Ao You, Lan Qing, Yu Tianhua, Wang Zhichao, Zhang Jing
Department of Orthopaedics, The Fifth Hospital of Harbin, Harbin, Heilongjiang, P. R. China.
PLoS One. 2025 Jan 16;20(1):e0317364. doi: 10.1371/journal.pone.0317364. eCollection 2025.
Rheumatoid arthritis (RA), a long-term autoinflammatory condition causing joint damage and deformities, involves a multifaceted pathogenesis with genetic, epigenetic, and immune factors, including early immune aging. However, its precise cause remains elusive. Cellular senescence, a hallmark of aging marked by a permanent halt in cell division due to damage and stress, is crucial in aging and related diseases. In our study, we analyzed RA microarray data from the Gene Expression Omnibus (GEO) and focused on cellular senescence genes from the CellAge database. We started by selecting five RA datasets from GEO. Next, we pinpointed 29 differentially expressed genes (DEGs) linked to cellular senescence in RA, aligning them with genes from CellAge. We explored the roles of these DEGs in cellular senescence through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. We then pinpointed three key genes (DHX9, CYR61, and ITGB) using random forest and LASSO Cox regression machine learning techniques. An integrated diagnostic model was created using these genes. We also examined the variance in immune cell infiltration and immune checkpoint gene expression between RA and normal samples. Our methodology's predictive accuracy was confirmed in external validation cohorts. Subsequently, RA samples were classified into three distinct subgroups based on the cellular senescence-associated DEGs, and we compared their immune landscapes. Our findings reveal a significant impact of cellular senescence-related DEGs on immune cell infiltration in RA samples. Hence, a deeper understanding of cellular senescence in RA could offer new perspectives for diagnosis and treatment.
类风湿性关节炎（RA）是一种导致关节损伤和畸形的长期自身炎症性疾病，其发病机制涉及遗传、表观遗传和免疫等多方面因素，包括早期免疫衰老。然而，其确切病因仍不明确。细胞衰老，是衰老的一个标志，其特征是由于损伤和应激导致细胞分裂永久停止，在衰老及相关疾病中至关重要。在我们的研究中，我们分析了来自基因表达综合数据库（GEO）的RA微阵列数据，并聚焦于来自CellAge数据库的细胞衰老基因。我们首先从GEO中选择了五个RA数据集。接下来，我们确定了29个与RA中细胞衰老相关的差异表达基因（DEG），并将它们与CellAge中的基因进行比对。我们通过基因本体论（GO）和京都基因与基因组百科全书（KEGG）通路分析，探讨了这些DEG在细胞衰老中的作用。然后，我们使用随机森林和LASSO Cox回归机器学习技术确定了三个关键基因（DHX9、CYR61和ITGB）。利用这些基因创建了一个综合诊断模型。我们还研究了RA样本与正常样本之间免疫细胞浸润和免疫检查点基因表达的差异。我们方法的预测准确性在外部验证队列中得到了证实。随后，根据与细胞衰老相关的DEG将RA样本分为三个不同的亚组，并比较了它们的免疫图谱。我们的研究结果揭示了与细胞衰老相关的DEG对RA样本中免疫细胞浸润有显著影响。因此，深入了解RA中的细胞衰老可为诊断和治疗提供新的视角。
