Dataset Information

Weighted Gene Co-expression Network Analysis for RNA-Sequencing Data of the Varicose Veins Transcriptome.

ABSTRACT: Objective:Varicose veins are a common problem worldwide and can cause significant impairments in health-related quality of life, but the etiology and pathogenesis remain not well defined. This study aims to elucidate transcriptomic regulations of varicose veins by detecting differentially expressed genes, pathways and regulator genes. Methods:We harvested great saphenous veins (GSV) from patients who underwent coronary artery bypass grafting (CABG) and varicose veins from conventional stripping surgery. RNA-Sequencing (RNA-Seq) technique was used to obtain the complete transcriptomic data of both GSVs from CABG patients and varicose veins. Weighted Gene Co-expression network analysis (WGCNA) and further analyses were then carried out with the aim to elucidate transcriptomic regulations of varicose veins by detecting differentially expressed genes, pathways and regulator genes. Results:From January 2015 to December 2016, 7 GSVs from CABG patients and 13 varicose veins were obtained. WGCNA identified 4 modules. In the brown module, gene ontology (GO) analysis showed that the biological processes were focused on response to stimulus, immune response and inflammatory response, etc. Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis showed that the biological processes were focused on cytokine-cytokine receptor interaction and TNF signaling pathway, etc. In the gray module, GO analysis showed that the biological processes were skeletal myofibril assembly related. The immunohistochemistry staining showed that the expression of ASC, Caspase-1 and NLRP3 were increased in GSVs from CABG patients compared with varicose veins. Histopathological analysis showed that in the varicose veins group, the thickness of vascular wall, tunica intima, tunica media and collagen/smooth muscle ratio were significantly increased, and that the elastic fiber/internal elastic lamina ratio was decreased. Conclusion:This study shows that there are clear differences in transcriptomic information between varicose veins and GSVs from CABG patients. Some inflammatory RNAs are down-regulated in varicose veins compared with GSVs from CABG patients. Skeletal myofibril assembly pathway may play a crucial role in the pathogenesis of varicose veins. Characterization of these RNAs may provide new targets for understanding varicose veins diagnosis, progression, and treatment.

SUBMITTER: Zhang J

PROVIDER: S-EPMC6433941 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Weighted Gene Co-expression Network Analysis for RNA-Sequencing Data of the Varicose Veins Transcriptome.

Zhang Jianbin J Nie Qiangqiang Q Si Chaozeng C Wang Cheng C Chen Yang Y Sun Weiliang W Pan Lin L Guo Jing J Kong Jie J Cui Yiyao Y Wang Feng F Fan Xueqiang X Ye Zhidong Z Wen Jianyan J Liu Peng P

Frontiers in physiology 20190319

<h4>Objective</h4>Varicose veins are a common problem worldwide and can cause significant impairments in health-related quality of life, but the etiology and pathogenesis remain not well defined. This study aims to elucidate transcriptomic regulations of varicose veins by detecting differentially expressed genes, pathways and regulator genes.<h4>Methods</h4>We harvested great saphenous veins (GSV) from patients who underwent coronary artery bypass grafting (CABG) and varicose veins from conventi ...[more]

PMID: 30941060

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Project description:BACKGROUND:Varicose veins are a common problem with no approved medical therapies. Although it is believed that varicose vein pathogenesis is multifactorial, there is limited understanding of the genetic and environmental factors that contribute to their formation. Large-scale studies of risk factors for varicose veins may highlight important aspects of pathophysiology and identify groups at increased risk for disease. METHODS:We applied machine learning to agnostically search for risk factors of varicose veins in 493?519 individuals in the UK Biobank. Predictors were further studied with univariable and multivariable Cox regression analyses (2441 incident events). A genome-wide association study of varicose veins was also performed among 337?536 unrelated individuals (9577 cases) of white British descent, followed by expression quantitative loci and pathway analyses. Because height emerged as a new candidate risk factor, we performed mendelian randomization analyses to assess a potential causal role for height in varicose vein development. RESULTS:Machine learning confirmed several known (age, sex, obesity, pregnancy, history of deep vein thrombosis) and identified several new risk factors for varicose vein disease, including height. After adjustment for traditional risk factors in Cox regression, greater height remained independently associated with varicose veins (hazard ratio for upper versus lower quartile, 1.74; 95% CI, 1.51-2.01; P<0.0001). A genome-wide association study identified 30 new genome-wide significant loci, identifying pathways involved in vascular development and skeletal/limb biology. Mendelian randomization analysis provided evidence that increased height is causally related to varicose veins (inverse-variance weighted: odds ratio, 1.26; P=2.07×10-16). CONCLUSIONS:Using data from nearly a half-million individuals, we present a comprehensive genetic and epidemiological study of varicose veins. We identified novel clinical and genetic risk factors that provide pathophysiological insights and could help future improvements of treatment of varicose vein disease.

Project description:Background: Currently, disease control in patients with severe eosinophilic asthma is not optimistic. Competing endogenous RNA (ceRNA) networks have been found to play a key role in asthma in recent years. However, it is unclear whether ceRNA networks play an important part in severe eosinophilic asthma. Methods: Firstly, gene expression profiles related to severe eosinophilic asthma were downloaded from the Gene Expression Omnibus (GEO) database. Secondly, the key modules were identified by the weighted gene co-expression network analysis (WGCNA). Thirdly, genes in modules highly associated with severe eosinophilic asthma were selected for further construction of the ceRNA network. Fourthly, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed on hub genes. Finally, the results of this study were validated on the GSE143303, GSE137268, and GSE147878 datasets. Results: 22 severe eosinophilic asthmatics and 13 healthy controls were extracted for WGCNA. We found that the genes in the black module (r = -0.75, p < 0.05) and yellow module (r = 0.65, p < 0.05) were highly associated with severe eosinophilic asthma. EP300 was discovered to serve the key connecting function in the ceRNA network. Surprisingly, lncRNAs seem to eliminate the role of EP300 in the black module and we discovered that CCT8 and miRNA-mRNA formed a circRNA-miRNA-mRNA network in the yellow module. We found that EP300 and FOXO3 in the black module were regulated by steroid hormones in the enrichment analysis, which were related to the medication used by the patient. Through validation of other datasets, we found that the hub genes in the yellow module were the key genes in the treatment of severe eosinophilic asthma. In particular, RPL17 and HNRNPK might specifically regulate severe eosinophilic asthma. Conclusion: RPL17 and HNRNPK might particularly regulate severe eosinophilic asthma. Our results could be useful to provide potential immunotherapy targets and prognostic markers for severe eosinophilic asthma.

Dataset Information

Weighted Gene Co-expression Network Analysis for RNA-Sequencing Data of the Varicose Veins Transcriptome.

Publications

Weighted Gene Co-expression Network Analysis for RNA-Sequencing Data of the Varicose Veins Transcriptome.

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