scholarly journals Deciphering The Molecular Pathogenesis Behind Neurological Manifestations of SARS-CoV-2 And Drug Repurposing, A Systems Biology Approach

2021 ◽  
Author(s):  
maryam mozafar ◽  
Seyed Amir Mirmotalebisohi ◽  
Marzieh Sameni ◽  
Zeinab Dehghan ◽  
Yalda Khazaei-Poul ◽  
...  
Keyword(s):  
Systems Biology ◽  
Regulatory Networks ◽  
Target Genes ◽  
Viral Infections ◽  
Drug Repurposing ◽  
Enrichment Analysis ◽  
Neurological Complications ◽  
Functional Enrichment ◽  
Neurological Manifestations ◽  
Ppi Networks

Abstract Introduction: As the COVID-19 pandemic spreads worldwide, reports about the neurological complications of SARS-CoV-2 are excessively increasing. However, there is still insufficient high-throughput data on neuronal cells infected with SARS-CoV-2 to help predict its neural pathogenesis. HCoV-OC43 is another member of the beta coronavirus family that has confirmed neuro-invasive effects and has available neural omics data. This study predicts the critical genes, biological processes, and pathways mediating in SARS-CoV-2 neurological manifestations using a systems biology approach.Method: We retrieved raw data related to SARS-CoV-2 and HCoV-OC43 infections from gene expression omnibus datasets (GSE147507 and GSE13879 respectively). We constructed gene regulatory networks for both infections, detected significant regulatory motifs by FANMOD software, and created their subnetworks. We also constructed PPI networks and identified the MCODE clusters. In the intersection of merged subnetworks of two viruses, the most critical genes were verified in GRN & PPI networks. We drug-repurposed for the selected target genes and performed the functional enrichment analysis using DAVID and String databases.Results: Some of the top KEGG pathway results included NF-kappa B, Toll-like receptor, NOD-like receptor, MAPK, and Neurotrophin signaling pathways. The most essential identified genes included IL6, TNF, HOXA5, POU2F2, ITGB3, STAT1, YY1, E2F6, ESR1, FOXO3, FOXO1, MEF2A, ATF3, ATF4, DDIT3, TCF4, BCL2L2, and BMP4. These genes were also involved in mechanisms of other viral infections of the nervous system. This study repurposes nine medicines with effects on COVID-19 neurological complications. Some of the repurposed drugs were previously registered in clinical trials for COVID-19 treatment.Conclusion: We recommended some identified crucial genes and medications to investigate further their potential role in treating COVID-19 neurological complications.

scholarly journals Deciphering the molecular pathogenesis behind neurological manifestations of SARS-CoV-2 and drug repurposing, a systems biology approach

2021 ◽  
Author(s):  
Maryam Mozafar ◽  
Seyed Amir Mirmotalebisohi ◽  
Marzieh Sameni ◽  
Zeinab Dehghan ◽  
Yalda Khazaei-Poul ◽  
...  
Keyword(s):  
Systems Biology ◽  
Regulatory Networks ◽  
Target Genes ◽  
Viral Infections ◽  
Drug Repurposing ◽  
Enrichment Analysis ◽  
Neurological Complications ◽  
Functional Enrichment ◽  
Neurological Manifestations ◽  
Ppi Networks

Abstract Introduction: As the COVID-19 pandemic spreads worldwide, reports about the neurological complications of SARS-CoV-2 are excessively increasing. However, there is still insufficient high-throughput data on neuronal cells infected with SARS-CoV-2 to help predict its neural pathogenesis. HCoV-OC43 is another member of the beta coronavirus family that has confirmed neuro-invasive effects and has available neural omics data. This study predicts the critical genes, biological processes, and pathways mediating in SARS-CoV-2 neurological manifestations using a systems biology approach.Method: We retrieved raw data related to SARS-CoV-2 and HCoV-OC43 infections from gene expression omnibus datasets (GSE147507 and GSE13879 respectively). We constructed gene regulatory networks for both infections, detected significant regulatory motifs by FANMOD software, and created their subnetworks. We also constructed PPI networks and identified the MCODE clusters. In the intersection of merged subnetworks of two viruses, the most critical genes were verified in GRN & PPI networks. We drug-repurposed for the selected target genes and performed the functional enrichment analysis using DAVID and String databases.Results: Some of the top KEGG pathway results included NF-kappa B, Toll-like receptor, NOD-like receptor, MAPK, and Neurotrophin signaling pathways. The most essential identified genes included IL6, TNF, HOXA5, POU2F2, ITGB3, STAT1, YY1, E2F6, ESR1, FOXO3, FOXO1, MEF2A, ATF3, ATF4, DDIT3, TCF4, BCL2L2, and BMP4. These genes were also involved in mechanisms of other viral infections of the nervous system. This study repurposes nine medicines with effects on COVID-19 neurological complications. Some of the repurposed drugs were previously registered in clinical trials for COVID-19 treatment.Conclusion: We recommended some identified crucial genes and medications to investigate further their potential role in treating COVID-19 neurological complications.

scholarly journals Identification of Key Genes and miRNA-mRNA Regulatory Pathways in Bronchopulmonary Dysplasia in Preterm Infants by Bioinformatics Methods

2020 ◽  
Author(s):  
Tong Sun ◽  
Haiyang Yu ◽  
Jianhua Fu
Keyword(s):  
Gene Expression ◽  
Preterm Infants ◽  
Bronchopulmonary Dysplasia ◽  
Regulatory Networks ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Regulatory Pathways ◽  
Ppi Networks ◽  
Key Genes

Abstract Background: Bronchopulmonary dysplasia (BPD) remains a severe respiratory complication of preterm infants in neonatal intensive care units (NICUs). However, its pathogenesis has been unclear. Bioinformatics analysis, which can help us explore genetic alternations and recognize latent diagnostic biomarkers, has recently promoted the comprehension of the molecular mechanisms underlying disease occurrence and development. Methods: In this study, we identified key genes and miRNA-mRNA regulatory networks in BPD in preterm infants to elucidate the pathogenesis of BPD. We downloaded and analyzed miRNA and gene expression microarray datasets from the Gene Expression Omnibus database (GEO). Differentially expressed miRNA (DEMs) and differentially expressed genes (DEGs) were obtained through NetworkAnalyst. We performed pathway enrichment analysis using the Database for Annotation, Visualization and Integrated Discovery program (DAVID), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG). Then we used the STRING to establish protein–protein interactions and the Cytoscape tool to establish miRNA–mRNA regulatory networks. Results: We identified 19 significant DEMs and 140 and 33 significantly upregulated and downregulated DEGs, respectively. Functional enrichment analysis indicated that significant DEGs were associated with the antigen processing and presentation, and B-cell receptor signaling pathways in BPD. Key DEGs, such as CD19, CD79B, MS4A1, and FCGR2B were selected as hub genes in PPI networks. Conclusions: In this study, we screened out 19 DEMs that might play important roles in the regulatory networks of BPD. Higher expression of miRNAs such as miR-15b-5p, hsa-miR-32-5p, miR-3613-3p, and miR-33a-5p and lower expression of miRNAs such as miR-3960, miR-425-5p, and miR-3202 might be correlated with the process of BPD.

scholarly journals A Novel Three-miRNA Signature Identified Using Bioinformatics Predicts Survival in Esophageal Carcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-11 ◽  
Author(s):  
KunZhe Wu ◽  
ChunDong Zhang ◽  
Cheng Zhang ◽  
DongQiu Dai
Keyword(s):  
Growth Factor ◽  
Esophageal Carcinoma ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Rna Seq ◽  
Mirna Signature ◽  
Cox Regression Analysis ◽  
Ppi Networks

Objective. We identified differentially expressed microRNAs (DEMs) between esophageal carcinoma (ESCA) tissues and normal esophageal tissues. We then constructed a novel three-miRNA signature to predict the prognosis of ESCA patients using bioinformatics analysis. Materials and Methods. We combined two microarray profiling datasets from the Gene Expression Omnibus (GEO) database and RNA-seq datasets from the Cancer Genome Atlas (TCGA) database to analyze DEMs in ESCA. The clinical data from 168 ESCA patients were selected from the TCGA database to assess the prognostic role of the DEMs. The TargetScan, miRDB, miRWalk, and DIANA websites were used to predict the miRNA target genes. Functional enrichment analysis was conducted using the Database for Annotation, Visualization, and Integrated Discovery (David), and protein-protein interaction (PPI) networks were obtained using the Search Tool for the Retrieval of Interacting Genes database (STRING). Results. With cut-off criteria of P<0.05 and |log2FC| > 1.0, 33 overlapping DEMs, including 27 upregulated and 6 downregulated miRNAs, were identified from GEO microarray datasets and TCGA RNA-seq count datasets. The Kaplan–Meier survival analysis indicated that a three-miRNA signature (miR-1301-3p, miR-431-5p, and miR-769-5p) was significantly associated with the overall survival of ESCA patients. The results of univariate and multivariate Cox regression analysis showed that the three-miRNA signature was a potential prognostic factor in ESCA. Furthermore, the gene functional enrichment analysis revealed that the target genes of the three miRNAs participate in various cancer-related pathways, including viral carcinogenesis, forkhead box O (FoxO), vascular endothelial growth factor (VEGF), human epidermal growth factor receptor 2 (ErbB2), and mammalian target of rapamycin (mTOR) signaling pathways. In the PPI network, three target genes (MAPK1, RB1, and CLTC) with a high degree of connectivity were selected as hub genes. Conclusions. Our results revealed that a three-miRNA signature (miR-1301-3p, miR-431-5p, and miR-769-5p) is a potential novel prognostic biomarker for ESCA.

scholarly journals Study on miRNAs in Pan-Cancer of the Digestive Tract Based on the Illumina HiSeq System Data Sequencing

2019 ◽  
Vol 2019 ◽  
pp. 1-24 ◽  
Author(s):  
Chun-hui Lai ◽  
Xu-zhi Liang ◽  
Xiu-yun Liang ◽  
Sheng-jun Ma ◽  
Jun-guo Li ◽  
...  
Keyword(s):  
Digestive Tract ◽  
Prognostic Value ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Diagnostic Value ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Overlapping Genes ◽  
Ppi Networks ◽  
Digestive Cancers

Objective. miRNA has gained attention as a therapeutic target in various malignancies. The proposal of this study was to investigate the biological functions of key miRNAs and target genes in cancers of the digestive tract which include esophageal carcinoma (ESCA), gastric adenocarcinoma (GAC), colon adenocarcinoma (COAD), and rectal adenocarcinoma (READ). Materials and Methods. After screening differentially expressed miRNAs (DEMIs) and differentially expressed mRNAs (DEMs) in four digestive cancers from The Cancer Genome Atlas (TCGA) database, the diagnostic value of above DEMIs was evaluated by receiver-operating characteristic (ROC) curve analysis. Then, corresponding DEMIs’ target genes were predicted by miRWalk 2.0. Intersection of predicted target genes and DEMs was taken as the target genes of DEMIs, and miRNA-mRNA regulatory networks between DEMIs and target genes were constructed. Meanwhile, the univariate Cox risk regression model was used to screen miRNAs with distinct prognostic value, and Kaplan–Meier analysis was used to determine their significance of prognosis. Furthermore, we performed bioinformatics methods including protein-protein interaction (PPI) networks, gene ontology (GO) annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and gene group RIDA analysis by Gene-Cloud of Biotechnology Information (GCBI) to explore the function and molecular mechanisms of DEMIs and predicted target genes in tumor development. Results. Eventually, 3 DEMIs (miR-7-3, miR-328, and miR-323a) with significant prognostic value were obtained. In addition, 3 DEMIs (miR-490-3p, miR-133a-3p, and miR-552-3p) and 281 target genes were identified, and the 3 DEMIs showed high diagnostic value in READ and moderate diagnostic value in ESCA, GAC, and COAD. Also, the miRNA-mRNA regulatory network with 3 DEMIs and 281 overlapping genes was successfully established. Functional enrichment analysis showed that 281 overlapping genes were mainly related to regulation of cell proliferation, cell migration, and PI3K-Akt signaling pathway. Conclusion. The diagnostic value and prognostic value of significant DEMIs in cancers of the digestive tract were identified, which may provide a novel direction for treatment and prognosis improvement of cancers of the digestive tract.

scholarly journals Regulatory role of non-coding RNA in ginseng rusty root symptom tissue

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xingbo Bian ◽  
Pengcheng Yu ◽  
Ling Dong ◽  
Yan Zhao ◽  
He Yang ◽  
...  
Keyword(s):  
Fatty Acid ◽  
Regulatory Networks ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Circular Rnas ◽  
Primary Metabolism ◽  
Non Coding Rna

AbstractGinseng rusty root symptom (GRS) is one of the primary diseases of ginseng. It leads to a severe decline in the quality of ginseng and significantly affects the ginseng industry. The regulatory mechanism of non-coding RNA (ncRNA) remains unclear in the course of disease. This study explored the long ncRNAs (lncRNAs), circular RNAs (circRNAs), and microRNAs (miRNAs) in GRS tissues and healthy ginseng (HG) tissues and performed functional enrichment analysis of the screened differentially expressed ncRNAs. Considering the predictive and regulatory effects of ncRNAs on mRNAs, we integrated ncRNA and mRNA data to analyze and construct relevant regulatory networks. A total of 17,645 lncRNAs, 245 circRNAs, and 299 miRNAs were obtained from HG and GRS samples, and the obtained ncRNAs were characterized, including the classification of lncRNAs, length and distribution of circRNA, and the length and family affiliations of miRNAs. In the analysis of differentially expressed ncRNA target genes, we found that lncRNAs may be involved in the homeostatic process of ginseng tissues and that lncRNAs, circRNAs, and miRNAs are involved in fatty acid-related regulation, suggesting that alterations in fatty acid-related pathways may play a key role in GRS. Besides, differentially expressed ncRNAs play an essential role in regulating transcriptional translation processes, primary metabolism such as starch and sucrose, and secondary metabolism such as alkaloids in ginseng tissues. Finally, we integrated the correlations between ncRNAs and mRNAs, constructed corresponding interaction networks, and identified ncRNAs that may play critical roles in GRS. These results provide a basis for revealing GRS's molecular mechanism and enrich our understanding of ncRNAs in ginseng.

scholarly journals Identification of the Key MicroRNAs and the miRNA-mRNA Regulatory Pathways in Prostate Cancer by Bioinformatics Methods

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Dongyang Li ◽  
Xuanyu Hao ◽  
Yongsheng Song
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Signaling Pathway ◽  
Regulatory Networks ◽  
Experimental Studies ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Tgf Beta ◽  
Regulatory Pathways ◽  
Ppi Networks

Objective. To identify key microRNAs (miRNAs) and their regulatory networks in prostate cancer.Methods. Four miRNA and three gene expression microarray datasets were downloaded for analysis from Gene Expression Omnibus database. The differentially expressed miRNA and genes were accessed by a GEO2R. Functional and pathway enrichment analyses were performed using the DAVID program. Protein-protein interaction (PPI) and miRNA-mRNA regulatory networks were constructed using the STRING and Cytoscape tool. Moreover, the results and clinical significance were validated in TCGA data.Results. We identified 26 significant DEMs, 633 upregulated DEGs, and 261 downregulated DEGs. Functional enrichment analysis indicated that significant DEGs were related to TGF-beta signaling pathway and TNF signaling pathway in PCa. Key DEGs such as HSPA8, PPP2R1A, CTNNB1, ADCY5, ANXA1, and COL9A2 were found as hub genes in PPI networks. TCGA data supported our results and the miRNAs were correlated with clinical stages and overall survival.Conclusions. We identified 26 miRNAs that may take part in key pathways like TGF-beta and TNF pathways in prostate cancer regulatory networks. MicroRNAs like miR-23b, miR-95, miR-143, and miR-183 can be utilized in assisting the diagnosis and prognosis of prostate cancer as biomarkers. Further experimental studies are required to validate our results.

scholarly journals Integrated network analysis identifying potential novel drug candidates and targets for Parkinson's disease

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Pusheng Quan ◽  
Kai Wang ◽  
Shi Yan ◽  
Shirong Wen ◽  
Chengqun Wei ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Drug Target ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Control Group ◽  
Drug Candidates ◽  
Novel Drug

AbstractThis study aimed to identify potential novel drug candidates and targets for Parkinson’s disease. First, 970 genes that have been reported to be related to PD were collected from five databases, and functional enrichment analysis of these genes was conducted to investigate their potential mechanisms. Then, we collected drugs and related targets from DrugBank, narrowed the list by proximity scores and Inverted Gene Set Enrichment analysis of drug targets, and identified potential drug candidates for PD treatment. Finally, we compared the expression distribution of the candidate drug-target genes between the PD group and the control group in the public dataset with the largest sample size (GSE99039) in Gene Expression Omnibus. Ten drugs with an FDR < 0.1 and their corresponding targets were identified. Some target genes of the ten drugs significantly overlapped with PD-related genes or already known therapeutic targets for PD. Nine differentially expressed drug-target genes with p < 0.05 were screened. This work will facilitate further research into the possible efficacy of new drugs for PD and will provide valuable clues for drug design.

scholarly journals Identification of Tumorigenic and Prognostic Biomarkers in Colorectal Cancer Based on microRNA Expression Profiles

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Yuntao Shi ◽  
Yingying Zhuang ◽  
Jialing Zhang ◽  
Mengxue Chen ◽  
Shangnong Wu
Keyword(s):  
Target Genes ◽  
Cox Regression ◽  
Expression Profiles ◽  
Survival Rates ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Risk Groups ◽  
Normal Mucosa ◽  
Microrna Expression ◽  
Functional Enrichment

Objective. Although noncoding RNAs, especially the microRNAs, have been found to play key roles in CRC development in intestinal tissue, the specific mechanism of these microRNAs has not been fully understood. Methods. GEO and TCGA database were used to explore the microRNA expression profiles of normal mucosa, adenoma, and carcinoma. And the differential expression genes were selected. Computationally, we built the SVM model and multivariable Cox regression model to evaluate the performance of tumorigenic microRNAs in discriminating the adenomas from normal tissues and risk prediction. Results. In this study, we identified 20 miRNA biomarkers dysregulated in the colon adenomas. The functional enrichment analysis showed that MAPK activity and MAPK cascade were highly enriched by these tumorigenic microRNAs. We also investigated the target genes of the tumorigenic microRNAs. Eleven genes, including PIGF, TPI1, KLF4, RARS, PCBP2, EIF5A, HK2, RAVER2, HMGN1, MAPK6, and NDUFA2, were identified to be frequently targeted by the tumorigenic microRNAs. The high AUC value and distinct overall survival rates between the two risk groups suggested that these tumorigenic microRNAs had the potential of diagnostic and prognostic value in CRC. Conclusions. The present study revealed possible mechanisms and pathways that may contribute to tumorigenesis of CRC, which could not only be used as CRC early detection biomarkers, but also be useful for tumorigenesis mechanism studies.

scholarly journals miRNA Mediated Noise Making of 3′UTR Mutations in Cancer

Genes ◽  
2018 ◽  
Vol 9 (11) ◽  
pp. 545 ◽  
Author(s):  
Wei Wu ◽  
Lingxiang Wu ◽  
Mengyan Zhu ◽  
Ziyu Wang ◽  
Min Wu ◽  
...  
Keyword(s):  
Somatic Mutations ◽  
Target Genes ◽  
Expression Profiles ◽  
Tumor Development ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Messenger Rnas ◽  
Cellular Functions ◽  
Mrna Binding

Somatic mutations in 3′-untranslated regions (3′UTR) do not alter amino acids and are considered to be silent in cancers. We found that such mutations can promote tumor progression by altering microRNA (miRNA) targeting efficiency and consequently affecting miRNA–mRNA interactions. We identified 67,159 somatic mutations located in the 3′UTRs of messenger RNAs (mRNAs) which can alter miRNA–mRNA interactions (functional somatic mutations, funcMutations), and 69.3% of these funcMutations (the degree of energy change > 12 kcal/mol) were identified to significantly promote loss of miRNA-mRNA binding. By integrating mRNA expression profiles of 21 cancer types, we found that the expression of target genes was positively correlated with the loss of absolute affinity level and negatively correlated with the gain of absolute affinity level. Functional enrichment analysis revealed that genes carrying funcMutations were significantly enriched in the MAPK and WNT signaling pathways, and analysis of regulatory modules identified eighteen miRNA modules involved with similar cellular functions. Our findings elucidate a complex relationship between miRNA, mRNA, and mutations, and suggest that 3′UTR mutations may play an important role in tumor development.

scholarly journals Integrative analyses of biomarkers and pathways for heart failure

2021 ◽  
Author(s):  
Shaowei Fan ◽  
Yuanhui Hu
Keyword(s):  
Heart Failure ◽  
Extracellular Matrix ◽  
Microarray Data ◽  
Enrichment Analysis ◽  
Signal Pathway ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Pathway Enrichment Analysis ◽  
Ppi Networks ◽  
Key Genes

Abstract Background: Heart failure (HF) is the most common potential cause of death, causing a huge health and economic burden all over the world. So far, some impressive progress has been made in the study of pathogenesis. However, the underlying molecular mechanisms leading to this disease remain to be fully elucidated. Methods: The microarray data sets of GSE76701, GSE21610 and GSE8331 were retrieved from the gene expression comprehensive database (GEO). After merging all microarray data and adjusting batch effects, differentially expressed genes (DEG) were determined. Functional enrichment analysis was performed based on Gene Ontology (GO) resources, Kyoto Encyclopedia of Genes and Genomes (KEGG) resources, gene set enrichment analysis (GSEA), response pathway database and Disease Ontology (DO). Protein protein interaction (PPI) network was constructed using string database. Combined with the above important bioinformatics information, the potential key genes were selected. The comparative toxicological genomics database (CTD) is used to explore the interaction between potential key genes and HF. Results: We identified 38 patients with heart failure and 16 normal controls. There were 315 DEGs among HF samples, including 278 up-regulated genes and 37 down-regulated genes. Pathway enrichment analysis showed that most DEGs were significantly enriched in BMP signal pathway, transmembrane receptor protein serine / threonine kinase signal pathway, extracellular matrix, basement membrane, glycosaminoglycan binding, sulfur compound binding and so on. Similarly, GSEA enrichment analysis showed that DEGs were mainly enriched in extracellular matrix and extracellular matrix related proteins. BBS9, CHRD, BMP4, MYH6, NPPA and CCL5 are central genes in PPI networks and modules. Conclusions: the enrichment pathway of DEGs and go ontology may reveal the molecular mechanism of HF. Among them, target genes EIF1AY, RPS4Y1, USP9Y, KDM5D, DDX3Y, NPPA, HBB, TSIX, LOC28556 and XIST are expected to become new targets for heart failure. Our findings provide potential biomarkers or therapeutic targets for the further study of heart failure and contribute to the development of advanced prediction, diagnosis and treatment strategies.

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