摘要
背景:类风湿关节炎与克罗恩病是常见的自身免疫性疾病,临床研究发现这两种疾病可伴发,可能存在相关性,但目前尚无研究证明两者之间存在共同发病基因和免疫机制。目的:通过生物信息学及两种机器学习鉴定类风湿关节炎与克罗恩病共同基因和免疫机制之间的关联。方法:从GEO数据库(由美国国立医学图书馆开发的开放数据库)中检索获得类风湿关节炎与克罗恩病对应的训练数据集和验证集(研究已获得相关机构审查委员会批准),并进行统一整理,使用“limma”包分析类风湿关节炎、克罗恩病的差异表达基因。分别在类风湿关节炎与克罗恩病的训练集上应用加权基因共表达网络分析识别疾病相关模块,取交集初步筛选基因集,同时进行GO、KEGG分析。通过蛋白质互作网络及MCODE算法识别出20个基因集,分别在类风湿关节炎与克罗恩病的训练集上应用LASSO回归和随机森林两种机器学习算法独立筛选各自疾病的关键特征基因。取类风湿关节炎与克罗恩病筛选结果交集,获得共有的潜在关键基因,通过验证集验证准确度确定核心基因。对核心基因与浸润免疫细胞进行CIBERSORT免疫浸润等功能分析,确定核心基因与类风湿关节炎、克罗恩病的相关性。结果与结论:类风湿关节炎有2516个差异基因,克罗恩病有281个差异基因。通WGCNA、蛋白互作网络和2种机器学习算法取交集后得到3个核心基因,半胱天冬酶1(CASP1)、三联基序21(TRIM21)及蛋白酶体亚基10(PSMB10)。富集分析显示两种疾病与抗原的加工和呈递、内质网膜腔面和多种免疫球蛋白结合相关;3个核心基因在两种疾病验证集的表达趋势与训练集一致。免疫细胞浸润分析显示,巨噬细胞(M0、M1)和中性粒细胞在类风湿关节炎与克罗恩病中的表达均显著增高,说明中性粒细胞可能在类风湿关节炎和克罗恩病发病机制中起重要作用。该研究不仅增进了对两种重要自身免疫病共性的认知,更重要的是为中国研究人员在新靶点的发现与验证、新型诊疗技术的开发以及转化医学研究模式应用等方面提供了宝贵的借鉴意义和具体的指导路径。
BACKGROUND:Rheumatoid arthritis and Crohn’s disease are common autoimmune diseases.Clinical studies have found that these two diseases can coexist and may be related,but there is currently no research to prove that there are common pathogenic genes and immune mechanisms between them.OBJECTIVE:To identify the shared genes and immune mechanisms between rheumatoid arthritis and Crohn’s disease through bioinformatics and two machine learning methods.METHODS:Training and validation datasets for rheumatoid arthritis and Crohn’s disease were retrieved from the GEO database(an open database developed by the United States National Library of Medicine)and uniformly organized.The“limma”package was used to perform differentially expressed genes of rheumatoid arthritis and Crohn’s disease.Weighted gene co-expression network analysis was applied to the training sets of rheumatoid arthritis and Crohn’s disease to identify disease-related modules,and the intersection was taken to preliminarily screen gene sets,while GO and KEGG analyses were conducted.Twenty gene sets were identified through the protein-protein interaction network and MCODE algorithm.Two machine learning algorithms,LASSO regression and random forest,were independently applied to the training sets of rheumatoid arthritis and Crohn’s disease to screen key characteristic genes for each disease.Subsequently,the intersection of the screening results of rheumatoid arthritis and Crohn’s disease was taken to obtain shared potential key genes,and the accuracy was verified through the validation set to determine the core genes.Finally,CIBERSORT immune infiltration and other functional analyses were performed to confirm the correlation between core genes and rheumatoid arthritis as well as Crohn’s disease.RESULTS AND CONCLUSION:A total of 2516 differentially expressed genes were obtained for rheumatoid arthritis,and 281 differentially expressed genes for Crohn’s disease.Following intersection analysis using WGCNA,protein-protein interaction network,and two machine learning algorithms,three core genes were identified:CASP1,TRIM21,and PSMB10.Enrichment analysis showed that the two diseases were associated with antigen processing and presentation,luminal side of endoplasmic reticulum membrane,and binding to multiple immunoglobulins.The expression trends of three core genes in the validation sets of the two diseases were consistent with those in the training set.Immune cell infiltration analysis revealed significantly increased expression of M0 macrophages,M1 macrophages,and neutrophils in both rheumatoid arthritis and Crohn’s disease.This indicates that neutrophils may play an important role in the pathogenesis of rheumatoid arthritis and Crohn’s disease.This study not only enhances our understanding of the commonalities between two important autoimmune diseases,but more importantly,it provides valuable insights and specific guidance for Chinese researchers in the discovery and validation of new targets,the development of novel diagnostic and therapeutic technologies,and the application of translational medicine research models.
作者
卢立炜
黄柯琪
陈跃平
卓映宏
朱乃辉
魏澎
Lu Liwei;Huang Keqi;Chen Yueping;Zhuo Yinghong;Zhu Naihui;Wei Peng(Graduate School of Guangxi University of Chinese Medicine,Nanning 530001,Guangxi Zhuang Autonomous Region,China;Ruikang Hospital Affiliated to Guangxi University of Chinese Medicine,Nanning 530011,Guangxi Zhuang Autonomous Region,China)
出处
《中国组织工程研究》
北大核心
2026年第16期4253-4264,共12页
Chinese Journal of Tissue Engineering Research
基金
国家自然科学基金项目(81960803),项目负责人:陈跃平
广西壮族自治区自然科学基金项目(2023JJA140318),项目负责人:陈跃平
广西中医药大学“桂派中医药传承创新团队”项目(2022A004),项目负责人:陈跃平。
