scholarly journals Integrative Analyses of Genes Associated With Right Ventricular Cardiomyopathy Induced by Tricuspid Regurgitation

2021 ◽  
Vol 12 ◽  
Author(s):  
Chengnan Tian ◽  
Yanchen Yang ◽  
Yingjie Ke ◽  
Liang Yang ◽  
Lishan Zhong ◽  
...  

Tricuspid regurgitation (TR) induces right ventricular cardiomyopathy, a common heart disease, and eventually leads to severe heart failure and serious clinical complications. Accumulating evidence shows that long non-coding RNAs (lncRNAs) are involved in the pathological process of a variety of cardiovascular diseases. However, the regulatory mechanisms and functional roles of RNA interactions in TR-induced right ventricular cardiomyopathy are still unclear. Accordingly, we performed integrative analyses of genes associated with right ventricular cardiomyopathy induced by TR to study the roles of lncRNAs in the pathogenesis of this disease. In this study, we used high-throughput sequencing data of tissue samples from nine clinical cases of right ventricular myocardial cardiomyopathy induced by TR and nine controls with normal right ventricular myocardium from the Genotype-Tissue Expression database. We identified differentially expressed lncRNAs and constructed a protein-protein interaction and lncRNA-messenger RNA (mRNA) co-expression network. Furthermore, we determined hub lncRNA-mRNA modules related to right ventricular myocardial disease induced by TR and constructed a competitive endogenous RNA network for TR-induced right ventricular myocardial disease by integrating the interaction of lncRNA-miRNA-mRNA. In addition, we analyzed the immune infiltration using integrated data and the correlation of each immune-related gene with key genes of the integrated expression matrix. The present study identified 648 differentially expressed mRNAs, 201 differentially expressed miRNAs, and 163 differentially expressed lncRNAs. Protein-protein interaction network analysis confirmed that ADRA1A, AVPR1B, OPN4, IL-1B, IL-1A, CXCL4, ADCY2, CXCL12, GNB4, CCL20, CXCL8, and CXCL1 were hub genes. CTD-2314B22.3, hsa-miR-653-5p, and KIF17ceRNA; SRGAP3-AS2, hsa-miR-539-5p, and SHANK1; CERS6-AS1, hsa-miR-497-5p, and OPN4; INTS6-AS1, hsa-miR-4262, and NEURL1B; TTN-AS1, hsa-miR-376b-3p, and TRPM5; and DLX6-AS1, hsa-miR-346, and BIRC7 axes were obtained by constructing the ceRNA networks. Through the immune infiltration analysis, we found that the proportion of CD4 and CD8 T cells was about 20%, and the proportion of fibroblasts and endothelial cells was high. Our findings provide some insights into the mechanisms of RNA interaction in TR-induced right ventricular cardiomyopathy and suggest that lncRNAs are a potential therapeutic target for treating right ventricular myocardial disease induced by TR.

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Xiaodong Sheng ◽  
Tao Fan ◽  
Xiaoqi Jin

Background. Acute myocardial infarction (AMI) is regarded as an urgent clinical entity, and identification of differentially expressed genes, lncRNAs, and altered pathways shall provide new insight into the molecular mechanisms behind AMI. Materials and Methods. Microarray data was collected to identify key genes and lncRNAs involved in AMI pathogenesis. The differential expression analysis and gene set enrichment analysis (GSEA) were employed to identify the upregulated and downregulated genes and pathways in AMI. The protein-protein interaction network and protein-RNA interaction analysis were utilized to reveal key long noncoding RNAs. Results. In the present study, we utilized gene expression profiles of circulating endothelial cells (CEC) from 49 patients of AMI and 50 controls and identified a total of 552 differentially expressed genes (DEGs). Based on these DEGs, we also observed that inflammatory response-related genes and pathways were highly upregulated in AMI. Mapping the DEGs to the protein-protein interaction (PPI) network and identifying the subnetworks, we found that OMD and WDFY3 were the hub nodes of two subnetworks with the highest connectivity, which were found to be involved in circadian rhythm and organ- or tissue-specific immune response. Furthermore, 23 lncRNAs were differentially expressed between AMI and control groups. Specifically, we identified some functional lncRNAs, including XIST and its antisense RNA, TSIX, and three lncRNAs (LINC00528, LINC00936, and LINC01001), which were predicted to be interacting with TLR2 and participate in Toll-like receptor signaling pathway. In addition, we also employed the MMPC algorithm to identify six gene signatures for AMI diagnosis. Particularly, the multivariable SVM model based on the six genes has achieved a satisfying performance ( AUC = 0.97 ). Conclusion. In conclusion, we have identified key regulatory lncRNAs implicated in AMI, which not only deepens our understanding of the lncRNA-related molecular mechanism of AMI but also provides computationally predicted regulatory lncRNAs for AMI researchers.


2021 ◽  
Vol 20 ◽  
pp. 153303382098329
Author(s):  
Yujie Weng ◽  
Wei Liang ◽  
Yucheng Ji ◽  
Zhongxian Li ◽  
Rong Jia ◽  
...  

Human epidermal growth factor 2 (HER2)+ breast cancer is considered the most dangerous type of breast cancers. Herein, we used bioinformatics methods to identify potential key genes in HER2+ breast cancer to enable its diagnosis, treatment, and prognosis prediction. Datasets of HER2+ breast cancer and normal tissue samples retrieved from Gene Expression Omnibus and The Cancer Genome Atlas databases were subjected to analysis for differentially expressed genes using R software. The identified differentially expressed genes were subjected to gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses followed by construction of protein-protein interaction networks using the STRING database to identify key genes. The genes were further validated via survival and differential gene expression analyses. We identified 97 upregulated and 106 downregulated genes that were primarily associated with processes such as mitosis, protein kinase activity, cell cycle, and the p53 signaling pathway. Visualization of the protein-protein interaction network identified 10 key genes ( CCNA2, CDK1, CDC20, CCNB1, DLGAP5, AURKA, BUB1B, RRM2, TPX2, and MAD2L1), all of which were upregulated. Survival analysis using PROGgeneV2 showed that CDC20, CCNA2, DLGAP5, RRM2, and TPX2 are prognosis-related key genes in HER2+ breast cancer. A nomogram showed that high expression of RRM2, DLGAP5, and TPX2 was positively associated with the risk of death. TPX2, which has not previously been reported in HER2+ breast cancer, was associated with breast cancer development, progression, and prognosis and is therefore a potential key gene. It is hoped that this study can provide a new method for the diagnosis and treatment of HER2 + breast cancer.


2021 ◽  
Vol 8 ◽  
Author(s):  
Aleksandr A. Khudiakov ◽  
Daniil D. Panshin ◽  
Yulia V. Fomicheva ◽  
Anastasia A. Knyazeva ◽  
Ksenia A. Simonova ◽  
...  

Introduction: Pericardial fluid is enriched with biologically active molecules of cardiovascular origin including microRNAs. Investigation of the disease-specific extracellular microRNAs could shed light on the molecular processes underlying disease development. Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited heart disease characterized by life-threatening arrhythmias and progressive heart failure development. The current data about the association between microRNAs and ARVC development are limited.Methods and Results: We performed small RNA sequence analysis of microRNAs of pericardial fluid samples obtained during transcutaneous epicardial access for ventricular tachycardia (VT) ablation of six patients with definite ARVC and three post-infarction VT patients. Disease-associated microRNAs of pericardial fluid were identified. Five microRNAs (hsa-miR-1-3p, hsa-miR-21-5p, hsa-miR-122-5p, hsa-miR-206, and hsa-miR-3679-5p) were found to be differentially expressed between patients with ARVC and patients with post-infarction VT. Enrichment analysis of differentially expressed microRNAs revealed their close linkage to cardiac diseases.Conclusion: Our data extend the knowledge of pericardial fluid microRNA composition and highlight five pericardial fluid microRNAs potentially linked to ARVC pathogenesis. Further studies are required to confirm the use of pericardial fluid RNA sequencing in differential diagnosis of ARVC.


2021 ◽  
pp. 1-26
Author(s):  
Sze Chung Yuen ◽  
Simon Ming-Yuen Lee ◽  
Siu-wai Leung

Background: Neuronal cell cycle re-entry (CCR) is a mechanism, along with amyloid-β (Aβ) oligomers and hyperphosphorylated tau proteins, contributing to toxicity in Alzheimer’s disease (AD). Objective: This study aimed to examine the putative factors in CCR based on evidence corroboration by combining meta-analysis and co-expression analysis of omic data. Methods: The differentially expressed genes (DEGs) and CCR-related modules were obtained through the differential analysis and co-expression of transcriptomic data, respectively. Differentially expressed microRNAs (DEmiRNAs) were extracted from the differential miRNA expression studies. The dysregulations of DEGs and DEmiRNAs as binary outcomes were independently analyzed by meta-analysis based on a random-effects model. The CCR-related modules were mapped to human protein-protein interaction databases to construct a network. The importance score of each node within the network was determined by the PageRank algorithm, and nodes that fit the pre-defined criteria were treated as putative CCR-related factors. Results: The meta-analysis identified 18,261 DEGs and 36 DEmiRNAs, including genes in the ubiquitination proteasome system, mitochondrial homeostasis, and CCR, and miRNAs associated with AD pathologies. The co-expression analysis identified 156 CCR-related modules to construct a protein-protein interaction network. Five genes, UBC, ESR1, EGFR, CUL3, and KRAS, were selected as putative CCR-related factors. Their functions suggested that the combined effects of cellular dyshomeostasis and receptors mediating Aβ toxicity from impaired ubiquitination proteasome system are involved in CCR. Conclusion: This study identified five genes as putative factors and revealed the significance of cellular dyshomeostasis in the CCR of AD.


2015 ◽  
Vol 4 (4) ◽  
pp. 35-51 ◽  
Author(s):  
Bandana Barman ◽  
Anirban Mukhopadhyay

Identification of protein interaction network is very important to find the cell signaling pathway for a particular disease. The authors have found the differentially expressed genes between two sample groups of HIV-1. Samples are wild type HIV-1 Vpr and HIV-1 mutant Vpr. They did statistical t-test and found false discovery rate (FDR) to identify the genes increased in expression (up-regulated) or decreased in expression (down-regulated). In the test, the authors have computed q-values of test to identify minimum FDR which occurs. As a result they found 172 differentially expressed genes between their sample wild type HIV-1 Vpr and HIV-1 mutant Vpr, R80A. They found 68 up-regulated genes and 104 down-regulated genes. From the 172 differentially expressed genes the authors found protein-protein interaction network with string-db and then clustered (subnetworks) the PPI networks with cytoscape3.0. Lastly, the authors studied significance of subnetworks with performing gene ontology and also studied the KEGG pathway of those subnetworks.


2020 ◽  
Author(s):  
wenxing su ◽  
biao huang ◽  
ying zhao ◽  
xiaoyan zhang ◽  
lu chen ◽  
...  

Abstract Background Chronic spontaneous urticaria (CSU) refers to recurrent urticaria that lasts for more than 6 weeks in the absence of an identifiable trigger. Due to its recurrent wheal and severe itching, CSU seriously affects patients' life quality. There is currently no radical cure for it and its vague pathogenesis limits the development of targeted therapy. With the goal of revealing the underlying mechanism, two data sets with accession numbers GSE57178 and GSE72540 were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the differentially expressed genes (DEGs) of CSU skin lesion samples and healthy controls, four kinds of analyses were performed, namely functional annotation, protein-protein interaction (PPI) network and module construction, co-expression and drug-gene interaction prediction analysis, and immune and stromal cells deconvolution analyses. Results 92 up-regulated genes and 7 down-regulated genes were selected for subsequent analyses. Through the enrichment analysis of the core modules, three signal pathways were found to be closely related to the occurrence and development of CSU, including TNF signaling pathway, NF-κB signaling pathway and Jak-STAT signaling pathway. Referring to protein-protein interaction (PPI) network analysis and GeneCards database, we identified four key genes, IL6, TLR4, ICAM1, and PTGS2. In addition, according to the results of immune infiltration analysis, CSU tissue generally contained a higher proportion of dendritic cells, Th2 cells, mast cells, megakaryocyte-erythroid progenitor, preadipocytes, and macrophages M1. Conclusions To conclude, the key genes and pathways identified from CSU lesions and normal controls along with the immune infiltration profile may provide new insights into the development of CSU.


2019 ◽  
Author(s):  
Florian Klimm ◽  
Enrique M. Toledo ◽  
Thomas Monfeuga ◽  
Fang Zhang ◽  
Charlotte M. Deane ◽  
...  

AbstractRecent advances in single-cell RNA sequencing (scRNA-seq) have allowed researchers to explore transcriptional function at a cellular level. In this study, we present scPPIN, a method for integrating single-cell RNA sequencing data with protein–protein interaction networks (PPINs) that detects active modules in cells of different transcriptional states. We achieve this by clustering RNA-sequencing data, identifying differentially expressed genes, constructing node-weighted PPINs, and finding the maximum-weight connected subgraphs with an exact Steiner-tree approach. As a case study, we investigate RNA-sequencing data from human liver spheroids but the techniques described here are applicable to other organisms and tissues. scPPIN allows us to expand the output of differential expressed genes analysis with information from protein interactions. We find that different transcriptional states have different subnetworks of the PPIN significantly enriched which represent biological pathways. In these pathways, scPPIN also identifies proteins that are not differentially expressed but have a crucial biological function (e.g., as receptors) and therefore reveals biology beyond a standard differentially expressed gene analysis.


2021 ◽  
Author(s):  
Yuxuan HUANG ◽  
Ge CUI

Abstract Aims: To utilize the bioinformatics to analyze the differentially expressed genes (DEGs), interaction proteins, perform gene enrichment analysis, protein-protein interaction network (PPI) and map the hub genes between colorectal cancer(CRC) and colorectal adenocarcinomas(CA).Methods: We analyzed a microarray dataset (GSE32323 and GSE4183) from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in tumor tissues and non-cancerous tissues were identified using the dplyr and Venn diagram packages of the R Studio software. Functional annotation of the DEGs was performed using the Gene Ontology (GO) website. Pathway enrichment (KEGG) used the WebGestalt to analyze the data and R Studio to generate the graph. We constructed a protein–protein interaction (PPI) network of DEGs using STRING and Cytoscape software was used for visualization. Survival analysis of the hub genes and was performed using the online platform GEPIA to determine the prognostic value of the expression of hub genes in cell lines from CRC patients. The expression of molecules with prognostic values was validated on the UALCAN database. The expression of hub genes was examined using the Human Protein Atlas. Results: Applying the GEO2R analysis and R studio, we identified a total of 471 upregulated and 278 downregulated DEGs. By using the online database WebGestalt, we identified the most relevant biological networks involving DEGs with statistically significant differences in expression were mainly associated with biological processes involved in the cell proliferation, cell cycle transition, cell homeostasis and indicated the role of each DEGs in cell cycle regulation pathways. We found 10 hub genes with prognostic values were overexpressed in the CRC and CA samples.Conclusion: we found out ten hub genes and three core genes closely associated with the pathogenesis and prognosis of CRC and CA, which is of great significance for colorectal tumor early detection and prognosis evaluation.


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