In Silico Integrative Approach Revealed Key MicroRNAs and Associated Target Genes in Cardiorenal Syndrome
| Autor: | Shahnawaz Ali, Aftab Alam, Nikhat Imam, Rafat Ali, Naaila Tamkeen, Romana Ishrat, Anam Farooqui, Armiya Sultan, Safia Tazyeen, Mohd Murshad Ahmed, Zubbair Malik |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
0301 basic medicine
QH301-705.5 In silico pathways Cardiorenal syndrome Computational biology 030204 cardiovascular system & hematology Biology Biochemistry literature mining 03 medical and health sciences 0302 clinical medicine Betweenness centrality microRNA medicine Diagnostic biomarker Biology (General) Molecular Biology Gene Original Research DEMs Applied Mathematics Organ dysfunction medicine.disease Computer Science Applications miRNA-mRNA network body regions Computational Mathematics 030104 developmental biology embryonic structures medicine.symptom Centrality module analysis CRS |
| Zdroj: | Bioinformatics and Biology Insights Bioinformatics and Biology Insights, Vol 15 (2021) |
| ISSN: | 1177-9322 |
| Popis: | Cardiorenal syndromes constellate primary dysfunction of either heart or kidney whereby one organ dysfunction leads to the dysfunction of another. The role of several microRNAs (miRNAs) has been implicated in number of diseases, including hypertension, heart failure, and kidney diseases. Wide range of miRNAs has been identified as ideal candidate biomarkers due to their stable expression. Current study was aimed to identify crucial miRNAs and their target genes associated with cardiorenal syndrome and to explore their interaction analysis. Three differentially expressed microRNAs (DEMs), namely, hsa-miR-4476, hsa-miR-345-3p, and hsa-miR-371a-5p, were obtained from GSE89699 and GSE87885 microRNA data sets, using R/GEO2R tools. Furthermore, literature mining resulted in the retrieval of 15 miRNAs from scientific research and review articles. The miRNAs-gene networks were constructed using miRNet (a Web platform of miRNA-centric network visual analytics). CytoHubba (Cytoscape plugin) was adopted to identify the modules and the top-ranked nodes in the network based on Degree centrality, Closeness centrality, Betweenness centrality, and Stress centrality. The overlapped miRNAs were further used in pathway enrichment analysis. We found that hsa-miR-21-5p was common in 8 pathways out of the top 10. Based on the degree, 5 miRNAs, namely, hsa-mir-122-5p, hsa-mir-222-3p, hsa-mir-21-5p, hsa-mir-146a-5p, and hsa-mir-29b-3p, are considered as key influencing nodes in a network. We suggest that the identified miRNAs and their target genes may have pathological relevance in cardiorenal syndrome (CRS) and may emerge as potential diagnostic biomarkers. |
| Databáze: | OpenAIRE |
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