Background and objectives: Behçet’s disease (BD) is a chronic inflammatory disease characterized by recurrent mucocutaneous ulceration and other complications such as blindness and large vessel inflammation. Immunosenescence, aging of immune system, is related to increased susceptibility to infectious diseases, vaccine failure, and chronic low grade systemic inflammation. Our previous study showed increased frequency of senescent CD8+ T cells in the peripheral blood of patients with BD. In this study, to find the global genet-expression characteristics of senescent CD8+ T cells in relation with BD, we examined the transcriptome of CD8+ T lymphocyte subsets (CD27-CD28- senescent and CD27+CD28+ nonsenescent) from BD patients and healthy control (HC) subjects.
Material and methods: Peripheral blood mononuclear cells (PBMCs) were collected from BD patients (n=18) and HCs (n=18). CD8+ T cells were isolated through CD8 microbeads, and those were labelled with conjugated monoclonal antibodies as follows: FITC anti-CD8, allophycocyanin (APC)-H7 anti-CD27 and APC anti-CD28. Using fluorescence-activated cell sorting (FACS), senescent CD8+ T cells (CD8+CD27-CD28-) and non-senescent CD8+ T cells (CD8+CD27+CD28+) were sorted. After sorting, each group of cells were pooled together and cultured in medium (RPMI 1640). Cells were stimulated with anti-CD3 (500ng/ml, clone OKT3) for 72 hours. Total RNA was extracted from anti-CD3-stimulated cells with the RNA isolation kit. Transcriptome analysis was performed. We analyzed the differentially expressed genes from the four different groups (BD patients vs. controls, senescent CD8+ T cells (CD8+ CD27- CD28-) vs. non-senescent CD8+ T cells (CD8+ CD27+ CD28+)). Differentially expressed genes were submitted to Ingenuity Pathway Analysis (IPA) for functional evaluation and identification of significant biological pathways. For the validation of genes that show large fold change value in transcriptome sequencing, additional five BD patients and five HCs were enrolled to collect RNA and perform the real-time PCR on eight genes.
Results: Differentially expressed 1103 genes were identified in BD CD27-CD28- subsets compared to HC, while 652 genes were differentially expressed in BD CD27+CD28+ subsets compared to HC. As a result of the real-time PCR, COL5A1, ARHGEF10 showed the same tendency with the transcriptome analysis in the BD CD27-CD28- subsets compared to HCs, among which the statistical significance was shown in COL5A1. Meanwhile, TRPV3, ARHGEF10, UBE2F-SCLY, CD302, and SHANK1 showed the same tendency with the transcriptome analysis in the BD CD27+CD28+ subsets compared to HCs, and the statistical significance was found in TRPV3 and ARHGEF10. Of the significant canonical pathways identified in IPA, 11 pathways showed activity in the opposite direction between CD27+CD28+ and CD27-CD28- subsets, while two pathways tended to be same. The most significant canonical pathway resulted from the IPA was the cAMP-mediated signaling.
Conclusion: This is the first study for transcriptome analysis of CD8+ T cells of BD patients compared to HCs. This study was also the first to separate senescent CD8+ T cells and non-senescent CD8+ T cells to perform RNA sequencing, respectively. Transcriptome analysis found differentially expressed genes in patients with BD. And IPA suggested the pathways in which these differences in gene expression may be involved in the pathogenesis of BD. Using these differentially expressed genes may be useful for developing biomarkers in BD that can predict the treatment response as well as help diagnosing easily. Consequently, we hope that this genetic profiling can be used as a key for approaching the pathogenesis of BD.