In Silico Characterization of Inflammatory and Anti-Inflammatory Modulation in Diabetic Nephropathy: The Construction of a Genetic Panel

• Published in: Journal of Molecular Pathology Vol. 5; no. 3; pp. 335 - 359
• Main Authors: Costa, Caroline Christine Pincela da, Assunção, Leandro do Prado, Santos, Kamilla de Faria, Silva, Laura da, Santos, Rodrigo da Silva, Reis, Angela Adamski da Silva
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-09-2024
• Subjects: Bias; Bioinformatics; Chemokines; Cohort analysis; Confounding (Statistics); Content analysis; Cross-sectional studies; Datasets; Diabetes; Diabetes mellitus; Diabetic nephropathy; End-stage renal disease; Etiology; Gene expression; Genetic analysis; genetic polymorphisms; Hyperglycemia; inflammation; Kidney diseases; Kidneys; Leukocytes; Meta-analysis; microvascular complications; Monocyte chemoattractant protein 1; Nephropathy; Polymorphism; Precision medicine; Protein arrays; Proteins; Public health; Single-nucleotide polymorphism; Software; susceptibility; Systematic review; Vascular endothelial growth factor
• ISSN: 2673-5261; 2673-5261
• DOI: 10.3390/jmp5030024

Diabetic Nephropathy (DN) stands as a primary cause of end-stage renal disease and its etiology remains unclear. Thus, this study aims to construct a genetic panel with potential biomarkers linked to the inflammatory pathway of DN associated with the pathology’s susceptibility. Through a systematic review and meta-analysis, we selected observational studies in English, Portuguese, and Spanish, selected from the PubMed, SCOPUS, Virtual Health Library, Web of Science, and EMBASE databases. Additionally, a protein–protein interaction network was constructed to list hub genes, with differential expression analysis by microarray of kidneys with DN from the GSE30529 database to further refine results. Seventy-two articles were included, and 54 polymorphisms in 37 genes were associated with the inflammatory pathway of DN. Meta-analysis indicated a higher risk of complication associated with SNPs 59029 G/A, −511 C/T, VNTR 86 bp, −308 G/A, and −1031 T/C. Bioinformatics analyses identified differentially expressed hub genes, underscoring the scarcity of studies on CCL2 and VEGF-A genes in relation to DN. This study highlighted the intrinsic relationship between inflammatory activity in the etiology and progression of DN, enabling the effective application of precision medicine in diabetic patients for potential prognosis of the complications and contributing to cost reduction in the public health system.