The landscape of DNA methylation in asthma: a data mining and validation

Human asthma is caused by interactions between a range of genetic and environmental factors. However, the specific pathogenesis of asthma remains controversial. This study explored the contribution of DNA methylation to asthma using computer learning methods. Relevant datasets and information relate...

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Autores principales:	Hui Yang, Fei-yang Na, Li Guo, Xuan Liang, Rong-Fang Zhang
Formato:	article
Lenguaje:	EN
Publicado:	Taylor & Francis Group 2021
Materias:	asthma dna methylation biomarker hla-dmb Biotechnology TP248.13-248.65
Acceso en línea:	https://doaj.org/article/4e244f3e632044deb7fc68860f7ca99e
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spelling	oai:doaj.org-article:4e244f3e632044deb7fc68860f7ca99e2021-11-04T15:51:54ZThe landscape of DNA methylation in asthma: a data mining and validation2165-59792165-598710.1080/21655979.2021.1997088https://doaj.org/article/4e244f3e632044deb7fc68860f7ca99e2021-10-01T00:00:00Zhttp://dx.doi.org/10.1080/21655979.2021.1997088https://doaj.org/toc/2165-5979https://doaj.org/toc/2165-5987Human asthma is caused by interactions between a range of genetic and environmental factors. However, the specific pathogenesis of asthma remains controversial. This study explored the contribution of DNA methylation to asthma using computer learning methods. Relevant datasets and information related to patients with asthma were collected from the Gene Expression Omnibus (GEO) database. A multivariate linear regression model was established. Differentially expressed genes and DNA methylation sites were identified. The results showed that the expression of 169 genes was significantly different between the two groups. Through differential analysis of methylation and differential analysis of gene expression, 44 differentially expressed genes that may be affected by DNA methylation modification were identified. The results of the multiple linear regression model showed that DNA methylation could explain 9.81% of the variation in gene expression. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses showed that the differentially expressed genes, HLA-DMB, IL4, HLA-DPB1, and CD40LG, were related to the occurrence of asthma, and HLA-DMB expression was significantly reduced in allergic asthma. There was a positive correlation between cg04933135 and HLA-DMB expression, and cg04933135 was a differential site for DNA methylation. Using blood samples from asthma patients, we confirmed that HLA-DMB expression is down-regulated, which may be affected by abnormal DNA methylation. DNA methylation plays an important role in the development of asthma, and HLA-DMB which modified by abnormal DNA methylation can be regarded as a new biomarker of asthma.Hui YangFei-yang NaLi GuoXuan LiangRong-Fang ZhangTaylor & Francis Grouparticleasthmadna methylationbiomarkerhla-dmbBiotechnologyTP248.13-248.65ENBioengineered, Vol 0, Iss 0 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	asthma dna methylation biomarker hla-dmb Biotechnology TP248.13-248.65
spellingShingle	asthma dna methylation biomarker hla-dmb Biotechnology TP248.13-248.65 Hui Yang Fei-yang Na Li Guo Xuan Liang Rong-Fang Zhang The landscape of DNA methylation in asthma: a data mining and validation
description	Human asthma is caused by interactions between a range of genetic and environmental factors. However, the specific pathogenesis of asthma remains controversial. This study explored the contribution of DNA methylation to asthma using computer learning methods. Relevant datasets and information related to patients with asthma were collected from the Gene Expression Omnibus (GEO) database. A multivariate linear regression model was established. Differentially expressed genes and DNA methylation sites were identified. The results showed that the expression of 169 genes was significantly different between the two groups. Through differential analysis of methylation and differential analysis of gene expression, 44 differentially expressed genes that may be affected by DNA methylation modification were identified. The results of the multiple linear regression model showed that DNA methylation could explain 9.81% of the variation in gene expression. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses showed that the differentially expressed genes, HLA-DMB, IL4, HLA-DPB1, and CD40LG, were related to the occurrence of asthma, and HLA-DMB expression was significantly reduced in allergic asthma. There was a positive correlation between cg04933135 and HLA-DMB expression, and cg04933135 was a differential site for DNA methylation. Using blood samples from asthma patients, we confirmed that HLA-DMB expression is down-regulated, which may be affected by abnormal DNA methylation. DNA methylation plays an important role in the development of asthma, and HLA-DMB which modified by abnormal DNA methylation can be regarded as a new biomarker of asthma.
format	article
author	Hui Yang Fei-yang Na Li Guo Xuan Liang Rong-Fang Zhang
author_facet	Hui Yang Fei-yang Na Li Guo Xuan Liang Rong-Fang Zhang
author_sort	Hui Yang
title	The landscape of DNA methylation in asthma: a data mining and validation
title_short	The landscape of DNA methylation in asthma: a data mining and validation
title_full	The landscape of DNA methylation in asthma: a data mining and validation
title_fullStr	The landscape of DNA methylation in asthma: a data mining and validation
title_full_unstemmed	The landscape of DNA methylation in asthma: a data mining and validation
title_sort	landscape of dna methylation in asthma: a data mining and validation
publisher	Taylor & Francis Group
publishDate	2021
url	https://doaj.org/article/4e244f3e632044deb7fc68860f7ca99e
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The landscape of DNA methylation in asthma: a data mining and validation

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