Collective effects of common SNPs and improved risk prediction in lung cancer

Abstract

AbstractLung cancer is the leading cause of cancer deaths in both men and women in the US. While most sporadic lung cancer cases are related to environmental factors such as smoking, genetic susceptibility may also play an important role and a number of lung cancer associated single nucleotide polymorphisms (SNPs) have been identified although many remain to be found. The collective effects of genome wide minor alleles of common SNPs, or the minor allele content (MAC) in an individual, have been linked with quantitative variations of complex traits and diseases. Here we studied MAC in lung cancer using previously published SNP datasets and found higher MAC in cases relative to matched controls. A set of 25883 SNPs with MA (MAF < 0.5) more common in cases (P < 0.1) was found to have the best predictive accuracy. A weighted risk score calculated by using this set can predict 2.6% of lung cancer cases (100% specificity). These results identify a novel genetic risk element or higher MAC in lung cancer susceptibility and provide a useful genetic method to identify a small fraction of lung cancer cases.