The shared role of neutrophils in ankylosing spondylitis and ulcerative colitis.
Tianyou ChenWeiming TanXinli ZhanChenxing ZhouJichong ZhuShaofeng WuBoli QinRongqing HeXiaopeng QinWendi WeiChengqian HuangBin ZhangSitan FengChong LiuPublished in: Genes and immunity (2024)
This study aimed to analyze single-cell sequencing data to investigate immune cell interactions in ankylosing spondylitis (AS) and ulcerative colitis (UC). Vertebral bone marrow blood was collected from three AS patients for 10X single-cell sequencing. Analysis of single-cell data revealed distinct cell types in AS and UC patients. Cells significantly co-expressing immune cells (P < 0.05) were subjected to communication analysis. Overlapping genes of these co-expressing immune cells were subjected to GO and KEGG analyses. Key genes were identified using STRING and Cytoscape to assess their correlation with immune cell expression. The results showed the significance of neutrophils in both diseases (P < 0.01), with notable interactions identified through communication analysis. XBP1 emerged as a Hub gene for both diseases, with AUC values of 0.760 for AS and 0.933 for UC. Immunohistochemistry verified that the expression of XBP1 was significantly lower in the AS group and significantly greater in the UC group than in the control group (P < 0.01). This finding highlights the critical role of neutrophils in both AS and UC, suggesting the presence of shared immune response elements. The identification of XBP1 as a potential therapeutic target offers promising intervention avenues for both diseases.
Keyphrases
- single cell
- ankylosing spondylitis
- rna seq
- end stage renal disease
- ulcerative colitis
- bone marrow
- immune response
- high throughput
- rheumatoid arthritis
- poor prognosis
- chronic kidney disease
- randomized controlled trial
- prognostic factors
- peritoneal dialysis
- big data
- bioinformatics analysis
- patient reported outcomes
- dna methylation
- disease activity
- cell death
- signaling pathway
- risk assessment
- copy number
- genome wide identification
- long non coding rna
- artificial intelligence
- endoplasmic reticulum stress