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An integrated co-expression network analysis reveals novel genetic biomarkers for immune cell infiltration in chronic kidney disease

BACKGROUND: Chronic kidney disease (CKD) is characterized by persistent damage to kidney function or structure. Progression to end-stage leads to adverse effects on multiple systems. However, owing to its complex etiology and long-term cause, the molecular basis of CKD is not completely known. METHO...

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Detalles Bibliográficos
Autores principales: Xia, Jia, Hou, Yutong, Cai, Anxiang, Xu, Yingjie, Yang, Wen, Huang, Masha, Mou, Shan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9981626/
https://www.ncbi.nlm.nih.gov/pubmed/36875100
http://dx.doi.org/10.3389/fimmu.2023.1129524
Descripción
Sumario:BACKGROUND: Chronic kidney disease (CKD) is characterized by persistent damage to kidney function or structure. Progression to end-stage leads to adverse effects on multiple systems. However, owing to its complex etiology and long-term cause, the molecular basis of CKD is not completely known. METHODS: To dissect the potential important molecules during the progression, based on CKD databases from Gene Expression Omnibus, we used weighted gene co-expression network analysis (WGCNA) to identify the key genes in kidney tissues and peripheral blood mononuclear cells (PBMC). Correlation analysis of these genes with clinical relevance was evaluated based on Nephroseq. Combined with a validation cohort and receiver operating characteristic curve (ROC), we found the candidate biomarkers. The immune cell infiltration of these biomarkers was evaluated. The expression of these biomarkers was further detected in folic acid-induced nephropathy (FAN) murine model and immunohistochemical staining. RESULTS: In total, eight genes (CDCP1, CORO1C, DACH1, GSTA4, MAFB, TCF21, TGFBR3, and TGIF1) in kidney tissue and six genes (DDX17, KLF11, MAN1C1, POLR2K, ST14, and TRIM66) in PBMC were screened from co-expression network. Correlation analysis of these genes with serum creatinine levels and estimated glomerular filtration rate from Nephroseq showed a well clinical relevance. Validation cohort and ROC identified TCF21, DACH1 in kidney tissue and DDX17 in PBMC as biomarkers for the progression of CKD. Immune cell infiltration analysis revealed that DACH1 and TCF21 were correlated with eosinophil, activated CD8 T cell, activated CD4 T cell, while the DDX17 was correlated with neutrophil, type-2 T helper cell, type-1 T helper cell, mast cell, etc. FAN murine model and immunohistochemical staining confirmed that these three molecules can be used as genetic biomarkers to distinguish CKD patients from healthy people. Moreover, the increase of TCF21 in kidney tubules might play important role in the CKD progression. DISCUSSION: We identified three promising genetic biomarkers which could play important roles in the progression of CKD.