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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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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. |
format | Online Article Text |
id | pubmed-9232301 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
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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