Abstract
AimsCurrently, diabetic nephropathy (DN) is considered the leading cause of the end-stage renal disease (ESRD). However, its specific molecular mechanism is still unclear, and there is still a lack of effective diagnostic and therapeutic methods. MethodA pathway was assumed after bioinformatics analysis of GEO datasets related to individuals with various levels of DN, LINC01410, MAFB, and FOSL1. Then, 46 patients with type 2 diabetes (T2DM) and different levels of albuminuria, and 12 individuals without diabetes, were selected. qPCR was performed to evaluate gene expression. One-way ANOVA followed by Tukey’s -and linear trend tests were performed to analyze gene expression in different stages of the disease. Moreover, receiver operating characteristic (ROC) curves and the correlation between LINC01410, FOSL1, and MAFB were analyzed. ResultsLINC01410, MAFB, and FOSL1 were selected based on bioinformatics analyses. The qPCR results showed that the expression of LINC01410 decreased, and FOSL1 and MAFB increased in micro-and macroalbuminuria groups compared to normoalbuminuria groups (P < 0.05). ROC curves demonstrated a significant diagnostic accuracy of LINC01410, MAFB, and FOSL1 between DN and participants with normoalbuminuria (P < 0.05). Pearson’s correlation analysis revealed a positive association between the expressions of FOSL1 and MAFB (p = 0.01, r = 0.39). However, there was no correlation between LINC01410 with MAFB and FOSL1 (p = 0.23 and p = 0.21, respectively). ConclusionDysregulation of LINC01410, MAFB, and FOSL1 is related to DN. These results may provide new insights into the role of LINC01410, MAFB, and FOSL1 as potential biomarkers in DN.
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