Wang Yun, Chen Jun, Shen Zheng-Yu, Zhang Jie, Zhu Yu-Jie, Xia Xu-Qiong
Department of Dermatology, Shanghai Ninth People's Hospital Affiliated Shanghai JiaoTong University School of Medicine, Shanghai, 200080, People's Republic of China.
The International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, People's Republic of China.
J Inflamm Res. 2024 Aug 1;17:5177-5195. doi: 10.2147/JIR.S467760. eCollection 2024.
Both rheumatoid arthritis (RA) and rosacea represent common chronic systemic autoimmune conditions. Recent research indicates a heightened RA risk among individuals with rosacea. However, the molecular mechanisms linking these diseases remain largely unknown. This study aims to uncover shared molecular regulatory networks and immune cell infiltration patterns in both rosacea and RA.
The gene expression profiles of RA (GSE12021, GSE55457), and the rosacea gene expression profile (GSE6591), were downloaded from Gene Expression Omnibus (GEO) databases, and obtained to screen differentially expressed genes (DEGs) by using "limma" package in R software. Various analyses including GO, KEGG, protein-protein interaction (PPI) network, and weighted gene co-expression network analyses (WGCNA) were conducted to explore potential biological functions and signaling pathways. CIBERSORT was used to assess the abundance of immune cells. Pearson coefficients were used to calculate the correlations between overlapped genes and the leukocyte gene signature matrix. Flow cytometry (FCM) analysis confirmed the most abundant immune cells detected in rheumatoid arthritis and rosacea. Receiver operator characteristic (ROC) analysis, enzyme-linked immunosorbent assay (ELISA), and qRT-PCR were used to confirm biomarkers and functions.
Two hundred seventy-seven co-expressed DEGs were identified from these datasets. Functional enrichment analysis indicated that these DEGs were associated with immune processes and chemokine-mediated signaling pathways. Fourteen and 17 hub genes overlapped between cytoHubba and WGCNA were identified in RA and rosacea, respectively. Macrophages and dendritic cells were RA and rosacea's most abundant immune cells, respectively. The ROC curves demonstrated potential diagnostic values of CXCL10 and CCL27, showing higher levels in the serum of patients with RA or rosacea, and suggesting possible regulation in the densities and functions of macrophages and dendritic cells from RA and rosacea, which were validated by FCM and qRT-PCR.
Importantly, our findings may contribute to the scientific basis for biomarkers and therapeutic targets for patients with RA and rosacea in the future.
类风湿性关节炎（RA）和酒渣鼻均为常见的慢性全身性自身免疫性疾病。近期研究表明，酒渣鼻患者患RA的风险增加。然而，连接这些疾病的分子机制在很大程度上仍不清楚。本研究旨在揭示酒渣鼻和RA中共同的分子调控网络和免疫细胞浸润模式。
从基因表达综合数据库（GEO）下载RA（GSE12021、GSE55457）和酒渣鼻基因表达谱（GSE6591），并使用R软件中的“limma”包筛选差异表达基因（DEG）。进行了包括基因本体论（GO）、京都基因与基因组百科全书（KEGG）、蛋白质-蛋白质相互作用（PPI）网络和加权基因共表达网络分析（WGCNA）等各种分析，以探索潜在的生物学功能和信号通路。使用CIBERSORT评估免疫细胞的丰度。采用皮尔逊系数计算重叠基因与白细胞基因特征矩阵之间的相关性。流式细胞术（FCM）分析证实了在类风湿性关节炎和酒渣鼻中检测到的最丰富的免疫细胞。采用受试者工作特征（ROC）分析、酶联免疫吸附测定（ELISA）和定量逆转录-聚合酶链反应（qRT-PCR）来确认生物标志物和功能。
从这些数据集中鉴定出277个共表达的DEG。功能富集分析表明，这些DEG与免疫过程和趋化因子介导的信号通路相关。在RA和酒渣鼻中，分别在CytoHubba和WGCNA之间鉴定出14个和17个枢纽基因。巨噬细胞和树突状细胞分别是RA和酒渣鼻中最丰富的免疫细胞。ROC曲线显示CXCL10和CCL27具有潜在的诊断价值，在RA或酒渣鼻患者血清中水平较高，提示可能对RA和酒渣鼻的巨噬细胞和树突状细胞的密度和功能有调节作用，这通过FCM和qRT-PCR得到验证。
重要的是，我们的研究结果可能为未来RA和酒渣鼻患者的生物标志物和治疗靶点提供科学依据。
