Comprehensive analysis of fifteen hub genes to identify a promising diagnostic model, regulated networks, and immune cell infiltration in acute kidney injury. Issue 11 (20th September 2022)

• Record Type: Journal Article
• Authors: Sun, Tao; Cao, Ying; Huang, Tiancha; Sang, Yiwen; Dai, Yibei; Tao, Zhihua
• Is Part Of: Journal of clinical laboratory analysis. Volume 36:Issue 11(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-09-20
• Subjects: acute kidney injury -- diagnosis -- GEO -- immune infiltration -- LASSO -- miRNA -- transcriptional factors -- WGCNA; Diagnosis, Laboratory -- Periodicals; Medical laboratory technology -- Periodicals; 616
• DOI: 10.1002/jcla.24709
• Languages: English
• ISSNs: 0887-8013

Abstract

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 to explore the underlying mechanisms and screen for novel diagnostic biomarkers, and therapeutic targets. Methods: The present study identified 15 hub genes by WGCNA analysis. LASSO‐based logistic regression analysis was used to select key features and construct a diagnostic model of AKI. In addition, GO and KEGG analyses 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: A diagnostic model was constructed by LASSO‐based logistic regression analysis and was validated by RT‐qPCR based on 15 hub genes. GO and KEGG analyses revealed DEGs were enriched in oxidation–reduction process, cell adhesion, proliferation, migration, and metabolic process. 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 15 hub genes based on WGCNA. Development and validation of a potentially diagnostic model based on 15 hub genes. In addition, exploring the interaction between transcriptional factors and 15 hub genes, and miRNA‐mRNA relationship pairs. Furthermore, immune infiltration analysis was performed by analyzing gene expression profiles of AKI. Our study provides some basis for further experimental studies. Abstract : The present study identified 15 hub genes by WGCNA analysis. LASSO‐based logistic regression analysis was used to select key features and construct a diagnostic model of AKI. Then, five biomarkers‐based AKI diagnostic model was validated by RT‐qPCR. In addition, GO and KEGG analyses 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.