A Novel Pathway-Based Approach Improves Lung Cancer Risk Prediction Using Germline Genetic Variations.

ABSTRACT:

Background

Although genome-wide association studies (GWAS) have identified many genetic variants that are strongly associated with lung cancer, these variants have low penetrance and serve as poor predictors of lung cancer in individuals. We sought to increase the predictive value of germline variants by considering their cumulative effects in the context of biologic pathways.

Methods

For individuals in the Environment and Genetics in Lung Cancer Etiology study (1,815 cases/1,971 controls), we computed pathway-level susceptibility effects as the sum of relevant SNP variant alleles weighted by their log-additive effects from a separate lung cancer GWAS meta-analysis (7,766 cases/37,482 controls). Logistic regression models based on age, sex, smoking, genetic variants, and pri

SUBMITTER: Qian DC 

PROVIDER: S-EPMC5492390 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature