Identification of inflammatory response genes in ANCA-associated vasculitis by bioinformatics analysis and experimental validation

Acta Universitatis Medicinalis Anhui 2024 04 v.59 581-589     font:big middle small

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Authors:Zhang Dongmei; Zhang Yannan; Qin Jianhua; Ou Santao; Wu Weihua

Keywords:ANCA-associated vasculitis;bioinformatics analysis;CSF1R;TNFRSF1B;inflammation;competing endogenous RNAs

DOI:10.19405/j.cnki.issn1000-1492.2024.04.004

〔Abstract〕 Objective To explore the candidate genes and potential molecular mechanisms of anti-neutrophil cytoplasmic antibodies(ANCA)-associated vasculitis by bioinformatics and experimental validation, and to provide a scientific theoretical basis for the treatment of potential inflammatory targets for ANCA-associated vasculitis. Methods The GSE108109 chip data was retrieved from the Gene Expression Omnibus(GEO) database, and the differential genes were processed, analyzed and screened using the R language related program package. Kyoto encyclopedia of genes and genomes(KEGG) and gene ontology(GO) enrichment analysis was carried out using DAVID online network cable, and the interaction network of the protein encoded by the selected genes of inflammatory syndrome was constructed through STRING website. Further endogenous competitive RNA(ceRNA) regulatory network was predicted and constructed through miRWalk and DIANA-LncBase databases, and key genes were screened from the network to draw ROC curve. The renal biopsy samples of patients with ANCA-associated vasculitis confirmed by our hospital were collected as the experimental group, and the renal biopsy samples of IgA nephropathy and micro-adaptive nephropathy were collected as the control group. Immunohistochemical staining was performed on the collected renal biopsy samples, and the average optical density was calculated by semi-quantitative analysis of immunohistochemical staining to further verify the expression of the key genes screened by the bioinformatics analysis. Pearson linear correlation analysis was performed between the average optical density results and the clinical inflammatory data of patients. Results 846 differential genes were screened, of which 444 genes were significantly up-regulated and 402 genes were significantly down-regulated. Through KEGG and GO analysis, important differentially expressed genes related to inflammation regulation were obtained. Among them, CSF1R and TNFRSF1B, two differentially expressed genes never reported in ANCA-associated vasculitis, attracted our attention. At the same time, we constructed multiple ceRNA regulatory axes including KCNQ1OT1-hsa-miR-125a-5p-TNFRSF1B. There were 15 samples of ANCA-associated vasculitis, 6 samples of IgA nephropathy, and 3 samples of micropathological kidney. Immunohistochemical results of renal biopsy specimens showed that the expression of CSF1R and TNFRSF1B in ANCA-associated vasculitis kidney tissue was higher than that in the control group. Pearson correlation analysis of clinical data of patients in ANCA group showed that the expression of CSF1R was positively correlated with the content of neutrophil count(r=0.587), and the expression of TNFRSF1B was positively correlated with the content of serum C-reactive protein(r=0.646). Conclusion Key genes related to inflammatory regulation such as CSF1R and TNFRSF1B were investigated by bioinformatics methods, and a rigorous ceRNA regulatory network was constructed. The expression of CSF1R and TNFRSF1B in ANCA vasculitis was higher than that in the control group through immunohistochemistry. The results provides a scientific theoretical basis for the molecular mechanism of inflammation, and laid a good foundation for new therapeutic targets of ANCA-related vasculitis for inflammation.