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.
We hypothesize that additional genetic factors can be identified that influence lung cancer risk by performing large scale genome wide association studies. We will also conduct further analytical studies to evaluate how these genetic factors influence risk and to develop polygenic risk scores that can help identify individuals at highest risk for lung cancer development.
