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Genome-wide assessment of gene-by-smoking interactions in COPD

Cigarette smoke exposure is a major risk factor in chronic obstructive pulmonary disease (COPD) and its interactions with genetic variants could affect lung function. However, few gene-smoking interactions have been reported. In this report, we evaluated the effects of gene-smoking interactions on l...

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Detalles Bibliográficos
Autores principales: Park, Boram, Koo, So-My, An, Jaehoon, Lee, MoonGyu, Kang, Hae Yeon, Qiao, Dandi, Cho, Michael H., Sung, Joohon, Silverman, Edwin K., Yang, Hyeon-Jong, Won, Sungho
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6006158/
https://www.ncbi.nlm.nih.gov/pubmed/29915320
http://dx.doi.org/10.1038/s41598-018-27463-5
Descripción
Sumario:Cigarette smoke exposure is a major risk factor in chronic obstructive pulmonary disease (COPD) and its interactions with genetic variants could affect lung function. However, few gene-smoking interactions have been reported. In this report, we evaluated the effects of gene-smoking interactions on lung function using Korea Associated Resource (KARE) data with the spirometric variables—forced expiratory volume in 1 s (FEV(1)). We found that variations in FEV(1) were different among smoking status. Thus, we considered a linear mixed model for association analysis under heteroscedasticity according to smoking status. We found a previously identified locus near SOX9 on chromosome 17 to be the most significant based on a joint test of the main and interaction effects of smoking. Smoking interactions were replicated with Gene-Environment of Interaction and phenotype (GENIE), Multi-Ethnic Study of Atherosclerosis-Lung (MESA-Lung), and COPDGene studies. We found that individuals with minor alleles, rs17765644, rs17178251, rs11870732, and rs4793541, tended to have lower FEV(1) values, and lung function decreased much faster with age for smokers. There have been very few reports to replicate a common variant gene-smoking interaction, and our results revealed that statistical models for gene-smoking interaction analyses should be carefully selected.