Identification of Hub Genes Associated With Clinical Characteristics and Potential Therapy of Diabetic Nephropathy by Bioinformatics Analysis.
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Abstract Background: To provide theoretical basis for the molecular mechanism of the development of diabetic nephropathy and targeted molecular therapy by screening expressed genes based on bioinformatic analysis. Methods: We analyzed diabetic nephropathy microarray datasets derived from GEO database. Perl and R programming packages were used for data processing and analysis and for drawing. STRING online database and Cytoscape software were utilized for protein-protein interaction network analysis and screened for hub genes. Also, WebGestalt was used to analyze the relationship between genes and microRNAs. Nephroseq online tool was used to visualize the correlation between genes and clinical properties. Results: We found 91 differentially expressed genes between diabetic nephropathy tissues and normal control tissues. Protein-protein interaction network analysis screened out 5 key modules and a total of 14 hub genes were identified by integration, also11 microRNAs were associated with hub genes. Especially mir29 could regulate COL6A3 and COL15A1. Conclusions: The internal biological information in diabetic nephropathy can be revealed by integrative bioinformatical analysis, providing theoretical basis for further research on molecular mechanism and potential targets for diagnosis and therapeutics of diabetic nephropathy.Keywords:
Identification
Diabetic Nephropathy (DN) is a debilitating consequence of both Type 1 and Type 2 diabetes affecting the kidney and renal tubules leading to End Stage Renal Disease (ESRD). As diabetes is a world epidemic and almost half of diabetic patients develop DN in their lifetime, a large group of people is affected. Due to the complex nature of the disease, current diagnosis and treatment are not adequate to halt disease progression or provide an effective cure. DN is now considered a manifestation of inflammation where inflammatory molecules regulate most of the renal physiology. Recent advances in genetics and genomic technology have identified numerous susceptibility genes that are associated with DN, many of which have inflammatory functions. Based on their role in DN, we will discuss the current aspects of developing biomarkers and molecular therapy for advancing precision medicine.
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Oxidative stress is hypothesized to play a role in the development of diabetes with and without nephropathy. In addition, it has been suggested that some metabolic abormalities associated with diabetes may be due to cytokine overproduction. In the light of this knowledge, we aimed to measure MDA levels as a marker of oxidative stress and the IL-6 level in diabetes with and without different stages of nephropathy. Plasma MDA levels in the group of NIDDM patients with advanced nephropathy were significantly higher than in the group of NIDDM patients without nephropathy, which had significantly higher levels compared with the control group. Although IL-6 levels were elevated in diabetic groups with and without nephropathy in comparison with the control, no significant difference was found between patient groups. As a conclusion, oxidative stress may play an important role in diabetes with and without nephropathy, but the IL-6 level may not be useful in the evaluation of diabetic nephropathy.
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Diabetes is associated with numerous metabolic and vascular risk factors that contribute to a high rate of micro-vascular and macro-vascular disorders leading to mortality and morbidity from diabetic complications. In this case, the major cause of death in overall diabetic patients results from diabetic nephropathy (DN) or renal failure. The risk factors and mechanisms that correspond to the development of DN are not fully understood and so far, no specific and sufficient diagnostic biomarkers are currently available other than micro- or macroalbuminuria. Therefore, this review describes current and novel protein biomarkers in the context of DN as well as probable proteins biomarkers associated with pathological processes for the early stage of DN via proteomics data together with bioinformatics. In addition, the mechanisms involved in early development of diabetic vascular disorders and complications resulting from glucose induced oxidative stress will also be explored.
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