| چکیده انگلیسی مقاله |
Objective: Autosomal dominant polycystic kidney disease (ADPKD) is the most common monogenic hereditary disease. The disease diagnosed by growing multiple cysts in the kidneys and organs such as liver, pancreas, spleen, intestine. Cerebral and aortic aneurysms are other symptoms of the disease. Studies shown that, mutations in two genes, polycystic kidney disease-1 (PKD-1) and PKD-2 gene are responsible of disease. The protein products of these genes, Polycystin-1 (PC-1) and PC-2 together form a functional complex. This complex protein regulated the common pathway including cell proliferation, apoptosis and cell polarity. According to studies, there are many doubts related to the progression of the disease. In this study, with computational analysis predicted the central genes associated with the ADPKD. Methods: Microarray data with accession series GSE7869 was selected from Gene Expression Omnibus (GEO) database. Using GEO2R tool of GEO, the differential express genes were determined. With the up and down regulated genes, protein interaction mapping was constructed using Cytoscape V3.4 software. Then, pathways enrichment analysis of DEGs were done. Central genes and clusters of complex network were distinguished based on degree, betweeness and closeness centrality and module defination. Results: The formation of the early cysts have shown the severe changes in the differential expression of the genes, and there are not difference in between normal and minimally cysts, and small and large cysts samples. Network topology and cluster analysis for network in this stage were shown MMP2, CXCL8, SLC9A3R1, BCAT1, and CCR2 genes have the highest parameters and predicted as central genes Conclusion: In conclusion, holistic approaches can be used as a powerful method for understanding the mechanisms underlying the development of monogenic disorder such as ADPKD. |
