RAB5C, SYNJ1, and RNF19B promote male ankylosing spondylitis by regulating immune cell infiltration

Abstract

Background: This study aimed to identify the key genes related to male ankylosing spondylitis (AS) and to analyze the role of immune cell infiltration in the pathological process of this disease. Methods:The AS dataset was downloaded from the Gene Expression Omnibus (GEO) public database, and the data of male healthy controls (M_HC) and male AS patients (M_AS) were extracted. R software was used to identify differentially expressed genes (DEGs). Functional and pathway enrichment analysis of the DEGs was performed. A protein-protein interaction (PPI) network was constructed, and the hub genes were screened out. All expression profile data were analyzed by weighted correlation network analysis (WGCNA) to screen out the hub genes, which were then intersected with the hub genes from the PPI network to obtain the key genes. Finally, the difference in immune cell infiltration in the two sets of samples was evaluated with CIBERSORT, and the correlation between the key genes and infiltrating immune cells was analyzed.Results: A total of 689 DEGs were obtained, of which 395 genes were up-regulated and 294 genes were down-regulated. Functional and pathway enrichment analysis showed that DEGs were mainly enriched in pathways related to immune response. Based on the PPI analysis, five clusters with high scores were selected.Through WGCNA, 14 gene modules were obtained. The green module with the highest correlation was selected and intersected with the cluster previously obtained to obtain three key genes, RAB5C, SYNJ1, and RNF19B. Immune infiltration analysis found that monocytes and gamma delta T cells may be involved in the process of AS. Also, RAB5C, SYNJ1, and RNF19B are all related to increased levels of monocytes and macrophages.Conclusions: RAB5C, SYNJ1, and RNF19B are key DEGs expressed in M_AS and may play a role in the disease's occurrence and development through regulating immune cell functions.

Differentially expressed protein‐coding genes in ankylosing spondylitis: Emerging insights into pathogenesis and therapeutic approaches

“…A substantial difference in expression of these two genes between AS patients and healthy control individuals and a significant positive connection between them and the neutrophil count were observed 128 . In addition, Zhang et al recently identified key DEPGs expressed in male AS patients including RAB5C, SYNJ1, and RNF19B, which may influence the development and occurrence of AS through influencing activities of immune cells like monocytes and macrophages 129 . MAPK7 and NUDFS4 were two significant contributors in the control of inflammatory response via the TGF‐β pathway through the cAMP‐mediated signaling pathway, and they may be potential target genes for indomethacin 126 .…”

New Insights into the Regulatory Role of Ferroptosis in Ankylosing Spondylitis via Consensus Clustering of Ferroptosis-Related Genes and Weighted Gene Co-Expression Network Analysis

“…Previous bioinformatics studies have provided data supporting our hypothesis. Zhang et al compared gene expression profiles between male AS patients ( n = 27) and matched healthy controls ( n = 10) in GSE73754, and identified that key genes in AS pathogenesis also regulated immune-cell functions [ 59 ]. That study also showed that the ferroptosis pathway is a significantly enriched term through a gene set enrichment analysis of KEGG pathways.…”

“…Epidemiological studies have reported hazard ratios ranging from 1.75 to 1.82 ( p < 0.001) for the development of Parkinson’s disease (PD) and parkinsonism in AS population [ 78 , 79 ]. Mitochondrial dysfunctions, particularly abnormal oxidative phosphorylation, and epithelial barrier disruption in the gut may be the mechanisms underlying the clinical association between AS and PD [ 59 , 80 , 81 ]. In addition, complex interactions between the ubiquitin-proteasome system and cellular degradation, which participate in autophagy-dependent ferroptosis and progression of AS, may be another possible link between ferroptosis and AS [ 82 , 83 , 84 , 85 ].…”

Identification of module genes and functional pathway analysis in septic shock subtypes by integrated bioinformatics analysis

“…WGCNA analysis is a systematic biological method used to describe the expression association patterns of different genes in samples 18 . It aggregates genes with highly correlated expression into different modules to explore the association between different modules and sample phenotypes 19 .…”

“…WGCNA analysis is a systematic biological method used to describe the expression association patterns of different genes in samples. 18 It aggregates genes with highly correlated expression into different modules to explore the association between different modules and sample phenotypes. 19 By referring to R packages such as limma and WGCNA, 20 we first input the corrected total gene expression matrix, SDEGs list and clinical data into R software, sorted out and extracted the relative expression of SDEGs in each sample, and clustered all SDEGs and samples by hierarchical clustering method based on Pearson correlation.…”