Identification of new immune subtypes of renal injury associated with anti-neutrophil cytoplasmic antibody-associated vasculitis based on integrated bioinformatics analysis

被引:1
|
作者
Lin, Lizhen [1 ]
Ye, Keng [2 ,3 ,4 ]
Chen, Fengbin [1 ]
Xie, Jingzhi [2 ,3 ,4 ]
Chen, Zhimin [2 ,3 ,4 ]
Xu, Yanfang [2 ,3 ,4 ,5 ]
机构
[1] Fujian Med Univ, Affiliated Hosp 1, Dept Tradit Chinese Med, Fuzhou, Peoples R China
[2] Fujian Med Univ, Affiliated Hosp 1, Blood Purificat Res Ctr, Dept Nephrol, Fuzhou, Peoples R China
[3] Fujian Med Univ, Affiliated Hosp 1, Fujian Clin Res Ctr Metab Chron Kidney Dis, Fuzhou, Peoples R China
[4] Fujian Med Univ, Affiliated Hosp 1, Natl Reg Med Ctr, Dept Nephrol, Binhai Campus, Fuzhou, Peoples R China
[5] Fujian Med Univ, Affiliated Hosp 1, Cent Lab, Fuzhou, Peoples R China
基金
中国国家自然科学基金;
关键词
ANCA-associated vasculitis; renal injury; bioinformatics; biomarkers; immune subtypes; WGCNA; ANCA-ASSOCIATED VASCULITIS; PATHOGENESIS; EXPRESSION; IL-17; CELLS;
D O I
10.3389/fgene.2023.1119017
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Background: Anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is a systemic autoimmune disease that may lead to end-stage renal disease. However, few specifific biomarkers are available for AAV-related renal injury. The aim of this study was to identify important biomarkers and explore new immune subtypes of AAV-related renal injury.Methods: In this study, messenger RNA expression profiles for antibody-associated vasculitis and AAV-associated kidney injury were downloaded from the Gene Expression Omnibus database. Weighted gene co-expression network analysis (WGCNA) was performed to identify the most relevant module genes to AAV. Key module genes from WGCNA were then intersected with AAV- and nephropathy-related genes from the Genecards database to identify key genes for AAV-associated kidney injury. Subsequently, the expression of key genes was validated in independent datasets and the correlation of genes with clinical traits of kidney injury was verified by the Nephroseq database. Finally, non-negative matrix factorization (NMF) clustering was performed to identify the immune subtypes associated with the key genes.Results: Eight co-key genes (AGTR2, ANPTL2, BDKRB1, CSF2, FGA, IL1RAPL2, PCDH11Y, and PGR) were identifified, and validated the expression levels independent datasets. Receiver operating characteristic curve analysis revealed that these eight genes have major diagnostic value as potential biomarkers of AAV-related renal injury. Through our comprehensive gene enrichment analyses, we found that they are associated with immune-related pathways. NMF clustering of key genes identified two and three immune-related molecular subtypes in the glomerular and tubular data, respectively. A correlation analysis with prognostic data from the Nephroseq database indicated that the expression of co-key genes was positively co-related with the glomerular filtration rate.Discussion: Altogether, we identifified 8 valuable biomarkers that firmly correlate with the diagnosis and prognosis of AAV-related renal injury. These markers may help identify new immune subtypes for AAV-related renal injury.
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页数:11
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