Identification of immune related cells and crucial genes in the peripheral blood of ankylosing spondylitis by integrated bioinformatics analysis

Abstract

Background Ankylosing spondylitis (AS) is a progressive rheumatic disease and studies reveal that the immune system is critical for the pathogenesis of AS. In the present study, various bioinformatics analysis methods were comprehensively applied, designed to identify potential key genes and inflammation states of AS. Methods The transcriptome profiles of GSE25101 and GSE73754 obtained from the Gene Expression Omnibus (GEO) database were merged for subsequent analyses. The differentially expressed genes (DEGs) were identified using the Bioconductor package Limma and threshold values. Functional enrichment and pathway enrichment analyses were performed using the clusterProfiler package and Gene Set Enrichment Analysis (GSEA). Next, protein–protein interaction (PPI) network of the identified DEGs was constructed by the online database, the Search Tool for the Retrieval of Interacting Genes (STRING), visualization and analysis were performed through Cytoscape software. Subsequently, we applied CIBERSORT algorithm to identify subpopulation proportions of immune cells in peripheral blood samples. Finally, we validated the hub genes with the GSE18781 dataset. Samples were collected from patients to validate gene and protein expression using qRT-PCR and ELISA. Results A total of 334 DEGs were identified, including 182 upregulated and 152 downregulated DEGs, between AS patients and normal human controls, which were primarily involved in immune response, autophagy, and natural killer cell-mediated cytotoxicity. The most prominent module and candidate biomarkers were identified from the PPI network. Biomarkers were selected for validation and their expressions were significantly decreased in peripheral blood samples which was consistent with transcriptome sequencing results. Nine genes with AUC > 0.70 were considered to be AS hub genes for ROC curve analysis, including GZMA, GZMK, PRF1, GNLY, NKG7, KLRB1, KLRD1, IL2RB and CD247. Furthermore, CIBERSORT results suggest that AS contained a higher proportion of CD8+ T cells, naive CD4+ T cells, neutrophils, and lower levels of gamma delta T cells compared with the normal controls. Conclusion In this study, we identified DEGs combined with their closely related biological functions and propose that granule-associated proteins and immune infiltration maybe involved in the progression of ankylosing spondylitis. These validated hub genes may provide new perspectives for understanding the molecular mechanisms of ankylosing spondylitis.

Novel peripheral blood diagnostic biomarkers screened by machine learning algorithms in ankylosing spondylitis

“…In this study, IL2RB and ZDHHC18 were the two finally screened hub genes. The former had already been identified by other researchers as one of the hub genes in AS (Zhu et al, 2013;Zheng et al, 2021), while to the best of our knowledge, the latter was first reported here by us. IL2RB, interleukin 2 receptor subunit beta, encoded the beta subunit of a heterodimer or heterotrimer receptor involved in T cell-mediated immune responses and is probably involved in the stimulation of neutrophil phagocytosis by IL15 (Ratthé and Girard, 2004; Frontiers in Genetics frontiersin.org Zhang et al, 2019).…”

Diagnostic Biomarkers Screened by Machine Learning Algorithms in Ankylosing Spondilytis

“…In this study, IL2RB and ZDHHC18 were the two final screened hubgenes. The former had already been reported by other researchers to be one of the hubgenes in AS [30,31], while the latter was first reported here by us.…”

Advances in CD247

“…CD247 is commonly defectively expressed in autoimmune diseases compared with healthy individuals, and its specific role and mechanisms are less studied compared with SLE (Table 1). The expression of CD247 in rheumatoid arthritis (RA), 70 paediatric primary nephrotic syndrome, 71 systemic sclerosis (SSc), 72 juvenile idiopathic arthritis, 73 osteoarthritis 74 and ankylosing spondylitis 75 patients is decreased compared with healthy people 76 and increased in patients with type 1 diabetes mellitus (T1DM) 77 . CD247 was downregulated in peripheral blood mononuclear cells, T cell subsets in synovial fluid and NK cells in RA patients, and CD247 mRNA expression levels were significantly lower in a highly active group compared to inactive RA patients 68 .…”