Integrated Profiling Identifies Key Molecule Drivers as Diagnostic Biomarkers and Therapeutic Targets in Acute Kidney Injury

Abstract

Background Acute kidney injury is a common clinical problem with no sensitive and specific diagnostic biomarkers and definitive treatments. The underlying molecular mechanisms of acute kidney injury are unclear. Therefore, it is pivotal and urgent to explore the underlying mechanisms and screen for novel diagnostic biomarkers, as well as therapeutic targets. Methods The present study constructed scale-free network using WGCNA analysis. LASSO logistic regression analysis was used to explore the optimal diagnostic model of AKI. In addition, GO and KEGG pathway enrichment analysis were performed and TF-mRNA and miRNA-mRNA network analysis and immune infiltration analysis of hub genes were performed to reveal the underlying mechanisms of AKI. Results Fifteen hub genes were uncovered and constructed a diagnostic model by LASSO logistic regression analysis. GO and KEGG analysis revealed that the genes were enriched in oxidation-reduction process, cell adhesion, proliferation, migration, metabolic process, mitochondria and iron ion binding. The enriched TFs were BRD2, EP300, ETS1, MYC, SPI1 and ZNF263. The enriched miRNAs were miR-181c-5p, miR-218-5p, miR-485-5p, miR-532-5p and miR-6884-5p. The immune infiltration analysis showed that Macrophages M2 was decreasing significantly revealing a protective factor for further AKI treatment. Conclusions The present study identified fifteen hub genes, a diagnostic model, transcriptional factors, miRNAs, immune infiltration and pathways by analyzing gene expression profiles of AKI, which provides some basis for further experimental studies.