Systemic lupus erythematosus (SLE) is a persistent autoimmune disorder that can culminate in lupus nephritis (LN), an intricate renal complication. In pursuit of unraveling the intricate molecular underpinnings governing LN progression, we conducted bioinformatics analysis employing gene expression data sourced from the GSE32591 dataset. Our scrutiny revealed a panoply of differentially expressed genes (DEGs) within the glomerulus and tubulointerstitial compartments of LN patients. Enrichment analysis for DEGs engaged in diverse processes, encompassing virus defense, viral life cycle, cell adhesion molecules, and the NOD-like receptor signaling pathway. Notably, STAT1 emerged as an eminent central hub gene intrinsically tied to NOD-like receptor signaling. To explore the functional significance of STAT1 in the context of LN, MRL-lpr mice model was used to knockout STAT1. The results unveiled that STAT1 silencing yielded a migratory effect on kidney injury, concurrently curbing inflammatory markers. Meanwhile, knockout STAT1 also reduced NLRP3 expression and Cleaved caspase-1 expression. These findings offer tantalizing prospects for targeting STAT1 as a potential therapeutic conduit in the management of LN.
Keyphrases
- systemic lupus erythematosus
- cell proliferation
- gene expression
- bioinformatics analysis
- signaling pathway
- poor prognosis
- cell adhesion
- binding protein
- end stage renal disease
- sars cov
- cell death
- genome wide
- dna methylation
- electronic health record
- long non coding rna
- epithelial mesenchymal transition
- adipose tissue
- disease activity
- rheumatoid arthritis
- nlrp inflammasome
- cancer therapy
- wild type
- machine learning
- genome wide identification
- single molecule
- deep learning
- endoplasmic reticulum stress