 4 weeks of antidepressant treatment.Results: Forty-seven patients with MDD and 52 healthy controls were recruited. Between the PBMC samples of 37 MDD patients and 42 controls, mRNA levels of SOCS1, SIGIRR, TNFAIP3, and MyD88s were significantly different. Between TNF-α secreting cells of 10 MDD patients and 10 controls, mRNA levels of SIGIRR and TNFAIP3 were significantly different. Change of Ham-D score only correlated significantly with TOLLIP mRNA level after treatment.Conclusion: SIGIRR and TNFAIP3, two negative regulators of TLR immune response pathways, were differentially expressed in both PBMC and TNF-α secreting cells of patients with MDD as compared to healthy controls. The negative regulations of innate immune response could contribute to the underlying mechanism of MDD.

scholarly journals Molecular mechanism of reward treatment ameliorating chronic stress-induced depressive-like behavior assessed by sequencing miRNA and mRNA in medial prefrontal cortex

2020 ◽  
Author(s):  
Tingting An ◽  
Zhenhua Song ◽  
Jin-Hui Wang
Keyword(s):  
Major Depressive Disorder ◽  
Prefrontal Cortex ◽  
Depressive Disorder ◽  
Molecular Mechanism ◽  
Chronic Stress ◽  
Medial Prefrontal Cortex ◽  
Differentially Expressed ◽  
Mild Stress ◽  
Major Depressive ◽  
Differentially Expressed Mirnas

Abstract Background Major depressive disorder (MDD) is a disease that seriously endangers human health and mental state. Chronic stress and lack of reward may reduce the function of the brain's reward circuits, leading to major depressive disorder. The effect of reward treatment on chronic stress-induced depression-like behaviors and its molecular mechanism in the brain remain unclear.Methods Mice were divided into the groups of control, chronic unpredictable mild stress (CUMS), and CUMS-companion. Mice of CUMS group was performed by CUMS for 4 weeks, and CUMS-companion group was treated by CUMS accompanied with companion. The tests of sucrose preference, Y-maze, and forced swimming were conducted to assess depression-like behaviors or resilience. High-throughput sequencing was used to analyze mRNA and miRNA profiles in the medial prefrontal cortex harvested from control, CUMS-MDD (mice with depression-like behaviors in CUMS group), Reward-MDD (mice with depression-like behaviors in CUMS-companion group), CUMS-resilience (resilient mice in CUMS group), Reward-resilience (resilient mice in CUMS-companion group) mice.Results The results provided evidence that accompanying with companion ameliorated CUMS-induced depression-like behaviors in mice. 45 differentially expressed genes (DEGs) are associated with depression-like behaviors, 8 DEGs are associated with resilience and 59 DEGs are associated with nature reward (companion) were identified. Furthermore, 196 differentially expressed miRNAs were found to be associated with companion. Based on the differentially expressed miRNAs and DEGs data, miRNA-mRNA network was established to be associated with companion.Conclusion Taken together, our data here provided a method to ameliorate depression-like behaviors, and numerous potential drug targets for the prevention or treatment of depression.

scholarly journals Comprehensive Analysis of Differentially Expressed Profiles of mRNA, lncRNA, and circRNA in the Uterus of Seasonal Reproduction Sheep

Genes ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 301 ◽  
Author(s):  
Yongfu La ◽  
Xiaoyun He ◽  
Liping Zhang ◽  
Ran Di ◽  
Xiangyu Wang ◽  
...  
Keyword(s):  
Thyroid Hormone ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Seasonal Reproduction ◽  
Hormone Synthesis ◽  
Long Photoperiod

Photoperiod is one of the important factors leading to seasonal reproduction of sheep. However, the molecular mechanisms underlying the photoperiod regulation of seasonal reproduction remain poorly understood. In this study, we compared the expression profiles of mRNAs, lncRNAs, and circRNAs in uterine tissues from Sunite sheep during three different photoperiods, namely, the short photoperiod (SP), short transfer to long photoperiod (SLP), and long photoperiod (LP). The results showed that 298, 403, and 378 differentially expressed (DE) mRNAs, 171, 491, and 499 DE lncRNAs, and 124, 270, and 400 DE circRNAs were identified between SP and LP, between SP and SLP, and between LP and SLP, respectively. Furthermore, functional enrichment analysis showed that the differentially expressed RNAs were mainly involved in the GnRH signaling pathway, thyroid hormone synthesis, and thyroid hormone signaling pathway. In addition, co-expression networks of lncRNA–mRNA were constructed based on the correlation analysis between the differentially expressed RNAs. Our study provides new insights into the expression changes of RNAs in different photoperiods, which might contribute to understanding the molecular mechanisms of seasonal reproduction in sheep.

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