Data_Sheet_1_Identification of the shared mechanisms and common biomarkers between Sjögren’s syndrome and atherosclerosis using integrated bioinformatics analysis.docx

BackgroundSjögren’s syndrome (SS) is a chronic autoimmune disease characterized by exocrine and extra-glandular symptoms. The literature indicates that SS is an independent risk factor for atherosclerosis (AS); however, its pathophysiological mechanism remains undetermined. This investigation aimed to elucidate the crosstalk genes and pathways influencing the pathophysiology of SS and AS via bioinformatic analysis of microarray data.
MethodsMicroarray datasets of SS (GSE40611) and AS (GSE28829) were retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were acquired using R software’s “limma” packages, and the functions of common DEGs were determined using Gene Ontology and Kyoto Encyclopedia analyses. The protein–protein interaction (PPI) was established using the STRING database. The hub genes were assessed via cytoHubba plug-in and validated by external validation datasets (GSE84844 for SS; GSE43292 for AS). Gene set enrichment analysis (GSEA) and immune infiltration of hub genes were also conducted.
ResultsEight 8 hub genes were identified using the intersection of four topological algorithms in the PPI network. Four genes (CTSS, IRF8, CYBB, and PTPRC) were then verified as important cross-talk genes between AS and SS with an area under the curve (AUC) ≥0.7. Furthermore, the immune infiltration analysis revealed that lymphocytes and macrophages are essentially linked with the pathogenesis of AS and SS. Moreover, the shared genes were enriched in multiple metabolisms and autoimmune disease-related pathways, as evidenced by GSEA analyses.
ConclusionThis is the first study to explore the common mechanism between SS and AS. Four key genes, including CTSS, CYBB, IRF8, and PTPRC, were associated with the pathogenesis of SS and AS. These hub genes and their correlation with immune cells could be a potential diagnostic and therapeutic target.

背景 干燥综合征（Sjögren’s syndrome, SS）是一种以外分泌腺和腺体外症状为特征的慢性自身免疫性疾病。现有文献表明，干燥综合征是动脉粥样硬化（atherosclerosis, AS）的独立危险因素，但其病理生理机制尚未明确。本研究旨在通过对微阵列数据的生物信息学分析，阐明影响干燥综合征与动脉粥样硬化病理生理过程的串扰基因及通路。
方法 从基因表达综合数据库（Gene Expression Omnibus, GEO）中检索干燥综合征的微阵列数据集GSE40611与动脉粥样硬化的微阵列数据集GSE28829。使用R软件的"limma"包获取差异表达基因（differentially expressed genes, DEGs），通过基因本体（Gene Ontology, GO）富集分析与京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes, KEGG）富集分析，确定共同差异表达基因的功能。使用STRING数据库构建蛋白质-蛋白质相互作用（protein-protein interaction, PPI）网络。通过cytoHubba插件筛选核心基因，并采用外部验证数据集进行验证：干燥综合征的验证数据集为GSE84844，动脉粥样硬化的验证数据集为GSE43292。此外，本研究还开展了核心基因的基因集富集分析（Gene Set Enrichment Analysis, GSEA）以及免疫浸润分析。
结果 通过PPI网络中的4种拓扑算法取交集，共鉴定出8个核心基因。其中4个基因（CTSS、IRF8、CYBB及PTPRC）经验证被确定为干燥综合征与动脉粥样硬化之间的重要串扰基因，其曲线下面积（area under the curve, AUC）≥0.7。进一步的免疫浸润分析显示，淋巴细胞与巨噬细胞与动脉粥样硬化及干燥综合征的发病机制密切相关。基因集富集分析结果表明，共享差异表达基因富集于多种代谢过程及自身免疫性疾病相关通路。
结论 本研究是首个探索干燥综合征与动脉粥样硬化共同发病机制的研究。鉴定出CTSS、CYBB、IRF8及PTPRC这4个关键基因与干燥综合征及动脉粥样硬化的发病机制相关。这些核心基因及其与免疫细胞的关联有望成为潜在的诊断与治疗靶点。