Uncovering potential biomarkers for chronic kidney disease of unknown etiology through a network-based bioinformatic approach.

CKDu is a renal disorder characterized by a decline in eGFR < 60 mL/min/1.73 m2 for a period of ≥ 3 months without any known risk factors. Biopsy reports in various case studies revealed the role of tubular injury in CKDu. We adopted a network-based bioinformatic approach to identify biomarkers and their role in CKDu. Through literature survey, 216 articles from Science Direct, PubMed, and Scopus were identified; 57 articles were selected on renal tubular injury markers, whereas 159 articles were not either research or on renal tubular injury markers. After excluding 17 duplicate articles, we found 40 research articles on various biomarkers of CKDu. Out of 40 research articles, we identified 37 biomarkers and 43 corresponding genes. Network centrality of these 43 genes with CKDu was performed using Cytoscape and enrichment analysis using Cluego. Out of selected 43 genes, topological enrichment interpretations revealed SPP1 as the hub gene, with top rank and scores. SPP1, TNF, CLU, CST3, CRP, TGFB1, and IL-6 genes had the top 5 rank and scores. Functional enrichment analysis revealed that cellular components were localized to collagen type IV trimer in the renal tubules; molecular enrichment analysis showed monooxygenase activity in kidney for detoxification. Reactome pathway accounts for TLR by endogenous ligand in renal cells upon inflammation as a possible mechanism behind CKDu. SPP1, TNF, CLU, CST3, CRP, TGFB1, and IL-6 genes were identified to play an important role in the initiation and progression of CKDu. Further biological validation studies are required to check their potential to act as biomarkers.