Common colorectal cancer risk alleles contribute to the multiple colorectal adenoma phenotype, but do not influence colonic polyposis in FAP

Abstract

The presence of multiple (5-100) colorectal adenomas suggests an inherited predisposition, but the genetic aetiology of this phenotype is undetermined if patients test negative for Mendelian polyposis syndromes such as familial adenomatous polyposis (FAP) and MUTYH-associated polyposis (MAP). We investigated whether 18 common colorectal cancer (CRC) predisposition single-nucleotide polymorphisms (SNPs) could help to explain some cases with multiple adenomas who phenocopied FAP or MAP, but had no pathogenic APC or MUTYH variant. No multiple adenoma case had an outlying number of CRC SNP risk alleles, but multiple adenoma patients did have a significantly higher number of risk alleles than population controls (P=5.7 × 10(-7)). The association was stronger in those with ≥10 adenomas. The CRC SNPs accounted for 4.3% of the variation in multiple adenoma risk, with three SNPs (rs6983267, rs10795668, rs3802842) explaining 3.0% of the variation. In FAP patients, the CRC risk score did not differ significantly from the controls, as we expected given the overwhelming effect of pathogenic germline APC variants on the phenotype of these cases. More unexpectedly, we found no evidence that the CRC SNPs act as modifier genes for the number of colorectal adenomas in FAP patients. In conclusion, common colorectal tumour risk alleles contribute to the development of multiple adenomas in patients without pathogenic germline APC or MUTYH variants. This phenotype may have 'polygenic' or monogenic origins. The risk of CRC in relatives of multiple adenoma cases is probably much lower for cases with polygenic disease, and this should be taken into account when counselling such patients.

Figure 1

Histograms comparing the risk score distribution in multiple adenoma cases (1) and controls (0). A simple count of an individual's total number of high-risk CRC alleles, without taking differing SNP effect sizes into account, yielded similar results.