scholarly journals Application of Bioinformatics Methods to Identify Key Genes and Functions in Chronic Pelvic Pain

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Wenchao Sun ◽  
Qiji Ju

Neuropathologic pain (NPP) occurs in most patients with chronic pelvic pain (CPP), and the unique physiological characteristics of visceral sensory neurons make the current analgesic effect of CPP patients not optimistic. Therefore, this study explored the possible biological characteristics of key genes in CPP through the bioinformatics method. CPP-related dataset GSE131619 was downloaded from Gene Expression Omnibus to investigate the differentially expressed genes (DEGs) between lumbar dorsal root ganglia (DRG) and sacral DRG, and the functional enrichment analysis was performed. A protein-protein interaction (PPI) network was constructed to search subnet modules of specific biological processes, and then, the genes in the subnet were enriched by single gene set analysis. A CPP mouse model was established, and the expression of key genes were identified by qPCR. The results showed that 127 upregulated DEGs and 103 downregulated DEGs are identified. Functional enrichment analysis showed that most of the genes involved in signal transduction were involved in the pathway of receptor interaction. A subnet module related to neural signal regulation was identified in PPI, including CHRNB4, CHRNA3, and CHRNB2. All three genes were associated with neurological or inflammatory activity and are downregulated in the sacral spinal cord of CPP mice. This study provided three key candidate genes for CPP: CHRNB4, CHRNA3, and CHRNB2, which may be involved in the occurrence and development of CPP, and provided a powerful molecular target for the clinical diagnosis and treatment of CPP.

2020 ◽  
Vol 48 (5) ◽  
pp. 030006052092167
Author(s):  
Yingyuan Li ◽  
Wulin Tan ◽  
Fang Ye ◽  
Shihong Wen ◽  
Rong Hu ◽  
...  

Objective Stroke is a severe complication of atrial fibrillation (AF). We aimed to discover key genes and microRNAs related to stroke risk in patients with AF using bioinformatics analysis. Methods GSE66724 microarray data, including peripheral blood samples from eight patients with AF and stroke and eight patients with AF without stroke, were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between AF patients with and without stroke were identified using the GEO2R online tool. Functional enrichment analysis was performed using the DAVID database. A protein–protein interaction (PPI) network was obtained using the STRING database. MicroRNAs (miRs) targeting these DEGs were obtained from the miRNet database. A miR–DEG network was constructed using Cytoscape software. Results We identified 165 DEGs (141 upregulated and 24 downregulated). Enrichment analysis showed enrichment of certain inflammatory processes. The miR–DEG network revealed key genes, including MEF2A, CAND1, PELI1, and PDCD4, and microRNAs, including miR-1, miR-1-3p, miR-21, miR-21-5p, miR-192, miR-192-5p, miR-155, and miR-155-5p. Conclusion Dysregulation of certain genes and microRNAs involved in inflammation may be associated with a higher risk of stroke in patients with AF. Evaluating these biomarkers could improve prediction, prevention, and treatment of stroke in patients with AF.


PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11321
Author(s):  
Di Zhang ◽  
Pengguang Yan ◽  
Taotao Han ◽  
Xiaoyun Cheng ◽  
Jingnan Li

Background Ulcerative colitis-associated colorectal cancer (UC-CRC) is a life-threatening complication of ulcerative colitis (UC). The mechanisms underlying UC-CRC remain to be elucidated. The purpose of this study was to explore the key genes and biological processes contributing to colitis-associated dysplasia (CAD) or carcinogenesis in UC via database mining, thus offering opportunities for early prediction and intervention of UC-CRC. Methods Microarray datasets (GSE47908 and GSE87466) were downloaded from Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) between groups of GSE47908 were identified using the “limma” R package. Weighted gene co-expression network analysis (WGCNA) based on DEGs between the CAD and control groups was conducted subsequently. Functional enrichment analysis was performed, and hub genes of selected modules were identified using the “clusterProfiler” R package. Single-gene gene set enrichment analysis (GSEA) was conducted to predict significant biological processes and pathways associated with the specified gene. Results Six functional modules were identified based on 4929 DEGs. Green and blue modules were selected because of their consistent correlation with UC and CAD, and the highest correlation coefficient with the progress of UC-associated carcinogenesis. Functional enrichment analysis revealed that genes of these two modules were significantly enriched in biological processes, including mitochondrial dysfunction, cell-cell junction, and immune responses. However, GSEA based on differential expression analysis between sporadic colorectal cancer (CRC) and normal controls from The Cancer Genome Atlas (TCGA) indicated that mitochondrial dysfunction may not be the major carcinogenic mechanism underlying sporadic CRC. Thirteen hub genes (SLC25A3, ACO2, AIFM1, ATP5A1, DLD, TFE3, UQCRC1, ADIPOR2, SLC35D1, TOR1AIP1, PRR5L, ATOX1, and DTX3) were identified. Their expression trends were validated in UC patients of GSE87466, and their potential carcinogenic effects in UC were supported by their known functions and other relevant studies reported in the literature. Single-gene GSEA indicated that biological processes and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to angiogenesis and immune response were positively correlated with the upregulation of TFE3, whereas those related to mitochondrial function and energy metabolism were negatively correlated with the upregulation of TFE3. Conclusions Using WGCNA, this study found two gene modules that were significantly correlated with CAD, of which 13 hub genes were identified as the potential key genes. The critical biological processes in which the genes of these two modules were significantly enriched include mitochondrial dysfunction, cell-cell junction, and immune responses. TFE3, a transcription factor related to mitochondrial function and cancers, may play a central role in UC-associated carcinogenesis.


2020 ◽  
Vol 19 ◽  
pp. 153303382097748
Author(s):  
Shao-wei Zhang ◽  
Nan Zhang ◽  
Na Wang

Background: Esophageal cancer (EC) is a primary malignant tumor originating from the esophageal of the epithelium. Surgical resection is a potential treatment for EC, but this is only appropriate for patients who have locally resectable lesions suitable for surgery. However, most patients with EC are at a late stage when diagnosed. Therefore, there is an urgent need to further explore the pathogenesis of EC to enable early diagnosis and treatment. Methods: Our study downloaded 2 expression spectrum datasets (GSE92396 and GSE100942) in the Gene Expression Omnibus (GEO) database. GEO2 R was used to identify the Differentially expressed genes (DEGs) between the samples of EC and control. Using the DAVID tool to make the Functional enrichment analysis. Constructing A protein–protein interaction (PPI) network. Identifying the Hub genes. The impact of hub gene expression on overall survival and their expression based on immunohistochemistry were analyzed. Associated microRNAs were also predicted. Results: There were 36 common DEGs identified. The analysis of GO and KEGG results shown that the variations were predominantly concentrated in the extracellular matrix (ECM), ECM organization, DNA binding, platelet activation, and ECM-receptor interactions. COL3A1 and POSTN had high expression in EC tissues which was compared with their expression in healthy tissues. Analysis of pathologic stages showed that when COL3A1 and POSTN were highly expressed, the stage of the pathologic of EC patients was relatively high (P < 0.005). Conclusions: COL3A1 and POSTN may play an important role in the advancement and occurrence of EC. These genes could provide some novel ideas and basis for the diagnosis and targeted treatment of EC.


2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Shuqiang Li ◽  
Huijie Shao ◽  
Liansheng Chang

Epilepsy is most common in patients with tuberous sclerosis complex (TSC). However, in addition to the challenging treatment, the pathogenesis of epilepsy is still controversial. To determine the transcriptome characteristics of perituberal tissue (PT) and clarify its role in the pathogenesis of epilepsy, GSE16969 was downloaded from the GEO database for further study by comprehensive bioinformatics analysis. Identification of differentially expressed genes (DEGs), functional enrichment analysis, construction of protein-protein interaction (PPI) network, and selection of Hub genes were performed using R language, Metascape, STRING, and Cytoscape, respectively. Comparing with cortical tuber (CT), 220 DEGs, including 95 upregulated and 125 downregulated genes, were identified in PT and mainly enriched in collagen-containing extracellular matrix and positive regulation of receptor-mediated endocytosis, as well as the pathways of ECM-receptor interaction and neuroactive ligand-receptor interaction. As for normal cortex (NC), 1549 DEGs, including 30 upregulated and 1519 downregulated genes, were identified and mainly enriched in presynapse, dendrite and axon, and also the pathways of dopaminergic synapse and oxytocin signaling pathway. In the PPI network, 4 hub modules were found between PT and CT, and top 5 hub modules were selected between PT and NC. C3, APLNR, ANXA2, CD44, CLU, CP, MCHR2, HTR1E, CTSG, APP, and GNG2 were identified as Hub genes, of which, C3, CD44, ANXA2, HTR1E, and APP were identified as Hub-BottleNeck genes. In conclusion, PT has the unique characteristics different from CT and NC in transcriptome and makes us further understand its importance in the TSC-associated epilepsy.


2021 ◽  
Vol 49 (6) ◽  
pp. 030006052110222
Author(s):  
Xin-mei Zhao ◽  
Yuan-Bin Li ◽  
Peng Sun ◽  
Ya-di Pu ◽  
Meng-jie shan ◽  
...  

Objective To identify key genes involved in occurrence and development of retinoblastoma. Methods The microarray dataset, GSE5222, was downloaded from the gene expression omnibus (GEO) database. Differentially expressed genes (DEGs) between unilateral and bilateral retinoblastoma were identified and functional enrichment analysis performed. The protein–protein interaction (PPI) network was constructed and analysed by STRING and Cytoscape. Results DEGs were mainly associated with activation of cysteine-type endopeptidase activity involved in apoptotic process and small molecule catabolic process. Seven genes (WAS, GNB3, PTGER1, TACR1, GPR143, NPFF and CDKN2A) were identified as HUB genes. Conclusion Our research provides more understanding of the mechanisms of the disease at a molecular level and may help in the identification of novel biomarkers for retinoblastoma.


2021 ◽  
Vol 33 (2) ◽  
pp. 147
Author(s):  
M. Rabaglino ◽  
J. B.-M. Secher ◽  
P. Hyttel ◽  
H. Kadarmideen

In cattle, ovarian superovulation followed by invivo embryo collection and transfer (MOET), and the invitro production (IVP) of embryos are used all over the world to improve animal genetics. Application of MOET has resulted in the production of billions of healthy animals during the past 40 years, and IVP has evolved and given rise to significant numbers of calves during the past 10 years. Nevertheless, the use of MOET and IVP can affect the embryo epigenome, and therefore its transcriptome, before and after elongation, as shown by different studies. The integration of publicly available epigenome-transcriptome datasets generated by these studies could lead to a robust characterisation of the impacts of the application of MOET and IVP. The goal of this study was to integrate all publicly available data about MOET and IVP embryos to determine temporally differentially methylated regions (DMRs) and differentially expressed genes (DEGs) from blastocyst to elongation between IVP and MOET embryos. Datasets were downloaded from the Gene Expression Omnibus (GEO) database. Accession numbers were (1) for epigenomics: GSE69173, GSE97517, and GSE101895, plus one provided dataset from O’Doherty et al. (2018 BMC Genomics, 19, 438; https://doi.org/10.1186/s12864-018-4818-3), all hybridized to the EDMA platform GPL18384; (2) for transcriptomics: GSE12327, GSE21030, GSE24596, GSE24936, GSE27817, and GSE40101, all hybridized to the Affymetrix platform GPL2112. Both types of data were analysed with the limma package for R software, and functional enrichment analysis was done with the DAVID database. For DMRs, comparisons between IVP and MOET were made from spherical blastocysts (n=16 per group) on Day 7, to embryos on Day 15, specifically in the trophectoderm (TE) or embryonic disc (ED) regions (n=4 per region and per group). For DEGs, comparisons between IVP and MOET were made from spherical blastocysts (n=9 per group) to elongated blastocysts on Day 13 and embryos undergoing gastrulation on Day 16 (n=6 per group). Considering a P-value &lt;0.05 and fold-change &gt;2, there were 16 672 (TE) and 26 264 (ED) DMRs and 2236 DEGs that temporally differed between IVP and MOET. Most of the identified DMRs were found in intronic regions (around 36%) rather than exonic regions (8%). However, DMRs that were more methylated at IVP compared with MOET contained exons encoding for genes that enriched the Wnt signalling Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway in the ED, and focal adhesion and ECM-receptor interaction KEGG pathways (P&lt;0.05) in the TE. Accordingly, DEGs with lower expression in elongated embryos (Day 13 and Day 16) at IVP as opposed to MOET were mainly associated with these three pathways. In conclusion, this multi-omics analysis demonstrates that even when embryos are produced under different conditions and experiments, the main changes imposed by IVP affected genes involved in embryonic development and adhesion to the endometrium, which could explain the lower survival rates at IVP compared with MOET.


2021 ◽  
Author(s):  
Dou-Dou Ding ◽  
Quan Zhou ◽  
Ze He ◽  
Hong-Xia He ◽  
Man-Zhen Zuo

Abstract Introduction:Epidemiological studies have found that the occurrence of endometrial cancer(EC) is closely related to metabolic diseases, and insulin resistance (IR) plays an important role in the pathogenesis of endometrium, but the specific pathogenesis is still unclear. The purpose of this study is to reveal the relationship between insulin resistance and endothelial cells by gene screening technology. Material and methods:We analyzed one endometrial carcinoma database (GSE106191) and one insulin-resistant database (GSE63992), with Gene Expression Omnibus (GEO) database and Venny online analysis tool, then, we found an add-up to 148 different genes. Functional enrichment analysis of these genes using DAVID showed that they were participated in transcription factor activity,signaling pathways and response to factors, etc. Then used cytoHubba in Cytoscape,we got 25 hub genes.Results: The results showed that the survival time of OGT, IGSF3, TRO, NEURL2 and PIK3C2B was significantly and closely related to EC, and the percentage of gene changes of five central genes ranged from 3% to 10% of a single gene, was also related to the infiltration of seven kinds of immune cells in endometrial carcinoma.Conclusion:The five key genes (OGT,IGSF3, PIK3C2B,TRO and NEURL2) are involved in immune infiltration in the progression of endometrial carcinoma, and there is also a certain mutation probability in gene mutation. This may be the pathogenesis of insulin resistance and endometrial cancer.


2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Shiying Wang ◽  
Huanmei Wang ◽  
Wei Liu ◽  
Biaofang Wei

Sex differences have been suggested to play critical roles in the pathophysiology of osteoarthritis (OA), resulting in sex-specific prevalence and incidence. However, their roles in the development of OA remain largely unknown. The aim of this study was to screen out key genes and pathways mediating biological differences between OA females after menopause and OA males. First, the gene expression data of GSE36700 and GSE55457 were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between sexes were identified using R software, respectively. The overlapping DEGs were obtained. Then, protein-protein interactive (PPI) network was constructed to further analyze interactions between the overlapping DEGs. Finally, enrichment analyses were separately performed using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes tools. In our results, a total of 278 overlapping DEGs were identified between OA females after menopause and OA males, including 219 upregulated and 59 downregulated genes. In the PPI network, seven hub genes were identified, including EGF, ERBB2, CDC42, PIK3R2, LCK, CBL, and STAT1. Functional enrichment analysis revealed that these genes were mainly enriched in PI3K-Akt signaling pathway, osteoclast differentiation, and focal adhesion. In conclusion, the results in the current study suggest that pathways of PI3K-Akt, osteoclast differentiation, and focal adhesion may play important roles in the development of OA females after menopause. EGFR, ERBB2, CDC42, and STAT1 may be key genes related to OA progression in postmenopausal women and may be promising therapeutic targets for OA.


2021 ◽  
Vol 4 (2) ◽  
pp. 01-12
Author(s):  
Aihua Chen

Background: Preterm birth(PTB) is a primary cause of neonatal morbidity and mortality, the pathogenic mechanisms of PTB still remain largely unexplored. In the present study, we aimed to identify potential key genes and pathway associated with PTB by bioinformatics analysis. Methods: The GSE46510 dataset was obtained from GEO database. Differentially expressed genes (DEGs) were identified using the limma package in R software, the functional enrichment analysis was performed, and the protein-protein interaction (PPI) network was constructed by Cytoscape software. The network topology was analyzed using MCODE. Results: A total of 335 DEGs were identified from the dataset. The majority of up-regulated DEGs were significantly enriched in inflammatory response, while down-regulated DEGs were mainly enriched in mitotic nuclear division. The top 5 hub up regulated genes were ITGAM, IL1B, ITGAX, NFKB1, and SOCS3. Pathway analysis indicated enrichment in Cytokine-cytokine receptor interaction, signaling by Interleukins. The top 5 hub down regulated genes were CXCR4, ANAPC10, ANAPC4, UBE2V2, UBA3, Pathway analysis indicated enrichment in Ubiquitin mediated proteolysis, Phosphorylation of the APC/C. Conclusion: Our study indicated genes and pathways in PTB by bioinformatics analysis, which may provide novel insights for unraveling pathogenesis of PTB.


PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0254326
Author(s):  
Yike Zhu ◽  
Dan Huang ◽  
Zhongyan Zhao ◽  
Chuansen Lu

Background Epilepsy is one of the most common brain disorders worldwide. It is usually hard to be identified properly, and a third of patients are drug-resistant. Genes related to the progression and prognosis of epilepsy are particularly needed to be identified. Methods In our study, we downloaded the Gene Expression Omnibus (GEO) microarray expression profiling dataset GSE143272. Differentially expressed genes (DEGs) with a fold change (FC) >1.2 and a P-value <0.05 were identified by GEO2R and grouped in male, female and overlapping DEGs. Functional enrichment analysis and Protein-Protein Interaction (PPI) network analysis were performed. Results In total, 183 DEGs overlapped (77 ups and 106 downs), 302 DEGs (185 ups and 117 downs) in the male dataset, and 750 DEGs (464 ups and 286 downs) in the female dataset were obtained from the GSE143272 dataset. These DEGs were markedly enriched under various Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) terms. 16 following hub genes were identified based on PPI network analysis: ADCY7, C3AR1, DEGS1, CXCL1 in male-specific DEGs, TOLLIP, ORM1, ELANE, QPCT in female-specific DEGs and FCAR, CD3G, CLEC12A, MOSPD2, CD3D, ALDH3B1, GPR97, PLAUR in overlapping DEGs. Conclusion This discovery-driven study may be useful to provide a novel insight into the diagnosis and treatment of epilepsy. However, more experiments are needed in the future to study the functional roles of these genes in epilepsy.


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