Lung cancer susceptibility model based on age, family history and genetic variants

Robert P Young, Raewyn J Hopkins, Bryan A Hay, Michael J Epton, Graham D Mills, Peter N Black, Heather D Gardner, Richard Sullivan, Gregory D Gamble, Robert P Young, Raewyn J Hopkins, Bryan A Hay, Michael J Epton, Graham D Mills, Peter N Black, Heather D Gardner, Richard Sullivan, Gregory D Gamble

Abstract

Background: Epidemiological and pedigree studies suggest that lung cancer results from the combined effects of age, smoking, impaired lung function and genetic factors. In a case control association study of healthy smokers and lung cancer cases, we identified genetic markers associated with either susceptibility or protection to lung cancer.

Methodology/principal findings: We screened 157 candidate single nucleotide polymorphisms (SNP) in a discovery cohort of 439 subjects (200 controls and 239 lung cancer cases) and identified 30 SNPs associated with either the healthy smokers (protective) or lung cancer (susceptibility) phenotype. After genotyping this 30 SNP panel in a validation cohort of 491 subjects (248 controls and 207 lung cancers) and, using the same protective and susceptibility genotypes from our discovery cohort, a 20 SNP panel was selected based on replication of SNP associations in the validation cohort. Following multivariate logistic regression analyses, including the selected SNPs from runs 1 and 2, we found age and family history of lung cancer to be significantly and independently associated with lung cancer. Numeric scores were assigned to both the SNP and demographic data, and combined to form a simple algorithm of risk.

Conclusions/significance: Significant differences in the distribution of the lung cancer susceptibility score was found between normal controls and lung cancer cases, which remained after accounting for differences in lung function. Validation in other case-control and prospective cohorts are underway to further define the potential clinical utility of this model.

Conflict of interest statement

Competing Interests: Dr. Robert Young is a Scientific Advisor to Synergenz BioSciences who has, through the University of Auckland, helped sponsor this study.

Figures

Figure 1
Figure 1
1a. Frequency of lung cancer according to the lung cancer susceptibility (risk) score. 1b. Odds ratio of lung cancer according to the lung cancer susceptibility (risk) score.
Figure 2. Frequency distribution of the lung…
Figure 2. Frequency distribution of the lung cancer susceptibility (risk) score in cases and controls.
Figure 3
Figure 3
3a Frequency distribution of the lung cancer score among controls and lung cancer cases divided according to low (COPD) and normal lung function. 3b Frequency distribution of the lung cancer score among controls and lung cancer cases with normal lung function (COPD excluded).

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Source: PubMed

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