Although tobacco exposure is the major determinant of lung cancer, only about 15% of smokers
develop lung cancer. In this study, we seek to identify genetic effects that influence lung cancer
risk, either independently or jointly with smoking behavior. We hypothesize that novel genetic
and host factors influencing the susceptibility for lung cancer can be identified
by genotyping. We will pursue 3 aims. In Aim 1 we will (a) Genotype on bead arrays an
23,103 lung cancer cases and 23,103 unrelated controls on genome wide arrays in order to
identify genetic variants and (b) Validate selected SNPs in additional populations.
Validation studies will be conducted for selected variants to assure results are consistent
between genotyping or Sanger sequencing analysis. In Aim 2, we will Evaluate strength
of genetic effects using the additional genotypes generated in aim (1) and combine
with our existing 29,683 lung cancer cases and 55,586 controls. In this aim, we take
advantage of the larger population of samples to impute variants and perform
association analyses for inferred variants for a much larger collection. Finally in Aim 4,
we will Construct a risk prediction algorithm to improve the accuracy of the current lung
cancer risk models. These models will be valuable for refining the selection of individuals to
be enrolled in lung screening studies.
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