Contribution of MC1R Genotype and Novel Common Genomic Variants to Melanoma Risk Prediction

Abstract

Abstract Genome-wide association studies have identified numerous common genomic variants associated with increased susceptibility to melanoma, but there is limited knowledge about the utility of adding them to risk prediction models for melanoma. Individuals diagnosed at a young age might have an underlying genetic susceptibility to melanoma, and young adulthood is a key age period for targeting primary prevention strategies for melanoma. Aim: To evaluate the contribution of melanocortin-1 receptor (MC1R) gene variants and novel common genomic variants to melanoma risk prediction, among young Australian adults. Methods: The sample included 552 cases with invasive cutaneous melanoma diagnosed between ages 18–39 years and 405 controls from an Australian population-based, case-control-family study. MC1R genotype was sequenced, and through a genome-wide association study we obtained genotype data for single nucleotide polymorphisms from 18 selected gene regions. Measures of discriminatory accuracy included the area under receiver operating characteristic curves (AUC) and net reclassification improvement (NRI), calculated based on predicted probabilities of melanoma from unconditional logistic regression models. We used 10-fold cross-validation and bootstrap methods to assess internal validation. Results: The AUC increased from 0.76 (95% CI 0.73–0.79) for the non-genetic multivariate model containing demographic and self-reported risk factors (UV exposure, phenotype, nevi, etc), to 0.81 (95% CI 0.78–0.84) for the genetic model that additionally included MC1R genotype and novel common genomic variants. The combined contribution to the AUC of the novel common genomic variants identified through genome-wide association studies was similar to that contributed from the known common variants in MC1R and CDKN2A. Inclusion of genomic variants in the multivariate model improved the quartile classification of predicted risk (NRI) by a net 17% (95% CI 9–24) compared to the non-genetic model. Conclusions: Our results suggest that MC1R and other common genomic variants could considerably improve risk prediction models for early-onset melanoma, and may have a role in primary prevention of melanoma.