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Postgrad Med J 85:515-524 doi:10.1136/pgmj.2008.077107
  • Original article

A gene-based risk score for lung cancer susceptibility in smokers and ex-smokers

  1. R P Young1,
  2. R J Hopkins1,
  3. B A Hay1,
  4. M J Epton2,
  5. G D Mills3,
  6. P N Black1,
  7. H D Gardner1,
  8. R Sullivan4,
  9. G D Gamble1
  1. 1
    Department of Medicine, Auckland Hospital, Auckland, New Zealand
  2. 2
    Department of Medicine, University of Otago, Christchurch, New Zealand
  3. 3
    Department of Medicine, Waikato Hospital, Hamilton, New Zealand
  4. 4
    Department of Oncology, Auckland Hospital, Auckland, New Zealand
  1. Correspondence to Dr R Young, Department of Medicine, Auckland Hospital, Private Bag 92019, Auckland, New Zealand; roberty{at}adhb.govt.nz
  • Received 23 November 2008
  • Accepted 2 May 2009

Abstract

Background: Epidemiological and family studies suggest that lung cancer results from the combined effects of age, smoking and genetic factors. Chronic obstructive pulmonary disease (COPD) is also an independent risk factor for lung cancer and coexists in 40–60% of lung cancer cases.

Methods: In a two-stage case–control association study, genetic markers associated with either susceptibility or protection against lung cancer were identified. In a test cohort of 439 Caucasian smokers or ex-smokers, consisting of healthy smokers and lung cancer cases, 157 candidate single nucleotide polymorphisms (SNPs) were screened. From this, 30 SNPs were identified, the genotypes (codominant or recessive model) of which were associated with either the healthy smokers (protective) or lung cancer (susceptibility) phenotype. After genotyping of this 30-SNP panel in a second validation cohort of 491 subjects and using the same protective and susceptibility genotypes from our test cohort, a 20-SNP panel was selected on the basis of independent univariate analyses.

Results: Using multivariate logistic regression, including the 20 SNPs, it was also found that age, history of COPD, family history of lung cancer and gender were significantly and independently associated with lung cancer.

Conclusions: When numeric scores were assigned to both the SNP and demographic data, and sequentially combined by a simple algorithm in a risk model, the composite score was found to be linearly related to lung cancer risk with a bimodal distribution. Genetic data may therefore be combined with other risk variables from smokers or ex-smokers to identify individuals who are most susceptible to developing lung cancer.

Footnotes

  • See Editorial, p 505

  • Funding This study was in part funded by the Health Research Council of New Zealand (Grant 9101-3602829), the Auckland Medical Research Foundation of New Zealand and the University of Auckland (Staff Research Fund), New Zealand.

  • Competing interests This study was part funded by Synergenz BioScience Ltd. RY is an advisor to this company.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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