Identification of key necroptosis-related genes and immune landscape in patients with immunoglobulin A nephropathy.

BACKGROUND

Immunoglobulin A nephropathy (IgAN) is a major cause of chronic kidney disease (CKD) and kidney failure. Necroptosis is a novel type of programmed cell death that has been proved to be associated with the pathogenesis of infectious disease, cardiovascular disease, neurological disorders and so on. However, the role of necroptosis in IgAN remains unclear.

METHODS

In this study, we explored the role of necroptosis-related genes in the pathogenesis of IgAN using a comprehensive bioinformatics method. Microarray datasets GSE93798 and GSE115857 were downloaded from Gene Expression Omnibus (GEO). "limma" package of R software was employed to identify necroptosis-related differentially expressed genes (NRDEGs) between IgAN and healthy controls. GO and KEGG functional enrichment analysis was performed by Clusterprofiler. Least absolute shrinkage and selection operator (LASSO) regression analysis identified hub NRDEGs. We further established a diagnostic model consisting of 7 diagnostic hub NRDEGs and validated the efficacy by an external dataset. The expression of hub genes was confirmed in sc-RNA dataset GSE171314. Immune infiltration, gene set enrichment analysis and transcription factor binding motifs enrichment analysis were conducted to further uncover their roles.

RESULTS

1076 differentially expressed genes were identified between healthy individuals and IgAN patients from RNA-seq dataset GSE9379. Then we cross-linked them with necroptosis-related genes to obtain 9 NRDEGs. LASSO regression analysis screened out 7 hub genes (JUN, CD274, SERTAD1, NFKBIA, H19, UCHL1 and EZH2) of IgAN. We further conducted functional enrichment analysis and constructed the diagnostic model based on dataset GSE93798. GSE115857 was used as the independent validation cohort and indicated a great predictive efficacy. Immune infiltration, gene set enrichment analysis and transcription factor binding motifs enrichment analysis revealed their potential function. Finally, we screened out four drugs that were predicted to have therapeutic value of IgAN.

CONCLUSIONS

In summary, we identified 7 hub necroptosis-associated genes, which can be used as potential genetic biomarkers for IgAN prediction and treatment. Four drugs were predicted as the potential therapeutic solutions. Collectively, we provided insights into the necroptosis-related mechanisms and treatment of IgAN at the transcriptome level.