Peng Zining, Deng Qian, Huang Yuanbo, Meng Fanyu, Long Yuan, Wei Yuanyuan, Yan Weitian, Zhang Xiaoyu, Peng Jiangyun, Li Zhaofu, Liu Nian
The First School of Clinical Medicine, Yunnan University of Chinese Medicine, Kunming, Yunnan, PR China.
Department of Rheumatology, The No.1 Affiliated Hospital of Yunnan University of Chinese Medicine/Yunnan Provincial Hospital of Traditional Chinese Medicine, Kunming, Yunnan, PR China.
PLoS One. 2025 Jul 11;20(7):e0326168. doi: 10.1371/journal.pone.0326168. eCollection 2025.
This study aims to identify autophagy-related biomarkers in rheumatoid arthritis (RA) synovium, analyze their immune infiltration characteristics, and validate therapeutic potential through multi-level experimental approaches.
We used public datasets to obtain synovial tissue genes of healthy people and RA patients, screened differentially expressed genes (DEGs) of RA, and intersected with the human autophagy gene database (HADb) to obtain RA autophagy genes. GO and KEGG enrichment analysis and single-gene genome enrichment analysis were performed. The diagnostic value of RA core autophagy genes in the validation set was screened and verified. The immune cell correlation analysis of RA autophagy core genes was performed to obtain the correlation between single disease autophagy core genes and immune cells. Finally, we prepared CIA rat models to verify the autophagy protein P62, Beclin-1 and the 11 core genes associated with RA-autophagy.
A total of 1098 RA DEGs were obtained. Intersecting with 222 autophagy genes obtained from the HADb database yielded 27 RA autophagy genes. GO analysis of RA autophagy genes showed 307 biological mechanisms. KEGG enrichment analysis obtained 86 signaling pathways, including FoxO, Necroptosis and other pathways related to RA autophagy. GSEA analysis found that the control group had a higher correlation with adipokine signaling pathways and others. And 11 RA autophagy-related core genes (IFNG, EGFR, MYC, CXCR4, MAPK8, CASP1, TNFSF10, CTSB, FAS, FOXO1, FOXO3) were obtained by screening the PPI network, and there were differences in expression in the training set (P < 0.001). External validation set verification showed diagnostic efficacy. Analysis of immune infiltration in RA autophagy-related genes revealed 14 immune cell types differentially abundant in synovial tissues of RA patients vs. normal controls. Significant correlations exist between autophagy genes and immune subsets. Finally, animal experiments showed that joint autophagy was enhanced (P < 0.001), and the mRNA of 11 RA-autophagy core genes had significant changes (P < 0.001).
We systematically identified 11 autophagy-related core genes as potential therapeutic targets for RA. Our CIA model validation provides preclinical evidence supporting their translational potential. These genes showed significant correlations with 14 synovial immune cell subtypes, may serve as novel therapeutic targets by modulating immune infiltration and inflammatory pathways. Future investigations should focus on elucidating the mechanistic basis of the observed gene-immune cell interactions in both autophagic and immune pathways to facilitate the development of precision therapies.
本研究旨在鉴定类风湿关节炎(RA)滑膜中自噬相关生物标志物,分析其免疫浸润特征,并通过多层次实验方法验证其治疗潜力。
我们使用公共数据集获取健康人和RA患者的滑膜组织基因,筛选RA的差异表达基因(DEG),并与人类自噬基因数据库(HADb)进行交叉分析以获得RA自噬基因。进行了基因本体(GO)和京都基因与基因组百科全书(KEGG)富集分析以及单基因基因组富集分析。筛选并验证了RA核心自噬基因在验证集中的诊断价值。对RA自噬核心基因进行免疫细胞相关性分析,以获得单个疾病自噬核心基因与免疫细胞之间的相关性。最后,我们制备了胶原诱导性关节炎(CIA)大鼠模型,以验证自噬蛋白P62、Beclin-1以及与RA自噬相关的11个核心基因。
共获得1098个RA差异表达基因。与从HADb数据库获得的222个自噬基因进行交叉分析,得到27个RA自噬基因。对RA自噬基因的GO分析显示有307种生物学机制。KEGG富集分析获得86条信号通路,包括与RA自噬相关的FoxO、坏死性凋亡等通路。基因集富集分析(GSEA)发现对照组与脂肪因子信号通路等的相关性更高。通过筛选蛋白质-蛋白质相互作用(PPI)网络获得了11个与RA自噬相关的核心基因(IFNG、EGFR、MYC、CXCR4、MAPK8、CASP1、TNFSF10、CTSB、FAS、FOXO1、FOXO3),且在训练集中其表达存在差异(P < 0.001)。外部验证集验证显示了诊断效能。对RA自噬相关基因的免疫浸润分析揭示,与正常对照组相比,RA患者滑膜组织中有14种免疫细胞类型的丰度存在差异。自噬基因与免疫亚群之间存在显著相关性。最后,动物实验表明关节自噬增强(P < 0.001),11个RA自噬核心基因的mRNA有显著变化(P < 0.001)。
我们系统地鉴定了11个自噬相关核心基因作为RA的潜在治疗靶点。我们的CIA模型验证提供了支持其转化潜力的临床前证据。这些基因与14种滑膜免疫细胞亚型显示出显著相关性,可能通过调节免疫浸润和炎症途径作为新的治疗靶点。未来的研究应专注于阐明在自噬和免疫途径中观察到的基因-免疫细胞相互作用的机制基础,以促进精准治疗的发展。