文献类型：期刊文献

英文题名：Identification of key biomarkers of the glomerulus in focal segmental glomerulosclerosis and their relationship with immune cell infiltration based on WGCNA and the LASSO algorithm

作者：Zhang, Yun Xia[1,2];Lv, Juan[1,2];Bai, Jun Yuan[1,3];Pu, XiaoWei[1];Dai, En Lai[1]

第一作者：Zhang, Yun Xia;张芸霞

通信作者：Dai, EL[1]

机构：[1]Gansu Univ Tradit Chinese Med, Coll Integrated Tradit & Western Med, Lanzhou, Peoples R China;[2]Gansu Prov Hosp Tradit Chinese Med, Lanzhou, Peoples R China;[3]Gansu Univ Chinese Med, Affiliated Hosp, Lanzhou, Peoples R China

第一机构：甘肃中医药大学

通信机构：[1]corresponding author), Gansu Univ Tradit Chinese Med, Coll Integrated Tradit & Western Med, Lanzhou, Peoples R China.|[10735]甘肃中医药大学;

年份：2023

卷号：45

期号：1

外文期刊名：RENAL FAILURE

收录：;Scopus(收录号：2-s2.0-85153623141);WOS:【SCI-EXPANDED(收录号:WOS:000974064600001)】；

语种：英文

外文关键词：Focal segmental glomerulosclerosis; weighted gene coexpression network analysis; least absolute shrinkage and selection operator; immune cell infiltration; TGFB1; NOTCH1

摘要：Objective The aim of our study was to identify key biomarkers of glomeruli in focal glomerulosclerosis (FSGS) and analyze their relationship with the infiltration of immune cells. Methods The expression profiles (GSE108109 and GSE200828) were obtained from the GEO database. The differentially expressed genes (DEGs) were filtered and analyzed by gene set enrichment analysis (GSEA). MCODE module was constructed. Weighted gene coexpression network analysis (WGCNA) was performed to obtain the core gene modules. Least absolute shrinkage and selection operator (LASSO) regression was applied to identify key genes. ROC curves were employed to explore their diagnostic accuracy. Transcription factor prediction of the key biomarkers was performed using the Cytoscape plugin IRegulon. The analysis of the infiltration of 28 immune cells and their correlation with the key biomarkers were performed. Results A total of 1474 DEGs were identified. Their functions were mostly related to immune-related diseases and signaling pathways. MCODE identified five modules. The turquoise module of WGCNA had significant relevance to the glomerulus in FSGS. TGFB1 and NOTCH1 were identified as potential key glomerular biomarkers in FSGS. Eighteen transcription factors were obtained from the two hub genes. Immune infiltration showed significant correlations with T cells. The results of immune cell infiltration and their relationship with key biomarkers implied that NOTCH1 and TGFB1 were enhanced in immune-related pathways. Conclusion TGFB1 and NOTCH1 may be strongly correlated with the pathogenesis of the glomerulus in FSGS and are new candidate key biomarkers. T-cell infiltration plays an essential role in the FSGS lesion process.