Risk of head and neck cancer and the alcohol dehydrogenase 3 genotype
Andrew F. Olshan1, ,2, ,4,
Mark C. Weissler2,
Mary A. Watson3 and
Douglas A. Bell3
1 Department of Epidemiology, School of Public Health, University of North Carolina, Chapel Hill, NC,
2 Division of ENT/Head and Neck Surgery, Department of Surgery, School of Medicine, University of North Carolina, Chapel Hill, NC and
3 Laboratory of Computational Biology and Risk Assessment, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
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Abstract
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Squamous cell carcinoma of the head and neck (SCCHN), including the oral cavity, pharynx and larynx, is an excellent tumor model to evaluate geneenvironment interactions, including alcohol and alcohol-metabolizing enzymes such as alcohol dehydrogenase (ADH). We conducted a hospital-based casecontrol study including 182 cases with newly diagnosed SCCHN and 202 controls with non-neoplastic conditions of the head and neck that required surgery. The joint effects of lifetime alcohol use and the presence of the ADH3 `rapid' allele (ADH3*1) was evaluated in relation to the risk of SCCHN. Logistic regression was used to estimate the interaction between alcohol use and ADH3 genotype with adjustment for tobacco use, age, sex and race. The interaction was evaluated on both the multiplicative and additive scales. The risk of SCCHN was increased nearly 6-fold with consumption of 40 or more alcoholic beverages per week [odds ratio (OR) = 5.9; 95% confidence interval (CI) = 2.017.7; adjusted for age, sex, race and years of tobacco use]. We did not find any increase in risk for ADH3*1 homozygotes (OR = 0.9; CI = 0.41.9) or heterozygotes (OR = 0.8; CI = 0.41.7) relative to ADH3*2 homozygotes. There was no suggestion of an interaction between any alcohol use variable and the ADH3*1 genotype. For example, the interaction term, including the continuous variable average number of drinks per week and the ADH3 genotypes, was non-significant (P = 0.22). The study does not indicate an important role for the ADH3 *1 polymorphism in SCCHN, but larger numbers are needed to more precisely estimate the interaction, if any, with ADH3.
Abbreviations: ADH, alcohol dehydrogenase; CI, confidence interval; ICR, interaction contrast ratio; OR, odds ratio; SCCHN, squamous cell carcinoma of the head and neck.
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Introduction
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Squamous cell carcinoma of the head and neck (SCCHN), including the oral cavity, pharynx, and larynx, is strongly related to the consumption of tobacco and alcohol. A large US casecontrol study estimated an ~9-fold risk for oro-pharyngeal cancer with more than 30 drinks of alcohol per week and a 37-fold elevated risk for the joint effects of heavy drinking (30+ drinks/week) and smoking (40+ per day for 20 or more years) (1). This study estimated that the combination of tobacco and alcohol accounted for 74% of all oral and pharyngeal cancers in the USA. Several mechanisms have been proposed to explain the carcinogenic effects of alcohol, including alcohol contaminants, free radical damage, impairment of DNA repair processes, acting as a `solvent' for tobacco carcinogens and induction of carcinogen-metabolizing enzymes (2,3). Ethanol is oxidized to acetaldehyde and then to acetate. Studies have suggested a direct mutagenic and carcinogenic effect of acetaldehyde (48). The metabolic reactions are mediated by alcohol dehydrogenase (ADH) and aldehyde dehydrogenase, respectively (911).
There are at least seven alcohol dehydrogenases present in humans (11). Among these, the ADH3 gene displays functional polymorphisms that appear to impact on ethanol metabolism and susceptibility to alcoholism (11). ADH3*2 is a low activity allele which reduces the rate of oxidation of ethanol to acetaldehyde by ~2.5-fold and is present at frequencies of from 0.12 to 0.39 depending on ethnicity. The more common, fully functional allele, ADH3*1, has been suggested to be a protective factor in the risk of alcoholism (12). Conversely, ADH3*1 has also been suggested as a risk factor in alcohol-related cancers, because rapid oxidation of ethanol would result in higher tissue levels of acetaldehyde (the putative carcinogen) (11).
Despite the plausibility of a differential cancer risk conferred by the ADH3*1 allele in an alcohol-related cancer such as head and neck cancer, there have been few studies that have directly investigated the hypothesis. A small study of French alcoholics reported an association with ADH3*1 genotype and oropharyngeal and laryngeal cancer, while a larger French study did not find any association (1315). A recent study of oral cancer in Puerto Rico reported an interaction between the ADH3*1/*1 genotype, alcohol use and the risk of oral cancer (16). We report the results of a casecontrol study of ADH3 genotype, alcohol use and risk of SCCHN in North Carolina.
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Materials and methods
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We conducted a hospital-based casecontrol study at the University of North Carolina Hospitals from April 1994 to June 1997. Cases included patients with a newly diagnosed first SCCHN. Cases were considered eligible for the study if they were older than 17 years of age, had pathologically confirmed squamous cell carcinoma of the oral cavity, pharynx or larynx, did not have a history of a previous malignant cancer or a diagnosis of a genetic disease or syndrome. Patients with nasopharyngeal cancer were excluded. Cases were also eligible if they spoke either English or Spanish. 182 patients (88%) of 207 eligible cases identified were successfully interviewed and 25 (12%) refused participation. The primary tumor site was distributed as: 93 oral cavity; 37 pharynx; 52 larynx. The oral cavity tumor sites included: tongue (n = 42); gum (n = 17); floor of mouth (n = 14); other (n = 20).
Control subjects were patients with non-cancer-related conditions requiring surgery and were identified in the same ENT clinic as cases. These major conditions included chronic sinusitis, nasal obstruction and obstructive sleep apnea. Eligibility criteria for controls were the same as for cases. Controls were frequency matched with cases on age and gender. A total of 202 control subjects participated (86% of eligible) in the study.
An in-person interview was conducted with each subject in the hospital clinic by a trained interviewer. The interview consisted of questions related to lifetime tobacco and alcohol consumption (not including the year prior to diagnosis), occupation, medical history, family history of cancer, demographics and diet. Informed consent, a blood sample and a buccal swab of exfoliated oral cells were obtained. Drinkers were defined as those subjects who reported ever consuming an alcoholic beverage four or more times per month prior to a year before the diagnosis reference date. A lifetime history of alcohol consumption (beer, wine and liquor) was obtained and variables corresponding to average weekly use and years of use were derived.
Blood samples or buccal swabs were not obtained from a total of 12 subjects [5 (3.5%) cases and 7 (3.3%) controls]. Blood was collected in one yellow-top (ACD) 8.5 ml vacutainer tube. Plasma, buffy coat and red cells were separated and stored at 70°C within 24 h of collection. The buffy coat was thawed and DNA was extracted using the ABI Nucleic Acid Purification System (Applied Biosystems, Foster City, CA). DNA samples were evaluated for quantity by spectrophotometry and quality by a 1% agarose gel run. Samples were stored at 4°C until genotyping. Genotyping was performed primarily using DNA from blood samples. If a blood sample was not obtained but a buccal swab was available, the buccal cell samples were used for genotyping. DNA was extracted from buccal swab samples using the Qiagen method (Qiagen, Chatsworth, CA). When there was difficulty in determining the genotype for a particular sample, both blood and buccal cell samples were utilized.
Genomic DNA was genotyped for the ADH3 alleles using a modified version of the PCR/RFLP method of Groppi et al. (17). Briefly, 50 ng of genomic DNA was amplified in a Perkin-Elmer 9600 with the following cycling profile: initial denaturation at 94°C for 4 min followed by 32 cycles of 94°C for 15 s, 55°C for 15 s and 72°C for 15 s. The primers used were ADH3ex8F (AAT AAT TAT TTT TCA GGC TTT AAG AGT AAA TAT TCT GT) and ADH3ex8R (AAT CTA CCT CTT TCC AGA GC), which generated a 162 bp fragment. Samples were digested with SspI at 37°C for 3 h and run on a 3% Metaphor agarose gel (FMC Bioproducts, Rockland, ME). The forward primer contains two mismatched bases (underlined), creating an SspI site which is used as an internal control for digestion, and also has a 9 nt `tail' that helps in resolving the control fragment. Recent versions of this method have used an 18 nt tail on the reverse primer to improve resolution of digested fragments. The 162 bp fragment is cut in all samples to 131 and 31 bp at the control SspI site. The difference between Ile (ADH3*1) and Val (ADH3*1) codons at amino acid residue 349 (nucleotide change guanine to adenine) is recognized by SspI, fully digesting the 131 bp fragment into 68 and 63 bp fragments in ADH3*1/*1 homozygotes. ADH3*1/*2 heterozygote samples display all four fragments (131, 68, 63 and 31 bp), whereas samples from ADH3*2/*2 homozygotes resist digestion and contain only the 131 and 31 bp fragments. The ADH3 genotype could not be determined for four cases and one control.
The odds ratio (OR) estimate and 95% confidence interval (CI) for the main effects of alcohol and ADH3 genotype were obtained using multivariate unconditional logistic regression (18). ADH3*2 is the less common, low activity allele which is presumed to be related to reduced risk; the more common ADH3*1 allele has full activity and is presumed to be the `at risk' allele. Adjustment was made for the potential confounding effects of age, sex and race (black or white). The ORs for the main effect of alcohol use and interaction with ADH3 were further adjusted for duration of tobacco consumption (total years of use). Use of other tobacco consumption variables, such as average number of cigarettes per week, did not alter the estimates. The interaction of alcohol and ADH3 was evaluated on the additive and multiplicative scales. Dummy variables were created each representing the combination of an alcohol consumption category and ADH3 genotype. Non-drinkers with the ADH3*2/*2 genotype were used as the referent category. Adjusted ORs were evaluated for departure from the expected null values on the additive and multiplicative scales. Departures from additivity were estimated using the interaction contrast ratio (ICR, also previously called the relative excess risk for interaction; 19). For multi-level alcohol exposure variables the ICR was estimated using a dichotomous coding for alcohol use level compared with non-drinkers and ADH3 genotype coded as ADH3*1 genotype compared with ADH3*2 homozygotes. In addition to these analyses with alcohol consumption in a categorical form we also examined the significance of the interaction term including the ADH3 genotype and alcohol use represented as a continuous variable (drinks per week or years of use).
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Results
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Cases were more likely than controls to be male (76 versus 56%) and black (38 versus 14%). The mean age of cases was 59.5 years and 56.8 years for controls. Table I
presents the main effects of alcohol use, adjusted for age, race, sex and years of tobacco use. A total of 15 cases and one control were missing information on the amount of alcohol used. A total of 82% of cases and 53% of controls reported regular drinking, i.e. four or more alcoholic beverages per month prior to the year before the diagnosis reference date (OR adjusted = 2.0; CI = 1.13.8). A doseresponse gradient was apparent when alcohol consumption was defined as the average number of drinks consumed per week. The risk was increased nearly 6-fold for 60 or more drinks per week, after adjustment for years of tobacco use.
The ADH3*1 allele frequencies were 0.62 among controls and 0.69 among cases; the allele frequency for the ADH3*2 allele was 0.38 and 0.31 among controls and cases, respectively (P = 0.05). The distribution of genotypes among all controls were consistent with expectations under HardyWeinberg equilibrium (P = 0.99). The genotype frequencies did not depart from the conditions of HardyWeinberg equilibrium separately among white and black controls.
The ADH3*1 allele was more common among African-American than white controls (0.88 versus 0.58; P < 0.0001) and cases (0.84 versus 0.60; P < 0.0001). The prevalence of the ADH3*1 allele was also higher among female (0.77) than male cases (0.67; P = 0.07). There were no gender-specific differences in allele frequencies among controls (P = 0.34). The distribution of genotypes is presented in Table II
. In general, there was no difference in genotypes between cases and controls. A total of 49% of cases and 39% of controls had the ADH3*1 genotype (OR = 0.9; CI = 0.41.9). The genotype distributions did not differ between cases and controls among whites or blacks separately.
Table III
presents the results of the analysis of the joint effects of alcohol consumption and presence of the ADH3 genotypes. In Table III
the ADH3*1/*1 and *1/*2 genotypes were combined. These results are not appreciably different from the results obtained for the ADH3*1/*2 heterozygotes and ADH3*1/*1 homozygotes separately (data not shown). The results do not indicate any increased risk of SCCHN for individuals with the ADH3*1/*2 or ADH3*1/*1 genotype compared with individuals carrying the ADH3*2/*2 genotype at any level of alcohol intake, regardless of the definition of consumption used. For example, the OR for persons reporting an average alcohol consumption of 60 or more drinks per week was 5.2 (CI = 0.927.7) among subjects with the ADH3*1 genotype compared with non-drinkers with the ADH3*2/*2 genotype. In comparison, there were six cases and no controls with the ADH3*2 genotype that reported 60 or more drinks per week. There was no evidence for a significant departure from the expected multiplicative or additive joint effect. For example, the ICR was 0.4 (a value of 0 indicates no departure from additivity; CI = 3.42.5) for ADH3*1 and ever use of alcohol and 0.07 (CI = 3.03.2) for total years of alcohol use. The regression coefficients for alcohol use [average drinks per week (continuous), adjusted for age, sex, race and years of tobacco use] were 0.047 (95% CI = 0.0240.118) for ADH3*2/*2, 0.004 (CI = 0.0040.013) for ADH3*1/*2 and 0.004 (CI = 0.0070.014) for ADH3*1/*1. The interaction term for alcohol use and the three genotypes was not statistically significant overall (P =0.22) or for an interaction term contrasting ADH3*2/*2 with ADH3*1/*2 and ADH3*1/*1 combined (P = 0.23).
We also examined whether the joint effects of alcohol use and the ADH3 genotype varied with other factors. These analyses were generally limited by the relatively small number of subjects and resultant imprecise OR estimates. There was no consistently different pattern of association by type of alcohol consumed (beer, wine or liquor). Analyses by tumor site showed no effect of the ADH3*1 homozygous genotype among cases with an oral cavity or pharyngeal tumor (n = 130, adjusted OR = 1.1; CI = 0.52.4; ADH3*1/*2 heterozygote OR = 0.9; CI = 0.42.0). There was no suggestion of an interaction between alcohol use and ADH3 genotype with cases limited to oro-pharyngeal tumors. Laryngeal cases (n = 52) were associated with an imprecise decreased odds ratio (ADH3*1 homozygotes and heterozygotes OR = 0.5; CI = 0.21.5). The wide confidence intervals associated with these estimates limit interpretation.
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Discussion
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The results of our study among North Carolina African-Americans and whites suggest no increased risk of head and neck cancer for individuals who have inherited the ADH3*1 allele. Furthermore, no joint effects or interactions were detected between `at risk' ADH3 genotypes and amount or duration of alcohol consumption. Caution must be used in interpreting these results owing to the imprecision of some of the effect estimates. The results of this study are in contrast with the findings of Harty et al. (16). Their population-based casecontrol study conducted in Puerto Rico found an increased risk of oral cancer among heavy drinkers (>57 drinks/week) with the ADH3*1/*1 (OR = 40.1; CI = 5.4296.0), ADH3*1/*2 (OR = 7.0;CI = 1.435.0) and ADH3*2/*2 (OR = 4.4; CI = 0.633.3) genotypes. Because there were no non-drinkers with the *2/*2 genotype non-drinkers with the ADH3*1/*1 genotype were used as the referent category. A small French study (13) of alcoholic men (39 cases and 37 alcoholic non-cancer controls) found associations with the ADH3*1/*1 genotype (OR = 2.6; CI = 0.710.0 for oropharyngeal cancer; OR = 6.1; CI = 1.328.6 for laryngeal cancer). A recent study from France (15) (121 cases of oral cavity and pharynx cancer, 129 laryngeal cancer cases and 172 hospital controls) reported no significant increase in the risk of oropharyngeal cancer among heavy drinkers (>120 g/day, ~>70 drinks/week) with the ADH3*1/*1 genotype (OR = 6.3;CI = 1.821.4) compared with those with either the ADH3*1/*2 or ADH3*2/*2 genotypes (OR = 5.8;CI = 1.917.6). No interaction between alcohol consumption and ADH3 genotype was seen for laryngeal cancer as well.
Harty et al. (20) offered several explanations for the differences between their study and the French study, including differences in the definition of the referent category and patterns of alcohol use. We used non-drinkers as our referent category, as in the Harty et al. study [Bouchardy et al. (15) used <40 g/day]. The Harty study did not include cases with larynx cancer. Bouchardy et al. reported no association with laryngeal cancer and we found no indication of an interaction after exclusion of laryngeal cases. Another possible source of variation among study findings is the source of control subjects. Harty et al. used area sampling and Medicare files to identify controls. We and Bouchardy et al. used hospital patients as controls. Harty et al. raised concerns regarding the exclusion of individuals with severe liver disease from the French control series. Our controls included ENT patients requiring surgery for a diverse array of medical conditions. It is possible that some conditions among controls may be associated with alcohol use and metabolism. With respect to alcohol use, the Harty et al. study reported an adjusted OR of 13.2 (CI = 3.944.0) for the highest use category (>57 drinks/week). Bouchardy et al. reported an OR of 4.6 (CI = 2.110.1) for >70 drinks/week and we found an adjusted OR of 5.9 (CI = 2.017.7) for
60 drinks/week. Among controls in the Harty et al. study 8.9% (n = 5) reported drinking
57 drinks/week compared with 2.5% (n = 5) among our control group. Therefore, our study would have less power to find an association in the heaviest alcohol consumption category considered by Harty et al.
The distribution of genotypes was similar between our control groups. Specifically, among our white controls 33% were ADH3*1/*1 (38% in Harty et al.), 51% were ADH3*1/*2 (48% in Harty et al.) and 16% were ADH3*2/2 (14% in Harty et al.). Furthermore, the joint distribution of alcohol use and ADH3*1/*1 genotype among our white controls was similar to the other studies. Among controls who reported drinking
15 drinks/week a total of 36% were ADH3*1/*1, compared with 37% among the Harty et al. control series. Finally, when we include only white cases and controls the joint effect of alcohol use and ADH3 was quite similar to the overall results with adjustment for race. For example, the OR (adjusted for age, sex and years of tobacco use) for 30 or more years of alcohol use among those with ADH3*1/*1 or ADH3*1/*2 genotypes was 2.5 (CI = 0.610.6) and 2.0 (CI = 0.312.3) for ADH3*2/*2 individuals.
The hypothesis that polymorphisms of alcohol-metabolizing genes may modify the risk of alcohol-related diseases is certainly plausible. Head and neck cancer provides an ideal tumor to evaluate this geneenvironment interaction. However, the small number of studies published to date have not yielded a consistent pattern of association. Ethanol metabolism is complex, with multiple alcohol dehydrogenases and cytochrome P450 2E1 potentially involved in its oxidation to acetaldehyde. The relative importance of different biochemical pathways and the amount of metabolism occurring in head and neck tissues versus liver have not been determined. The difference in enzymatic activity between ADH3*1 and ADH3*2 proteins is estimated to be ~2.5-fold (9). It may be that the ADH3 pathway is not the primary ethanol metabolism pathway in head and neck tissues and that genetic risk differences for ADH3 alleles are only observed when there are very high, chronic alcohol exposures. Consideration of other polymorphic genes in the ethanol metabolism pathway may also be useful in understanding geneenvironment interactions in SCCHN. Polymorphic variation in ADH2, ADH4 and CYP2E1 could potentially influence cancer risk following ethanol exposure (9,15,21). In addition, there are recent reports that describe a 96 bp insertion polymorphism in the promoter region of the CYP2E1 gene and this appears to be associated with alcohol-induced gene expression (22,23). It is unknown how this CYP2E1 polymorphism affects alcohol metabolism, risk of alcoholism or risk of cancer.
Analysis of the role of genetic variation in all alcohol metabolism pathways would be of great interest for future studies. Nevertheless, the strongest recommendation from the present study is to establish a population-based study that is large enough (~10002000 cases) to provide adequate statistical power to precisely estimate the interaction (if any) between alcohol use and ADH genotype, as well as to consider other important exposures and genotypes.
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Notes
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4 To whom correspondence should be addressed at: Department of Epidemiology, CB 7400, School of Public Health, University of North Carolina, Chapel Hill, NC 27599-7400, USA 
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Acknowledgments
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We wish to thank Cathy Van Doren, Rosemary McKaig, Stacy Geisler and Christopher Lyu and staff at Battelle/SRA for assistance with data collection and Joanna Smith for programming help. In addition, the support of the nurses and surgeons of the Division of ENT and Head and Neck Surgery is greatly appreciated. This work was supported by NIH grant CA61188 and by a grant from the Institute of Nutrition, University of North Carolina.
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Received July 13, 2000;
revised September 11, 2000;
accepted September 25, 2000.