PDF(Pubmed)
Abstract：
The pathogenesis of ankylosing spondylitis (AS) remains unclear, and while recent studies have implicated necroptosis in various autoimmune diseases, an investigation of its relationship with AS has not been reported. In this study, we utilized the Gene Expression Omnibus database to compare gene expressions between AS patients and healthy controls, identifying 18 differentially expressed necroptosis-related genes (DENRGs), with 8 upregulated and 10 downregulated. Through the application of three machine learning algorithms-least absolute shrinkage and selection operation, support vector machine-recursive feature elimination and random forest-two hub genes, FASLG and TARDBP, were pinpointed. These genes demonstrated high specificity and sensitivity for AS diagnosis, as evidenced by receiver operating characteristic curve analysis. These findings were further supported by external datasets and cellular experiments, which confirmed the downregulation of FASLG and upregulation of TARDBP in AS patients. Immune cell infiltration analysis suggested that CD4+ T cells, CD8+ T cells, NK cells and neutrophils may be associated with the development of AS. Notably, in the group with high FASLG expression, there was a significant infiltration of CD8+ T cells, memory-activated CD4+ T cells and resting NK cells, with relatively less infiltration of memory-resting CD4+ T cells and neutrophils. Conversely, in the group with high TARDBP expression, there was enhanced infiltration of naïve CD4+ T cells and M0 macrophages, with a reduced presence of memory-resting CD4+ T cells. In summary, FASLG and TARDBP may contribute to AS pathogenesis by regulating the immune microenvironment and immune-related signalling pathways. These findings offer new insights into the molecular mechanisms of AS and suggest potential new targets for therapeutic strategies.
摘要：
强直性脊柱炎（AS）的发病机制尚不清楚，虽然最近的研究表明坏死与各种自身免疫性疾病有关，尚未报道其与AS关系的调查。在这项研究中,我们利用基因表达综合数据库来比较AS患者和健康对照之间的基因表达，鉴定18个差异表达的坏死相关基因（DENRGs），其中8个上调，10个下调。通过应用三种机器学习算法-最小绝对收缩和选择操作，支持向量机-递归特征消除和随机森林-两个中心基因，FASLG和TARDBP,被精确定位。这些基因对AS诊断表现出高特异性和敏感性，接收器工作特性曲线分析证明了这一点。这些发现得到了外部数据集和细胞实验的进一步支持，这证实了AS患者FASLG的下调和TARDBP的上调。免疫细胞浸润分析提示CD4+T细胞,CD8+T细胞，NK细胞和中性粒细胞可能与AS的发生发展有关。值得注意的是,在FASLG高表达组中，有明显的CD8+T细胞浸润，记忆激活的CD4+T细胞和静息NK细胞，记忆静息CD4+T细胞和中性粒细胞浸润相对较少。相反，在TARDBP高表达组中，原始CD4+T细胞和M0巨噬细胞的浸润增强，记忆静息CD4+T细胞的存在减少。总之,FASLG和TARDBP可能通过调节免疫微环境和免疫相关信号通路来促进AS发病。这些发现为AS的分子机制提供了新的见解，并为治疗策略提供了潜在的新靶标。
