Cancers, including cutaneous melanoma, can cluster in families.,In addition to environmental etiological factors such as ultraviolet radiation, cutaneous melanoma has a strong genetic component.,Genetic risks for cutaneous melanoma range from rare, high-penetrance mutations to common, low-penetrance variants.,Known high-penetrance mutations account for only about half of all densely affected cutaneous melanoma families, and the causes of familial clustering in the remainder are unknown.,We hypothesize that some clustering is due to the cumulative effect of a large number of variants of individually small effect.,Common, low-penetrance genetic risk variants can be combined into polygenic risk scores.,We used a polygenic risk score for cutaneous melanoma to compare families without known high-penetrance mutations with unrelated melanoma cases and melanoma-free controls.,Family members had significantly higher mean polygenic load for cutaneous melanoma than unrelated cases or melanoma-free healthy controls (Bonferroni-corrected t-test P = 1.5 × 10−5 and 6.3 × 10−45, respectively).,Whole genome sequencing of germline DNA from 51 members of 21 families with low polygenic risk for melanoma identified a CDKN2A p.G101W mutation in a single family but no other candidate high-penetrance melanoma susceptibility genes.,This work provides further evidence that melanoma, like many other common complex disorders, can arise from the joint action of multiple predisposing factors, including rare high-penetrance mutations, as well as via a combination of large numbers of alleles of small effect.
It is unclear to what degree genomic and traditional (phenotypic and environmental) risk factors overlap in their prediction of melanoma risk.,We evaluated the incremental contribution of common genomic variants (in pigmentation, nevus, and other pathways) and their overlap with traditional risk factors, using data from two population-based case-control studies from Australia (n = 1,035) and the United Kingdom (n = 1,460) that used the same questionnaires.,Polygenic risk scores were derived from 21 gene regions associated with melanoma and odds ratios from published meta-analyses.,Logistic regression models were adjusted for age, sex, center, and ancestry.,Adding the polygenic risk score to a model with traditional risk factors increased the area under the receiver operating characteristic curve (AUC) by 2.3% (P = 0.003) for Australia and by 2.8% (P = 0.002) for Leeds.,Gene variants in the pigmentation pathway, particularly MC1R, were responsible for most of the incremental improvement.,In a cross-tabulation of polygenic by traditional tertile risk scores, 59% (Australia) and 49% (Leeds) of participants were categorized in the same (concordant) tertile.,Of participants with low traditional risk, 9% (Australia) and 21% (Leeds) had high polygenic risk.,Testing of genomic variants can identify people who are susceptible to melanoma despite not having a traditional phenotypic risk profile.