scholarly journals Identification of Differentially Expressed Genes and Pathways in Human Atrial Fibrillation by Bioinformatics Analysis

2022 ◽  
Vol Volume 15 ◽  
pp. 103-114
Author(s):  
Defeng Pan ◽  
Yufei Zhou ◽  
Shengjue Xiao ◽  
Yue Hu ◽  
Chunyan Huan ◽  
...  
2019 ◽  
Vol 45 (9-10) ◽  
pp. 288-296 ◽  
Author(s):  
Huaibin Wang ◽  
Miaomiao Wang ◽  
Kun Xiao ◽  
Xu Zhang ◽  
Peng Wang ◽  
...  

2019 ◽  
Vol 245 (1) ◽  
pp. 42-53 ◽  
Author(s):  
Nan-Nan Shen ◽  
Chi Zhang ◽  
Zheng Li ◽  
Ling-Cong Kong ◽  
Xin-Hua Wang ◽  
...  

Association between microRNA (miRNA) expression signatures and atrial fibrillation has been evaluated with inconsistent findings in different studies. This study aims to identify miRNAs that actually play vital role in pathophysiological process of atrial fibrillation and explore miRNA-targeted genes and the involved pathways. Relevant studies were retrieved from the electronic databases of Embase, Medline, and Cochrane Library to determine the miRNA expression profiles between atrial fibrillation subjects and non-atrial fibrillation controls. Robustness of results was assessed using sensitivity analysis. Subgroup analyses were performed based on species, miRNA detection method, sample source, and ethnicity. Quality assessment of studies was independently conducted according to QUADAS-2. Bioinformatics analysis was applied to explore the potential genes and pathways associated with atrial fibrillation, which were targeted by differentially expressed miRNAs. Form of pooled results was shown as log10 odds ratios (logORs) with 95% confidence intervals (CI), and random-effects model was used. In total, 40 articles involving 283 differentially expressed miRNAs were reported. And 51 significantly dysregulated miRNAs were identified in consistent direction, with 22 upregulated and 29 downregulated. Among above-mentioned miRNAs, miR-223-3p (logOR 6.473; P < 0.001) was the most upregulated, while miR-1-5p (logOR 7.290; P < 0.001) was the most downregulated. Subgroup analysis confirmed 53 significantly dysregulated miRNAs (21 upregulated and 32 downregulated) in cardiac tissue, with miRNA-1-5p and miRNA-223-3p being the most upregulated and downregulated miRNAs, respectively. Additionally, miR-328 and miR-1-5p were highly blood-specific, and miR-133 was animal-specific. In the detection method sub-groups, miRNA-29b and miRNA-223-3p were differentially expressed consistently. Four miRNAs, including miRNA-223-3p, miRNA-21, miRNA-328, and miRNA-1-5p, were consistently dysregulated in both Asian and non-Asian. Results of sensitivity analysis showed that 47 out of 51 (92.16%) miRNAs were dysregulated consistently. Totally, 51 consistently dysregulated miRNAs associated with atrial fibrillation were confirmed in this study. Five important miRNAs, including miR-29b, miR-328, miR-1-5p, miR-21, and miR-223-3p may act as potential biomarkers for atrial fibrillation. Impact statement Atrial fibrillation (AF) is considered as the most common arrhythmia, and it subsequently causes serious complications including thrombosis and heart failure that increase the social burden. The definite mechanisms underlying AF pathogenesis remain complicated and unclear. Many studies attempted to discover the transcriptomic changes using microarray technologies, and the present studies for this hot topic have assessed individual miRNAs profiles for AF. However, results of different articles are controversial and not each reported miRNA is actually associated with the pathogenesis of AF. The present systematic review and meta-analysis identified that 51 consistently dysregulated miRNAs were associated with AF. Of these miRNAs, five miRNAs (miRNA-1-5p, miRNA-328, miRNA-29b, miRNA-21, and miRNA-223-3p) may act as novel biomarkers for AF. The findings could offer a better description of the biological characteristics of miRNAs, meanwhile might serve as new target for the intervention and monitoring AF in future studies.


2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Chunchen Xiang ◽  
Shengri Cong ◽  
Bin Liang ◽  
Shuyan Cong

Abstract Background Huntington’s disease (HD) is a neurodegenerative disorder characterized by psychiatric symptoms, serious motor and cognitive deficits. Certain pathological changes can already be observed in pre-symptomatic HD (pre-HD) patients; however, the underlying molecular pathogenesis is still uncertain and no effective treatments are available until now. Here, we reanalyzed HD-related differentially expressed genes from the GEO database between symptomatic HD patients, pre-HD individuals, and healthy controls using bioinformatics analysis, hoping to get more insight in the pathogenesis of both pre-HD and HD, and shed a light in the potential therapeutic targets of the disease. Methods Pre-HD and symptomatic HD differentially expressed genes (DEGs) were screened by bioinformatics analysis Gene Expression Omnibus (GEO) dataset GSE1751. A protein–protein interaction (PPI) network was used to select hub genes. Subsequently, Gene Ontology (GO) enrichment analysis of DEGs and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of hub genes were applied. Dataset GSE24250 was downloaded to verify our hub genes by the Kaplan–Meier method using Graphpad Prism 5.0. Finally, target miRNAs of intersected hub genes involved in pre-HD and symptomatic HD were predicted. Results A total of 37 and 985 DEGs were identified in pre-HD and symptomatic HD, respectively. The hub genes, SIRT1, SUZ12, and PSMC6, may be implicated in pre-HD, and the hub genes, FIS1, SIRT1, CCNH, SUZ12, and 10 others, may be implicated in symptomatic HD. The intersected hub genes, SIRT1 and SUZ12, and their predicted target miRNAs, in particular miR-22-3p and miR-19b, may be significantly associated with pre-HD. Conclusion The PSMC6, SIRT1, and SUZ12 genes and their related ubiquitin-mediated proteolysis, transcriptional dysregulation, and histone metabolism are significantly associated with pre-HD. FIS1, CCNH, and their related mitochondrial disruption and transcriptional dysregulation processes are related to symptomatic HD, which might shed a light on the elucidation of potential therapeutic targets in HD.


Medicine ◽  
2019 ◽  
Vol 98 (27) ◽  
pp. e16240
Author(s):  
Jian Zhou ◽  
Chenxi Li ◽  
Anqi Yu ◽  
Shuo Jie ◽  
Xiadong Du ◽  
...  

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