Investigating the Validity of the Fitzpatrick Scale to Infer Quantitative Pigmentation Phenotype and Melanoma Risk Allele Status in Diverse Populations

A thesis submitted to the Graduate School of the University of Cincinnati in partial fulfillment of the requirements for the degree of

Master of Arts

in the Department of Anthropology of the College of Arts and Sciences by

Lindsay A. Fist

B.A. University of Cincinnati, 2016

Committee Chair: Heather L. Norton, Ph.D. Committee Member: C. Jeffrey Jacobson, Ph.D.

Abstract

Approximately 60-80% of all skin cancer deaths are attributed to melanoma, making it the deadliest form of skin cancer. Melanoma is most prevalent in white populations, but African

American and Hispanic patients have much lower 5-year survival rates, partly due to the fact that melanoma is often diagnosed at more advanced stages in people of color (Cormier et al.,

2006). While exposure to UV radiation is the primary environmental factor for the development of melanoma, a genetic predisposition is an important factor as well. The Fitzpatrick Skin Type scale, which measures skin phototype, is the most widespread method of determining skin’s sensitivity to UV radiation and susceptibility to skin cancers. However, studies have noted that the scale may not be an accurate indicator of melanoma risk in people of color. The goal of this study was to investigate how well the Fitzpatrick Skin Type scale correlated with another known melanoma risk factor (skin pigmentation) and genotype at melanoma risk alleles.

Saliva samples and phenotypic data, including melanin index (MI) and Fitzpatrick skin type, were available for 189 self-identified African Americans, 81 self-identified Hispanics, and

213 self-identified European-Americans. Nineteen SNPs (single nucleotide polymorphisms) that had previously been associated with melanoma risk were genotyped in all participants.

African Americans in this study exhibited a very wide range in skin pigmentation (33.4 – 104.7), and MI values overlapped between all populations. The MI values of the Hispanic individuals sampled in this study are more similar to those observed in the European-American sample.

Associations were found between FST and MI in the African American and Hispanic groups, but not in the European-American group, suggesting that FST is not an accurate indicator of skin pigmentation in some populations. Twelve out of nineteen SNPs are common (occurring

ii at frequency of 10% or greater) in all three populations, with many occurring at frequencies greater than 50%. Among African Americans, the IRF4 SNP rs12203592 was significantly associated with lower MI (P = 0.0021, β = - 15.7). Among Hispanics, rs16953002 in intron 8 of

FTO was significantly associated with FST I (p=0.00022). In the European-American sample, rs1805008 (p=0.000082) and rs1805009 (p=0.000082), both in MC1R, were significantly associated with FST I. Increased awareness of melanoma risk for people of all backgrounds is needed in order to reduce the prevalence of melanoma in the United States.

iii

Acknowledgements

Financial support for this thesis was provided by the University of Cincinnati Charles

Phelps Taft Research Center Graduate Enrichment Award. It is with great pleasure that I acknowledge the individuals who provided support and assistance to me while completing this thesis. I am eternally grateful to my thesis advisor, Dr. Heather Norton, for her guidance, patience, and enthusiasm throughout this entire journey. She has awarded me so many opportunities that I appreciate immensely. I have learned so much from her, and I could not have imagined having a better advisor and mentor. I would also like to thank my thesis committee member, Dr. Jeff Jacobson, for his insightful comments and encouragement.

I owe great thanks to my parents, Sandy and Alan, who have always pushed me to achieve my goals and have never failed to acknowledge my hard work, which I owe to them.

Thank you for always believing in me even when I didn’t believe in myself. I truly could not have done this without you both and I cannot thank you enough.

Thank you to Jeremy for your endless patience through the many late nights spent writing. The support and love you have given me while writing this thesis, and in life in general, has meant everything to me. And lastly, thank you to my daughter, Alexa, whose laughter has rescued me from peril more times than I can recall. Thank you for being my biggest inspiration and for making this all worth it.

Table of Contents

1. Introduction ...... 1

1.1 Overview ...... 1

1.2 Research Goals and Hypotheses ...... 3

2. Background ...... 5

2.1 Fitzpatrick Scale ...... 5

2.2 Variation in Skin Pigmentation ...... 7

2.3 African American Skin Pigmentation and Melanoma Risk ...... 9

2.4 Hispanic Skin Pigmentation and Melanoma Risk ...... 12

2.5 Biology and Genetics of Melanoma ...... 15

3. Methods ...... 21

3.1 Phenotype Data Collection ...... 21

3.2 Genetic Data Collection and Analyses ...... 22

3.3 Statistical Analyses ...... 26

4. Results ...... 27

4.1 Phenotype Data ...... 27

4.2 Genotype Data ...... 31

5. Discussion ...... 46

6. Conclusion ...... 52

References ...... 56 Appendix A ...... 66

List of Tables

Table 2.1. Fitzpatrick Skin Types ...... 7

Table 3.1 SNPs genotyped in this study ...... 25

Table 3.2. Restriction digest enzyme PCR conditions of rs6059655 ...... 25

Table 4.1. Raw mean (and SD) Melanin Index values and range in each population ...... 27

Table 4.2. Risk allele frequencies, genotypes, and HWE in African American,

Hispanic, and European-American study populations ...... 32

Table 4.3. Genotype Association with Melanin Index ...... 34

Table 4.4. Genotype Association with FST I ...... 36

Table 4.5. Genotype Association with FST II ...... 37

Table 4.6. Genotype Association with FST III ...... 39

Table 4.7. Genotype Association with FST IV ...... 41

Table 4.8. Genotype Association with FST V ...... 42

Table 4.9. Genotype Association with FST VI ...... 44

vii

List of Figures

Figure 3.1. DNA Extraction Protocol ...... 23

Figure 4.1. Skin Melanin Index values of European-American, Hispanic, and African

Americans for Fitzpatrick Skin Types I through VI ...... 28

Figure 4.2. FST distribution in Hispanics ...... 30

Figure 4.3. FST distribution in African Americans ...... 30

Figure 4.4. FST distribution in European-Americans ...... 31

viii

1. Introduction

1.1 Overview

Melanoma is the deadliest form of skin cancer, and over the past 30 years its incidence worldwide has nearly doubled (Dellinger et al., 2014). Skin cancer is most prevalent in white populations, but African American and Hispanic patients have much lower 5-year survival rates. When skin cancer does occur in people of color, it often presents at a more advanced stage, leading to increased mortality rates among African American and Hispanic populations as compared to whites (Agbai et al., 2014). The low survival rates among people of color can also be partly attributed to socioeconomic factors such as low awareness of risk and limited access to care (Kelly et al., 2014). Furthermore, many melanoma cases are diagnosed in non- hospital settings, which could result in severe underreporting of melanoma in people of color, who are most likely to be diagnosed this way (Agbai et al., 2014). Nearly all melanoma cases are curable if diagnosed and treated early, but non-white populations are generally diagnosed in the later stages of skin cancer because there is limited information available on melanoma risk in people of color (Satyamoorthy and Herlyn, 2002). This reflects the fact that melanoma risk is often conflated with ancestry, when other factors, including constitutive skin pigmentation (genetically determined skin color without the effects of sunlight) and genetic mutations may also play a significant role in contributing to melanoma susceptibility. This may result in later diagnoses and poorer outcomes, particularly in people of color.

Skin cancer disparities are driven by a complex amalgamation of economic, social, cultural, and biological factors. Poverty is one of the major influencing factors of cancer rates in

America. According to the US Census Bureau in 2002, 24% of African Americans and 22% of

Hispanics/Latinos were considered poor, compared with 8% of Whites Americans (Proctor and

Dalaker, 2002). Unfortunately, residents living in poorer areas have 13% higher cancer death rates in men and 3% higher rates in women (Ward et al. 2004). Additionally, Hispanics and

African Americans are more likely to be uninsured than White Americans. In 2017, 6.3% of

White Americans, 10.6% of African Americans, and 16.1% of Hispanics were uninsured

(Berchick et al., 2018). Lack of insurance decreases the chances of early detection, which allows tumors to mature to advanced stages before patients are diagnosed and treated. Hispanics are

3.6 times more likely to present with stage IV melanoma than whites, with African Americans

4.2 times more likely (Cormier et al., 2006). Disparities in treatment are also observed, with whites significantly more likely than African Americans to be treated for melanoma surgically, which is associated with prolonged survival (Mahendraraj et al., 2017).

It is estimated that 95% of melanoma cases are curable if diagnosed and treated early on, so it is crucial that patients of all backgrounds have similar awareness of their own skin cancer risk, as well as access to health care (Satyamoorthy and Herlyn, 2002). Unfortunately, health disparities do exist, and low rates of sunscreen use, low perception of risk, and limited access to care are all factors that play into the lower survival rates of minority groups with melanoma.

These socioeconomic differences are in addition to genetic mutations and differences in tumor development that can vary between populations.

1.2 Research Goals and Hypotheses

The purpose of this research project is to investigate the susceptibility to melanoma in diverse populations by assessing whether or not an objective measure of skin pigmentation phenotype (Melanin Index, or MI) and/or genotype at melanoma risk alleles is well correlated with self-assessments using the six-point Fitzpatrick Scale. Comparing associations between

Melanin Index and Fitzpatrick Skin Type (FST) will provide insight on whether or not FST is a good predictor of skin pigmentation for studies that intend to use it as such. This thesis has two primary goals. The first is to determine how well FST is correlated with a quantitative measure of skin pigmentation (MI) in populations of European, African American, and Hispanic ancestry. The second goal is to identify possible associations between phenotype (FST or

Melanin Index) and a set of known melanoma risk alleles.

Based on available research, I predict that the African American and Hispanic samples will contain a wide range of MI values (wider than that observed in the European comparison sample). I also predict that MI will be more strongly correlated with FST in Europeans than in

African Americans or Hispanics. If the Fitzpatrick skin classification scale is a good indicator of constitutive skin pigmentation, then there should not be significant differences in mean MI between the Hispanic, African American, and European-American samples in each Fitzpatrick category. I predict that melanoma risk alleles will not be well correlated with FST or MI in

Hispanics and African Americans. I also expect to observe melanoma risk alleles occurring at frequencies greater than 10% in each of the three populations.

Ultimately, this research will add to the growing literature on melanoma risk in people of color by investigating the validity of the Fitzpatrick Scale and by reporting the frequencies of significant melanoma risk alleles in African Americans and Hispanics. If these susceptibility alleles are present at appreciable frequencies in these populations, then it may show that melanoma risk cannot be assessed based on skin color or ethnicity alone, suggesting that it may be necessary to develop educational materials designed specifically to explain potential melanoma risk to people of Hispanic or African American ancestry.

2. Background

2.1 Fitzpatrick Scale

One of the primary methods by which dermatologists evaluate skin cancer risk in their patients is through the Fitzpatrick Skin Type (FST) classification system. A known risk factor for the development of melanoma is exposure to ultra-violet (UV) radiation. This classification scale first arose as a way to better predict a patient’s reaction to UVA radiation as part of a treatment for Psoriasis-Oral Methoxsalen Photochemotherapy (Fitzpatrick, 1988). The motivation to develop a scale to assess UVA reaction arose when patients with dark skin had unexpected phototoxic reactions to the ultraviolet radiation. A brief interview with the patient allowing them to self-report their sunburn and suntan experience was designed to ensure that patients with white skin were receiving the correct dose of UVA.

The Fitzpatrick Skin Typing System asks patients a series of questions about their natural skin color, number of freckles, hair and eye color, and their skin’s tendency to tan or burn. The patient is ultimately placed into a phototype category ranging from skin type I-VI

(Table 2.1). As stated, the assessment was originally intended for those with white skin, and only included types I-IV. Later, types V and VI were added to classify those with darker skin

(Pathak et al., 1976). Type I represents an individual who always develops a sunburn upon initial sun exposure, and who is incapable of tanning. Those with skin belonging to FST IV rarely develop a sunburn, and tan with ease. FST II is proposed as a subgroup to FST I (patients report a slight tan whereas FST I has no tan), and FST III is a subgroup to FST IV (patients report slight burning, whereas FST IV rarely burns).

Because sensitivity to UV radiation is a major risk factor for the development of melanoma, physicians use the classification system to determine a patient’s overall risk of developing skin cancer. FST I is considered to be at high risk, and FST VI is considered to be at low risk of developing melanoma. Because four of the six types are intended for those with white skin (and only two types represent those with darker skin), many researchers have noted that the classification scale may not be an accurate representation of phototypes in non-White populations (Pichon et al., 2010c, Chan et al., 2005, Venkataram and Haitham, 2003). People of color may be clustered into FST IV or FST V, although these categories often contain the largest range in actual melanin levels (Pichon et al., 2010c).

Part of the problem lies in the fact that phototype placement relies on the terms

“tanning” and “burning”, which may not be defined the same way in people with darker skin.

A study examining the utility of the Fitzpatrick scale administered FST surveys to African

Americans with the added option of “none of the above describe me” and found that over half of the participants selected this option rather than one of the original options regarding tanning and burning habits (Pichon et al., 2010c). The researchers suggest that the classification scale is not culturally sensitive because the terms are biased towards the sun reactivity experiences of those with white skin. Those with darker skin may in fact experience tanning or burning of the skin but might not describe it as such. Darker skin may get darker following exposure to the sun, but individuals may not describe it as “tanning” and burning or flaking of the skin may not be recognized as a legitimate sunburn. In these cases, self-assessments may not be a true reflection of the skin’s reaction to ultraviolet radiation, and thus skin phototype may not be an accurate measure of melanoma risk. If the Fitzpatrick skin classification system is not accurate

6 for assessing skin cancer risk in people of color, then large groups of people are likely not getting the necessary information about melanoma risk factors and preventative measures.

Table 2.1 Fitzpatrick Skin Types1

Skin Phototype Reactions to the Sun I Always burn, never tan II Usually burn, tan with difficulty III Sometimes burn, average tan IV Rarely burn, tan with ease V Very rarely burn, tan very easily VI Never burn, tan very easily 1 Refer to Appendix A for information on how skin/hair/eye color influence FST placement.

2.2 Variation in Skin Pigmentation

Variation in skin color is a result of the types and amount of melanin found in cells called melanocytes in the skin (melanin is also responsible for hair and eye color). Melanocytes are specialized cells that produce melanin, which is responsible for the vast range of skin and hair pigmentation that we see in humans. There are two main types of melanin: eumelanin (a dark brown/black pigment), and pheomelanin (a lighter red/yellow pigment). It is the combination of both that determines hair and skin color (García-Borrón, 2014). Eumelanin is said to be photoprotective because of its ability to block UV and scavenge free radicals better than pheomelanin (Abdel-Malek et al., 2010, Kadekaro et al., 2010). Darker skin will contain higher levels of eumelanin than lighter skin. Because of the photoprotective properties of eumelanin, constitutive skin pigmentation is considered to be a factor in melanoma risk and may partially explain the higher levels of melanoma among individuals of European descent, who may exhibit lighter levels of constitutive skin pigmentation when compared to Hispanics or African Americans (Norton et al., 2016).

Human skin pigmentation is an adaptive trait that has been maintained by natural selection. Variation in skin color evolved first in response to changing environmental pressures, and later as a byproduct of developing cultural practices, including the increased use of clothing and time spent indoors. The loss of body hair in humans allowed skin to be the direct barrier between the body and its environment, and evidence suggests that darkly-pigmented skin evolved soon after the rise of the genus Homo in Africa (Jablonski and Chaplin, 2000).

It had previously been suggested that skin cancer may have been one of the selective pressures driving the evolution of eumelanin-rich dark skin (Blum, 1961). A criticism of this hypothesis is that skin cancer is predicted to have only modest effects on reproductive success

(Jablonski and Chaplin, 2010). An alternative hypothesis suggests that darker pigmentation has been favored in regions of intense UVR as a way to prevent folate depletion, which can lead to neural tube birth defects (Jablonski and Chaplin, 2000).

It has long been suggested that light skin then evolved in response to insufficient vitamin D production due to conditions of reduced sunlight after migrations out of UVR-rich

Africa into areas with much less consistent UVR in respect to intensity and seasonal variation

(Loomis, 1967). Vitamin D deficiency has a negative impact on fertility because of the increased risk of bacterial infections, viral infections, and autoimmune diseases (Yuen and Jablonski,

2010). Vitamin D requirements are higher in women who are pregnant or lactating because it is needed for calcium absorption in order to build the fetal skeletal system and maintain adequate calcium homeostasis in the mother (Whitehead et al., 1981). Given the selective pressure to maintain sufficient levels of Vitamin D in lower UVR environments, lighter skin color is

8 believed to have evolved via natural selection in populations in these regions. Separate occurrences of the evolution of light skin have been documented in the genetic lineages leading to modern northern Europeans and modern east Asians (Norton et al., 2007), as well as in Homo neanderthalensis (Lalueza-Fox et al., 2007).

While dark skin evolved to protect the body from harmful UVR in geographical locations near the equator, and light skin evolved to combat Vitamin D deficiency in areas near the poles, intermediate areas developed the ability to increase eumelanin levels in response to seasonally high UVB levels in the form of tanning (Jablonski and Chaplin, 2010).

2.3 African American Skin Pigmentation and Melanoma Risk

Very little data exists on the prevalence of melanoma in African Americans. Melanoma is most common in white populations and because of this, most of the research on melanoma risk factors has been drawn from observations in these populations. Average incidence rates per 100,000 people are around 14.2 for whites, 2.9 for Hispanics, and 0.9 for African Americans

(Cress and Holly, 1997). Although African Americans are generally at a lower risk of developing melanoma than whites, the 5-year survival rates of African Americans with melanoma is the lowest of all ethnicities at 78%, compared with 92% for whites (Howlader et al.,

2017).

There are many possible reasons for disparities in the incidence of melanoma between whites and African Americans. One reason could be a result of biological differences in tumor

9 presentation, as one study found that African Americans often present with tumors that are deeper than in Caucasians (1.26 vs 0.83 mm), contributing to the group’s poorer prognosis

(Mahendraraj et al., 2017). Cultural differences associated with awareness and behavior toward primary and secondary skin cancer prevention practices likely play a large role as well.

Cancer is the second leading cause of death among African Americans (American

Cancer Society, 2014), and evidence suggests that mortality rates can be decreased through increased awareness, better access to healthcare, and increased quality of health insurance

(American Cancer Society, 2011). According to the 2009 U.S. Census, 1 in 4 African Americans lived below the poverty line, while only 1 in 11 non-Hispanic whites lived in poverty.

Furthermore, 1 in 5 African Americans were uninsured, compared with 1 in 8 non-Hispanic whites (Denavas-White et al., U.S. Census Bureau, 2010). According to calculations by the

American Cancer Society, if all African Americans had the same cancer death rates as the most educated African Americans, cancer deaths in this population would be decreased by 40%. If all African Americans had the same cancer death rates as white Americans with the same level of education, 20% of African American deaths from cancer could be avoided (American Cancer

Society, 2011). Therefore, eliminating socioeconomic disparities could immensely increase the survival rate of minority groups with cancer.

Several studies have indicated minimal levels of sun-protection behaviors among

African Americans (Pichon et al., 2010a, Hall, 2001). Low perception of melanoma risk may influence an individual’s decision to practice primary prevention methods such as sunscreen use, wearing protective clothing, or limiting time spent outdoors (Pichon et al., 2010b). In fact, one study found that 76% of African American adults perceived their skin cancer risk as zero or

10 low risk (Pichon et al., 2010b). This same study found no relationship between perceived risk and actual sunscreen use, reporting that even those with a higher perceived risk of skin cancer had low levels of sunscreen use. An investigation of sunscreen use among high school students revealed that relatively low numbers of Hispanics (10.8%) and African Americans (4.8) frequently use sunscreen, compared with 16.5% of white students (Hall et al., 2001), although it is difficult to know how generalized these numbers are to other age groups.

The lower incidence of melanoma in African Americans is usually attributed to the photoprotective properties of melanin. However, there is extensive variation in skin pigmentation observed in African American individuals (Norton et al., 2016), suggesting that the protective effects of melanin are not experienced among the entire population to the same degree. Further, it has been suggested that melanin is not a complete barrier to UV radiation as it confers only partial photoprotection from melanoma. For example, Hu et al compared melanoma incidence rates with latitude and UV index and found a positive correlation between

UV radiation and the development of melanoma in non-white ethnic groups (Hu et al., 2004).

Specifically, they found that increasing annual UV index increased the rate of melanoma in

Hispanics and in African Americans, suggesting a bigger role for UV radiation in the development of melanoma in non-white populations than would be expected.

Despite the association between UV radiation and melanoma in people of color, the most common type of melanoma among African Americans often presents in areas of the body not typically exposed to direct sunlight. Acral-lentiginous melanoma, which accounts for up to

35% of melanomas in African Americans is most commonly found on the soles of the feet, palms of the hands, and underneath fingernails, suggesting that UV radiation plays a lesser role

11 in these cases (Bradford et al., 2009). Because of the often-abnormal presentation in African

Americans, melanomas may be misdiagnosed as a plantar wart or talon noir (Halder and Ara,

2003).

2.4 Hispanic Skin Pigmentation and Melanoma Risk

Americans often associate Hispanic origin with brown skin, and very few studies have been done on the variation in skin pigmentation among Hispanics. Those available highlight a wide range in skin pigmentation, and the fact that not all members of an ethnic group can be expected to have similar melanin levels or to have the same susceptibility to photodamage from

UVR exposure (Robinson et al, 2017, Galindo et al., 2007).

Data on cancer in Hispanics may be limited due to difficulties classifying Hispanic ethnicity. While the terms “Hispanic” and “Latino” are often used interchangeably, “Hispanic” refers to individuals of Spanish-speaking origin, while “Latino” can refer to anyone with ancestors from Latin America. The Census Bureau considers Hispanic to be an ethnic, rather than racial category. Most Latinos, however, conflate race and ethnicity and consider their

Hispanic background a part of their racial identity (Parker et al., 2015). Although Hispanics report having sun-sensitive skin similar to that of non-Hispanic Whites (Galindo et al., 2007), the recognition of a “Hispanic” racial background may obstruct awareness of risks associated with UV radiation from the sun (Robinson et al., 2017).

In a study investigating skin phototypes of Latinos, participants were asked a series of questions to determine FST and MI was measured via spectrophotometry. Results showed that

42% of Mexican-American individuals were classified as FST type II, which is typically assigned to individuals with light skin that burns fairly easily (Robinson et al., 2017). This is significant since the lower incidence of melanoma in Hispanics is generally attributed to the protective effects of a darker skin color (Cress and Holly, 1997).

A study of UVR damage in White, Hispanic, and Black skin (Dasgupta and Katdare,

2015) found that White and Hispanic skin melanocytes contained nearly the same levels of melanin, although the Hispanic skin was visually darker than the White skin. This is potentially due to differing ratios of the types of melanin within the skin. While skin color can be suggestive of overall melanoma risk, it is ultimately the melanocytes within the skin that are affected by melanoma and are a better indicator of risk than visual pigmentation. In this same study, White and Hispanic skin melanocytes exhibited similar levels of DNA damage following exposure to ultraviolet radiation, which could be explained by the similar amounts of melanin within the skin (Dasgupta and Katdare, 2015). These results indicate that Hispanic skin is susceptible to UVR-induced genetic damage that can lead to melanoma.

California has one of the highest rates of melanoma in the world, and 1/3 of the

California population identifies as Hispanic (Cockburn et al., 2006). Data from the California

Cancer Registry between 1988 and 2001 indicates a significant increase in invasive melanoma

(melanoma that has spread to other areas of the body) in the Hispanic population of California, with a 7.3% annual increase among Hispanic males between 1996 and 2001 (Cockburn et al.,

2006). Most importantly, perhaps, is the fact that thicker tumors accounted for much of this increase. For Hispanics, the increase in thicker tumors was far more pronounced than in thin or moderately sized tumors, contrary to trends found in non-Hispanic white populations. This is

13 problematic because thicker tumors are generally associated with a poorer prognosis (MacKie and Hole, 1996, MacKie and Hole, 1997). A difference in five-year survival rates of 42% was observed between tumors thinner than 1.5mm and thicker than 3.5mm in Hispanics (MacKie and Hole, 1997).

Little is known about Hispanic melanoma prevention practices, but the few studies focusing on Hispanics suggest that they do not take the same precautions against UV radiation that whites do (Hall et al., 2001). The limited sun protection practices of Hispanics are perhaps due to a lower awareness of skin cancer risk factors, and a low perception of their own susceptibility to skin cancer (Cockburn et al., 2006). Even when Hispanic individuals are compared with white individuals with the same melanoma risk according to MI, Hispanics still have a lower awareness and risk perception than non-Hispanic whites (Pipitone et al., 2002). It has also been reported that Hispanics have a similar prevalence of sunburn as non-Hispanic whites (Saraiya et al., 2002), which sheds light on Hispanic susceptibility to melanoma since the occurrence of a severe sunburn either in childhood or adulthood is one of the major risk factors for the development of melanoma (MacKie and Achison, 1982, Satyamoorthy and Herlyn, 2002).

Socioeconomic status is believed to play a role in the poorer prognosis of Hispanic cancer patients, as the association between low socioeconomic status and the occurrence of thick tumors is much stronger in Hispanics than in non-Hispanic whites (Pollitt et al., 2011).

Hispanics of low socioeconomic status may have lower access to care that may involve language barriers or decreased job-related benefits which make early detection and treatment less likely when compared to whites of low socioeconomic status. The few studies focusing on

14 melanoma risk in Hispanics suggest that little has been achieved in preventing melanoma in this group.

2.5 Biology and Genetics of Melanoma

Melanoma is ultimately the result of a transformation of melanocytes in the skin.

Melanocytes are specialized cells, derived from the neural crest, that are distributed within the basal layer of the epidermis (Satyamoorthy and Herlyn, 2002). These specialized cells are responsible for the transfer of melanin-containing melanosomes to keratinocytes (Abdel-Malek et al., 2010). Melanocytes are characterized by their longevity and resistance to apoptosis, which increases the chance for mutations to accumulate after repeated sun exposure throughout an individual’s lifetime (Plettenberg et al., 1995). These mutations can then lead to transformation of the melanocytes into melanoma.

In addition to constitutive skin pigmentation, there are several other risk factors associated with the development of cutaneous malignant melanoma, both environmental and genetic. These include prior history of melanoma (Benvenuto-Andrade et al., 2005), family history of melanoma (Greene et al., 1985), prolonged sun exposure (Consensus Development

Conference on Sunlight, Ultraviolet Radiation, and the Skin, 1989), socioeconomic status (Pollitt et al., 2011), immunosuppression (Merkle et al., 1991), etc. A twin study on melanoma highlights the genetic component of melanoma, revealing that identical twins of an affected individual are far more likely than non-identical twins to develop melanoma themselves

(Shekar et al., 2009). There are a number of identified melanoma susceptibility genes that are

15 associated with pigmentation, DNA repair, number of nevi (moles), telomere maintenance, and tumor suppression. Knowledge about the transformation of normal melanocytes into melanoma cells is expanding and is important for developing targeted treatment mechanisms for melanoma, especially melanomas that are aggressive or not easily treated by chemotherapy

(Bandarchi et al., 2013).

The most significant exogenous risk factor for melanoma is exposure to ultraviolet radiation (Gandini et al., 2005). Cellular DNA strongly absorbs ultraviolet radiation and produces photoproducts as a result of exposure, mostly cyclobutene pyrimidine dimers (CPDs)

(Vink and Roza, 2001). CPDs, which are formed when two adjacent pyrimidine bases are linked, have various effects on the outer skin and within cells. Following UV exposure, CPD repair is responsible for the red coloration associated with sunburn (known as erythema), as well as the brown color related to UV-induced tanning (Berg, 1998, Eller et al., 1996). Aside from these more acute effects, CPDs derived from UV radiation can have negative effects on the immune system by introducing DNA damage to immune cells and keratinocytes, which are responsible for protecting melanocytes from cell proliferation (Satyamoorthy and Herlyn, 2002).

The damaged keratinocytes produce cytokines that generate an immunosuppressive environment both locally and at distant sites (Vink and Roza, 2001). In humans, DNA is repaired through nucleotide excision repair. In this mechanism, incisions are made on either side of the damaged DNA lesion, and the gap is then filled in by DNA polymerases using the template strand, and finally sealed by DNA ligase (Sancar, 1996). Because UV radiation can penetrate through the layers of skin to damage DNA, individuals with insufficient DNA repair capabilities are at a greater risk of developing melanoma.

The melanocortin 1 receptor (MC1R) plays a key role in the regulation of eumelanin synthesis in melanocytes (Swope and Abdel-Malek, 2016). MC1R is expressed on the membrane of melanocytes and encodes a cyclic AMP-stimulating G-protein-coupled receptor.

Typically, individuals with a red hair and fair skin phenotype are at a higher risk of developing melanoma than other phenotypes due to minimal receptor activity (Rhodes et al., 1987).

Recently, MC1R variants have been associated with an increased risk of melanoma independent of pigmentation (Maresca et al., 2015, Mitra et al., 2012, Pasquali et al., 2015).

When the skin is exposed to UVR, DNA photoproducts are formed from the direct absorption of UVR by pyrimidine bases (Swope and Abdel-Malek, 2016). These photoproducts can disrupt the DNA helix, and lead to mutations that result in skin cancers. Variants of MC1R that result in loss of function are associated with a decreased ability to repair damaged DNA (Maresca et al., 2015). Many of these loss- of- function variants are independent of pigmentation and can be found in people with darker skin, indicating a possible source of melanoma susceptibility in people of color through a disruption in the DNA repair pathway. It has even been suggested that an increased risk of melanoma caused by certain MC1R variants is strongest in Caucasians with darker skin (FST types III and IV) who would typically be considered to have a protective phenotype (Palmer et al., 2000, Kanetsky et al., 2010). Pigmentation and DNA repair capacity are both important pathways in the development of melanoma, making MC1R an especially significant susceptibility gene.

Aside from DNA repair and pigmentation, nevus count and tumor suppression are also important factors in the development of melanoma. Increased number of nevi, large nevi,

17 and abnormal nevi contribute to an increased risk of melanoma, particularly on sun-exposed areas of the skin (Chang et al., 2009). Melanocytic nevi are proliferations of melanocytes that cease to grow and become stable due to melanocyte senescence induced by tumor suppressive proteins (Gray-Schopfer et al., 2006). In some individuals, however, the melanocytes continue to proliferate longer before senescence is induced, leading to an increased number of nevi that are larger in size. Nevus count is primarily genetically determined (Easton et al., 1991), with a smaller percentage of variation attributable to sun exposure (Wachsmuth et al., 2005). Nevus count is a complex melanoma risk factor that is influenced by many factors and can be considered both a precursor and marker for melanoma. There is strong evidence that melanoma arises in pre-existing nevi, especially in individuals who already have a genetic susceptibility to melanoma (Bataille et al., 2000).

The gene methylthioadenosine phosphorylase (MTAP) is associated with both nevus count and tumor suppression and has been linked to melanoma risk (Ainger at al., 2017). Loss- of-function variants cause cells to secrete methylthioadenosine, which can influence tumor progression in surrounding cells through increased invasiveness, enhanced cell proliferation, and resistance against cytokines (Stevens et al., 2009).

PLA2G6, IRF4 and ASIP are additional genes associated with nevus count as well as other biological risk factors for melanoma (Kvaskoff et al., 2011, Jacobs et al., 2015).

Phospholipase A2 (PLA2G6) belongs to a family of genes that is associated with the maintenance of membrane phospholipids but has also been shown to regulate cell growth and proliferation (Falchi et al., 2009). Interferon regulatory factor 4 (IRF4) is associated with facial

18 pigmented spots (Jacobs et al., 2015), large nevi (Newton-Bishop et al., 2010), and immune response (Pena-Chilet et al., 2013). Agouti signaling protein (ASIP) acts as an antagonistic ligand of MC1R, inhibiting receptor activity and allowing for an increase in pheomelanin production (Maccioni et al., 2012). Although ASIP is strongly associated with pigmentation, it is also linked to facial pigmented spots associated with skin aging, independent of skin color

(Jacobs et al., 2015).

Another genetic factor that has been associated with melanoma is telomere length. The telomerase reverse transcriptase (TERT) gene is considered a high-risk melanoma susceptibility gene. TERT encodes the catalytic subunit of telomerase, which is responsible for maintaining telomere length (Horn et al., 2013). Telomeres are located at the ends of chromosomes, and protect chromosome ends from degradation, end-to-end fusion, and abnormal recombination

(O’Sullivan and Karlseder, 2010). Over time, telomeres become shortened due to ineffective replication of the 3’ end of DNA (Burke et al., 2013). The association of telomere length with cancer is very complex, and seems to be cancer-specific, as well as dependent on a number of genetic and environmental factors. While shorter telomere lengths have been associated with cancers of the bladder, esophagus, head, and neck (Wentzensen et al., 2011), longer telomere length is associated with other cancers, including melanoma, as well as increased size and number of nevi (Bataille et al., 2007). It has been suggested that longer telomeres express a delayed cell senescence with increased replicative potential in melanocytes, which is reflected on the skin by increased nevi size and number (Bataille et al., 2007).

Interestingly, studies on telomere length among different populations have shown that

Hispanics (Hamad et al., 2016) and African Americans (Zhu et al., 2011, Hunt et al., 2008,

Needham et al. 2013, Adler et al., 2013) have longer telomeres than white Americans. Hamad et al. (2016) aimed to investigate associations between telomere length and socioeconomic status and ultimately found that African Americans have significantly longer telomeres than similarly- educated whites, suggesting that African Americans are genetically predisposed to longer telomere length. They propose that there may have been evolutionary pressure on telomere length in African populations within the last 25,000 years since shorter telomeres have been associated with increased risk of infection (Cohen et al., 2013).

3. Methods

3.1 Phenotype Data Collection

The phenotypic data used for this project were originally collected as part of two larger studies by Dr. Heather Norton. The Hispanic and African American samples derive from the

Genomewide Association of Quantitative Pigmentary Traits in Admixed US Populations study

(UC IRB #: 2013-7610), funded by the National Institute of Justice. The European-American samples were collected for the Genetics of Skin and External Traits (GenSET) study (UC IRB #:

2015-3073), funded by Proctor and Gamble. Participants were recruited through flyers posted on the University of Cincinnati campus and in the city of Cincinnati. The African American and

Hispanic samples include individuals between the ages of 18 and 35, and the European-

American samples belong to individuals over the age of 30. Only participants who consented to allow their genetic material to be used for future studies by Dr. Heather Norton or other investigators, and for any condition or disease, were included in this research project.

Phenotypic data was available for 189 self-identified African Americans, 81 self-identified

Hispanics, and 213 self-identified European-Americans. The protocol for this study was approved by the Institution Review Board of the University of Cincinnati (UC IRB#2017-3676).

Self-identified ancestry was reported through a questionnaire completed by all participants, and it is important to note that data from the Hispanic group may include individuals who identify as Hispanic and/or Latino. Participants also answered a series of questions about their physical appearance and their skin’s response to sunlight. Their answers were used to place them into one of six Fitzpatrick Scale categories. The questionnaire for the

Admixed Population study can be found in Appendix A. These same questions were used in a larger questionnaire in the GenSET study. An objective measure of skin pigmentation (Melanin index, or MI) was assessed using the DSM II Dermaspectrometer (Cortex Technologies,

Hadsund, Denmark). Measurements were taken on the skin of the upper inner arm a total of three times, and then averaged to get a final Melanin index value. Higher MI values typically correspond to darker skin colors, while lower values correspond to lighter skin colors.

3.2 Genetic Data Collection and Analyses

African American and Hispanic participants provided a saliva sample using Oragene

DNA OG500 extraction Kits, and DNA was extracted following the protocols recommended by the manufacturer. A 2 mL saliva sample was collected from European-American participants in the GenSET study. 2 mL of collection buffer (50 mM tris, pH 8, 50 mM EDTA, 50 mM Sucrose,

100 mM NaCl, 1% SDS) were then added to each saliva sample. This helped to stabilize the sample until extraction could take place. DNA was extracted from these saliva samples following the protocol outlined in Quinque et al., 2006 (Figure 3.1).

Figure 3.1. DNA Extraction Protocol. Follows protocol outlined by Quinque et al., 2006. 1 50 mM tris, pH 8, 50 mM EDTA, 50 mM Sucrose, 100 mM NaCl, 1% SDS

Nineteen Single Nucleotide Polymorphisms (SNPs) that have been associated with melanoma risk, primarily in European populations, were genotyped in all participants. The

SNPs genotyped in this study were identified via the following steps. First, a list of candidate polymorphisms associated with melanoma risk was generated by reviewing the literature for

SNPs that had been previously identified as having an association with melanoma risk. These included candidate gene and genome-wide association studies that were found primarily by searching PubMed (https://www.ncbi.nlm.nih.gov/pubmed) for articles containing the term

“melanoma risk”, as well as searching the MelGene database (Athanasiadis et al., 2014), a synopsis and meta-analysis of all genetic association studies in Cutaneous Melanoma.

The final list of SNPs to examine (Table 3.1) was determined using the following criteria: allele frequency within African American, Hispanic, and European populations (minor allele frequency > 1%), identification across multiple studies, ability to genotype using restriction enzymes, and availability on the Illumina iSelect LCG custom microarray. Because the African

American and Hispanic samples were already being genotyped for Dr. Heather Norton’s studies using the Illumina iSelect LCG custom microarray, we prioritized SNPs that were found on that array.

One SNP related to melanoma risk was not included on the array and was genotyped directly in the Molecular and Computational Human-variation Analyses Laboratory at the

University of Cincinnati (rs6059655 in the gene RALY). A restriction enzyme was identified for the SNP using the program WebCutter (Version 2.0) (Heiman, 1997). Primers were then designed in order to amplify the target region of the SNP using the program Primer3 (v. 0.4.0)

(Untergasser et al., 2012, Koressaar and Remm, 2007). Primers were selected based on primer length, melting temperature (Tm), GC content, PrimerDimer information, resulting fragment size, and primer pair compatibility. A PCR optimization was performed to determine the ideal

PCR conditions. This process involved varying the parameters that influence DNA amplification, including variables such as Mg++ concentrations and cycling conditions. The

PCR reaction and restriction digest conditions for rs6059655 are shown in Table 3.2.

Table 3.1. SNPs genotyped in this study Shown are the SNPs that were genotyped in this study, including nearest gene, location, alleles, risk allele, and allele frequencies within five populations as listed on Ensembl (release 93) (Zerbino et al., 2018).

Chr SNP rs# Nearest Alleles Risk Allele AFR AMR EAS EUR SAS Previous Studies Gene

2 rs13016963 CASP8 G/A A 0.42 0.51 0.31 0.38 0.20 Barrett 2012 5 rs4635969 TERT A/G A 0.33 0.11 0.14 0.19 0.09 Burke et al., 2013 5 rs2735940 TERT G/A G 0.48 0.57 0.52 0.49 0.33 Burke et al., 2013 5 rs401681 TERT T/C A 0.60 0.43 0.32 0.44 0.20 Rafnar et al., 2009; Stacey et al., 2009 6 rs12203592 IRF4 C/T T 0.01 0.07 0 0.12 0.01 Pena-Chilet, 2013; Jacobs, 2015 9 rs1408799 TYRP1 T/C C 0.19 0.36 0.02 0.65 0.22 Antonopoulou, 2015 9 rs7023329 MTAP A/G A 0.49 0.50 0.53 0.52 0.73 Ainger, 2017; Bishop, 2009 11 rs1801516 ATM G/A G 0.99 0.90 0.98 0.84 0.92 Barrett 2012 12 rs731236 VDR T/C T 0.71 0.74 0.93 0.60 0.63 Denzer 2011 16 rs16953002 FTO G/A A 0.19 0.12 0.31 0.18 0.20 Ranshohoff, 2017; Antonopoulou, 2015, Iles et al., 2013 16 rs1805007 MC1R C/T T 0 0.02 0 0.07 0.01 Pasquali et al., 2015 16 rs1805008 MC1R C/T T 0 0 0 0.06 0 Pasquali et al., 2015 16 rs1805009 MC1R G/C C 0 0.01 0 0.01 0 Pasquali et al., 2015 16 rs4785763 AFG3L1P A/C A 0.31 0.24 0.27 0.30 0.25 Ranshohoff 2017; Antonopoulou 2015 20 rs6059655 RALY/ G/A A 0 0.01 0 0.04 0.01 Ranshohoff, 2017; ASIP Jacobs, 2015 20 rs4911414 ASIP T/G T 0.12 0.34 0.17 0.30 0.15 Maccioni, 2012 20 rs1015362 ASIP G/A G 0.18 0.58 0.82 0.72 0.85 Maccioni, 2012 20 rs910873 MYH7B/ G/A A 0 0.01 0 0.05 0.01 Chatzinasiou, 2011 PIGU 22 rs2284063 PLA2G6 G/A A 0.47 0.59 0.75 0.64 0.49 Falchi et al., 2009; Ainger, 2017

Table 3.2. Restriction digest enzyme PCR conditions of rs6059655

PCR (C)1 % amplification Digest Fragment size Agarose Gene SNP rs# Primer sequence [cycles in seconds] MgCl2 Enzyme Total (frag 1/frag 2) gel RALY/ rs6059655 F: GAGAATGGGAGATTCGGACA 95/63.5/72 0 BssSaI 1008 bp (433/575) 3% ASIP R: GTCCTGGCTGTGTTCCTGAT [30/30/60]

1 PCR conditions: After Initial denaturation temperature for five minutes, samples were amplified for 35 cycles, and followed by 72C for five minutes.

Amplifications were conducted in a 25 l reaction with DreamTaq and 10X DreamTaq buffer (Thermo Scientific, Walthum, MA), following Manufacturers Protocol and digested at 37C for 12 to 24 hours.

3.2 Statistical Analyses

Phenotype data. Summary statistics (mean and SD) were calculated for MI in Hispanics,

African Americans, and European-American participants, and for MI of each FST category in all three populations. An analysis of variance (ANOVA) was conducted to compare the mean skin

MI values among the Hispanic, African American, and European-American samples, followed by the Tukey’s post hoc test to determine between which groups the difference lies. ANOVAs were performed to compare mean MI in each FST category within each of the three populations, followed by the Tukey’s post hoc test, to discover whether there was a significant difference in

Melanin Index between the Fitzpatrick Skin Types. ANOVAs were also conducted to compare mean MI of participants in each population within the same FST category. The correlation between MI and self-reported FST in all three ethnic groups was assessed using the Spearman correlation coefficient. Statistical analyses were performed using SAS Enterprise statistical software (Version 7.1). Statistical significance was assigned based on p<.05.

Genotype data. Information pertaining to genetic data and its association with phenotype was analyzed using the whole genome association analyses toolset PLINK, specifically gPlink v1.07 (Purcell et al., 2007). Allele frequencies were obtained for 19 SNPs and tested for Hardy-

Weinberg equilibrium in order to compare expected and observed frequencies. All SNPs were tested for allelic associations with two phenotypes: Melanin Index and Fitzpatrick Type.

Multiple testing was taken into account using Bonferroni correction, and so P<0.05/19 (0.0026) was used to define statistical significance.

4. Results

4.1 Phenotype data

TABLE 4.1. Raw mean (and SD) Melanin Index values and range in each population.

Population N Melanin Index (SD) Range African American 189 63.35 (12.90) 33.38 – 104.71 Hispanic 81 39.36 (5.35) 30.02 – 61.16 European-American 212 39.03 (4.34) 19.49 – 54.39

The mean and standard deviation (SD) of MI in each of the three populations are shown in

Table 4.1. The group with the highest mean MI is African Americans (63.35), which also has the highest SD of all the groups (12.90). The lowest mean MI belonged to the European-American population (39.03). Only skin types III, IV, and V represented individuals from all three populations (Figure 4.1). A one-way ANOVA was conducted to compare MI in Hispanics,

African Americans, and European-Americans. This test concluded that there is a difference in mean MI (p = <0.0001), and Melanin index is associated with ethnicity. A post-hoc test (Tukey) revealed differences in mean MI between African Americans and European-Americans, and between African Americans and Hispanics. There is no significant difference in mean Melanin index between European-Americans and Hispanics.

Figure 4.1: Skin Melanin index values of European-American, Hispanic, and African Americans for Fitzpatrick Skin Types I through VI.

Correlation of MI and FST. The distribution of FST among Hispanics is shown in Figure 4.2.

Mean MI in Hispanics showed an increase from FST I to FST V and there were no Hispanic individuals in this study who identified as belonging to FST II or FST VI. The highest proportion of Hispanics (57%) self-identified as belonging to FST IV. In Hispanics, MI and FST demonstrate a positive correlation (Spearman ρ = 0.484; P = 0.000003). A one-way ANOVA performed to compare MI for Hispanics showed that there is an association between self- identified Fitzpatrick skin type and Melanin Index in Hispanics (p = <0.0001). A post-hoc test

(Tukey) showed differences in mean MI of Hispanics between FST I and FST V, FST III and FST

V, and FST IV and FST V. There was no statistical difference in mean MI between FST I and FST

III, FST I and FST IV, and FST III and FST IV.

The distribution of FST in African Americans is shown in Figure 4.3. Mean MI in African

Americans increased from FST III to FST VI, and there were no African American participants that self-identified as FST I or FST II. The highest proportion (54%) of African Americans self- identified as belonging to FST IV. In African Americans, MI and FST demonstrate a positive correlation (Spearman ρ = 0.291; P = .00002). A one-way ANOVA showed that there is an association between self-identified Fitzpatrick skin type and Melanin Index in African

Americans (p = 0.0009). The results of a post-hoc test (Tukey) showed no difference in mean MI between FST III and FST IV, but differences were observed between all other groups.

FST distribution in European-Americans is shown in Figure 4.4. Mean MI in European-

Americans showed a general increase from FST I to FST V, although mean MI of FST III was slightly higher than in FST IV. There were no participants of European descent that self- identified as FST VI. The highest proportion (46%) of European-American participants self- identified as belonging to FST III. In European-Americans, MI and FST demonstrate a positive correlation (Spearman ρ = 0.256; P = .00008). A one-way ANOVA comparing MI for European-

Americans showed no difference in mean MI among the different FST categories in this group

(p = 0.074).

A one-way ANOVA was conducted to compare Melanin index in each of the three FST categories in which all three populations were represented (FST III, FST IV, FST V). The test demonstrated that there is a significant difference in MI among European-American, African

American, and Hispanic participants who identified as belonging to FST III. A post hoc test

(Tukey) revealed differences in mean MI of FST III between African Americans and Europeans,

29 and between African Americans and Hispanics. These same results were found for both FST IV and FST V. The distribution of MI values for the European American, Hispanic, and African

American samples are plotted by FST category in Figure 4.1. No differences in mean MI were found between Europeans and Hispanics belonging to the same FST category.

Figure 4.2. FST distribution in Hispanics. FST II and FST VI comprised zero individuals.

Figure 4.3. FST distribution in African Americans. FST I and FST II comprised zero individuals.

Figure 4.4. FST distribution in European-Americans. FST VI comprised zero individuals.

4.2 Genotype data

Risk allele frequencies, genotype counts, and assessments of Hardy-Weinberg Equilibrium are found in Table 4.2. Twelve out of nineteen SNPs are common (occurring at frequency of

10% or greater) in all populations. In the African American sample, 7 of 19 SNPs exhibited risk allele frequencies greater than 50% (rs4635969, rs2735940, rs401681, rs7023329, rs1801516, rs731236, rs2284063). In the Hispanic sample, risk allele frequency of 6 SNPs was greater than

50% (rs13016963, rs7023329, rs1801516, rs731236, rs4911414, rs2284063). In the European-

American sample, risk allele frequency of 6 SNPs was greater than 50% (rs4635969, rs1408799, rs1801516, rs731236, rs1015362, rs2284063). Risk allele frequencies of all three of the MC1R SNPs

(rs1805007, rs1805008, rs1805009) were low for all three study populations.

All polymorphisms were checked for deviation from Hardy-Weinberg equilibrium (HWE)

(Table 4.2). In the African American group, deviation from HWE was found only in rs13016963

(p=0.017). In the Hispanic group, only rs731236 showed Hardy-Weinberg disequilibrium

(p=0.033). In the European-Americans, only rs1015362 showed Hardy-Weinberg disequilibrium

(p=0.04). These differences may possibly be explained by natural selection or population structure.

Table 4.2. Risk allele frequencies, genotypes, and HWE in African American, Hispanic, and European- American study populations.

SNP Risk Allele Genotype Hardy- Frequency Counts Weinberg Exact Test (P) rs13016963 A AA/AG/GG African American 0.427 33/56/54 0.017 Hispanic 0.522 18/35/15 1.000 European American 0.335 24/94/94 1.000 rs4635969 A AA/AG/GG African American 0.514 36/75/32 0.618 Hispanic 0.449 12/37/19 0.471 European American 0.543 66/98/48 0.333 rs2735940 G GG/AG/AA African American 0.731 79/51/13 0.287 Hispanic 0.0794 40/28/0 0.056 European American 0.185 140/64/7 1.000 rs401681 A AA/AC/CC African American 0.580 49/68/26 0.864 Hispanic 0.471 13/38/17 0.464 European American 0.427 42/97/73 0.399 rs12203592 T TT/CT/CC African American 0.025 0/7/136 1.000 Hispanic 0.100 0/13/55 1.000 European American 0.177 140/69/3 0.102 rs1408799 C CC/CT/TT African American 0.273 10/58/75 1.000 Hispanic 0.471 18/28/22 0.151 European American 0.668 96/91/25 0.643 rs7023329 A AA/AG/GG African American 0.517 39/70/34 0.868 Hispanic 0.529 22/28/18 0.151 European American 0.476 54/94/64 0.101 rs1801516 G GG/AG/AA African American 0.975 136/7/0 1.000 Hispanic 0.900 56/11/1 0.469 European American 0.886 166/42/3 0.737 rs731236 T TT/TC/CC African American 0.734 76/58/9 0.830 Hispanic 0.721 39/20/9 0.033 European American 0.580 69/108/35 0.574 rs16953002 A AA/AG/GG African American 0.199 8/49/116 0.324

Hispanic 0.132 4/17/33 0.231 European American 0.165 6/58/148 0.808 rs1805007 T TT/CT/CC African American 0.025 0/7/136 1.000 Hispanic 0.029 0/4/64 1.000 European American 0.073 3/25/184 0.085 rs1805008 T TT/CT/CC African American 0.014 0/4/138 1.000 Hispanic 0.022 0/3/65 1.000 European American 0.068 1/27/184 1.000 rs1805009 C CC/CG/GG African American 0.007 0/2/141 1.000 Hispanic 0.007 0/1/67 1.000 European American 0.033 1/12/199 0.199 rs4785763 A AA/AC/CC African American 0.315 15/60/68 0.703 Hispanic 0.294 7/26/35 0.560 European American 0.281 21/77/114 0.172 rs6059655 A AA/AG/GG African American 0.049 0/8/156 1.000 Hispanic 0.121 0/8/66 1.000 European American 0.074 1/13/188 0.236 rs4911414 T TT/GT/GG African American 0.179 4/43/96 1.000 Hispanic 0.706 4/32/32 0.385 European American 0.328 18/103/91 0.162 rs1015362 G GG/AG/AA African American 0.294 8/68/67 0.107 Hispanic 0.324 31/30/7 1.000 European American 0.724 105/97/10 0.040 rs910873 A AA/AG/GG African American 0.031 0/9/134 1.000 Hispanic 0.044 0/6/62 1.000 European American 0.071 0/30/182 0.606 rs2284063 A AA/AG/GG African American 0.517 38/72/33 1.000 Hispanic 0.610 24/35/9 0.614 European American 0.625 84/97/31 0.770

4.2.1 Genetic Associations between Melanin Index and FST

After Bonferroni correction, no SNPs were significantly associated with MI in the

European-American and Hispanic samples. The rs12203592 SNP in the IRF4 locus was the only

SNP significantly associated with MI in the African American sample (p = 0.0021). SNPs were also tested for association with FST. No significant associations with any FST category were observed in the African American sample. The rs16953002 SNP in the FTO locus was significantly associated with FST I in the Hispanic sample (p = 0.00022). In the European-

American sample, two SNPs were significantly associated with FST I: rs1805008 (P = 0.000082) and rs1805009 (P = 0.0000082), both in MC1R.

Table 4.3. Genotype association with Melanin Index.

SNP Population Number of P individuals (n) rs13016963 African American 138 0.009 Hispanic 65 0.564 European-American 211 0.256 rs4635969 African American 138 0.822 Hispanic 65 0.070 European-American 211 0.918 rs2735940 African American 138 0.005 Hispanic 65 0.693 European-American 210 0.137 rs401681 African American 138 0.068 Hispanic 65 0.938 European-American 211 0.370 rs12203592 African American 138 0.002 Hispanic 65 0.093 European-American 211 0.325 rs1408799 African American 138 0.098 Hispanic 65 0.677 European-American 211 0.574 rs7023329 African American 138 0.572 Hispanic 65 0.076

European-American 211 0.495 rs1801516 African American 138 0.235 Hispanic 65 0.632 European-American 210 0.804 rs731236 African American 138 0.488 Hispanic 65 0.409 European-American 211 0.578 rs16953002 African American 138 0.529 Hispanic 65 0.916 European-American 211 0.41 rs1805007 African American 138 0.679 Hispanic 65 0.569 European-American 211 0.905 rs1805008 African American 137 0.639 Hispanic 65 0.113 European-American 211 0.075 rs1805009 African American 138 0.049 Hispanic 65 0.359 European-American 211 0.869 rs4785763 African American 138 0.164 Hispanic 65 0.211 European-American 211 0.622 rs6059655 African American 129 0.245 Hispanic 65 0.854 European-American 201 0.879 rs4911414 African American 138 0.267 Hispanic 65 0.042 European-American 211 0.154 rs1015362 African American 138 0.036 Hispanic 65 0.067 European-American 211 0.559 rs910873 African American 138 0.260 Hispanic 65 0.268 European-American 211 0.627 rs2284063 African American 138 0.811 Hispanic 65 0.360 European-American 211 0.123

Table 4.4. Genotype Association with FST I.

SNP Population ChiSq P OR

rs13016963 African American - - - Hispanic 0.008 0.929 1.095 European-American 3.290 0.070 0.411 rs4635969 African American - - - Hispanic 0.044 0.834 1.237 European-American 0.006 0.941 1.029 rs2735940 African American - - - Hispanic 0.049 0.825 1.296 European-American 5.910 0.015 2.663 rs401681 African American - - - Hispanic 0.014 0.905 1.129 European-American 2.560 0.110 1.867 rs12203592 African American - - - Hispanic 0.436 0.509 0 European-American 2.439 0.118 1.964 rs1408799 African American - - - Hispanic 0.014 0.905 1.129 European-American 0.297 0.586 0.791 rs7023329 African American - - - Hispanic 0.014 0.905 1.129 European-American 0.067 0.796 1.106 rs1801516 African American - - - Hispanic 1.137 0.286 3.333 European-American 0.013 0.909 0.931 rs731236 African American - - - Hispanic 1.598 0.206 0 European-American 0.089 0.765 0.887 rs16953002 African American - - - Hispanic 13.69 0 23.40 European-American 0.108 0.743 0.833 rs1805007 African American - - - Hispanic 7.025 0.008 14.33 European-American 8.817 0.003 4.047 rs1805008 African American - - -

Hispanic 0.093 0.760 0 European-American 15.52 0 5.667 rs1805009 African American - - - Hispanic 0.031 0.861 0 European-American 19.89 0 9.348 rs4785763 African American - - - Hispanic 0.039 0.844 0.795 European-American 5.007 0.025 2.371 rs6059655 African American - - - Hispanic 0.266 0.606 0 European-American 1.160 0.281 0 rs4911414 African American - - - Hispanic 1.717 0.190 0 European-American 0.006 0.941 0.970 rs1015362 African American - - - Hispanic 1.971 0.160 0 European-American 0.014 0.905 1.053 rs910873 African American - - - Hispanic 0.190 0.663 0 European-American 0.604 0.431 1.640 rs2284063 African American - - - Hispanic 2.632 0.105 0 European-American 0.041 0.840 1.084

Table 4.5. Genotype Association with FST II.

SNP Population ChiSq P OR

rs13016963 African American - - - Hispanic - - - European-American 1.370 0.242 0.764 rs4635969 African American - - - Hispanic - - - European-American 0.510 0.475 1.164 rs2735940 African American - - - Hispanic - - - European-American 0.006 0.937 0.979

37 rs401681 African American - - - Hispanic - - - European-American 0.662 0.416 0.839 rs12203592 African American - - - Hispanic - - - European-American 2.531 0.112 1.526 rs1408799 African American - - - Hispanic - - - European-American 0.428 0.513 0.861 rs7023329 African American - - - Hispanic - - - European-American 0.043 0.834 1.045 rs1801516 African American - - - Hispanic - - - European-American 0.091 0.763 1.105 rs731236 African American - - - Hispanic - - - European-American 0.167 0.683 0.916 rs16953002 African American - - - Hispanic - - - European-American 0.118 0.732 1.102 rs1805007 African American - - - Hispanic - - - European-American 1.295 0.255 1.546 rs1805008 African American - - - Hispanic - - - European-American 1.006 0.316 1.488 rs1805009 African American - - - Hispanic - - - European-American 0.476 0.490 0.636 rs4785763 African American - - - Hispanic - - - European-American 0.104 0.747 0.926 rs6059655 African American - - - Hispanic - - - European-American 4.851 0.028 3.051 rs4911414 African American - - - Hispanic - - - European-American 0.005 0.945 0.984

rs1015362 African American - - - Hispanic - - - European-American 1.881 0.170 0.713 rs910873 African American - - - Hispanic - - - European-American 0.202 0.653 1.198 rs2284063 African American - - - Hispanic - - - European-American 0.870 0.351 0.813

Table 4.6. Genotype association with FST III.

SNP Population ChiSq P OR

rs13016963 African American 2.069 0.150 0.437 Hispanic 2.298 0.130 1.883 European-American 1.079 0.299 1.239 rs4635969 African American 0.008 0.931 1.046 Hispanic 7.405 0.007 3.171 European-American 0.543 0.461 0.866 rs2735940 African American 0.600 0.439 0.605 Hispanic 4.563 0.033 0.220 European-American 2.67 0.102 0.657 rs401681 African American 1.509 0.219 1.875 Hispanic 8.697 0.003 0.262 European-American 0.185 0.667 1.088 rs12203592 African American 7.103 0.008 7.514 Hispanic 4.854 0.028 3.536 European-American 1.844 0.174 0.703 rs1408799 African American 0.926 0.336 1.665 Hispanic 1.669 0.197 0.579 European-American 0.862 0.353 1.211 rs7023329 African American 0.030 0.862 1.094 Hispanic 0.002 0.961 0.980 European-American 1.121 0.290 0.813

39 rs1801516 African American 1.011 0.315 2.911 Hispanic 0.009 0.926 1.067 European-American 3.483 0.062 0.551 rs731236 African American 0.027 0.870 0.907 Hispanic 0.556 0.456 1.393 European-American 0.494 0.482 1.149 rs16953002 African American 0.606 0.436 0.553 Hispanic 1.446 0.229 0.402 European-American 0 0.994 0.998 rs1805007 African American 0.429 0.513 0 Hispanic 0.021 0.886 1.184 European-American 2.455 0.117 0.541 rs1805008 African American 0.244 0.621 0 Hispanic 3.550 0.060 7.500 European-American 1.594 0.207 0.604 rs1805009 African American 7.457 0.006 17.80 Hispanic 0.285 0.593 0 European-American 0.588 0.443 0.650 rs4785763 African American 0 0.994 0.996 Hispanic 0.006 0.936 1.037 European-American 0.099 0.753 0.934 rs6059655 African American 0.396 0.529 0 Hispanic 0.025 0.874 1.143 European-American 4.409 0.036 0.276 rs4911414 African American 0.007 0.932 1.058 Hispanic 0.285 0.593 1.267 European-American 0.249 0.618 1.109 rs1015362 African American 3.395 0.065 2.526 Hispanic 0.017 0.897 1.059 European-American 1.989 0.158 1.359 rs910873 African American 0.525 0.469 2.167 Hispanic 2.850 0.091 3.815 European-American 2.007 0.157 0.571 rs2284063 African American 1.381 0.240 1.850 Hispanic 0.959 0.328 1.503 European-American 0.307 0.580 0.894

Table 4.7. Genotype association with FST IV.

SNP Population ChiSq P OR

rs13016963 African American 2.142 0.143 0.703 Hispanic 0.209 0.647 0.854 European-American 1.595 0.207 1.404 rs4635969 African American 0.022 0.881 1.036 Hispanic 0.001 0.976 0.989 European-American 0.065 0.799 1.069 rs2735940 African American 1.011 0.315 0.764 Hispanic 5.227 0.022 2.891 European-American 0.128 0.720 1.125 rs401681 African American 1.469 0.226 1.342 Hispanic 4.654 0.031 2.134 European-American 0.248 0.619 0.876 rs12203592 African American 0.856 0.355 2.148 Hispanic 0.024 0.876 0.913 European-American 0.667 0.414 0.741 rs1408799 African American 0.041 0.840 0.947 Hispanic 1.253 0.263 1.476 European-American 0.126 0.723 0.905 rs7023329 African American 0.798 0.372 0.808 Hispanic 0.915 0.339 0.718 European-American 1.484 0.223 1.376 rs1801516 African American 0.025 0.875 1.129 Hispanic 1.769 0.184 0.458 European-American 2.770 0.096 1.816 rs731236 African American 0.563 0.453 1.225 Hispanic 0.087 0.769 1.120 European-American 0.026 0.871 1.044 rs16953002 African American 1.480 0.224 1.444 Hispanic 1.101 0.294 0.588 European-American 0.024 0.876 1.056 rs1805007 African American 0.856 0.355 2.148 Hispanic 0.058 0.810 0.784 European-American 1.133 0.287 0.521 rs1805008 African American 0.681 0.409 2.523

Hispanic 0.633 0.426 0.387 European-American 3.853 0.050 0.169 rs1805009 African American 0.015 0.904 0.843 Hispanic 0.795 0.373 - European-American 0.922 0.337 0.380 rs4785763 African American 0.036 0.849 1.050 Hispanic 0.060 0.806 1.098 European-American 0.035 0.851 0.946 rs6059655 African American 1.951 0.162 4.149 Hispanic 0.217 0.641 1.418 European-American 1.076 0.300 1.847 rs4911414 African American 0.530 0.467 1.256 Hispanic 1.615 0.204 0.619 European-American 0.070 0.792 0.928 rs1015362 African American 0.858 0.354 0.786 Hispanic 1.755 0.185 0.614 European-American 0.148 0.700 0.892 rs910873 African American 2.077 0.150 3.048 Hispanic 1.295 0.255 0.378 European-American 1.091 0.296 1.599 rs2284063 African American 2.247 0.134 0.699 Hispanic 0.048 0.827 0.926 European-American 2.414 0.120 1.505

Table 4.8. Genotype Association with FST V.

SNP Population ChiSq P OR

rs13016963 African American 4.968 0.026 1.744 Hispanic 1.122 0.290 0.625 European-American 0 0.994 0.993 rs4635969 African American 0.523 0.470 0.836 Hispanic 8.532 0.004 0.230 European-American 0.378 0.539 0.589 rs2735940 African American 1.462 0.227 1.392

Hispanic 0.532 0.466 0.652 European-American 0.891 0.345 2.237 rs401681 African American 1.823 0.177 0.710 Hispanic 0.112 0.738 1.157 European-American 0.218 0.641 0.668 rs12203592 African American 4.022 0.045 0 Hispanic 3.397 0.065 0 European-American 1.308 0.253 0 rs1408799 African American 0.426 0.514 1.197 Hispanic 0.011 0.918 0.956 European-American 0.769 0.381 2.029 rs7023329 African American 1.058 0.304 1.290 Hispanic 1.459 0.227 1.698 European-American 0.500 0.480 0.545 rs1801516 African American 0.168 0.682 0.708 Hispanic 1.262 0.261 2.040 European-American 2.911 0.088 4.022 rs731236 African American 0.411 0.521 0.834 Hispanic 0.378 0.539 1.731 European-American 1.601 0.206 0.272 rs16953002 African American 2.855 0.091 0.575 Hispanic 1.006 0.316 1.777 European-American 1.203 0.273 0 rs1805007 African American 1.459 0.227 0.290 Hispanic 0.974 0.324 0 European-American 0.480 0.488 0 rs1805008 African American 0.194 0.660 0.603 Hispanic 0.725 0.395 0 European-American 0.447 0.504 0 rs1805009 African American 1.129 0.288 0 Hispanic 0.238 0.626 0 European-American 0.208 0.649 0 rs4785763 African American 0.275 0.600 0.869 Hispanic 0.096 0.757 0.860 European-American 2.375 0.123 0 rs6059655 African American 0.894 0.344 0.367 Hispanic 0.279 0.597 0.566 European-American 0.235 0.628 0 rs4911414 African American 1.142 0.285 0.699

Hispanic 2.575 0.109 2.048 European-American 0.717 0.397 0.406 rs1015362 African American 0.051 0.822 1.063 Hispanic 4.574 0.033 2.548 European-American 0.100 0.751 1.317 rs910873 African American 2.485 0.115 0.215 Hispanic 0.024 0.876 0.840 European-American 0.463 0.496 0 rs2284063 African American 0.479 0.489 1.187 Hispanic 0.004 0.953 0.974 European-American 0.406 0.524 1.679

Table 4.9. Genotype Association with FST VI.

SNP Population ChiSq P OR

rs13016963 African American 0.002 0.967 0.975 Hispanic - - - European-American - - - rs4635969 African American 1.575 0.210 2.153 Hispanic - - - European-American - - - rs2735940 African American 0.245 0.620 1.363 Hispanic - - - European-American - - - rs401681 African American 1.413 0.235 0.455 Hispanic - - - European-American - - - rs12203592 African American 0.317 0.574 0 Hispanic - - - European-American - - - rs1408799 African American 4.661 0.031 0 Hispanic - - - European-American - - - rs7023329 African American 0.194 0.659 0.769 Hispanic - - - European-American - - -

44 rs1801516 African American 0.317 0.574 0 Hispanic - - - European-American - - - rs731236 African American 0.020 0.888 0.909 Hispanic - - - European-American - - - rs16953002 African American 3.643 0.056 3.022 Hispanic - - - European-American - - - rs1805007 African American 1.795 0.180 4.030 Hispanic - - - European-American - - - rs1805008 African American 0.180 0.671 0 Hispanic - - - European-American - - - rs1805009 African American 0.089 0.766 0 Hispanic - - - European-American - - - rs4785763 African American 0.621 0.431 1.599 Hispanic - - - European-American - - - rs6059655 African American 0.242 0.623 0 Hispanic - - - European-American - - - rs4911414 African American 0.422 0.516 1.556 Hispanic - - - European-American - - - rs1015362 African American 0.126 0.723 0.786 Hispanic - - - European-American - - - rs910873 African American 0.410 0.522 0 Hispanic - - - European-American - - - rs2284063 African American 0.511 0.475 1.529 Hispanic - - - European-American - - -

5. Discussion

Among African Americans, there are more participants in this study that identify as FST III, originally created for people with white skin, than as FST VI, which was added to include people with darker skin. This implies that based on self-identified FST, more African American participants say that their skin burns moderately than not at all and tans gradually rather than always tanning very easily. Based on this information alone, if FST is meant to be an accurate indicator of melanoma risk, then many African Americans ought to be considered at risk.

African American participants in this study were found to have the widest range in Melanin index values among all three populations. The lowest value assigned to an African American participant was 33.4, while the highest value was recorded at 104.7. Overlap of Melanin Index values was observed between all populations, especially within the three skin types (III, IV, V) that represented individuals of all populations.

Self-assessed Fitzpatrick skin type is often used as a method of inferring skin pigmentation by researchers, but it may not be accurate, at least in European-American populations. A one- way ANOVA comparing MI of each FST category in European-Americans showed no difference in mean MI between the FST types. This suggests that skin color cannot be assumed based on FST alone, and researchers may derive more accuracy from a device that measures

Melanin index.

Interestingly, three European-American participants self-identified as belonging to FST V, which was added onto the original Fitzpatrick scale to include individuals with darker skin.

Therefore, individuals in this category taking the self-assessment prior to the addition would not have had a category that represented their skin type and were likely required to choose FST

IV instead.

The phenotypic information obtained from this study demonstrates that the MI values of the

Hispanic individuals sampled in this study are more similar to those observed in the European sample than to those in the African American sample. The mean MI for Hispanics (39.4) and for

European-Americans (39.0) are not significantly different and means for each FST category remain similar between the two populations.

Three of the Fitzpatrick Skin Types included individuals from all three populations: FST III,

FST IV, and FST V. In the 1988 article by Fitzpatrick, individuals with skin type IV are described as “exhibiting white skin with no clinical evidence of inherent melanin pigmentation”. In that same article, individuals with skin type III are also described as having visibly white skin, while those with skin type IV are considered to have visibly brown skin. The data from this study suggests that these might not correlate well with objectively measured skin color, as MI in FST IV alone ranges from 24.7 to 94.6. Furthermore, the highest MI observed within FST III is actually higher than the highest Melanin index observed in FST IV, which is higher than the highest Melanin index observed in FST V. This may suggest that the boundaries between skin types are much more fluid than would be expected and have little to do with actual skin color and more to do with the skin’s reaction to the sun. Alternatively, this might suggest that self-assessment of Fitzpatrick skin type (which is how FST was determined in this study) is not as accurate as FST assessment carried out by a trained clinician. While the

47 questions asked by the FST self-assessment do focus on skin reactivity, and do not explicitly ask for skin color, guidelines are given as to which skin color is associated with each skin type.

If FST is a good predictor of skin color regardless of ethnicity, one would expect to observe no significant differences in skin MI between the same FST category across all three populations. Across the three FST categories in which all three populations were represented, there were no significant differences in MI between European-American and Hispanic participants. There were, however, differences in mean MI between African American and

European-American participants, and African American and Hispanic participants who self- classified as the same FST. This casts doubt on the accuracy of the Fitzpatrick scale as a method of inferring skin pigmentation across diverse populations, since the African American population measured at higher Melanin indexes than European and Hispanic populations within shared FST categories.

If participants are accurately answering questions about their skin’s reactivity to the sun, then skin color isn’t necessarily associated with reactivity. As shown here, individuals with darker skin can have similar burning/tanning experiences as individuals with lighter skin. It has also been suggested that the questions asked in the self-assessment are not culturally sensitive and may not accurately capture the skin reactivity experiences of people with color

(Pichon et al., 2010c, Galindo et al., 2007, Venkataram and Haitham, 2003). If this is the case, participants are required to choose an answer that may not reflect their skin’s reactivity, which may ultimately place them into a category that doesn’t accurately represent their skin type.

Many of the risk alleles were observed at moderate frequencies (> 10%) in all populations.

This included 13 of the 19 SNPs in African Americans, and 14 SNPs in both Hispanic and

European-American populations. SNPs with risk alleles greater than 50% in all three populations included rs1801516, rs731236 and rs2284063. The polymorphism rs1801516 is a mutation in the gene ATM, which codes for a protein that repairs breaks in double-stranded

DNA (Barrett et al., 2012). The A allele is protective, and the G allele (listed here as the risk allele) is typically the most common in all populations. The VDR SNP rs731236, specifically the

TT genotype, has been significantly associated with increased melanoma risk (Li et al., 2008).

The frequencies of the T allele observed in all three populations here are consistent with those reported by Ensembl (Table 3.1). The PLA2G6 SNP rs2284063 is associated with nevus count.

Presence of the A allele significantly increases the number of nevi, and increased nevus count is one of the major risk factors for the development of melanoma. Risk alleles at the three MC1R

SNPs genotyped here occurred at the lowest frequencies observed in all three populations.

These observed low frequencies are consistent with previous reports (Pasquali et al., 2015).

Because constitutive pigmentation is a known risk factor for melanoma, I tested for associations between the genotyped melanoma risk SNPs and MI. Among African Americans, the IRF4 SNP rs12203592 was significantly associated with lower MI (P = 0.0021, β = - 15.7). This

SNP has previously been associated with lighter eye color, darker hair color, lighter skin color, and nevus count in populations of European descent (Duffy et al., 2010, Pena-Chilet et al., 2013,

Jacobs et al., 2015). Although the T allele of rs12203592 has actually been found to offer slight protection against melanoma (Pena-Chilet et al., 2013), it was found to increase risk of

49 melanoma in another study (Han et al., 2011). In this study, none of the 19 SNPs were significantly associated with MI in the Hispanic or the European-American groups.

SNPs were also tested for association with all Fitzpatrick Skin Types. There were no significant associations found between the genotyped SNPs and FST, indicating that none of the

SNPs are significantly more common in any specific skin type. Among Hispanics, rs16953002 in intron 8 of FTO was significantly associated with FST I (p=0.00022). According to this result, patients with FST I (the skin type typically assigned to patients with fair skin and light eyes who sunburn very easily) are more likely to carry the A allele of rs16953002 than other phenotypes. FTO has been associated with numerous traits related to body mass index, including osteoarthritis (arcOGEN Consortium and arcOGEN Collaborators, 2012) and end- stage renal disease (Hubachek et al., 2012). Rs16953002 is the first SNP identified within FTO to be associated with a trait not related to body mass index, and it was selected for this study based on its association with melanoma risk (Iles et al., 2013). It is unknown how or why the rs16953002 polymorphism increases melanoma risk, but researchers suggest it is possible, though unlikely, that the SNP could be in linkage disequilibrium with SNPs outside of FTO.

In the European-American sample, rs1805008 (p=0.000082) and rs1805009 (p=0.000082), both in MC1R, were significantly associated with FST I. MC1R is a gene on chromosome 16 that is important for regulating pigmentation and is also associated with DNA repair. This result suggests that participants who self-identified as FST I are more likely to carry these risk alleles than participants of other skin types. However, since this study showed no difference in mean

MI between FST’s in the European-American group, it cannot be inferred that rs1805008 and

50 rs1805009 are more frequent in those with lighter skin. In fact, no association was found between the MC1R SNPs and MI.

The two MC1R SNPs rs1805008 and rs1805009 have both been found to increase melanoma risk in darker-skinned Europeans who would otherwise be considered to have a somewhat protective phenotype (Pasquali et al., 2015, Kanetsky et al.,2010). Pasquali et al. found that being a carrier of just one MC1R variant increased melanoma risk 28%, but this risk only increased in Europeans identifying as FST III or IV. This suggests that MC1R variants can increase melanoma risk in ways not related to pigmentation or UV exposure. For example, wild-type MC1R has been shown to generate a DNA repair mechanism when melanocytes are exposed to UV, while inactivated MC1R, acting similarly to loss-of-function variants (including rs1805008 and rs1805009), increases the damage caused by reactive oxygen species even without exposure to UV (Mitra et al., 2012). While no significant associations between these MC1R variants and skin MI were observed in this sample, the association of rs1805008 and rs1805009 with FST I may reflect MC1R’s role in DNA repair.

Study limitations include the relatively small sample sizes, as well as the fact that data from participants were not compared to patients who actually have melanoma. Assumptions have been made that none of the participants themselves knowingly have melanoma or have had melanoma in the past. This study also does not control for population substructure, which could lead to false-positive associations between genotype and phenotype. SNPs genotyped in this study were found in populations of primarily European descent, as there is little awareness of specific variants that may impose melanoma risk in non-white populations.

6. Conclusion

Melanoma is responsible for the most deaths of all skin cancers and is rapidly growing in incidence in the United States (Dellinger et al., 2014). Physicians often use the Fitzpatrick Skin

Type classification scale to assess melanoma risk because it captures important information about risk factors such as hair color, eye color, and the skin’s reaction to the sun. There are, however, many genetic and biological factors that can contribute to melanoma risk as well, such as pigmentation, nevus count, telomere length, DNA repair, and tumor suppression.

One goal of this thesis was to investigate how well FST correlated with MI in African

Americans, Hispanics, and European-Americans. FST is often used as an indicator of skin color in genome-wide association studies that do not/are not able to directly measure melanin index, but this study found that FST is not a good indicator of skin color in European-Americans since no significant difference in mean MI was found between the six FST categories in this group.

Additionally, there were significant differences in mean MI between African-Americans and individuals from the other two populations belonging to the same FST category. The African

Americans in FST III had higher MI values than the Hispanics and the European-Americans in

FST III, and this is true of FST IV and V as well. Studies that intend to use skin color as a variable in any way would benefit from directly measuring MI values rather than relying on

FST.

This thesis also aimed to assess the relationships between phenotype and known melanoma risk alleles in order to gauge whether skin color and/or FST are dependable indicators of melanoma risk. Many of the SNPs were common in all three populations, with several

52 appearing at frequencies greater than 50%. The IRF4 SNP rs12203592 is known to increase melanoma risk, and was associated with lower MI in African Americans, suggesting that

African Americans with lighter skin are in danger of DNA damage from UV rays and should take precautions to protect themselves. FTO SNP rs16953002 in Hispanics, and MC1R SNPS rs1805008 and rs1805009 in European-Americans were associated with FST I, but not with MI.

These SNPs may have an influence on the non-pigment factors involved with the determination of FST (tanning and burning reaction).

The Fitzpatrick skin type classification scale was originally created to classify those with

“white skin”, and types V and VI were added on later to classify those with darker skin. The data from this study, however, show that African Americans have the widest range in skin color, and that FST is not a good predictor of skin color. FST III, IV, and V included individuals from all three study populations, with wide ranges of MI exhibited within each skin type. If physicians are relying on skin color to determine melanoma risk, they are not capturing important information regarding the skin’s reactions to the sun. If physicians are relying on the

FST scale to determine risk, it is possible that patients (especially minority groups) are not being assigned to their correct skin type since it has been shown that the questions asked do not give enough options to accurately capture the experiences of all individuals. Additionally, FST and

MI both do not capture the inherent genetic risk that cannot be seen easily by the naked eye.

Melanoma is continuing to become more prevalent and it is crucial that physicians have the appropriate tools needed to accurately assess a patient’s melanoma risk.

While it is extremely important for physicians to be able to accurately assess melanoma risk, it is equally important for individuals to recognize their own risk of developing the disease so that they can adjust their sun behavior practices accordingly and seek medical advice when needed. One of the major risk factors for melanoma is at least one severe sunburn during childhood. Sunburns trigger mutations in the DNA that can accumulate if not properly repaired and contribute to the development of melanoma in adulthood. Because people of color may not recognize burning and flaking of the skin as a legitimate sunburn, they may not be aware of the need to use sunscreen. In fact, 76% of African American adults believe they are at little to no risk of developing melanoma (Pichon et al., 2010b) and less than 5% of African

American high school students frequently use sunscreen (Hall et al., 2001). Regardless of there being no significant difference in mean MI of Hispanics and European-Americans, Hispanics use sunscreen much less frequently than whites as well (Hall et al., 2001).

Despite many other risk factors and biological pathways for melanoma, UV radiation remains the most imminent danger, so it is important for the public to realize that melanin offers only partial protection from melanoma. Although it is common knowledge that people with light skin would benefit from the use of sunscreen, it is often misinterpreted as a benefit for only people of European descent, and as such, non-white populations typically do not believe they need to use sunscreen regularly. It would be beneficial for sunscreen companies to direct marketing toward groups of people who are less likely to consider themselves at risk.

Unfortunately, even if minority groups do recognize their own risk, access to care for these groups is often limited. Minority groups are less likely to carry health insurance than white

54 populations, and many cases of melanoma are diagnosed in non-hospital settings as a result.

Because non-white populations do not visit a doctor as frequently, diagnosis and treatment are delayed, contributing to poorer outcomes. Cancer fatalism is believed to play an especially important role in how African Americans make health decisions as well (Powe, 1996). Cancer fatalism, described as the belief that one has no power or influence over the development of cancer, contributes to a lack of prevention practices and delayed treatment. Adding to the poorer prognosis of minority groups are the biological differences in tumor development between populations. Minority groups are more likely to present with tumors that are deeper, thicker, and exist on areas of the body not typically exposed to sunlight.

Because early detection greatly increases survival rate in melanoma patients, increased awareness of melanoma risk for people of all backgrounds is needed in order to reduce the prevalence of melanoma in the United States. According to census bureau projections, the

Hispanic population in the US will reach 29% by 2060 – nearly one-third of the total US population (Colby and Ortman, 2015). As the Hispanic population continues to increase, their experience with skin cancer will have a significantly greater influence on public health messaging and clinical practice in the U.S. It may be necessary to develop educational materials designed specifically to explain potential melanoma risk to people who identify as Hispanic or

African American. Finally, rephrasing the questions about burning and tanning asked in the

FST scale using terms that have meaning to people of color may allow for more accurate placement into an FST category so that physicians can better assess a patient’s risk.

References

Abdel-Malek ZA, Kadekaro AL, Swope VB. 2010. Stepping up melanocytes to the challenge of UV exposure. Pigment Cell & Melanoma Research 23:171–186.

Adler N, Pantell MS, O’Donovan A, Blackburn E, Cawthon R, Koster A, Opresko P, Newman A, Harris TB, Epel E. 2013. Educational attainment and late life telomere length in the Health, Aging and Body Composition Study. Brain, Behavior, and Immunity 27:15– 21.

Agbai ON, Buster K, Sanchez M, Hernandez C, Kundu RV, Chiu M, Roberts WE, Draelos ZD, Bhushan R, Taylor SC, Lim HW. 2014. Skin cancer and photoprotection in people of color: A review and recommendations for physicians and the public. Journal of the American Academy of Dermatology 70:748–762.

Ainger SA, Jagirdar K, Lee KJ, Soyer HP, Sturm RA. 2017. Skin Pigmentation Genetics for the Clinic. Dermatology 233:1–15.

American Cancer Society. 2011. Cancer Facts and Figures 2011. Atlanta American Cancer Society.

American Cancer Society. 2014. Cancer Facts and Figures 2014. Atlanta American Cancer Society.

Antonopoulou K, Stefanaki I, Lill CM, Chatzinasiou F, Kypreou KP, Karagianni F, Athanasiadis E, Spyrou GM, Ioannidis JP, Bertram L, Evangelou E, Stratigos AJ. 2015. Updated Field Synopsis and Systematic Meta-Analyses of Genetic Association Studies in Cutaneous Melanoma: The MelGene Database. Journal of Investigative Dermatology 135:1074– 1079.

ArcOGEN Consortium, arcOGEN Collaborators. 2012. Identification of new susceptibility loci for osteoarthritis (arcOGEN): a genome-wide association study. Lancet 380.

Bandarchi B, Jabbari CA, Vedadi A, Navab R. 2013. Molecular biology of normal melanocytes and melanoma cells. Journal of Clinical Pathology 66:644–648.

Barrett JH, Iles MM, Harland M. 2012. Genome-wide association study identifies three new melanoma susceptibility loci. Nature Genetics 43.

Bataille V, Snieder H, Macgregor AJ, Sasieni P, Spector TD. 2000. Genetics of Risk Factors for Melanoma: An Adult Twin Study of Nevi and Freckles. JNCI: Journal of the National Cancer Institute 92:457–463.

Bataille V, Kato BS, Falchi M, Gardner J, Kimura M, Lens M, Perks U, Valdes AM, Bennett DC, Aviv A, Spector TD. 2007. Nevus Size and Number Are Associated with Telomere Length and Represent Potential Markers of a Decreased Senescence In vivo. Cancer Epidemiology Biomarkers & Prevention 16:1499–1502.

Benvenuto-Andrade C, Oseitutu A, Agero AL, Marghoob AA. 2005. Cutaneous melanoma: surveillance of patients for recurrence and new primary melanomas. Dermatologic Therapy 18:423–435.

Berchick ER, Hood E, Barnett JC. 2018. Health Insurance Coverage in the United States: 2017. United States Census Bureau.

Berg RJW. 1998. Defective Global Genome Repair in XPC Mice Is Associated with Skin Cancer Susceptibility But Not with Sensitivity to UVB Induced Erythema and Edema. Journal of Investigative Dermatology 110:405.

Bishop DT, Demenais F, Iles MM, Harland M, Taylor JC. 2009. Genome-wide association study identifies three loci associated with melanoma risk. Nature Genetics 41.

Blum HF. 1961. Does the Melanin Pigment of Human Skin Have Adaptive Value?: An Essay in Human Ecology and the Evolution of Race. The Quarterly Review of Biology 36:50–63.

Bradford PT, Goldstein AM, Mcmaster ML, Tucker MA. 2009. Acral Lentiginous Melanoma: Incidence and Survival Patterns in the United States, 1986-2005. Archives of Dermatology 145.

Burke LS, Hyland PL, Pfeiffer RM, Prescott J, Wheeler W, Mirabello L, Savage SA, Burdette L, Yeager M, Chanock S, Vivo ID, Tucker MA, Goldstein AM, Yang XR. 2013. Telomere Length and the Risk of Cutaneous Malignant Melanoma in Melanoma-Prone Families with and without CDKN2A Mutations. PLoS ONE 8.

Chan JL, Moshell A, Turner M, Kimball A. 2004. Assessing the role of race in quantitative measures of skin pigmentation and clinical assessments of photosensitivity. Journal of the American Academy of Dermatology 50.

Chang Y-M, Newton-Bishop JA, Bishop DT, Armstrong BK, Bataille V, Bergman W, Berwick M, Bracci PM, Elwood JM, Ernstoff MS, Green AC, Gruis NA, Holly EA, Ingvar C, Kanetsky PA, Karagas MR, Marchand LL, Mackie RM, Olsson H, Ø sterlind A, Rebbeck TR, Reich K, Sasieni P, Siskind V, Swerdlow AJ, Titus-Ernstoff L, Zens MS, Ziegler A, Barrett JH. 2009. A pooled analysis of melanocytic nevus phenotype and the risk of cutaneous melanoma at different latitudes. International Journal of Cancer 124:420– 428.

Chatzinasiou F, Lill CM, Kypreou K, Stefanaki I, Nicolaou V, Spyrou G, Evangelou E, Roehr JT, Kodela E, Katsambas A, Tsao H, Ioannidis JPA, Bertram L, Stratigos AJ. 2011. Comprehensive Field Synopsis and Systematic Meta-analyses of Genetic Association Studies in Cutaneous Melanoma. JNCI Journal of the National Cancer Institute 103:1227–1235.

Cockburn MG, Zadnick J, Deapen D. 2006. Developing epidemic of melanoma in the hispanic population of California. Cancer 106:1162–1168.

Cohen S, Janicki-Deverts D, Turner RB, Casselbrant ML, Li-Korotky H-S, Epel ES, Doyle WJ. 2013. Association Between Telomere Length and Experimentally Induced Upper Respiratory Viral Infection in Healthy Adults. Jama 309:699.

Colby SL, Ortman JM. 2015. Projections of the Size and Composition of the U.S. Population: 2014 to 2060. United States Census Bureau.

Consensus Development Panel. 1989. National institutes of health summary of the consensus development conference on sunlight, ultraviolet radiation, and the skin. Journal of the American Academy of Dermatology 24:608–612.

Cormier JM, Xing Y, Ding M, Lee JE, Mansfield PF, Gershenwald JE, Ross MI, Du XL. 2006. 4. Ethnic Differences Among Patients With Cutaneous Melanoma. Archives of Internal Medicine 166.

Cress RD, Holly EA. 1997. Incidence of Cutaneous Melanoma among Non-Hispanic Whites, Hispanics, Asians, and Blacks: An Analysis of California Cancer Registry Data. Cancer Causes & Control 8:246–252.

Dasgupta A, Katdare M. 2015. Ultraviolet Radiation-Induced Cytogenetic Damage in White, Hispanic and Black Skin Melanocytes: A Risk for Cutaneous Melanoma. Cancers 7:1586–1604.

Dellinger RW, Liu-Smith F, Meyskens FL. 2014. Continuing to illuminate the mechanisms underlying UV-mediated melanomagenesis. Journal of Photochemistry and Photobiology B: Biology 138:317–323.

Denzer N, Vogt T, Reichrath J. 2011. Vitamin D receptor (VDR) polymorphisms and skin cancer. Dermato-Endocrinology 3:205–210.

Duffy DL, Iles MM, Glass D, Zhu G, Barrett JH, Höiom V, Zhao ZZ, Sturm RA, Soranzo N, Hammond C, Kvaskoff M, Whiteman DC, Mangino M, Hansson J, Newton-Bishop JA, Bataille V, Hayward NK, Martin NG, Bishop DT, Spector TD, Montgomery GW. 2010. IRF4 Variants Have Age-Specific Effects on Nevus Count and Predispose to Melanoma. The American Journal of Human Genetics 87:6–16.

Easton D, Cox G, Macdonald A, Ponder B. 1991. Genetic susceptibility to naevi – a twin study. British Journal of Cancer 64:1164–1167.

Eller MS, Ostrom K, Gilchrest BA. 1996. DNA damage enhances melanogenesis. Proceedings of the National Academy of Sciences 93:1087–1092.

Falchi M, Bataille V, Hayward NK, Duffy DL, Bishop JAN, Pastinen T, Cervino A, Zhao ZZ, Deloukas P, Soranzo N, Elder DE, Barrett JH, Martin NG, Bishop DT, Montgomery GW, Spector TD. 2009. Genome-wide association study identifies variants at 9p21 and 22q13 associated with development of cutaneous nevi. Nature Genetics 41:915–919.

Fitzpatrick TB. 1988. The Validity and Practicality of Sun-Reactive Skin Types I Through VI. Archives of Dermatology 124:869.

Galindo GR, Mayer JA, Slymen D, Almaguer DD, Clapp E, Pichon LC, Hoerster K, Elder JP. 2007. Sun Sensitivity in 5 US Ethnoracial Groups. Cutis 80:25–30.

Gandini S, Sera F, Cattaruzza MS, Pasquini P, Picconi O, Boyle P, Melchi CF. 2005. Meta- analysis of risk factors for cutaneous melanoma: II. Sun exposure. European Journal of Cancer 41:45–60.

García-Borrón JC, Abdel-Malek Z, Jiménez-Cervantes C. 2014. MC1R, the cAMP pathway, and the response to solar UV: extending the horizon beyond pigmentation. Pigment Cell & Melanoma Research 27:699–720.

Gray-Schopfer VC, Cheong SC, Chong H, Chow J, Moss T, Abdel-Malek ZA, Marais R, Wynford-Thomas D, Bennett DC. 2006. Cellular senescence in naevi and immortalisation in melanoma: a role for p16? British Journal of Cancer 95:496–505.

Greene MH. 1985. High Risk of Malignant Melanoma in Melanoma-Prone Families with Dysplastic Nevi. Annals of Internal Medicine 102:458.

Halder RM, Ara CJ. 2003. Skin cancer and photoaging in ethnic skin. Dermatologic Clinics 21:725–732.

Hall HI, Jones SE, Saraiya M. 2001. Prevalence and Correlates of Sunscreen Use Among US High School Students. Journal of School Health 71:453–457.

Hamad R, Tuljapurkar S, Rehkopf DH. 2016. Racial and Socioeconomic Variation in Genetic Markers of Telomere Length: A Cross-Sectional Study of U.S. Older Adults. EBioMedicine 11:296–301.

Han J, Qureshi AA, Nan H, Zhang J, Song Y, Guo Q, Hunter DJ. 2011. A Germline Variant in the Interferon Regulatory Factor 4 Gene as a Novel Skin Cancer Risk Locus. Cancer Research 71:1533–1539.

Heiman M. 1997. Webcutter 2.0. Heiman Lab. Available from: http://heimanlab.com/cut2.html

Iles MM, Law MH, Stacey SN, Han J, Fang S. 2013. A variant in FTO shows association with melanoma risk not due to BMI. Nature Genetics 45.

Jacobs LC, Hamer MA, Gunn DA, Deelen J, Lall JS, Heemst DV, Uh H-W, Hofman A, Uitterlinden AG, Griffiths CE, Beekman M, Slagboom PE, Kayser M, Liu F, Nijsten T. 2015. A Genome-Wide Association Study Identifies the Skin Color Genes IRF4, MC1R, ASIP, and BNC2 Influencing Facial Pigmented Spots. Journal of Investigative Dermatology 135:1735–1742.

Horn S, Figl A, Rachakonda PS, Fischer C, Sucker A, Gast A, Kadel S, Moll I, Nagore E, Hemminki K, Schadendorf D, Kumar R. 2013. TERT Promoter Mutations in Familial and Sporadic Melanoma. Science 339:959–961.

Howlader N, Noone AM, Krapcho M. 2017. SEER Cancer Statistics Review, 1975-2014. National Cancer Institute.

Hubacek JA, Viklicky O, Dlouha D, Bloudickova S, Kubinova R, Peasey A, Pikhart H, Adamkova V, Brabcova I, Pokorna E, Bobak M. 2011. The FTO gene polymorphism is associated with end-stage renal disease: two large independent case-control studies in a general population. Nephrology Dialysis Transplantation 27:1030–1035.

Hunt SC, Chen W, Gardner JP, Kimura M, Srinivasan SR, Eckfeldt JH, Berenson GS, Aviv A. 2008. Leukocyte telomeres are longer in AfricanAmericans than in whites: the National Heart, Lung, and Blood Institute Family Heart Study and the Bogalusa Heart Study. Aging Cell 7:451–458.

Jablonski NG, Chaplin G. 2000. The evolution of human skin coloration. Journal of Human Evolution 39:57–106.

Jablonski NG, Chaplin G. 2010. Human skin pigmentation as an adaptation to UV radiation. Proceedings of the National Academy of Sciences 107:8962–8968.

Kadekaro AL, Leachman S, Kavanagh RJ, Swope V, Cassidy P, Supp D, Sartor M, Schwemberger S, Babcock G, Wakamatsu K, Ito S, Koshoffer A, Boissy RE, Manga P, Sturm RA, Abdel-Malek ZA. 2010. Melanocortin 1 receptor genotype: an important determinant of the damage response of melanocytes to ultraviolet radiation. The FASEB Journal 4:3850–3860.

Kanetsky PA, Panossian S, Elder DE, Guerry D, Ming ME, Schuchter L, Rebbeck TR. 2010. Does MC1R genotype convey information about melanoma risk beyond risk phenotypes? Cancer.

Kelly S, Miller LE, Ahn H-Y, Haley JE. 2014. Perceptions and Portrayals of Skin Cancer among Cultural Subgroups. ISRN Dermatology 2014:1–7.

Koressaar T, Remm M. 2007. Enhancements and modifications of primer design program Primer3. Bioinformatics 23:1289–1291.

Kvaskoff M, Whiteman DC, Zhao ZZ, Montgomery GW, Martin NG, Hayward NK, Duffy DL. 2011. Polymorphisms in Nevus-Associated Genes MTAP, PLA2G6, and IRF4 and the Risk of Invasive Cutaneous Melanoma. Twin Research and Human Genetics 14:422– 432.

Lalueza-Fox C, Rompler H, Caramelli D, Staubert C, Catalano G, Hughes D, Rohland N, Pilli E, Longo L, Condemi S, Rasilla MDL, Fortea J, Rosas A, Stoneking M, Schoneberg T, Bertranpetit J, Hofreiter M. 2007. A Melanocortin 1 Receptor Allele Suggests Varying Pigmentation Among Neanderthals. Science 318:1453–1455.

Loomis WF. 1967. Skin-Pigment Regulation of Vitamin-D Biosynthesis in Man: Variation in solar ultraviolet at different latitudes may have caused racial differentiation in man. Science 157:501–506.

Maccioni L, Rachakonda S, Scherer D, Bermejo JL, Planelles D, Requena C, Hemminki K, Nagore E, Kumar R. 2012. Variants at chromosome 20 (ASIP locus) and melanoma risk. International Journal of Cancer 132:42–54.

Maccioni L, Rachakonda PS, Bermejo JL, Planelles D, Requena C, Hemminki K, Nagore E, Kumar R. 2013. Variants at the 9p21 locus and melanoma risk. BMC Cancer 13.

MacKie RM, Aitchison T. 1982. Severe sunburn and subsequent risk of primary cutaneous malignant melanoma in scotland. British Journal of Cancer 46:955–960.

MacKie RM, Hole DJ. 1996. Incidence and thickness of primary tumours and survival of patients with cutaneous malignant melanoma in relation to socioeconomic status. BMJ 312:1125–1128.

MacKie RM, Hole D, Hunter JA, Rankin R, Evans A, Mclaren K, Fallowfield M, Hutcheon A, Morris A. 1997. Cutaneous malignant melanoma in Scotland: incidence, survival, and mortality, 1979-94. BMJ 315.

Mahendraraj K, Sidhu K, Lau CS, Mcroy GJ, Chamberlain RS, Smith FO. 2017. Malignant Melanoma in African–Americans: A Population-Based Clinical Outcomes Study Involving 1106 African-American Patients from the Surveillance, Epidemiology, and End Result (SEER) Database (1988-2011). Medicine 96.

Maresca V, Flori E, Picardo M. 2015. Skin phototype: a new perspective. Pigment Cell & Melanoma Research 28:378–389.

Merkle T, Landthaler M, Eckert F, Braun-Falco O. 1991. Acral verrucous malignant melanoma in an immunosuppressed patient after kidney transplantation. Journal of the American Academy of Dermatology 24:505–506.

Mitra D, Luo X, Morgan A, Wang J, Hoang MP, Lo J, Guerrero CR, Lennerz JK, Mihm MC, Wargo JA, Robinson KC, Devi SP, Vanover JC, D’Orazio JA, Mcmahon M, Bosenberg MW, Haigis KM, Haber DA, Wang Y, Fisher DE. 2012. An ultraviolet-radiation- independent pathway to melanoma carcinogenesis in the red hair/fair skin background. Nature 491:449–453.

Needham BL, Adler N, Gregorich S, Rehkopf D, Lin J, Blackburn EH, Epel ES. 2013. Socioeconomic status, health behavior, and leukocyte telomere length in the National Health and Nutrition Examination Survey, 1999–2002. Social Science & Medicine 85:1– 8.

Newton-Bishop JA, Chang Y-M, Iles MM, Taylor JC, Bakker B, Chan M, Leake S, Karpavicius B, Haynes S, Fitzgibbon E, Elliott F, Kanetsky PA, Harland M, Barrett JH, Bishop DT. 2010. Melanocytic Nevi, Nevus Genes, and Melanoma Risk in a Large Case-Control Study in the United Kingdom. Cancer Epidemiology Biomarkers & Prevention 19:2043–2054.

Norton HL, Kittles RA, Parra E, Mckeigue P, Mao X, Cheng K, Canfield VA, Bradley DG, Mcevoy B, Shriver MD. 2006. Genetic Evidence for the Convergent Evolution of Light Skin in Europeans and East Asians. Molecular Biology and Evolution 24:710–722.

Norton HL, Edwards M, Krithika S, Johnson M, Werren EA, Parra EJ. 2016. Quantitative assessment of skin, hair, and iris variation in a diverse sample of individuals and associated genetic variation. American Journal of Physical Anthropology 160:570–581.

O’sullivan RJ, Karlseder J. 2010. Telomeres: protecting chromosomes against genome instability. Nature Reviews Molecular Cell Biology 11:171–181.

Palmer JS, Duffy DL, Box NF, Aitken JF, Ogorman LE, Green AC, Hayward NK, Martin NG, Sturm RA. 2000. Melanocortin-1 Receptor Polymorphisms and Risk of Melanoma: Is the Association Explained Solely by Pigmentation Phenotype? The American Journal of Human Genetics 66:176–186.

Parker K, Horowitz JM, Morin R, Lopez MH. 2015. Multiracial in America Chapter 7: The Many Dimensions of Hispanic Racial Identity. Pew Research Center.

Pasquali E, García-Borrón JC, Fargnoli MC, Gandini S, Maisonneuve P, Bagnardi V, Specchia C, Liu F, Kayser M, Nijsten T, Nagore E, Kumar R, Hansson J, Kanetsky PA, Ghiorzo P, Debniak T, Branicki W, Gruis NA, Han J, Dwyer T, Blizzard L, Landi MT, Palmieri G, Ribas G, Stratigos A, Council ML, Autier P, Little J, Newton-Bishop J, Sera F, Raimondi S. 2015. MC1R variants increased the risk of sporadic cutaneous melanoma in darker- pigmented Caucasians: A pooled-analysis from the M-SKIP project. International Journal of Cancer 136:618–631.

Pathak MA, Jimbow K, Szabo G, Fitzpatrick TB. 1976. Sunlight and Melanin Pigmentation. Photochemical and Photobiological Reviews:211–239.

Peña-Chilet M, Blanquer-Maceiras M, Ibarrola-Villava M, Martinez-Cadenas C, Martin- Gonzalez M, Gomez-Fernandez C, Mayor M, Aviles JA, Lluch A, Ribas G. 2013. Genetic variants in PARP1 (rs3219090) and IRF4(rs12203592) genes associated with melanoma susceptibility in a Spanish population. BMC Cancer 13.

Pichon LC, Landrine H, Corral I, Hao YP, Mayer JA, Hoerster KD. 2010c. Measuring Skin Cancer Risk in African Americans: Is the Fitzpatrick Skin Type Classification Scale Culturally Sensitive? Ethnicity and Disease 20.

Pichon LC, Corral I, Landrine H, Mayer JA, Adams-Simms D. 2010b. Perceived Skin Cancer Risk and Sunscreen Use among African American Adults. Journal of Health Psychology 15:1181–1189.

Pichon LC, Corral I, Landrine H, Mayer JA, Norman GJ. 2010a. Sun-Protection Behaviors Among African Americans. American Journal of Preventive Medicine 38:288–295.

Pipitone M, Robinson JK, Camara C, Chittineni B, Fisher SG. 2002. Skin cancer awareness in suburban employees: A Hispanic perspective. Journal of the American Academy of Dermatology 47:118–123.

Plettenberg A, Pammer J, Tschachler E. 1996. Merkel cells and Merkel cell carcinoma express the BCL-2 proto-oncogene. Experimental Dermatology 5:183–188.

Pollitt RA, Clarke CA, Swetter SM, Peng DH, Zadnick J, Cockburn M. 2011. The expanding melanoma burden in California hispanics: Importance of socioeconomic distribution, histologic subtype, and anatomic location. Cancer 117:152–161.

Proctor BD, Dalaker J. 2003. Poverty in the United States: 2002. United States Census Bureau.

Purcell S. Plink Whole Genome Association Analyses Toolset. Available from: http://pngu.mgh.harvard.edu/purcell/plink/

Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, Maller J, Sklar P, Bakker PID, Daly MJ, Sham PC. 2007. PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses. The American Journal of Human Genetics 81:559– 575.

Quinque D, Kittler R, Kayser M, Stoneking M, Nasidze I. 2006. Evaluation of saliva as a source of human DNA for population and association studies. Analytical Biochemistry 353:272–277.

Rafnar T, Sulem P, Stacey SN, Geller F. 2009. Sequence variants at the TERT- CLPTM1L locus associate with many cancer types. Nature Genetics 41.

Ransohoff KJ, Wu W, Cho HG, Chahal HC, Lin Y, Dai H-J, Amos CI, Lee JE, Tang JY, Hinds DA, Han J, Wei Q, Sarin KY. 2017. Two-stage genome-wide association study identifies a novel susceptibility locus associated with melanoma. Oncotarget 8.

Rhodes AR, Weinstock MA, Fitzpatrick TB, Mihm MC, Sober AJ. 1987. Risk Factors for Cutaneous Melanoma A Practical Method of Recognizing Predisposed Individuals. JAMA 258:3146–3154.

Robinson JK, Penedo FJ, Hay JL, Jablonski NG. 2017. Recognizing Latinos’ range of skin pigment and phototypes to enhance skin cancer prevention. Pigment Cell & Melanoma Research 30:488–492.

Sancar A. 1996. DNA Excision Repair. Annual Review of Biochemistry 65.

Saraiya M, Hall H, Uhler RJ. 2002. Sunburn prevalence among adults in the United States, 1999. American Journal of Preventive Medicine 23:91–97.

Satyamoorthy, K., and M. Herlyn. 2002. Cellular and Molecular Biology of Human Melanoma. Cancer Biology & Therapy 1(1): 14–17

Shekar SN, Duffy DL, Youl P, Baxter AJ, Kvaskoff M, Whiteman DC, Green AC, Hughes MC, Hayward NK, Coates M, Martin NG. 2009. A Population-Based Study of Australian Twins with Melanoma Suggests a Strong Genetic Contribution to Liability. Journal of Investigative Dermatology 129:2211–2219.

Stacey SN, Sulem P, Masson G, Gudjonsson SA. 2009. New common variants affecting susceptibility to basal cell carcinoma. Nature Genetics 41.

Stevens AP, Spangler B, Wallner S, Kreutz M, Dettmer K, Oefner PJ, Bosserhoff AK. 2009. Direct and tumor microenvironment mediated influences of 5′-deoxy-5′-(methylthio)adenosine on tumor progression of malignant melanoma. Journal of Cellular Biochemistry 106:210– 219.

Swope VB, Abdel-Malek ZA. 2016. Significance of the Melanocortin 1 and Endothelin B Receptors in Melanocyte Homeostasis and Prevention of Sun-Induced Genotoxicity. Frontiers in Genetics 7.

Untergasser A, Cutcutache I, Koressaar T, Ye J, Faircloth BC, Remm M, Rozen SG. 2012. Primer3—new capabilities and interfaces. Nucleic Acids Research 40.

Venkataram MN, Haitham AA. 2003. Correlating skin phototype and minimum erythema dose in Arab skin. International Journal of Dermatology 42:191–192.

Vink AA, Roza L. 2001. Biological consequences of cyclobutane pyrimidine dimers. Journal of Photochemistry and Photobiology 65.

Wachsmuth RC, Turner F, Barrett JH, Gaut R, Randerson-Moor JA, Bishop DT, Bishop JAN. 2005. The Effect of Sun Exposure in Determining Nevus Density in UK Adolescent Twins. Journal of Investigative Dermatology 124:56–62.

Ward E, Jemal A, Cokkinides V, Singh GK, Cardinez C, Ghafoor A, Thun M. 2004. Cancer Disparities by Race/Ethnicity and Socioeconomic Status. CA: A Cancer Journal for Clinicians 54:78–93.

Wentzensen IM, Mirabello L, Pfeiffer RM, Savage SA. 2011. The Association of Telomere Length and Cancer: a Meta-analysis. Cancer Epidemiology Biomarkers & Prevention 20:1238– 1250.

Whitehead M, Lane G, Young O, Campbell S, Abeyasekera G, Hillyard CJ, Macintyre I, Phang KG, Stevenson JC. 1981. Interrelations of calcium-regulating hormones during normal pregnancy. Bmj 283:10–12.

Yuen A, Jablonski N. 2010. Vitamin D: In the evolution of human skin colour. Medical Hypotheses 74:39–44.

Zerbino DR, Achuthan P, Akanni W, Amode MR. 2018. Ensembl 2018. Nucleic Acids Research 46:D754–D761.

Zhu H, Wang X, Gutin B, Davis CL, Keeton D, Thomas J, Stallmann-Jorgensen I, Mooken G, Bundy V, Snieder H, Harst PVD, Dong Y. 2011. Leukocyte Telomere Length in Healthy Caucasian and African-American Adolescents: Relationships with Race, Sex, Adiposity, Adipokines, and Physical Activity. The Journal of Pediatrics 158:215–220.

Appendix A.

Pigmentation Study Personal Questionnaire with Fitzpatrick Scale

Subject ID ______Name:______Date of Birth:____/____/____ (DD/MM/YY) Phone Number:______e-mail:______Pigmentation study Subject ID______Place of Birth (City/Country):______Ethnic Background:______Current residence (City/Country):______First Spoken Language:______Other languages:______Family History Country of Birth Native Language Ethnic Backgrounds Mother Maternal Grandmother Maternal Grandfather Father Paternal Grandmother Paternal Grandfather 1. Have you recently (3 months) visited a tanning salon? Yes No a. If yes, how many hours per week? ______2. Have you recently (3 months) traveled to a tropical/sunny destination? Yes No a. If yes, how long was your stay? ______3. Do you dye your hair? Yes No 4. Do you wear coloured contact lenses? Yes No 5. Have you been diagnosed any pigmentation disorder (e.g. melasma, vitiligo, albinism)? Pigmentation study Subject ID______Yes No a. If yes, which disorder? ______

SKIN TYPE QUESTIONNAIRE (FITZPATRICK) PART I (Please circle your answer) Your eye colour is: Light blue, light gray or light green = 0 Blue, gray or green =1 Hazel or light brown =2 Dark brown = 3 Brownish black =4 Your natural hair colour is: Red or light blonde = 0 Blonde = 1 Dark blonde or light brown = 2 Dark brown = 3 Black = 4 Your natural skin colour (before sun exposure) is: Ivory white = 0 Fair or pale = 1 Fair to beige, with golden undertone = 2 Olive or light brown = 3 Dark brown or black =4 How many freckles do you have on unexposed areas of your skin? Many = 0 Several = 1 Pigmentation study Subject ID______A few = 2 Very few = 3 None = 4

PART II (Please circle your answer) How does your skin respond to the sun? Always burns, blisters and peels = 0 Often burns, blisters and peels = 1 Burns moderately = 2 Burns rarely, if at all = 3 Never burns = 4 Does your skin tan? Never, I always burn = 0 Seldom = 1 Sometimes = 2 Often = 3 Always = 4 How deeply do you tan? Not at all or very little = 0

Lightly = 1 Moderately = 2 Deeply = 3 My skin is naturally dark = 4 How sensitive is your face to the sun? Very sensitive = 0 Sensitive = 1 Pigmentation study Subject ID______Normal = 2 Resistant = 3 Very resistant/Never had a problem = 4 Please, add up your scores in part I and II of the Fitzpatrick questionnaire.

Fitzpatrick Skin Type Scale Type I (0-6 points) Type II (7-12 points) Type III (13-18 points) Type IV (19-24 points) Type V (25-30 points) Type VI (31+ points)