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Identification of Molecular Signatures in Mild Intrinsic Atopic Dermatitis by Bioinformatics Analysis

BACKGROUND: Atopic dermatitis (AD) is recognized as a common inflammatory skin disease and frequently occurred in Asian and Black individuals. OBJECTIVE: Since the limitation of dataset associated with human severe AD, this study aimed to screen potential novel biomarkers involved in mild AD. METHOD...

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Autores principales: Yin, Huibin, Wang, Shangshang, Gu, Chaoying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Dermatological Association; The Korean Society for Investigative Dermatology 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7992548/
https://www.ncbi.nlm.nih.gov/pubmed/33911724
http://dx.doi.org/10.5021/ad.2020.32.2.130
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author Yin, Huibin
Wang, Shangshang
Gu, Chaoying
author_facet Yin, Huibin
Wang, Shangshang
Gu, Chaoying
author_sort Yin, Huibin
collection PubMed
description BACKGROUND: Atopic dermatitis (AD) is recognized as a common inflammatory skin disease and frequently occurred in Asian and Black individuals. OBJECTIVE: Since the limitation of dataset associated with human severe AD, this study aimed to screen potential novel biomarkers involved in mild AD. METHODS: Expression profile data (GSE75890) were obtained from the database of Gene Expression Omnibus. Using limma package, the differentially expressed genes (DEGs) between samples from AD and healthy control were selected. Furthermore, function analysis was conducted. Meanwhile, the protein-protein interaction (PPI) network and transcription factor (TF)-miRNA-target regulatory network were constructed. And quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate the expressions patterns of key genes. RESULTS: In total, 285 DEGs including 214 upregulated and 71 downregulated genes were identified between samples from two groups. The upregulated DEGs were mainly involved in nine pathways, such as hematopoietic cell lineage, pertussis, p53 signaling pathway, staphylococcus aureus infection, and cell cycle, while tight junction was the only pathway enriched by the downregulated DEGs. Cyclin B (CCNB)1, CCNB2, cyclin A (CCNA)2, C-X-C motif chemokine ligand (CXCL)10, and CXCL9 were key nodes in PPI network. The TF-miRNA-target gene regulatory network focused on miRNAs such as miR-106b, miR-106a, and miR-17, TFs such as nuclear factor kappa B subunit 1, RELA proto-oncogene, Sp1 transcription factor, and genes such as matrix metallopeptidase 9, peroxisome proliferator activated receptor gamma , and serpin family E member 1. Moreover, the upregulation of these genes, including CCNB1, CCNB2, CCNA2, CXCL10, and CXCL9 were confirmed by qRT-PCR. CONCLUSION: CCNB1, CCNB2, CCNA2, and CXCL9 might be novel markers of mild AD. miR-106b and miR-17 may involve in regulation of immune response in AD patients.
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spelling pubmed-79925482021-04-27 Identification of Molecular Signatures in Mild Intrinsic Atopic Dermatitis by Bioinformatics Analysis Yin, Huibin Wang, Shangshang Gu, Chaoying Ann Dermatol Original Article BACKGROUND: Atopic dermatitis (AD) is recognized as a common inflammatory skin disease and frequently occurred in Asian and Black individuals. OBJECTIVE: Since the limitation of dataset associated with human severe AD, this study aimed to screen potential novel biomarkers involved in mild AD. METHODS: Expression profile data (GSE75890) were obtained from the database of Gene Expression Omnibus. Using limma package, the differentially expressed genes (DEGs) between samples from AD and healthy control were selected. Furthermore, function analysis was conducted. Meanwhile, the protein-protein interaction (PPI) network and transcription factor (TF)-miRNA-target regulatory network were constructed. And quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate the expressions patterns of key genes. RESULTS: In total, 285 DEGs including 214 upregulated and 71 downregulated genes were identified between samples from two groups. The upregulated DEGs were mainly involved in nine pathways, such as hematopoietic cell lineage, pertussis, p53 signaling pathway, staphylococcus aureus infection, and cell cycle, while tight junction was the only pathway enriched by the downregulated DEGs. Cyclin B (CCNB)1, CCNB2, cyclin A (CCNA)2, C-X-C motif chemokine ligand (CXCL)10, and CXCL9 were key nodes in PPI network. The TF-miRNA-target gene regulatory network focused on miRNAs such as miR-106b, miR-106a, and miR-17, TFs such as nuclear factor kappa B subunit 1, RELA proto-oncogene, Sp1 transcription factor, and genes such as matrix metallopeptidase 9, peroxisome proliferator activated receptor gamma , and serpin family E member 1. Moreover, the upregulation of these genes, including CCNB1, CCNB2, CCNA2, CXCL10, and CXCL9 were confirmed by qRT-PCR. CONCLUSION: CCNB1, CCNB2, CCNA2, and CXCL9 might be novel markers of mild AD. miR-106b and miR-17 may involve in regulation of immune response in AD patients. The Korean Dermatological Association; The Korean Society for Investigative Dermatology 2020-04 2020-03-11 /pmc/articles/PMC7992548/ /pubmed/33911724 http://dx.doi.org/10.5021/ad.2020.32.2.130 Text en Copyright © 2020 The Korean Dermatological Association and The Korean Society for Investigative Dermatology http://creativecommons.org/licenses/by-nc/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Yin, Huibin
Wang, Shangshang
Gu, Chaoying
Identification of Molecular Signatures in Mild Intrinsic Atopic Dermatitis by Bioinformatics Analysis
title Identification of Molecular Signatures in Mild Intrinsic Atopic Dermatitis by Bioinformatics Analysis
title_full Identification of Molecular Signatures in Mild Intrinsic Atopic Dermatitis by Bioinformatics Analysis
title_fullStr Identification of Molecular Signatures in Mild Intrinsic Atopic Dermatitis by Bioinformatics Analysis
title_full_unstemmed Identification of Molecular Signatures in Mild Intrinsic Atopic Dermatitis by Bioinformatics Analysis
title_short Identification of Molecular Signatures in Mild Intrinsic Atopic Dermatitis by Bioinformatics Analysis
title_sort identification of molecular signatures in mild intrinsic atopic dermatitis by bioinformatics analysis
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7992548/
https://www.ncbi.nlm.nih.gov/pubmed/33911724
http://dx.doi.org/10.5021/ad.2020.32.2.130
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