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Gene-Environment Interactions in Asthma: Genetic and Epigenetic Effects

Authors
Lee, Jong-UkKim, Jeong DongPark, Choon-Sik
Issue Date
1-Jul-2015
Publisher
연세대학교의과대학
Keywords
Asthma; gene; environment; polymorphism; genome; epigenetics; variants
Citation
Yonsei Medical Journal, v.56, no.4, pp 877 - 886
Pages
10
Journal Title
Yonsei Medical Journal
Volume
56
Number
4
Start Page
877
End Page
886
URI
https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/10468
DOI
10.3349/ymj.2015.56.4.877
ISSN
0513-5796
1976-2437
Abstract
Over the past three decades, a large number of genetic studies have been aimed at finding genetic variants associated with the risk of asthma, applying various genetic and genomic approaches including linkage analysis, candidate gene polymorphism studies, and genome-wide association studies (GWAS). However, contrary to general expectation, even single nucleotide polymorphisms (SNPs) discovered by GWAS failed to fully explain the heritability of asthma. Thus, application of rare allele polymorphisms in well defined phenotypes and clarification of environmental factors have been suggested to overcome the problem of 'missing' heritability. Such factors include allergens, cigarette smoke, air pollutants, and infectious agents during pre- and post-natal periods. The first and simplest interaction between a gene and the environment is a candidate interaction of both a well known gene and environmental factor in a direct physical or chemical interaction such as between CD14 and endotoxin or between ITLA and allergens. Several GWAS have found environmental interactions with occupational asthma, aspirin exacerbated respiratory disease, tobacco smoke-related airway dysfunction, and farm-related atopic diseases. As one of the mechanisms behind gene-environment interaction is epigenetics, a few studies on DNA CpG methylation have been reported on subphenotypes of asthma, pitching the exciting idea that it may be possible to intervene at the junction between the genome and the environment. Epigenetic studies are starting to include data from clinical samples, which will make them another powerful tool for research on gene-environment interactions in asthma.
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