Abstract
Background: The Melanocortin 1 Receptor (MC1R) contributes to pigmentation, an important risk factor for developing melanoma. Evaluating SNPs in MC1R and association with race/ethnicity, skin type, and perceived cancer risk in a New Mexico (NM) population will elucidate the role of MC1R in a multicultural population.
Methods: We genotyped MC1R in 191 NMs attending a primary care clinic in Albuquerque. We obtained individuals' self-identified race/ethnicity, skin type, and perceived cancer risk. We defined genetic risk as carriage of any one or more of the nine most common SNPs in MC1R.
Results: We found that one MC1R SNP, R163Q (rs885479), was identified in 47.6% of self-identified Hispanics and 12.9% of non-Hispanic whites (NHW), making Hispanics at higher “genetic risk” (as defined by carrying one of the MC1R common variants). When we deleted R163Q from analyses, Hispanics were no longer at higher genetic risk (33.3%) compared with NHW (48.3%), consistent with melanoma rates, tanning ability, and lower perceived risk. Hispanics had a perceived risk significantly lower than NHW and a nonsignificant better tanning ability than NHW.
Conclusions: The R163Q variant in MC1R may not be a risk factor for melanoma among NM Hispanics. This suggestion points to the need to carefully interpret genetic risk factors among specific populations.
Impact: Genetic risk cannot be extrapolated from Northern European populations directly to non-European populations.
Introduction
In 2019, it is estimated that 96,480 new cases of invasive melanoma, the most deadly form of skin cancer, will be diagnosed in the United States, and 7,230 people are expected to die of the disease (1). The most recent data for the United States indicates there were approximately 6,623 cases of melanoma among Hispanics in 2015 (2). While there are reports of increasing incidence among Hispanics from California (2) and Florida (3), data from 2003 to 2012 show an overall 1.4% decline in the incidence of melanoma in this population (2) with a stable frequency of deeper lesions. Overall, the lifetime risk of getting melanoma is about 2.6% (1 in 38) for whites and 0.58% (1 in 172) for Hispanics (1). Although fewer Hispanics are diagnosed with melanoma than non-Hispanic whites (NHW), they are more often diagnosed at an advanced stage (4) and at a younger age (56 vs. 63; ref. 5). Hispanics are one of the fastest growing populations in the United States, further highlighting that understanding their risk for melanoma is an important public health issue.
The major risk factor for melanoma is pigmentation. Melanin, a major determinant of pigmentation important in skin, hair, and eye color (6), is primarily located on the surface of melanocytes. Individuals with less eumelanin, the darker pigment, and more pheomelanin, the lighter pigment, are at highest risk for cutaneous malignant melanoma. Individuals with more pheomelanin generally tan poorly and potentially perceive themselves at high risk, whereas those with more eumelanin tan more easily (6) and potentially perceive themselves to be at lower risk for melanoma.
The melanocortin 1 receptor (MC1R), a G-protein–coupled receptor, plays a major role in skin and hair pigmentation (7). MC1R is polymorphic, and some of these SNPs may alter the receptor's function (8). A number of SNPs have been associated with cutaneous melanoma, basal cell carcinoma, and squamous cell carcinoma risk (9, 10). Few studies have examined MC1R SNPs in U.S. Hispanic populations, where their frequency and impact are unknown, particularly in relation to phenotype.
New Mexico's population comprises 48% Hispanic (1.8% of all Hispanics in the United States, the largest Hispanic statewide population nationally), and has a unique mixture of individuals who identify as Spanish and/or recent mixed Native American and European ancestry (11, 12). New Mexico therefore provides a distinctive study population for characterizing MC1R variants.
This work aimed to determine whether presence of SNPs in the MC1R gene, defined as higher than average genetic risk for melanoma, are associated with self-identified race/ethnicity, skin type, and perceived cancer risk in a New Mexico (NM) population. A better understanding of genetic risk in the Hispanic population will guide the development of public health interventions to raise skin cancer awareness.
Materials and Methods
Data were collected as part of a randomized controlled trial (NCT03130569) examining interest, uptake, and outcomes associated with an offer of testing for MC1R gene variants associated with increased melanoma risk (10). Study enrollment methods have been described previously (13, 14). In brief, 600 participants were recruited from a primary care clinic in Albuquerque, New Mexico (Supplementary Table S1). They were randomized 5:1 to an intervention group which received an invitation to assess their genetic risk for melanoma using MC1R genotyping compared with a control group where the participants were not offered genetic assessment until after the follow-ups in the intervention group were complete (n = 499 in the intervention arm; n = 101 in the control arm). Participants in the intervention arm were balanced across self-reported Hispanic (n = 242) versus NHW ethnicity (n = 220; 36 reported “other” ethnicity; 1 did not report ethnicity). Participants in the control group were evenly distributed across self-reported Hispanic (n = 44) versus NHW ethnicity (n = 44;13 reported “other”). Each participant provided informed consent as approved by the University of New Mexico Health Sciences Center Institutional Review Board.
Baseline surveys were completed in-person and have been published. Measures used in this study included (i) phenotype (ability to tan; ref. 15 and history of sunburn), (ii) demographics (ethnicity, race, age, income, and education level), (iii) family and personal history of skin cancer, and (iv) perceived skin cancer risk compared with persons of the same age and sex. Participants in the intervention arm were given access to the study website with information about skin cancer prevention and genetic testing (232, or 46%, accessed the website and 166 of those sent saliva samples for genetic testing). The controls were offered access to the study website, and the potential for genetic testing, after the final follow-up assessment (25 sent saliva samples for genetic testing). Genetic risk was assigned on the basis of the nine most common and most-studied MC1R genotypes (10). These included V60L, D84E, V92M, R142H, R151C, I155T, R160W, R163Q, and D294H. The entire MC1R gene was sequenced, but only these genotypes were used to assess risk. If an individual had one or more of the nine SNPs, they were told that they had a “higher risk” variant. If a participant had none of the nine, then they were told that they were at “average” risk. Results from the genetic tests were sent by email or mail to participants. Two weeks after receiving their results, those in the intervention arm were contacted to complete a survey regarding their responses to receiving their results.
MC1R genotyping
Saliva samples were mailed to the University of New Mexico Molecular Epidemiology Laboratory. MC1R genotypes were described in Kanetsky and colleagues (16). Genomic DNA was isolated from buccal cells using a version of the QIAamp DNA Mini Kit protocol by the manufacturer (Qiagen, Inc.). Using standard PCR technique, an Eppendorf Mastercycler gradient thermocycler was used to amplify the entire 951-nucleotide MC1R coding region. All amplified products were directly sequenced on a 3730 Series Genetic Analyzer (Applied Biosystems) using BigDye Terminators (Applied Biosystems) according to the manufacturer's specifications. PCR primers consisted of a set of two oligonucleotides: 5′-GCCATGAGCACCAGCATAG-3′ and 5′-GACCACACAAATATCACCACCT-3′ and a set of four sequencing primers: 5′-TCGTCTTCAGCACGCTCTTC-3′; 5′-TTTAAGGCCAAAGCCCTGGT-3′; 5′-AACCTGCACTCACCCATGTA-3′; and 5′-CTGCAGGTGATCACGTCAAT. MC1R chromatograms were read aided by Finchtv sequencing software version 1.5 (Geospiza Inc.). All MC1R genotypes were double entered into a customized Excel sheet and a RedCAP database. We used the MC1R consensus sequence (GenBank accession no. AF326275) nomenclature and definitions suggested by Pasquali and colleagues (10) to group MC1R variants by risk.
Univariate associations (OR) were evaluated for MC1R variants and self-reported race and ethnicity. Unconditional logistic regression was used to obtain adjusted estimates. Models were adjusted for age, sex, and family history of skin cancer. Both unadjusted and adjusted ORs and corresponding 95% confidence intervals (CI) are presented. Analyses were carried out in SAS 9.4 (SAS). We restricted analyses to Hispanics and NHW given the “other” category (Asian, American Indian or Alaskan Native, Native Hawaiian/Pacific Islander, African American, or other) that provided a sample for genotyping represented a small group (n = 12).
Results
Characteristics of those genotyped, on the basis of 63 Hispanic and 116 NHW individuals (159 from the intervention group and 20 from the control group who requested genetic testing, excluding “other” category n = 12) show that in this analysis Hispanics compared with NHW are more likely to be female, have less education beyond high school, have a lower income (borderline significant), and be of similar age (Table 1).
Comparison of key demographic characteristics between Hispanics and NHW who were genotyped (n = 179)
Genetic results comparing Hispanics and NHW showed carriage of several different variants. The variant R163Q (rs885479) was more common among Hispanic individuals and V92M (rs2228479) and R160W (rs1805008) were more common among NHW (Table 2).
Comparison of MC1R genotype in Hispanic and NHWa
Only 22.2% of Hispanics perceived themselves to be at increased risk of skin cancer; in contrast, 46.6% of NHW felt themselves to be at increased risk of skin cancer. On the basis of the genotyping of the nine MC1R variants, 63.5% of Hispanics and 56.4% of NHW are at increased genetic risk. When R163Q was excluded from genetic risk assessment, the number of Hispanics with a higher risk variant was reduced by almost half to 33.3% compared with a small reduction to 48.3% among NHW (Table 3).
Tanning ability, perceived risk, and genetic risk among Hispanics and NHW
There was no significant difference in genetic risk, that is, between those with any MC1R variant compared with those with no variants, between Hispanics and NHW who reported a family history of skin cancer (P = 1.00; Supplementary Table S2). In NHW participants, there was a borderline association between family history and high risk genotypes (OR = 2.00; 95% CI, 0.93–4.30; P = 0.08; Supplementary Table S2).
Even after adjusting for family history of skin cancer, Hispanics still perceived themselves to be at a lower skin cancer risk than NHW (P = 0.004; Table 3). The majority of genetic risk in Hispanics was due to the contribution of R163Q (Table 3). In this sample, MC1R risk variants were associated neither with tanning ability (P = 0.60) nor with perceived risk (P = 0.82; Supplementary Table S2).
Discussion
Few studies have examined the frequency and impact of MC1R SNPs in the U.S. Hispanic population. MC1R risk variants have been considered major determinants of sun sensitivity, conferring a 2- to 3-fold increase in melanoma risk in the general population, including those who report increased ability to tan. Interestingly, MC1R variants predict melanoma risk in darker-skinned European populations more strongly than those with lighter skin (17). As Hispanics are a phenotypically diverse group with marked variations in tanning ability (17), one might expect relatively wide variation in MC1R SNPs.
A genome-wide association study of pigmentation SNPs in more than 6,000 subjects in Latin America found a very strong association of R163Q with Native American populations (17). As many Hispanics in New Mexico have approximately 24%–37% Native American ancestry, our results regarding R163Q are not surprising (18).
NM Hispanics may have a significant contribution of Native American genes (18), and as Native Americans have genetic ties to Northeast Asia (17) where R163Q does not appear to increase risk for melanoma (19), it is critical to continue to evaluate the role of R163Q in NM Hispanics in relationship to melanoma risk. Other studies have found similarly divergent associations for risk SNPs in populations looking at different diseases (e.g., 20). There have been no specific explanations proposed explaining why the particular SNP variant is not associated with melanoma risk in Native Americans. It is likely that pigmentary risk in relationship to melanoma will differ by population and that there are a variety of as yet unstudied interactions among pigmentary genes in Native Americans and Europeans to produce different risk profiles (21). Relationships among MC1R genotype, ethnicity/race, self-reported skin cancer, family history of skin cancer, and tannability all contribute to skin cancer risk and warrant further investigation in Hispanic populations.
Our study is the first to evaluate MC1R variants with self-identified ethnicity in a diverse NM population. Results indicate that when participants are categorized by self-reported ethnicity, the most common MC1R variant in Hispanics is R163Q compared with NHW who had increased risk with R151C and R160W. As the Hispanics in our study perceive their skin cancer risk to be lower, understanding how or whether the R163Q variants contribute to genetic risk for melanoma among NM Hispanics could inform public health initiatives. A relatively small sample size limits generalizability of our results; they should be investigated in a larger group of Hispanics and NHWs in NM. As the incidence rate of melanoma among NM Hispanics is low and steady, the role of MC1R may be more complex than originally thought. New Mexico is a unique setting to further evaluate the role of MC1R and other genetic factors in its multi-cultural population.
Disclosure of Potential Conflicts of Interest
D.B. Buller is a senior scientist at and has ownership interest (including patents) in Klein Buendel, Inc. No potential conflicts of interest were disclosed by the other authors.
Authors' Contributions
Conception and design: K.A.M. White, K. Zielaskowski, A. Sussman, K. Hunley, J.L. Hay, M. Berwick
Development of methodology: K.A.M. White, K. Zielaskowski, C.R. Hughes, D.B. Buller, J.L. Hay, M. Berwick
Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): K.A.M. White, Y.T. Dailey, D.D. Guest, E. Robers, C.R. Hughes, M.R. Schwartz, M. Berwick
Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): K.A.M. White, D.D. Guest, K. Zielaskowski, A. Sussman, C.R. Hughes, D.B. Buller, M. Berwick
Writing, review, and/or revision of the manuscript: K.A.M. White, Y.T. Dailey, D.D. Guest, K. Zielaskowski, A. Sussman, K. Hunley, C.R. Hughes, K.A. Kaphingst, D.B. Buller, J.L. Hay, M. Berwick
Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): D.D. Guest, K. Zielaskowski, E. Robers, J.L. Hay, M. Berwick
Study supervision: K.A.M. White, D.D. Guest, K. Zielaskowski, E. Robers, J.L. Hay, M. Berwick
Acknowledgments
The authors gratefully acknowledge the support of the Behavioral Core at the UNM Cancer Center and the family practice clinics at UNM. This study was supported by a research grant from the NCI at the NIH, which is a part of the U.S. government (grant nos. 1R01CA181241-01A1 to J.L. Hay and M. Berwick and P01 CA 206980-01A1 to M. Berwick). This research used the facilities or services of the Behavioral Measurement and Population Sciences Shared Resource, a facility supported by the state of New Mexico and the UNM Cancer Center P30CA118100.
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
Footnotes
Note: Supplementary data for this article are available at Cancer Epidemiology, Biomarkers & Prevention Online (http://cebp.aacrjournals.org/).
Cancer Epidemiol Biomarkers Prev 2019;28:1853–6
- Received April 5, 2019.
- Revision received June 10, 2019.
- Accepted August 30, 2019.
- Published first September 5, 2019.
- ©2019 American Association for Cancer Research.
References
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