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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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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
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author Xia, Jia
Hou, Yutong
Cai, Anxiang
Xu, Yingjie
Yang, Wen
Huang, Masha
Mou, Shan
author_facet Xia, Jia
Hou, Yutong
Cai, Anxiang
Xu, Yingjie
Yang, Wen
Huang, Masha
Mou, Shan
author_sort Xia, Jia
collection PubMed
description 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.
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spelling pubmed-99816262023-03-04 An integrated co-expression network analysis reveals novel genetic biomarkers for immune cell infiltration in chronic kidney disease Xia, Jia Hou, Yutong Cai, Anxiang Xu, Yingjie Yang, Wen Huang, Masha Mou, Shan Front Immunol Immunology 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. Frontiers Media S.A. 2023-02-17 /pmc/articles/PMC9981626/ /pubmed/36875100 http://dx.doi.org/10.3389/fimmu.2023.1129524 Text en Copyright © 2023 Xia, Hou, Cai, Xu, Yang, Huang and Mou https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Immunology
Xia, Jia
Hou, Yutong
Cai, Anxiang
Xu, Yingjie
Yang, Wen
Huang, Masha
Mou, Shan
An integrated co-expression network analysis reveals novel genetic biomarkers for immune cell infiltration in chronic kidney disease
title An integrated co-expression network analysis reveals novel genetic biomarkers for immune cell infiltration in chronic kidney disease
title_full An integrated co-expression network analysis reveals novel genetic biomarkers for immune cell infiltration in chronic kidney disease
title_fullStr An integrated co-expression network analysis reveals novel genetic biomarkers for immune cell infiltration in chronic kidney disease
title_full_unstemmed An integrated co-expression network analysis reveals novel genetic biomarkers for immune cell infiltration in chronic kidney disease
title_short An integrated co-expression network analysis reveals novel genetic biomarkers for immune cell infiltration in chronic kidney disease
title_sort integrated co-expression network analysis reveals novel genetic biomarkers for immune cell infiltration in chronic kidney disease
topic Immunology
url 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
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