Exploring genetic and immune cell dynamics in systemic lupus erythematosus patients with Epstein-Barr virus infection via machine learning

doi:10.1093/rheumatology/keae537

科研成果详情

题名	Exploring genetic and immune cell dynamics in systemic lupus erythematosus patients with Epstein-Barr virus infection via machine learning
作者	Jiajun Gui; Mengyuan Fang; Jianxin Tu; Xiaowei Chen; Li Sun
发表日期	2024-10-03
发表期刊	Rheumatology (Oxford, England) 影响因子和分区
语种	英语
原始文献类型	Journal Article
关键词	B cells CD4 T cells Epstein–Barr Virus Systemic Lupus Erythematosus type I interferon
摘要	Epstein-Barr Virus (EBV) is a widespread virus implicated in various diseases, including Systemic Lupus Erythematosus (SLE). However, the specific genes and pathways altered in SLE patients with EBV infection remain unclear. We aimed to identify key genes and immune cells in SLE patients with EBV infection., The datasets of SLE (GSE50772 and GSE81622) or EBV infection (GSE85599 and GSE45918) were obtained from the Gene Expression Omnibus (GEO) database. Next, differential gene expression (DEGs) analysis were conducted to identify overlapping DEGs and then enrichment analysis was performed. Machine learning was applied to identify key genes. Validation was conducted using ROC curve analysis and expression level verification in test datasets and single-cell RNA sequencing. Immune cell infiltration patterns were analyzed using CIBERSORTx, and clinical data were reviewed for SLE patients., We identified 58 overlapping DEGs enriched in interferon-related pathways. Five overlapping DEGs (IFI27, TXK, RAPGEF6, PIK3IP1, PSENEN) were selected as key genes by machine learning algorithms, with IFI27 showing the highest diagnostic performance. The expression level of IFI27 was found higher in CD4 CTL, CD8 naïve and various B cell subsets of SLE patients with EBV infection. IFI27 showed significant correlation with B intermediate and CD4 CT. Clinical data showed lower CD4 T cell proportions in SLE patients with EBV infection., This study identifies IFI27 as a key gene for SLE patients with EBV infection, influencing CD4 CTL and B cell subtypes. These findings enhance the understanding of the molecular mechanisms linking SLE and EBV infection, providing potential targets for diagnostic and therapeutic strategies.
ISSN	1462-0324
EISSN	1462-0332
DOI	10.1093/rheumatology/keae537
收录类别	PUBMED
URL	查看原文
PubMed ID	39361430
引用统计
文献类型	期刊论文
条目标识符	https://kms.wmu.edu.cn/handle/3ETUA0LF/220942
专题	附属第一医院第一临床医学院（信息与工程学院）、附属第一医院附属第一医院_风湿免疫科
作者单位	Department of Rheumatology and Immunology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.
第一作者单位	附属第一医院; 第一临床医学院（信息与工程学院）、附属第一医院; 风湿免疫科
第一作者的第一单位	附属第一医院
推荐引用方式 GB/T 7714	Jiajun Gui,Mengyuan Fang,Jianxin Tu,et al. Exploring genetic and immune cell dynamics in systemic lupus erythematosus patients with Epstein-Barr virus infection via machine learning[J]. Rheumatology (Oxford, England),2024.
APA	Jiajun Gui, Mengyuan Fang, Jianxin Tu, Xiaowei Chen, & Li Sun. (2024). Exploring genetic and immune cell dynamics in systemic lupus erythematosus patients with Epstein-Barr virus infection via machine learning. Rheumatology (Oxford, England).
MLA	Jiajun Gui,et al."Exploring genetic and immune cell dynamics in systemic lupus erythematosus patients with Epstein-Barr virus infection via machine learning".Rheumatology (Oxford, England) (2024).