Genetic variants in pigmentation genes, pigmentary phenotypes, and risk of skin cancer in Caucasians

Authors

  • Hongmei Nan,

    Corresponding author
    1. Program in Molecular and Genetic Epidemiology, Department of Epidemiology, Harvard School of Public Health, Boston, MA
    2. Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
    • Program in Molecular and Genetic Epidemiology, Department of Epidemiology, Harvard School of Public Health, 677 Huntington Ave, Boston, MA 02115, USA
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    • 1

      Fax: +617-432-1722.

  • Peter Kraft,

    1. Program in Molecular and Genetic Epidemiology, Department of Epidemiology, Harvard School of Public Health, Boston, MA
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  • David J. Hunter,

    1. Program in Molecular and Genetic Epidemiology, Department of Epidemiology, Harvard School of Public Health, Boston, MA
    2. Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
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  • Jiali Han

    1. Program in Molecular and Genetic Epidemiology, Department of Epidemiology, Harvard School of Public Health, Boston, MA
    2. Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
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Abstract

Human pigmentation is a polygenic quantitative trait with high heritability. Although a large number of single nucleotide polymorphisms (SNPs) have been identified in pigmentation genes, very few SNPs have been examined in relation to human pigmentary phenotypes and skin cancer risk. We evaluated the associations between 15 SNPs in 8 candidate pigmentation genes (TYR, TYRP1, OCA2, SLC24A5, SLC45A2, POMC, ASIP and ATRN) and both pigmentary phenotypes (hair color, skin color and tanning ability) and skin cancer risk in a nested case-control study of Caucasians within the Nurses' Health Study (NHS) among 218 melanoma cases, 285 squamous cell carcinoma (SCC) cases, 300 basal cell carcinoma (BCC) cases and 870 common controls. We found that the TYR Arg402Gln variant was significantly associated with skin color (p-value = 7.7 × 10−4) and tanning ability (p-value = 7.3 × 10−4); the SLC45A2 Phe374Leu variant was significantly associated with hair color (black to blonde) (p-value = 2.4 × 10−7), skin color (p-value = 1.1 × 10−7) and tanning ability (p-value = 2.5 × 10−4). These associations remained significant after controlling for MC1R variants. No significant associations were found between these polymorphisms and the risk of skin cancer. We observed that the TYRP1 rs1408799 and SLC45A2 1721 C>G were associated with melanoma risk (OR, 0.77; 95% CI, 0.60–0.98 and OR, 0.75; 95% CI, 0.60–0.95, respectively). The TYR Ser192Tyr was associated with SCC risk (OR, 1.23; 95% CI, 1.00–1.50). The TYR haplotype carrying only the Arg402Gln variant allele was significantly associated with SCC risk (OR, 1.35; 95% CI, 1.04–1.74). The OCA2 Arg419Gln and ASIP g.8818 A>G were associated with BCC risk (OR, 1.50; 95% CI, 1.06–2.13 and OR, 0.73; 95% CI, 0.53–1.00, respectively). The haplotype near ASIP (rs4911414[T] and rs1015362[G]) was significantly associated with fair skin color (OR, 2.28; 95% CI, 1.46–3.57) as well as the risks of melanoma (OR, 1.68; 95% CI, 1.18–2.39) and SCC (OR, 1.54; 95% CI, 1.08–2.19). These associations remained similar after adjusting for pigmentary phenotypes and MC1R variants. The statistical power of our study was modest and additional studies are warranted to confirm the associations observed in the present study. Our study provides evidence for the contribution of pigmentation genetic variants, in addition to the MC1R variants, to variation in human pigmentary phenotypes and possibly the development of skin cancer. © 2009 UICC

Human pigmentation shows substantial variation both within and among human populations, with high heritability.1, 2 Ultraviolet (UV) exposure is one of the most important environmental variables partially influencing evolutionary selective pressure on human pigmentation.3 Melanin synthesized within melanosomes in melanocyte is the main contributor to human pigmentation. There are two main types of melanin: pheomelanin (red or yellow) and eumelanin (black or brown).4

It has been hypothesized that human pigmentation is tightly regulated by multiple pigmentation genes harboring a handful of genetic variants (Figure 1). The genes involved in the process of pigmentation, such as formation, transport and distribution of melanosome, have been identified through animal models.5 Melanin production is initiated by α-melanocyte-stimulating hormone (α-MSH), which is produced by proteolysis from a multicomponent precursor polypeptide encoded by the pro-opiomelanocortin (POMC) gene.6 A previously well-documented pigmentation gene, MC1R (melanocortin 1 receptor), encodes a 317-amino acid 7-pass transmembrane G-protein coupled receptor. As an agonist of MC1R, the induced POMC/α-MSH binds to MC1R, leading to elevated cAMP levels and resulting in eumelanin production.7, 8 Alternatively, the agouti signaling protein (ASIP) can also bind to the MC1R, blocking the MC1R-stimulated elevation of cAMP, and over-expression of ASIP produces a yellow coat color in mice.5, 9, 10 Attractin encoded by the ATRN gene is a low-affinity receptor for the ASIP protein product. A recessive color mutation mahogany (Atrnmg) was recognized as a modifier of agouti coat color in mice.11, 12 Tyrosinase (TYR) is required for melanization in both types of melanosome, whereas the tyrosinase-related protein 1 (TYRP1) is exclusive to the melanization of eumelanosome.13, 14 Hence, tyrosinase is a critical enzyme during melanosomal maturation and its high activity leads to the formation of eumelanosome.15, 16 The optimal activity of tyrosinase in human melanocytes requires an appropriate ionic environment, which is partially controlled by P-protein functioning as a pH exchange membrane channel.17, 18 The twelve transmembrane-spanning P-protein encoded by the OCA2 gene (human type II oculocutaneous albinism-related gene) was discovered in the “pink-eyed dilution” mouse mutant.19 In addition to P-protein, MATP, a membrane-associated transporter protein encoded by the SLC45A2 gene, has been considered as a sodium-hydrogen exchanger of melanosomes, regulating tyrosinase activity in human melanocyte.20 Another cation exchanger, SLC24A5, transports calcium or potassium ions into the melanosome and is involved in melanogenesis. It has been proposed that the human SLC24A5 gene is required for maturation of melanosome and has a role in skin pigmentation.21, 22

Figure 1.

The function of select pigmentation genes in the pigmentation pathway. Induction of POMC/α-MSH activates the MC1R, inducing cAMP production in melanocyte. This elevated signaling leads to eumelanin production, resulting in the maturation of the pheomelanosome to the eumelanosome. Attractin (ATRN) is a low-affinity receptor for agouti signaling protein (ASIP), an antagonist of MC1R. Some proteins, such as TYR, TYRP1, P-protein, SLC24A5 and MATP, are involved in inducing melanization of pheomelanosome or eumelanosome, as described in the text.

Lighter pigmentation is the host susceptibility risk factor for skin cancer.23 Although a large number of single nucleotide polymorphisms (SNPs) were identified in pigmentation genes, very few SNPs have been examined in relation to human pigmentary phenotypes and skin cancer risk. Recent genome-wide association studies on pigmentary traits and skin cancer risks (melanoma and basal cell carcinoma (BCC)) have generated additional information on both pigmentary phenotype related- and skin cancer related-genetic variants.24–28 In the present study, we evaluated the associations of 15 SNPs in 8 candidate pigmentation genes (TYR, TYRP1, OCA2, SLC24A5, SLC45A2, POMC, ASIP and ATRN) with both pigmentary phenotypes (hair color, skin color and tanning ability) and the risk of melanoma and nonmelanoma skin cancer (squamous cell carcinoma (SCC) and BCC) in a nested case-control study within the Nurses' Health Study (NHS).

Material and methods

Study population

The NHS was established in 1976, when 121,700 female registered nurses between the ages of 30 and 55, residing in 11 larger US states, completed and returned the initial self-administered questionnaire on their medical histories and baseline health-related exposures, forming the basis for the NHS cohort. Updated information has been obtained by questionnaires every 2 years. From May 1989 through September 1990, we collected blood samples from 32,826 participants in the NHS cohort. The distributions of risk factors for skin cancer were very similar in the subcohort of those who donated blood samples as in the overall cohort.29 Eligible cases in our study consisted of women with incident skin cancer from the subcohort who had given a blood specimen, including SCC and BCC cases with a diagnosis anytime after blood collection up to June 1, 1998, and melanoma cases up to June 1, 2000, that had no previously diagnosed skin cancer. All available pathologically confirmed melanoma and SCC cases and 300 self-reported BCC cases randomly selected from ∼ 2,600 available self-reported BCC cases were included. The validity of self-report of BCC is high in this medically sophisticated population (90%).30, 31 A common control series was randomly selected from participants who gave a blood sample and were free of diagnosed skin cancer up to and including the questionnaire cycle in which the case was diagnosed. One or two controls were matched to each case by year of birth (±1 year). All subjects were the US non-Hispanic Caucasian women in our study. The nested case-control study consisted of 218 melanoma cases, 285 SCC cases, a sample of 300 BCC cases from the large number of incident cases and 870 matched controls. The study protocol was approved by the Committee on Use of Human Subjects of the Brigham and Women's Hospital, Boston, MA.

Exposure data

We obtained information regarding skin cancer risk factors from the prospective biennial questionnaires and a retrospective supplementary questionnaire. Information on natural hair color at age 20 and childhood and adolescent tanning tendency were collected in the 1982 prospective questionnaire into 5 categories (black, dark brown, light brown, blonde and red) and 4 categories (practically none, light tan, average tan and deep tan), respectively. Question on ethnic group was ascertained in the 1992 questionnaire. In the skin cancer nested case-control study, natural skin color and other sun exposure-related information were collected by the retrospective supplementary questionnaire in 2002. The response rate of cases and controls were 92 and 89%, respectively. Information on natural skin color was classified into 3 categories (fair, medium and olive). In addition, the 11 states of residence of cohort members at baseline were grouped into 3 regions: Northeast (CT, MA, MD, NJ, NY and PA), North Central (MI and OH) and West and South (CA, TX and FL).

Laboratory assays

We genotyped 15 SNPs in 8 candidate pigmentation genes (TYR, TYRP1, OCA2, SLC24A5, SLC45A2, POMC, ASIP and ATRN) using the OpenArray™ SNP Genotyping System (BioTrove, Woburn, MA). Because the assay failed, we genotyped rs1393350 as a surrogate for the TYR Arg402Gln (rs1126809) (D' = 1 and r2 = 0.86) (http://snp500cancer.nci.nih.gov). Laboratory personnel were blinded to the case-control status, and 42 blinded quality control samples were inserted to validate genotyping procedures; concordance for the blinded samples was 100%. Primers, probes and conditions for genotyping assays are available upon request. The genotyping method for the MC1R variants was described previously.29

Statistical methods

We used the χ2 test to assess whether the genotypes for all 15 SNPs were in Hardy–Weinberg equilibrium among the controls.

The MC1R gene has been strongly associated with human pigmentary phenotypes, especially with red hair color.32–34 We previously reported the frequency distribution of 7 common MC1R variants among controls, including 3 “red hair color” (RHC) variants (Arg151Cys, Arg160Trp and Asp294His) and 4 “non-red hair color” (NRHC) variants (Val60Leu, Val92Met, Ile155Thr and Arg163Gln).29 To compare the contribution of these 15 SNPs to pigmentary phenotypes with that of the MC1R variants, we evaluated the associations between the MC1R variants and pigmentary phenotypes in parallel. We regressed an ordinal coding for skin color (1 = fair; 2 = medium; 3 = olive) or tanning ability (1 = practically none; 2 = light tan; 3 = average tan; 4 = deep tan) on an ordinal coding for genotype (0, 1 or 2 copies of SNP minor allele). For hair color, we used 2 different statistical models: (i) we tested the association between the ordinal genotype coding and an ordinal coding of hair color excluding the women with red hair (1 = black; 2 = dark brown; 3 = light brown; 4 = blonde) using linear regression; and (ii) we used logistic regression to test the association between the ordinal genotype coding and a binary red hair phenotype (red hair vs. non-red hair color). For the SLC45A2 Gln272Lys and 3 MC1R NRHC variants (Val92Met, Ile155Thr and Arg163Gln), we used Fisher's exact test for “red vs. non-red hair color” analysis because none of the women with red hair color carried the variant allele.

We evaluated the association between each genotype and skin cancer risk using unconditional logistic regression. We compared each type of skin cancer to the common control series to increase the statistical power.

In the haplotype analysis, haplotype frequencies and expected haplotype counts for each individual were estimated using a simple expectation-maximization algorithm, as implemented in SAS PROC HAPLOTYPE. The association analyses between haplotypes and binary pigmentary phenotypes and skin cancer risk were performed using the expectation-substitution technique.35 All statistical analyses were two-sided and carried out using SAS V9.1 (SAS Institute, Cary, NC).

Results

Descriptive characteristics of cases and controls

At the beginning of the follow-up of this nested case-control study, the women were between 43 and 68 years old, with a mean age of 58.7 years. The mean age at diagnosis of melanoma cases was 63.4 and that of SCC and BCC cases was 64.7 and 64.0, respectively. Basic characteristics of cases and controls in our study are presented in Table I. Detailed description and statistical tests were published previously.23 Briefly, skin cancer cases were more likely to possess red hair color and fair skin color. The childhood tanning ability of cases was less than that of controls. Women in the West and South regions were more likely to be diagnosed with SCC or BCC compared to those in Northeast. A family history of skin cancer was a risk factor for the three types of skin cancer. Those with skin cancers were more likely to have used sunlamps or attended tanning salons. Those with skin cancers had higher cumulative sun exposure while wearing a bathing suit and more lifetime severe sunburns that blistered.

Table I. Characteristics of Skin Cancer Cases and Controls in the Nested Case-Control Study
CharacteristicControls (n = 870)Melanoma cases (n = 218)SCC cases (n = 285)BCC cases (n = 300)
  1. The percentages may not sum to 100 due to rounding.

Age at diagnosis (mean, years)64.563.464.764.0
Natural hair color at age 20 (%)    
 Black or dark brown43.931.541.330.3
 Light brown40.042.534.645.7
 Blonde12.015.516.818.0
 Red2.910.55.24.7
Natural skin color (%)    
 Fair40.057.154.653.0
 Medium36.725.632.231.3
 Olive4.80.91.81.3
Tanning ability (%)    
 Practically none8.313.813.911.7
 Light tan21.129.524.125.5
 Average tan47.340.047.446.5
 Tan23.316.714.716.3
Geographic region at baseline (%)    
 Northeast55.258.051.749.3
 Northcentral23.416.917.120.3
 West and South21.425.131.130.3
Family history of skin cancer (%)25.136.535.742.7
Sunlamp use or tanning salon attendance (%)10.019.214.314.7
Highest tertile of cumulative sun exposure with a bathing suit (%)33.453.346.142.6
Number of lifetime severe sunburns (mean)5.49.67.88.2

Association between the 15 SNPs in pigmentation genes and pigmentary phenotypes

Information on the 15 SNPs in pigmentation genes is presented in Table II. We selected putative functional SNPs in the 6 pigmentation genes (TYR, OCA2, SLC45A2, POMC, ASIP and ATRN), including nonsynonymous SNPs and those in the promoter and UTR regions. For the SLC24A5 gene, the Ala111Thr (rs1426654) is monomorphic in HapMap CEU samples. The SNP rs17426596 is the only one with minor allele frequency >1% in the HapMap CEU samples. Recently, an eye-color variant in TYRP1 (rs1408799) was reported to be associated with melanoma risk.25, 27 A haplotype near ASIP carrying rs4911414 variant allele[T] and rs1015362 major allele[G] (hereafter called ASIP AH) was associated with pigmentary phenotypes (skin sensitivity to sun, burn and freckle) as well as the risks of melanoma and BCC.25, 27 These 3SNPs were evaluated for the association with pigmentary phenotypes and the risk of skin cancer as well in our study. The distributions of genotypes for these 15 SNPs were in Hardy-Weinberg equilibrium among controls. The participants of our study were from 11 states, which were grouped into 3 regions (Northeast, North Central, and West and South). The minor allele frequencies of the 15 genetic variants according to the 11 individual states are presented in Supporting Information Table 1. There were no significant differences in minor allele frequencies of these 15 SNPs across the 11 states (all p-values > 0.05).

Table II. 15 SNPS in the Selected Pigmentation Genes
SNPrs#GeneProteinMAF–controls (%)2MAF–CEU (%)3MAF–CHB/JPT (%)4MAF–YRI (%)5
  • 2

    The SNP rs1126809 failed the assay and the rs1393350 was genotyped instead (D′ = 1 and r2 = 0.86).

  • 3

    Minor allele frequency (MAF) was calculated among controls in this study.

  • 4

    MAF was based on the HapMap CEU (Utah residents with ancestry from northern and western Europe) samples.

  • 5

    MAF was based on the HapMap CHB and JPT (CHB: Han Chinese in Beijing, China; JPT: Japanese in Tokyo, Japan) samples.

  • 1

    MAF was based on the HapMap YRI (Yoruba in Ibadan, Nigeria) samples.

TYR Ser192Tyrrs1042602TYRTyrosinase354200
TYR Arg402Glnrs11268091TYRTyrosinase2200
TYR -6895 G>Ars13933501TYRTyrosinase281900
TYRP1 C>Trs1408799TYRP1Tyrosinase-related protein 132309878
OCA2 Arg305Trprs1800401OCA2P-protein6
OCA2 Arg419Glnrs1800407OCA2P-protein6700
SLC45A2 -1721 C>Grs13289SLC45A2MATP40323473
SLC45A2 Glu272Lysrs26722SLC45A2MATP20405
SLC45A2 Phe374Leurs16891982SLC45A2MATP4299100
SLC24A5 intron2 T>Crs17426596SLC24A5SLC24A54300
POMC 3′ UTR C>Trs1042571POMCPOMC, MSH, ACTH19
ASIP G>Trs4911414ASIPAgouti signaling protein31281913
ASIP G>Ars1015362ASIPAgouti signaling protein27231983
ASIP g.8818 A>Grs6058017ASIPAgouti signaling protein13
ATRN Ile426Thrrs17782078ATRNAttractin5400
ATRN Arg1152Lysrs3886999ATRNAttractin6400

We evaluated the associations between the 15 SNPs and pigmentary phenotypes including hair color, skin color and tanning ability among controls (Table III). We observed significant associations between SLC45A2 Phe374Leu (p-value = 2.4 × 10−7) and SLC45A2 Glu272Lys (p-value = 6.0 × 10−5), and hair color (black to blonde). We then mutually adjusted these 2 significant SLC45A2 SNPs and found that only the SLC45A2 Phe374Leu remained significant. The p-value for SLC45A2 Phe374Leu and SLC45A2 Glu272Lys was 8.0 × 10−4 and 0.15, respectively. The SLC45A2 Phe374Leu remained significantly associated with hair color after adjusting for MC1R variants (p-value = 3.3 × 10−6) (Supporting Information Table 2a and 2b). However, in the analysis of “red hair vs. non-red hair color,” there was no significant association between any of the 15 polymorphisms and red hair color (Table III). In contrast, the three MC1R RHC variants were significantly associated with red hair color phenotype.

Table III. Associations Between the 15 SNPs in the Selected Pigmentation Genes and Pigmentary Phenotypes among Controls
SNPHair color (black to blonde)Hair color (red vs. nonred)Skin colorTanning ability
βSEp-valueβSEp-valueβSEp-valueβSEp-value
  • The regression parameter beta refers to the mean change in scoring in hair color (black to blonde), skin color and tanning ability (or change in log odds of red hair for red hair analyses) per copy of the SNP minor allele.

  • 2

    TYR -6895 G>A (rs1393350) was genotyped instead.

  • 1

    Fisher's exact test was used. The β value was not calculated because none of the women with red hair color carried the variant allele.

TYR Ser192Tyr0.080.040.06−0.260.330.420.060.040.100.000.050.97
TYR Arg402Gln10.000.040.92−0.310.350.38−0.120.047.7E−04−0.160.057.3E−04
TYRP1 C>T (rs1408799)0.020.040.600.320.300.280.020.040.650.040.050.46
OCA2 Arg305Trp−0.080.080.310.110.620.850.150.070.040.020.100.84
OCA2 Arg419Gln−0.090.080.23−1.051.010.30−0.100.070.18−0.050.090.61
SLC45A2 -1721 C>G0.030.040.49−0.110.300.710.020.030.640.040.040.33
SLC45A2 Glu272Lys−0.580.146.0E−051.0020.440.131.1E−030.480.187.0E−03
SLC45A2 Phe374Leu−0.490.102.4E−070.510.600.390.480.091.1E−070.420.112.5E−04
SLC24A5 intron2 T>C0.110.100.260.970.540.08−0.080.080.34−0.030.120.78
POMC 3′ UTR C>T−0.060.050.230.090.360.79−0.030.040.52−0.010.060.86
ASIP G>T (rs4911414)0.020.040.680.330.300.27−0.110.031.4E−03−0.110.050.02
ASIP G>A (rs1015362)−0.060.040.15−0.370.350.29−0.010.040.760.000.050.96
ASIP g.8818 A>G−0.010.060.810.070.440.880.000.050.980.080.070.25
ATRN Ile426Thr0.040.080.650.500.540.35−0.070.070.31−0.020.100.87
ATRN Arg1152Lys0.050.080.500.450.530.40−0.080.070.24−0.020.100.82
MC1R variants 
 MC1R Val60Leu−0.030.050.63−1.911.010.06−0.060.050.23−0.130.060.05
 MC1R Val92Met−0.130.060.040.0120.000.061.00−0.100.070.18
 MC1R Arg151Cys0.170.080.032.210.402.6E−08−0.240.061.4E−04−0.460.091.4E−07
 MC1R Ile155Thr0.090.160.581.002−0.050.130.71−0.180.190.34
 MC1R Arg160Trp0.200.075.9E−032.140.345.0E−10−0.190.069.4E−04−0.280.084.1E−04
 MC1R Arg163Gln0.050.090.580.2520.010.090.92−0.070.110.54
 MC1R Asp294His0.270.160.081.940.599.6E−04−0.370.134.2E−03−0.670.182.1E−04

We found that the TYR Arg402Gln and SLC45A2 Phe374Leu were significantly associated with skin color (p-value = 7.7 × 10−4 and 1.1 × 10−7, respectively) and tanning ability (p-value = 7.3 × 10−4 and 2.5 × 10−4, respectively). The OCA2 Arg305Trp was associated with skin color (p-value = 0.04). These associations remained significant after controlling for the MC1R variants (Table III, Supporting Information Table 2a and 2b). The significant associations between the SLC45A2 Glu272Lys and skin color and tanning ability were eliminated after controlling for the SLC45A2 Phe374Leu (p-value = 0.97 and 0.49, respectively).

We found a significant association of ASIP G>T (rs4911414) polymorphism with skin color and tanning ability (p-value = 1.4×10−3 and 0.02, respectively). However, the association with tanning ability was eliminated after adjusting for the MC1R variants (p-value = 0.19), while the association with skin color remained significant (p-value = 0.01) (Table III, Supporting Information Table 2a and 2b). We also performed a global test to evaluate whether the haplotype frequencies were different between various pigmentary phenotypes (Supporting Information Table 3). Consistent with the single SNP analysis of ASIP G>T (rs4911414), the haplotype ASIP AH was significantly associated with fair skin color (OR, 2.28; 95% CI, 1.46–3.57) (p-value for global test, 0.003). This association remained significant after adjusting for the ASIP g.8818 A>G (OR, 2.54; 95% CI, 1.58–4.07).

All the significant associations described earlier with pigmentary phenotypes remained significant after controlling for the geographic regions (either by 11 states or 3 combined groups) (data not shown).

Association between the 15 SNPs in pigmentation genes and skin cancer risk

The main effect of each polymorphism was evaluated across the 3 types of skin cancer (Table IV). In the analyses controlling for age, we observed that the TYRP1 rs1408799 and SLC45A2-1721 C>G were associated with melanoma risk (OR, 0.77; 95% CI, 0.60–0.98 and OR, 0.75; 95% CI, 0.60–0.95, respectively); the TYR Ser192Tyr and ASIP rs4911414 were associated with SCC risk (OR, 1.23; 95% CI, 1.00–1.50 and OR, 1.29; 95% CI, 1.05–1.59, respectively); the OCA2 Arg419Gln and ASIP g.8818 A>G were associated with BCC risk (OR, 1.50; 95% CI, 1.06–2.13 and OR, 0.73; 95% CI, 0.53–1.00, respectively). These associations remained similar after adjusting for either pigmentary phenotypes (hair color, skin color and tanning ability) (Supporting Information Table 4) or MC1R variants (Supporting Information Table 5a and 5b) or skin cancer risk factors including constitutional susceptibility score (tertiles), family history of skin cancer, the number of lifetime severe sunburns that blistered, sunlamp use or tanning salon attendance, cumulative sun exposure while wearing a bathing suit and geographic regions (either by 11 states or 3 combined groups) (data not shown). None of those significant associations with skin cancer risk remained significant after the Bonferroni correction (all p-values > 0.05/45 (15 SNPs and 3 types of skin cancer) = 0.001).

Table IV. Associations Between the 15 SNPS in the Selected Pigmentation Genes and Skin Cancer Risk
SNPMelanomaSCCBCC
Additive OR1p for trendAdditive OR1p for trendAdditive OR1p trend
  • 2

    Additive OR was calculated based on the unconditional logistic regression adjusted for the age.

  • 1

    TYR -6895 G>A (rs1393350) was genotyped instead.

TYR Ser192Tyr1.18 (0.94–1.48)0.151.23 (1.00–1.50)0.051.08 (0.89–1.33)0.43
TYR Arg402Gln21.05 (0.83–1.32)0.711.07 (0.87–1.32)0.521.04 (0.84–1.27)0.74
TYRP1 C>T (rs1408799)0.77 (0.60–0.98)0.030.96 (0.78–1.18)0.710.95 (0.77–1.16)0.60
OCA2 Arg305Trp0.92 (0.56–1.52)0.760.87 (0.56–1.36)0.550.97 (0.63–1.50)0.91
OCA2 Arg419Gln1.33 (0.89–2.01)0.171.39 (0.97–2.01)0.071.50 (1.06–2.13)0.02
SLC45A2 -1721 C>G0.75 (0.60–0.95)0.011.08 (0.89–1.31)0.420.91 (0.75–1.11)0.36
SLC45A2 Glu272Lys1.19 (0.53–2.67)0.680.55 (0.21–1.45)0.231.04 (0.49–2.17)0.93
SLC45A2 Phe374Leu0.66 (0.34–1.29)0.220.76 (0.43–1.34)0.340.61 (0.33–1.11)0.10
SLC24A5 intron2 T>C0.75 (0.39–1.43)0.380.86 (0.50–1.48)0.580.80 (0.47–1.38)0.43
POMC 3′ UTR C>T0.99 (0.74–1.31)0.920.95 (0.74–1.22)0.680.95 (0.75–1.22)0.71
ASIP G>T (rs4911414)1.21 (0.96–1.51)0.101.29 (1.05–1.59)0.011.16 (0.95–1.42)0.14
ASIP G>A (rs1015362)0.89 (0.69–1.13)0.341.14 (0.92–1.41)0.231.06 (0.86–1.31)0.59
ASIP g.8818 A>G0.89 (0.64–1.24)0.500.79 (0.58–1.09)0.150.73 (0.53–1.00)0.05
ATRN Ile426Thr0.87 (0.52–1.45)0.591.14 (0.75–1.72)0.541.08 (0.72–1.62)0.72
ATRN Arg1152Lys0.86 (0.53–1.42)0.561.09 (0.72–1.63)0.691.09 (0.73–1.61)0.67

Haplotypes for the TYR, OCA2, SLC45A2 and ASIP genes and skin cancer risk

We performed the global test to evaluate the difference in haplotype frequencies between cases and controls (Table V). We found significant differences in TYR haplotype frequency for SCC (p-value = 0.007), OCA2 haplotype frequency for BCC (p-value = 0.03) and ASIP haplotype frequencies for melanoma and SCC (p-value = 0.008 and 0.004, respectively). For the TYR gene, the haplotypes that carried only 1 variant allele at the 2 sites were significantly associated with an increased risk of SCC. The adjusted ORs (95% CI) for the haplotype carrying only the Ser192Tyr or only the Arg402Gln variant alleles were 1.48 (1.16–1.89) and 1.35 (1.04–1.74), respectively. The Arg402Gln variant was not significantly associated with risk of SCC in the single SNP analysis. We observed that the haplotype carrying OCA2 Arg419Gln variant allele and the OCA2 Arg305Trp major allele was significantly associated with an increased risk of BCC (adjusted OR, 1.62; 95% CI, 1.13–2.32). For the ASIP gene, the haplotype AH was significantly associated with an increased risk of melanoma (OR, 1.68; 95% CI, 1.18–2.39) and SCC (OR, 1.54; 95% CI, 1.08–2.19). The ASIP rs4911414 variant allele was not significantly associated with melanoma risk in the single SNP analysis.

Table V. Haplotypes for SNPS in the TYR, OCA2, SLC45A2 and ASIP Genes and Skin Cancer Risk
TYRControls Melanoma CasesSCC2 CasesBCC Cases
ABn% n%n%n%
  • 0, common allele; 1, rare allele; Logistic regression adjusted for the age.

  • 3

    TYR -6895 G>A (rs1393350) was genotyped instead.–2p-value for global test for SCC is 0.007.

  • 4

    p-value for global test for BCC is 0.03.

  • 5

    p-value for global test for melanoma is 0.008.

  • 6

    p-value for global test for SCC is 0.004.

  • e

    AH means the ASIP haplotype carrying the rs4911414 variant allele [T] and the rs1015362 major allele [G].

0061838.0 13632.516431.220637.0
  Multivariate OR 1.001.001.00
1055133.9 15737.620639.419034.2
  Multivariate OR 1.34 (1.03–1.75)1.48 (1.16–1.89)1.05 (0.83–1.34)
0143826.9 12229.215028.715327.6
  Multivariate OR 1.29 (0.97–1.71)1.35 (1.04–1.74)1.06 (0.83–1.35)
11191.2 30.740.771.2
  Multivariate OR 0.43 (0.07–2.79)0.34 (0.05–2.30)0.89 (0.32–2.51)
A, Ser192Tyr; B, Arg402Gln1
OCA2Controls Melanoma CasesSCC CasesBCC3 Cases
ABn% n%n%n%
00141788.3 35187.346886.746585.2
  Multivariate OR 1.001.001.00
01945.9 317.7448.1519.3
  Multivariate OR 1.33 (0.88–2.03)1.40 (0.97–2.03)1.62 (1.13–2.32)
10935.8 205.0285.2305.5
  Multivariate OR 0.91 (0.54–1.51)0.91 (0.58–1.41)0.99 (0.64–1.53)
A, Arg305Trp; B, Arg419Gln.
SLC45A2ControlsMelanoma CasesSCC CasesBCC Cases
ABCn%n%n%n%
00096659.426865.531257.435762.1
   Multivariate OR1.001.001.00
10060137.013031.621639.720335.4
   Multivariate OR0.77 (0.61–0.97)1.11 (0.91–1.35)0.93 (0.76–1.13)
101231.440.981.540.7
   Multivariate OR0.54 (0.16–1.84)1.17 (0.48–2.84)0.48 (0.16–1.47)
Rare < 1%362.282.081.5101.7
   Multivariate OR0.84 (0.38–1.86)0.66 (0.29–1.50)0.75 (0.36–1.57)
A, -1721C>G; B, Glu272Lys; C, Phe374Leu.
ASIPControlsMelanoma4 CasesSCC5 CasesBCC Cases
 ABn%n%n%n%
 00102065.72536329460.833763.1
   Multivariate OR1.001.001.00
 1136623.69122.613227.313425.1
   Multivariate OR0.99 (0.76–1.29)1.25 (0.99–1.58)1.09 (0.87–1.38)
AH6101207.75213.05210.7489.0
   Multivariate OR1.68 (1.18–2.39)1.54 (1.08–2.19)1.22 (0.86-1.74)
 00483.161.661.2152.8
   Multivariate OR0.52 (0.21–1.29)0.43 (0.17–1.08)1.00 (0.54–1.83)
A, rs4911414; B, rs1015362.

Power calculation

The Quanto statistical software version 1.2.3 was used for power calculation.36 We calculated the power to detect the specified ORs at various allele frequencies of variant allele in additive models. The calculations were based on a two-sided alpha of 0.05, and the particular sizes of different phenotypic population groups presented in the Table I of our study. For melanoma (SCC or BCC), we have 80% power to detect an OR of 1.80 (1.72 or 1.70), 1.48 (1.42 or 1.41) and 1.35 (1.32 or 1.31) if the minor allele frequency is 5, 15 and 40%, respectively. For pigmentary phenotypes, we calculated the power to detect the difference between dark and light pigmentation: black/brown and blonde hair color, medium/olive and fair skin color and average/deep tan and practically none/light tan. For hair color (skin color or tanning ability), we have 80% power to detect an OR of 2.26 (1.99 or 1.90), 1.71 (1.52 or 1.50) and 1.52 (1.36 or 1.35) if the minor allele frequency is 5, 15 and 40%, respectively.

Discussion

Hair color and skin color show striking variations between human subgroups. The dark pigmentation and tanning response protect the skin from UV.37 To date, although more than 100 candidate pigmentation genes containing common genetic variants have been identified, only the variants in the MC1R gene have been consistently implicated in the variation of pigmentary phenotypes as well as skin cancer risk.5, 29, 34, 38–40 In our study only the 3 MC1R RHC variants were significantly associated with red hair color, supporting the major contribution of the MC1R gene to the red hair color phenotype, an autosomal recessive trait.28, 29, 33, 41 In addition, some genetic variants in the other pigmentation genes showed significant associations with non-red hair color (black to blonde) in our study, suggesting distinct mechanisms in the formation of non-red hair color and red hair color. Previous studies reported possible associations between some genetic variants evaluated in our study and pigmentary phenotypes. We summarized these studies in Supporting Information Table 6.

TYR Arg402Gln, a common polymorphism of tyrosinase, was correlated with reduced pigmentation of the retina and iris resulting from low tyrosinase activity.42 In addition to the associations of this SNP with skin color and tanning ability observed in our study, Sulem et al. reported that this SNP was associated with eye color and possibly with blond hair color.28 Mutations in murine SLC45A2 gene lead to hypopigmentation of the eyes and fur.43 Two nonsynonymous SNPs in this gene, SLC45A2 Phe374Leu and SLC45A2 Glu272Lys, were associated with darker pigmentary phenotypes in our study, which is consistent with a previous report.44 However, our multivariate analysis mutually adjusting for these 2 SNPs showed that the effect of SLC45A2 Glu272Lys on pigmentary phenotypes was explained by the variant SLC45A2 Phe374Leu. For the promoter polymorphism SLC45A2-1721 C>G, we did not detect any significant associations with pigmentary traits, while a previous study reported an association between this SNP and olive skin color.45

The deletion of OCA2 gene has been linked to reduced pigmentation of skin, hair and eyes in Prader-Willi Syndrome.46 Two genetic variants in this gene, Arg305Trp and Arg419Gln, have been correlated with dark eye color.47 However, these 2 SNPs were not associated with pigmentary phenotypes measured in our study, such as hair color, skin color and tanning ability, except that the Arg305Trp was marginally associated with skin color. A polymorphism in the 3' untranslated region of ASIP gene (g.8818 A>G) has been previously reported to be associated with dark pigmentary phenotypes among populations of African Americans or European ancestry.48–51 Although we did not find a significant association of this SNP with any of the pigmentary phenotypes, our haplotype analysis showed that the haplotype ASIP AH was significantly associated with fair skin color and this association remained significant after adjusting for ASIP g.8818 A>G. Similarly, Sulem et al. reported that the ASIP AH haplotype remained significant for the pigmentary traits, such as burning and freckling, after adjusting for ASIP g.8818 A>G, while the association of ASIP g.8818 A>G with pigmentary traits were eliminated after adjusting for the haplotype.27

We evaluated the contributions of genetic variants in the pigmentation genes not only to pigmentary phenotypes but also to the risks of 3 types of skin cancers among US Caucasians, whereas most previous studies only evaluated the relation of those genetic variants to the pigmentary traits. Ours is the first report evaluating the association between genetic variants in the pigmentation genes and the 3 types of skin cancer simultaneously. We summarized the results from previous studies assessing the associations of the SNPs evaluated in our study with melanoma risk in Supporting Information Table 7. Only 1 previous study examined pigmentation genes with BCC risk.25 Overall, in our study, the associations observed with an altered risk of at least 1 skin cancer in the single SNP analysis remained similar after adjusting for either pigmentary phenotypes or MC1R variants, suggesting that these genetic variants play a role in development of skin cancer beyond their influence on pigmentary phenotypes. Furthermore, most of these genetic variants were not associated with the pigmentary phenotypes. The genes involved in pigmentation process may also contribute to other cellular responses to UV exposure. For example, the immune and inflammatory responses to UV exposure are at least partially mediated by the MC1R gene.52–54 Also, the OCA2 gene increases cellular sensitivity to toxic compounds in addition to its role in controlling melanosome biogenesis.55 In addition, tyrosinase is recognized as melanoma-associated antigen by cytotoxic T lymphocytes.56 It is therefore plausible that these genetic variants associated with skin cancer risks may influence other cellular responses leading to skin cancer development. However, we cannot rule out the possibility that the associations with skin cancer risk could be due to chance considering the number of tests performed. Therefore, we should be cautious when interpreting the results on skin cancer risks.

Recently, Gudbjartsson et al. reported a significant association of the TYR 402Gln variant and the ASIP AH haplotype with the increased risks of melanoma and BCC.25 The haplotype analysis performed in our study showed that the risk estimate associated with the TYR 402Gln was elevated for melanoma (OR, 1.29; 95% CI, 0.97–1.71) and SCC (OR, 1.35; 95% CI, 1.04–1.74), which was not observed in the single SNP analysis. For the ASIP AH haplotype, in addition to the association with an increased risk of melanoma, we also found significant association with an increased risk of SCC. The inverse association between the OCA2 Arg305Trp polymorphism and melanoma risk among French Caucasians reported by Jannot et al. is inconsistent with the result of our study.57 We did not find any significant associations between this SNP and 3 types of skin cancer risks in our study.

Two of the 4 regions that we found to be associated with variation in pigmentary phenotypes among Europeans (SLC45A2 and OCA2) show strong evidence of recent positive selection, based on a comparison of allele frequencies across samples from 3 continental populations (Africa, Asia and Europe).58 Allele frequencies for the SLC45A2 Phe374Leu polymorphism have been shown to vary greatly across continental populations,58 and less drastically within Europe.59 The TYR SNP rs1126809 Arg402Gln also shows significant differences in allele frequency across the HapMap CEU, CHB, JPT and YRI panels. This SNP and its surrogate SNP rs1393350 were monomorphic in CHB, JPT and YRI panels (the minor allele was absent from these samples).

Eight SNPs out of the 15 SNPs were either genotyped as part of the Cancer Genetic Markers of Susceptibility (CGEMS) breast cancer genome-wide association scan or could be imputed with high confidence using the observed genotypes and the HapMap phased data.60 The CGEMS breast cancer scan consists of 1,200 cases of breast cancer and 1,200 controls from the Nurses' Health Study of European ancestry genotyped using the Illumina 500k HumanHap platform.61 To assess the potential for within-Europe population stratification bias, we examined the association between these 8 SNPs and the top principal components of genetic variation inferred from the CGEMS genome-wide scan data.62, 63 For example, the TYR rs1393350 SNP, which was strongly associated with skin color and tanning ability in the skin cancer controls, was also significantly associated with 2 of the top 10 principal components of genetic variation (Supporting Information Table 8), suggesting that allele frequency for this marker also vary among European populations. This SNP was strongly associated with tanning ability (information on the skin color is not recorded in the CGEMS data) in the CGEMS genome-wide association study samples (p-value = 5.8 × 10−11) and this association remained significant after adjusting for the top four principal components (p-value = 8.0 × 10−8). In fact, only 3 of the top 10 principal components were associated with tanning ability, and together these explained 4.5% of the residual variation in tanning ability, while the TYR rs1126809 (a surrogate for Arg402Gln) polymorphism explained 1.5% of the residual variation in tanning ability beyond the effect of top 3 principal components. We believe it is unlikely that the strong associations we see between these markers and pigmentary phenotypes are solely due to population stratification bias. Rather it is likely that differences in the distribution of pigmentary phenotypes across Europe are due in part to differences in allele frequencies at these loci and other as-yet-unknown loci.

Population stratification may be a particularly important issue in assessment of the association of the pigmentation genetic polymorphism with skin cancer risk because of the variation of the allele frequency and the predominance of the disease among light pigmented people, even among European populations. However, the ancestry informative variants mentioned above were not associated with any type of skin cancer, suggesting that the associations of other variants with skin cancer risk is not due to bias rooted in stratification, a possibility that is also made less likely by the fact that these associations remained significant after controlling for the geographic regions (either by 11 states or 3 combined groups). However, these modest associations require further replication in other populations.

One limitation of our study would be the modest statistical power. It is possible that the modest effects of some genetic variants cannot be detected due to insufficient statistical power. Another limitation of our study was that we used self-reported pigmentary phenotypes. Such assessment may miss certain aspects of pigmentary phenotypes influenced by these genetic variants, such as melanin content and composition.64, 65 In addition, misclassification is always a concern in epidemiologic studies. The high education level and interest in health of cohort members allows high quality information to be collected. Test-retest reliability of collecting phenotypic factors from questionnaires is moderate to substantial, including skin color, tanning/burning tendency and sunburn history.66–68

In conclusion, our study evaluated the associations between genetic variants in the pigmentation genes and pigmentary phenotypes and skin cancer risk. As this reported is one of the very few studies examining such associations, additional studies are warranted to confirm these associations. This information may be useful in understanding the involvement of different pigmentation genes in Caucasian pigmentary phenotypes and skin cancer risk.

Acknowledgements

The authors thank Dr. Hardeep Ranu and Ms. Pati Soule for their laboratory assistance, and Ms. Carolyn Guo and Ms. Constance Chen for their programming support. The authors are indebted to the participants in the Nurses' Health Study for their dedication and commitment.

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