Genome-wide association studies have identified a large number of single nucleotide polymorphisms (SNPs) associated with a wide array of cancer sites. Several of these variants demonstrate associations with multiple cancers, suggesting pleiotropic effects and shared biological mechanisms across some cancers. We hypothesised that SNPs previously associated with other cancers may additionally be associated with colorectal cancer. In a large-scale study, we examined 171 SNPs previously associated with 18 different cancers for their associations with colorectal cancer.We examined 13 338 colorectal cancer cases and 40 967 controls from three consortia: Population Architecture using Genomics and Epidemiology (PAGE), Genetic Epidemiology of Colorectal Cancer (GECCO), and the Colon Cancer Family Registry (CCFR). Study-specific logistic regression results, adjusted for age, sex, principal components of genetic ancestry, and/or study specific factors (as relevant) were combined using fixed-effect meta-analyses to evaluate the association between each SNP and colorectal cancer risk. A Bonferroni-corrected p value of 2.9210(-4) was used to determine statistical significance of the associations.Two correlated SNPs–rs10090154 and rs4242382–in Region 1 of chromosome 8q24, a prostate cancer susceptibility region, demonstrated statistically significant associations with colorectal cancer risk. The most significant association was observed with rs4242382 (meta-analysis OR1.12; 95% CI 1.07 to 1.18; p1.7410(-5)), which also demonstrated similar associations across racial/ethnic populations and anatomical sub-sites.This is the first study to clearly demonstrate Region 1 of chromosome 8q24 as a susceptibility locus for colorectal cancer; thus, adding colorectal cancer to the list of cancer sites linked to this particular multicancer risk region at 8q24.
Posted in featured publications and tagged Aged, Chromosomes, Human, Pair 8, Colorectal Neoplasms, Female, Genetic Markers, Genetic Pleiotropy, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotyping Techniques, Humans, Logistic Models, Male, Middle Aged, Polymorphism, Single Nucleotide, Principal Component Analysis, Registries, Risk Factors.