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Prediction of Immune Infiltration Diagnostic Gene Biomarkers in Kawasaki Disease

Kawasaki disease (KD) is characterized by disorder of immune response with unknown etiology. Immune cells may be closely related to the onset of KD. The focus of this research was to evaluate the significance of the infiltration of immune cells for this disease and find possible diagnostic biomarker...

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Autores principales: Ba, Hongjun, Wang, Yao, Zhang, Lili, Wang, Huishen, Huang, Zhan-Peng, Qin, Youzhen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9232301/
https://www.ncbi.nlm.nih.gov/pubmed/35755167
http://dx.doi.org/10.1155/2022/8739498
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author Ba, Hongjun
Wang, Yao
Zhang, Lili
Wang, Huishen
Huang, Zhan-Peng
Qin, Youzhen
author_facet Ba, Hongjun
Wang, Yao
Zhang, Lili
Wang, Huishen
Huang, Zhan-Peng
Qin, Youzhen
author_sort Ba, Hongjun
collection PubMed
description Kawasaki disease (KD) is characterized by disorder of immune response with unknown etiology. Immune cells may be closely related to the onset of KD. The focus of this research was to evaluate the significance of the infiltration of immune cells for this disease and find possible diagnostic biomarkers for KD. The Gene Expression Omnibus database was utilized to retrieve two freely accessible gene expression patterns (GSE68004 and GSE18606 datasets) from human KD and control specimens. 114 KD, as well as 46 control specimens, were searched for obtaining differentially expressed genes (DEGs). Candidate biological markers were determined utilizing the support vector machine recursive feature elimination and the least absolute shrinkage and selection operator regression model analysis. To assess discriminating capacity, the area under the receiver operating characteristic curve (AUC) was computed. The GSE73461 dataset was utilized to observe the biomarkers' expression levels and diagnostic significance in KD (78 KD patients and 55 controls). CIBERSORT was employed to assess the composition profiles of the 22 subtypes of immune cell fraction in KD on the basis of combined cohorts. 37 genes were discovered. The DEGs identified were predominantly involved in arteriosclerotic cardiovascular disease, atherosclerosis, autoimmune disease of the urogenital tract, and bacterial infectious disease. Gene sets related to complement and coagulation cascades, Toll-like receptor signaling pathway, Fc gamma R-mediated phagocytosis, NOD-like receptor signaling pathway, and regulation of actin cytoskeleton underwent differential activation in KD as opposed to the controls. KD diagnostic biomarkers, including the alkaline phosphatase (ALPL), endoplasmic reticulum degradation-enhancing alpha-mannosidase-like protein 2 (EDEM2), and histone cluster 2 (HIST2H2BE), were discovered (AUC = 1.000) and verified utilizing the GSE73461 dataset (AUC = 1.000). Analyses of immune cell infiltration demonstrated that ALPL, EDEM2, and HIST2H2BE were linked to CD4 memory resting T cells, monocytes, M0 macrophages, CD8 T cells, neutrophils, and memory CD4 T cells. ALPL, EDEM2, and HIST2H2BE could be utilized as KD diagnostic indicators, and they can also deliver useful information for future research on the disease's incidence and molecular processes.
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spelling pubmed-92323012022-06-25 Prediction of Immune Infiltration Diagnostic Gene Biomarkers in Kawasaki Disease Ba, Hongjun Wang, Yao Zhang, Lili Wang, Huishen Huang, Zhan-Peng Qin, Youzhen J Immunol Res Research Article Kawasaki disease (KD) is characterized by disorder of immune response with unknown etiology. Immune cells may be closely related to the onset of KD. The focus of this research was to evaluate the significance of the infiltration of immune cells for this disease and find possible diagnostic biomarkers for KD. The Gene Expression Omnibus database was utilized to retrieve two freely accessible gene expression patterns (GSE68004 and GSE18606 datasets) from human KD and control specimens. 114 KD, as well as 46 control specimens, were searched for obtaining differentially expressed genes (DEGs). Candidate biological markers were determined utilizing the support vector machine recursive feature elimination and the least absolute shrinkage and selection operator regression model analysis. To assess discriminating capacity, the area under the receiver operating characteristic curve (AUC) was computed. The GSE73461 dataset was utilized to observe the biomarkers' expression levels and diagnostic significance in KD (78 KD patients and 55 controls). CIBERSORT was employed to assess the composition profiles of the 22 subtypes of immune cell fraction in KD on the basis of combined cohorts. 37 genes were discovered. The DEGs identified were predominantly involved in arteriosclerotic cardiovascular disease, atherosclerosis, autoimmune disease of the urogenital tract, and bacterial infectious disease. Gene sets related to complement and coagulation cascades, Toll-like receptor signaling pathway, Fc gamma R-mediated phagocytosis, NOD-like receptor signaling pathway, and regulation of actin cytoskeleton underwent differential activation in KD as opposed to the controls. KD diagnostic biomarkers, including the alkaline phosphatase (ALPL), endoplasmic reticulum degradation-enhancing alpha-mannosidase-like protein 2 (EDEM2), and histone cluster 2 (HIST2H2BE), were discovered (AUC = 1.000) and verified utilizing the GSE73461 dataset (AUC = 1.000). Analyses of immune cell infiltration demonstrated that ALPL, EDEM2, and HIST2H2BE were linked to CD4 memory resting T cells, monocytes, M0 macrophages, CD8 T cells, neutrophils, and memory CD4 T cells. ALPL, EDEM2, and HIST2H2BE could be utilized as KD diagnostic indicators, and they can also deliver useful information for future research on the disease's incidence and molecular processes. Hindawi 2022-06-17 /pmc/articles/PMC9232301/ /pubmed/35755167 http://dx.doi.org/10.1155/2022/8739498 Text en Copyright © 2022 Hongjun Ba et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Ba, Hongjun
Wang, Yao
Zhang, Lili
Wang, Huishen
Huang, Zhan-Peng
Qin, Youzhen
Prediction of Immune Infiltration Diagnostic Gene Biomarkers in Kawasaki Disease
title Prediction of Immune Infiltration Diagnostic Gene Biomarkers in Kawasaki Disease
title_full Prediction of Immune Infiltration Diagnostic Gene Biomarkers in Kawasaki Disease
title_fullStr Prediction of Immune Infiltration Diagnostic Gene Biomarkers in Kawasaki Disease
title_full_unstemmed Prediction of Immune Infiltration Diagnostic Gene Biomarkers in Kawasaki Disease
title_short Prediction of Immune Infiltration Diagnostic Gene Biomarkers in Kawasaki Disease
title_sort prediction of immune infiltration diagnostic gene biomarkers in kawasaki disease
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9232301/
https://www.ncbi.nlm.nih.gov/pubmed/35755167
http://dx.doi.org/10.1155/2022/8739498
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