Lin Weiyi, Lin Zien, Lin Xiaobing, Peng Zhishen, Liang Xiaofeng, Wei Shanshan
Zhujiang Hospital, The Second School of Clinical Medicine, Southern Medical University, Guangzhou, The People's Republic of China.
Department of Dermatology, Zhujiang Hospital, Southern Medical University, Guangzhou, The People's Republic of China.
Lupus. 2023 Apr;32(5):633-643. doi: 10.1177/09612033231161587. Epub 2023 Mar 13.
Lupus nephritis (LN) is the most common complication of systemic lupus erythematosus (SLE). This study aimed to explore biomarkers, mechanisms, and potential novel agents regarding LN through bioinformatic analysis.
Four expression profiles were downloaded from the Gene Expression Omnibus (GEO) database and differentially expressed genes (DEGs) were acquired. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGGs) pathway enrichment analyses of DEGs were performed using the R software. The protein-protein interaction (PPI) network was developed using the STRING database. Additionally, five algorithms were used to screen out the hub genes. Expression of the hub genes were validated using Nephroseq v5. CIBERSORT was used to evaluate the infiltration of immune cells. Finally, The Drug-Gene Interaction Database was used to predict potential targeted drugs.
FOS and IGF1 were identified as hub genes, with excellent specificity and sensitivity diagnosis of LN. FOS was also related to renal injury. LN patients had lower activated and resting dendritic cells (DCs) and higher M1 macrophages and activated NK cells than healthy control (HC). FOS had a positive correlation with activated mast cells and a negative correlation with resting mast cells. IGF1 had a positive correlation with activated DCs and a negative correlation with monocytes. The targeted drugs were dusigitumab and xentuzumab target for IGF1.
We analyzed the transcriptomic signature of LN along with the landscape of the immune cell. FOS and IGF1 are promising biomarkers for diagnosing and evaluating the progression of LN. The drug-gene interaction analyses provide a list of candidate drugs for the precise treatment of LN.
狼疮性肾炎(LN)是系统性红斑狼疮(SLE)最常见的并发症。本研究旨在通过生物信息学分析探索与LN相关的生物标志物、机制及潜在的新型药物。
从基因表达综合数据库(GEO)下载四个表达谱,获取差异表达基因(DEG)。使用R软件对DEG进行基因本体论(GO)和京都基因与基因组百科全书(KEGG)通路富集分析。利用STRING数据库构建蛋白质-蛋白质相互作用(PPI)网络。此外,使用五种算法筛选出枢纽基因。使用Nephroseq v5验证枢纽基因的表达。使用CIBERSORT评估免疫细胞的浸润情况。最后,利用药物-基因相互作用数据库预测潜在的靶向药物。
FOS和IGF1被鉴定为枢纽基因,对LN具有出色的特异性和敏感性诊断能力。FOS也与肾损伤有关。与健康对照(HC)相比,LN患者的活化和静息树突状细胞(DC)较少,M1巨噬细胞和活化自然杀伤细胞较多。FOS与活化肥大细胞呈正相关,与静息肥大细胞呈负相关。IGF1与活化DC呈正相关,与单核细胞呈负相关。靶向药物为针对IGF1的dusigitumab和xentuzumab。
我们分析了LN的转录组特征以及免疫细胞图谱。FOS和IGF1是诊断和评估LN进展的有前景的生物标志物。药物-基因相互作用分析提供了一份用于LN精准治疗的候选药物清单。