Screening diagnostic markers for diabetic kidney disease based on the renal tubule transcriptome and exosome proteomics

Abstract The commonly used clinical diagnostic indicators of diabetic kidney disease (DKD) include urinary microalbumin and estimated glomerular filtration rate, which have controversial sensitivities and specificities. Therefore, it is essential to identify biomarkers for the early diagnosis and prognosis of DKD. Exosome data can be obtained by extracting, separating, and purifying renal tubular exosomes, followed by proteomic analysis. The renal tubular transcriptome dataset GSE30122 was searched and screened using the GEO database. Twenty-two intersection targets were obtained by the intersection of the two. GO enrichment analysis was performed for intersection targets through the clusterProfiler package in R language. Moreover, pathway enrichment analysis was conducted using the KEGG database. Biological process (BP) analysis revealed that intersection targets participated in renal system development. According to KEGG enrichment analysis, the intersection targets of these genes were involved in the PI3K-Akt signaling pathway. Nine key targets were identified by constructing a random forest (RF) model, support vector machine (SVM) model, and generalized linear model (GLM) using the R language. An ROC curve was constructed to screen three key targets (CFH, COL4A1, and ANXA2) with an AUC > 0.9 as biomarkers for DKD diagnosis. Then, the three potential targets were subjected to differential expression analysis and clinical correlation verification (eGFR, proteinuria, and serum creatinine), which indicated that CFH, COL4A1, and ANXA2 were differentially expressed and clinically related. Western blot analysis also verified that compared with those in the normal group, the protein expression of CFH, COL4A1, and ANXA2 in the DKD group was upregulated (P < 0.05). Initially, the current study screened three potential diagnostic targets using proteomic and transcriptional analysis of renal tubular exosomes, providing clues for discovering new DKD biomarkers.