Literature DB >> 19233139

A novel polymorphism in CDC6 is associated with the decline in lung function of ex-smokers in COPD.

Noriaki Takabatake1, Sayumi Toriyama, Akira Igarashi, Yoshikane Tokairin, Yasuchika Takeishi, Tsuneo Konta, Sumito Inoue, Shuichi Abe, Yoko Shibata, Isao Kubota.   

Abstract

The effect of smoking cessation on the rate of decline in lung function in patients with advanced stages of chronic obstructive pulmonary disease (COPD) has not been clarified. Saccharomyces cerevisiae cell division cycle 6 homolog (CDC6) protein possesses the pro-apoptotic properties. We tested our hypothesis that the individual susceptibility to rapid decline in lung function despite smoking cessation in patients with advanced stages of COPD is attributed to the genetic variants in the CDC6 gene. We prospectively followed 82 patients (ex-smokers) during 30months and evaluated the differences among the genotypes in the annual rate of decline in FEV(1.0) (%predicted) with ten single nucleotide polymorphisms (SNPs) in and around the CDC6 gene. We found significant differences in SNP5 (National Center for Biotechnology Information SNP reference: rs2077464), SNP6 (rs13706), SNP7 (rs7217852), and SNP8 (rs9904270) with a gene-dosage effect (ANOVA overall-P=0.029-0.030). The individual allele of SNP5G, SNP6A, SNP7G, and SNP8T were associated with rapid decline in FEV(1.0) (%predicted) [odds ratio (95% confidence interval)=2.35 (1.19-4.65), P=0.014]. The SNP5G/SNP6A/SNP7G/SNP8T haplotype was associated with an increased risk of deterioration of FEV(1.0) (%predicted) (P=0.017). Importantly, SNP6 caused a change in amino acids in CDC6 protein (Val441Ile), immediately upstream of the caspase-3-dependent cleavage site of CDC6 (Asp442) during apoptosis. These results suggest that CDC6 may be one of the susceptibility genes that contribute to rapid decline in lung function despite smoking cessation in these patients with COPD.

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Year:  2009        PMID: 19233139     DOI: 10.1016/j.bbrc.2009.02.080

Source DB:  PubMed          Journal:  Biochem Biophys Res Commun        ISSN: 0006-291X            Impact factor:   3.575


  6 in total

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5.  Meta-analysis of mRNA expression profiles to identify differentially expressed genes in lung adenocarcinoma tissue from smokers and non-smokers.

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6.  Identification of nine key genes by bioinformatics analysis for predicting poor prognosis in smoking-induced lung adenocarcinoma.

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  6 in total

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