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

Abstract

ABSTRACT 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.