RESULTS: Weighted gene co-expression network analysis (WGCNA) analysis identified 2 RA-positive related modules and 4 idiopathic pulmonary fibrosis (IPF)-positive related modules. A total of 553 overlapped differentially expressed genes (DEG) were obtained, of which 144 in the above modules were further analyzed. The biological process of \"oxidative phosphorylation\" was found to be the most relevant with both RA and IPF. Additionally, 498 up-regulated genes in lung tissues of RA-UIP were screened out and enriched by 7 clusters, of which 3 were closely related to immune regulation. The analysis of immune infiltration showed a characteristic distribution of peripheral immune cells in RA-UIP, compared with IPF-UIP in lung tissues.
CONCLUSIONS: These results describe the complex molecular and functional landscape of RA-UIP, which will help illustrate the molecular pathological mechanism of RA-UIP and identify new biomarkers and therapeutic targets for RA-UIP in the future.
结果:加权基因共表达网络分析(WGCNA)分析确定了2个RA阳性相关模块和4个特发性肺纤维化(IPF)阳性相关模块。共获得553个重叠的差异表达基因(DEG),其中以上模块中的144个进行了进一步分析。发现“氧化磷酸化”的生物学过程与RA和IPF最相关。此外,在RA-UIP的肺组织中筛选出498个上调基因,并富集7个簇,其中3个与免疫调节密切相关。免疫浸润分析显示外周免疫细胞在RA-UIP中呈特征性分布,与肺组织中的IPF-UIP相比。
结论:这些结果描述了RA-UIP的复杂分子和功能景观,这将有助于阐明RA-UIP的分子病理机制,并确定未来RA-UIP的新生物标志物和治疗靶标。