Candidate genes for COPD in two large data sets

P. S. Bakke, G. Zhu, A. Gulsvik, X. Kong, A. G.N. Agusti, P. M.A. Calverley, C. F. Donner, R. D. Levy, B. J. Make, P. D. Paré, S. I. Rennard, J. Vestbo, E. F.M. Wouters, W. Anderson, D. A. Lomas, E. K. Silverman, S. G. Pillai

Research output: Contribution to journalArticlepeer-review

37 Scopus citations

Abstract

Lack of reproducibility of findings has been a criticism of genetic association studies on complex diseases, such as chronic obstructive pulmonary disease (COPD). We selected 257 polymorphisms of 16 genes with reported or potential relationships to COPD and genotyped these variants in a case-control study that included 953 COPD cases and 956 control subjects. We explored the association of these polymorphisms to three COPD phenotypes: a COPD binary phenotype and two quantitative traits (post-bronchodilator forced expiratory volume in 1 s (FEV1) % predicted and FEV1/forced vital capacity (FVC)). The polymorphisms significantly associated to these phenotypes in this first study were tested in a second, family-based study that included 635 pedigrees with 1,910 individuals. Significant associations to the binary COPD phenotype in both populations were seen for STAT1 (rs13010343) and NFKBIB/SIRT2 (rs2241704) (p<0.05). Single-nucleotide polymorphisms rs17467825 and rs1155563 of the GC gene were significantly associated with FEV1 % predicted and FEV1/FVC, respectively, in both populations (p<0.05). This study has replicated associations to COPD phenotypes in the STAT1, NFKBIB/SIRT2 and GC genes in two independent populations, the associations of the former two genes representing novel findings. Copyright

Original languageEnglish (US)
Pages (from-to)255-263
Number of pages9
JournalEuropean Respiratory Journal
Volume37
Issue number2
DOIs
StatePublished - Feb 1 2011

Keywords

  • Chronic obstructive pulmonary disease
  • Genetic association
  • Replication
  • Smoking

ASJC Scopus subject areas

  • Pulmonary and Respiratory Medicine

Fingerprint Dive into the research topics of 'Candidate genes for COPD in two large data sets'. Together they form a unique fingerprint.

Cite this