Genome-wide association studies of pigmentation, sun sensitivity, and skin cancer phenotypes have identified new loci associated with these phenotypes, some of which are shared and some of which are distinct. There are two main subsets of SNPs associated with melanoma risk, one associated with melanoma and pigmentation and one associated with melanoma and nevus count. SNPs in these subsets did not overlap, suggesting that there may be unique pathways to melanoma development. There also appears to be at least two pathways to BCC development: a pigmentation-dependent pathway and a pigmentation-independent pathway. Interestingly, all of the SNPs associated with both BCC and melanoma, except the one around TERT-CLPTM1L,
are also associated with pigmentation, including SLC45A2, TYR, MC1R
, and ASIP
, suggesting that BCC and melanoma share a common pathway to development via pigmentation. An alternative possibility is that these SNPs are associated with pigmentation traits that predispose to skin cancer (melanoma and BCC) but that they do not themselves mechanistically lead to the development of skin cancer. A major limitation for the GWAS reviewed in this manuscript is that all but two skin cancer GWAS (Stacey et al., 2008
and Stacey et al., 2009
) did not examine or adjust for skin cancer risk factors when reporting risk loci. Replication studies that adjusted for pigmentation did not consistently confirm associations for some SNPs with melanoma and BCC, including TYRP1, TYR
, and ASIP
(Duffy et al., 2010
and Nan et al., 2009a
). Thus, future studies of these genes should focus on whether subjects carrying these SNPs are at increased risk of melanoma and/or BCC risk through pigmentation alone or through pathways independent of pigmentation.
In the GWAS of nevus count, it did appear that melanoma risk was mediated by nevi, since the association between SNPs and melanoma risk was diminished following adjustment for nevus count (Falchi et al., 2009
). In this study, the number of nevi was not associated with frequency of sunburns or skin type; however, other pigmentation factors were not tested for association with nevus count. Similarly, SNPs found associated with nevus count were not tested for association with pigmentation or cutaneous UV-response. Therefore, we cannot definitively conclude that the association between nevus count and melanoma is independent of pigmentation or cutaneous UV-response. In future studies, pigmentation factors and other risk factors for melanoma should be fully accounted for so as to conclusively determine whether the genetic associations with skin cancer are direct or are mediated by pigmentation, nevi, or both. Further studies of the SNPs associated with BCC but not pigmentation may uncover novel pathways for BCC development. Finally, SNPs associated with pigmentation but not other phenotypes in these GWAS should be further examined and tested for skin cancer associations in additional populations.
GWAS have been a powerful tool for identifying novel loci associated with pigmentation and skin cancer phenotypes. Interestingly, many novel associations were found when significant loci identified in one GWAS were replicated for a different phenotype. It was difficult to perform a meta-analysis given varying phenotypic definitions of pigmentation and sun sensitivity traits, suggesting that future studies should employ consistent definitions and categorizations, when possible, to allow for data harmonization.
GWAS do have two major intrinsic limitations; first, only a relatively small number of SNPs are contained on the chip used for genotyping, leaving large numbers of SNPs untested for associations. Second, the identified loci may not be the causal variants, so associated SNPs are not necessarily causally related to the examined phenotype. Studies with MC1R
demonstrate these limitations. The MC1R
RHC alleles are not on the common platforms that were used for these GWAS. As noted for GWAS of red hair color, in all GWAS reviewed here, a signal on chromosome 16 near MC1R
prompted further genotyping of the RHC alleles and multivariable analyses demonstrating that the signals were due to RHC alleles (Han et al., 2008
; Nan et al., 2009b
; Sulem et al., 2007
; and Sulem et al., 2008
). Interestingly, some of the MC1R
SNPs identified in GWAS were not in linkage disequilibrium with the RHC alleles, suggesting that they acted independently; however, in multivariable analyses, only the association with RHC alleles remained significant. Therefore, GWAS results must be interpreted with caution: significant GWAS findings do not necessarily identify the causal variants or SNPs in linkage disequilibrium with the causal variants. Supporting this cautionary note is a recent study showing that the most significant SNP from a GWAS of a well-studied disease, sickle cell anemia, was located 9kb from the known causal variant; furthermore, these authors suggest that rare causal mutations may create ‘synthetic’ associations in GWAS that are credited to common variants (Dickson et al., 2010
). This signifies the importance of prior knowledge of risk factors (like MC1R
for melanoma), even in an apparent unbiased, or agnostic, approach and indicates that other tools such as direct genomic sequencing examining rarer variants should be considered in future studies.
In conclusion, although there are limitations, GWAS have provided important information regarding loci associated with pigmentation phenotypes and skin cancer. These data can guide future studies using sequencing and other techniques to identify causal variants, and generate hypotheses regarding biological mechanisms and functional consequences of the identified variants.