Published online before print August 22, 2009, doi: 10.1161/CIRCGENETICS.109.873604
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Original Articles |
Alcohol Intake, Myocardial Infarction, Biochemical Risk Factors, and Alcohol Dehydrogenase Genotypes
From the Center for Alcohol Research (J.S.T., M.G.), National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark; The Copenhagen City Heart Study (M.G., B.G.N.), Bispebjerg Hospital, Copenhagen University Hospital, Copenhagen, Denmark; and Department of Clinical Biochemistry (J.S.T., B.G.N.), Herlev Hospital, Copenhagen University Hospital, Herlev, Denmark.
Correspondence to Janne S. Tolstrup, Center for Alcohol Research, National Institute of Public Health, Øster Farimagsgade 5a, DK-1399 Copenhagen, Denmark. E-mail jst{at}niph.dk
Received April 16, 2009; accepted July 27, 2009.
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Abstract |
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Background— The risk of myocardial infarction is lower among light-to-moderate alcohol drinkers compared with abstainers. We tested associations between alcohol intake and risk of myocardial infarction and risk factors and whether these associations are modified by variations in alcohol dehydrogenases.
Methods and Results— We used information on 9584 men and women from the Danish general population in the Copenhagen City Heart Study. During follow-up, from 1991 to 2007, 663 incident cases of myocardial infarction occurred. We observed that increasing alcohol intake was associated with decreasing risk of myocardial infarction, decreasing low-density lipoprotein cholesterol and fibrinogen, increasing diastolic and systolic blood pressure and high-density lipoprotein cholesterol, and with U-shaped nonfasting triglycerides. In contrast, ADH1B and ADH1C genotypes were not associated with risk of myocardial infarction or with any of the cardiovascular biochemical risk factors, and there was no indication that associations between alcohol intake and myocardial infarction and between alcohol intake and risk factors were modified by genotypes.
Conclusions— Increasing alcohol intake is associated with decreasing risk of myocardial infarction, decreasing low-density lipoprotein cholesterol and fibrinogen, increasing diastolic and systolic blood pressure and high-density lipoprotein cholesterol, and U-shaped nonfasting triglycerides. These associations were not modified by ADH1B and ADH1C are genotypes.
Key Words: blood pressure • genetics • cardiovascular diseases • myocardial infarction • epidemiology • alcohol • cardiovascular risk factors • alcohol dehydrogenase genes
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Introduction |
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Substantial epidemiological evidence suggests that alcohol has beneficial effects on the cardiovascular system.1–5 First, a lower risk of coronary heart disease among light-to-moderate alcohol consumers compared with abstainers is consistently observed in different populations.6 Second, plausible mediating factors such as increased high-density lipoprotein (HDL) cholesterol levels and reduced low-density lipoprotein (LDL) cholesterol and plasma fibrinogen levels have also been identified.7,8 In recent research, focus has been on identifying possible genetic and environmental modifiers of the association between alcohol and coronary heart disease. Specifically, it has been suggested that the effect of alcohol on the risk of coronary heart disease depends on variations in genes coding for alcohol-degrading enzymes: individuals carrying genotypes that code for slow alcohol degradation has persistently higher blood alcohol concentrations that leads to a lower risk of coronary heart disease compared with individuals with genotypes that code for fast alcohol degradation.
Clinical Perspective on p 507
Alcohol degradation is mainly catalyzed by different alcohol dehydrogenases (ADHs). In vitro studies have shown that at ADH1B, alleles ADH1B · 2 and ADH1B · 1 produce enzymes with a 38-fold difference in alcohol degradation rate, and at ADH1C, alleles ADH1C · 1 and ADH1C · 2 produce enzymes with a 2.5-fold difference.9 However, the size of in vivo effects of these variations is much more modest and not even consistently observeable.10–15 In whites, the frequency of the most active alleles (ADH1B · 2 and ADH1C · 1) are 
2% and 58%.16
Although the idea that the risk reduction of coronary heart disease in low-to-moderate drinkers depends on the genetic capacity for alcohol degradation is both appealing and plausible, the evidence for this modification is sparse and inconsistent. In the first study on the subject, which was conducted among American physicians, ADH1C slow metabolizers seemingly had a lower risk of myocardial infarction (MI) than ADH1C fast metabolizers, but this was confined to individuals in the highest drinking category17; however, this is in contrast to findings from another study, where this effect was only observed in men with a very low intake (less than 3 drinks per week).18 In some other studies, no significant interaction between the ADH1C genotype and alcohol on risk of coronary heart disease was found.19–21 The potential interaction between ADH1B genotypes and alcohol has not been addressed among whites, most likely because the ADH1B · 2 allele is relatively rare in this population.
In this study, we aim at testing the association between alcohol intake and risk of MI, and whether this association is modified by ADH1B and ADH1C genotypes. We also tested the association between alcohol intake and cardiovascular biochemical risk factors, such as blood pressure, HDL cholesterol, LDL cholesterol, triglycerides, and fibrinogen, and whether these associations differ according to genotype.
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Methods |
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Study Population
Our data originates from the Copenhagen City Heart Study, which is a series of studies conducted in the Danish general population. Examinations consisted of interview, physical examination, and more especially, blood was given for DNA purification at the examination that was performed in 1991–1994. Enrollment and examination procedures have been described in more detail elsewhere.22,23 All participants gave informed consent, and the ethics committee for Copenhagen and Frederiksberg approved the study (100.2039/91).
Questionnaire Measures
Amount of usual alcohol intake was reported as weekly consumption of beer (in bottles), wine (in glasses), and spirits (in units). Assuming 1 drink to be equal to 12 g of pure alcohol, a measure of total weekly alcohol intake was calculated. Smoking was reported as status (never, former, or current) and amount of smoking (in number of daily cigarettes, cheroots, cigars, and pipes). Assuming 1 cigarette to be equivalent to 1 g of tobacco, 1 cheroot or 1 cigar to be equivalent to 3 g of tobacco, and 1 pipe to be equivalent to 5 g of tobacco, total amount of daily smoking was calculated. School education was reported as number of years of basic schooling and categorized as <8, 8 to 11, and >11 years of education, corresponding to lower primary school, higher primary school, and secondary school. Participants were classified as having diabetes, hypertension, or hypercholesterolemia if they reported a physician-made diagnosis. Familial predisposition to cardiovascular disease was defined as having 1 or 2 affected parents before the age 60 years. Among women, we used information on menstruations and hormone replacement therapy to define their menopausal status in categories of pre and post-menopausal with and without hormone replacement therapy.
Clinical and Laboratory Measures
Arterial blood pressure was measured in the left arm with the participant in the sitting position after 5 minutes of rest. Study staff obtained blood samples and measured height and weight. Total plasma cholesterol, plasma HDL cholesterol, plasma nonfasting triglycerides, and plasma fibrinogen were measured using standard hospital assays (Boehringer Mannheim) subjected to daily internal quality control assessing assay precision and monthly external quality control assessing assay accuracy.
The ADH1B · 2 allele (rs1229984, Arg47His in exon 3) and ADH1C · 2 allele (rs698, Ile349Val in exon 8) were identified by means of duplex polymerase chain reaction followed by Nanogen microelectronic chip technology (Nanogen NMW 1000 Nanochip Molecular Biology Workstation24) using standard conditions (details available from authors). In a validation study, the accuracy of the Nanogen method was found to be comparable with restriction fragment length polymorphism.25
Assessment of MI and Vital Status
Information on MI was obtained from the Danish Patient Registry26 and the Danish Causes of Death Registry,27 where all somatic hospitalizations and causes of death are registered for every citizen in the entire country. Diagnoses are classified according to the World Health Organization’s International Classification of Diseases (ICD), 8th and 10th revisions. The relevant diagnose codes were ICD-8 410 and ICD-10 I21 and I22. Participants who had revascularization procedures (and no MI) during follow-up were treated as unaffected in the analysis ie, their risk time was not censored, and they did not count as cases (unless they had a later MI event). Most cases of MI deaths are registered in both registries mentioned earlier, ie, such patients have also been hospitalized with a valid MI diagnosis based on characteristic symptoms, electrocardiographic changes and/or elevated cardiac enzymes. Information on 8% of the MI death cases is solely contributed from the Danish Causes of Death Registry. These are likely cases that are found dead in their apartment. In such cases, the MI diagnosis may be less valid, but because these cases constitute the minority of MI cases, we do not expect this to have a major influence on our results.
Vital status of the participants was obtained from the Danish Civil Registration System, where information on address and vital status are registered for every Danish citizen.
Statistical Analysis
Of the 17 180 individuals who were invited to the 1991–1994 examination, 10 135 participated (59%). Participants of Asian or black descent (n=161), missing questionnaire data (n=74), and acute MI before baseline (316) were excluded, leaving 9584 individuals. Of these, 8777 had given blood and 8740 were successfully genotyped for ADH1B and ADH1C. In all analyses, ADH1B · 1/2 was combined with ADH1B · 2/2 because of the low number in the latter group (n=5).
We used the 
2 test to determine whether the ADH1B and ADH1C genotypes were in Hardy-Weinberg equilibrium.28 Haplotype frequencies for calculation of linkage disequilibrium coefficients were estimated by HPlus.29,30 Linkage disequilibrium coefficients Lewontin’s D’ was 0.90 and the correlation coefficient r2 was 0.01 between ADH1B · 2 and ADH1C · 1, both coding for the fast alcohol degradation enzymatic forms.31,32
Risk estimates for acute MI during follow-up were computed by means of Cox proportional hazard regression models. Age was used as the time axis to ensure that the estimation procedure was based on comparisons of individuals at the same age and hence remove confounding by age. The observation time for each participant was the period from the Copenhagen City Heart Study 1991–1994 examination, until date of MI, death from other causes, emigration outside Denmark, or August 1, 2007, whichever came first. We had follow-up information on all participants.
Test for linear trend was performed by treating the median within alcohol categories as a continuous variable and tests for interaction between genotypes and alcohol were performed by comparing a model including main effects of alcohol and ADH1C genotypes with a model also including the interaction terms by a log likelihood test.
Associations between alcohol intake, ADH1B and ADH1C genotypes and blood pressure, HDL, LDL, triglyceride, and fibrinogen were investigated by general linear models (all log-transformed to approximate normal distributions). Tests for effects of a low-to-moderate alcohol intake (<14 drinks/wk for women and <21 drinks/wk for men) on blood pressure, HDL, LDL, triglyceride, and fibrinogen levels were performed by modeling alcohol intake with linear splines with a knot placed at 14 and 21 drinks per week for women and men, respectively, and testing for statistical significance for each portion of alcohol intake. Furthermore, statistically significant U-shaped effects for triglycerides were tested by including the alcohol intake as a linear and a squared term. P values less than 0.05 were considered statistically significant.
Finally, we calculated posthoc power using the Quanto program,33 by assuming effect sizes for the ADH1C-alcohol interaction as in the study by Hines et al,17 and by using information on distribution on alcohol intake and genotype and number of MI cases from our study. Assuming a significance level of 0.05, we had 97% power to pick up an ADH1C-alcohol interaction of a size similar to what was found in the Hines study.
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Results |
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Baseline Characteristics
Of the 9584 participants, 4105 (57%) were women, and the median age of participants was 61 years (10–90%, 35 to 77). The median alcohol intake was 3.0 drinks/wk among women and 10 drinks/wk among men (Table 1). Approximately half of the participants were current smokers. Frequencies of ADH1B · 1/2+2/2 and of ADH1C · 1/1 (genotypes coding for the most active enzymes) were 4.5% and 34%. ADH1B and the ADH1C genotypes were both in Hardy-Weinberg equilibrium (P=0.43 and 0.64, respectively).
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Alcohol Intake/ADH1B/ADH1C/Genotypes, and Risk of MI
Increasing amount of alcohol intake was associated with decreasing risk of MI among men and women (Figure 1). In contrast, ADH1B and ADH1C genotypes were not associated with risk of MI in men or women (Table 2).
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The association between alcohol intake and risk of MI was not modified by ADH1C genotype, because hazard ratios were comparable within strata of ADH1C genotype (Figure 2); the probability value for interaction between ADH1C genotype and alcohol intake was 0.56 in a model combining men and women. Similar results were obtained when analyzing each sex separately. We did not have sufficient statistical power to perform similar analysis for the ADH1B genotype because the ADH1B · 2 allele is relatively rare.
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Alcohol Intake/ADH1B/ADH1C/Genotypes, and Cardiovascular Biochemical Risk Factors
Among women, alcohol was statistically significantly associated with increasing levels of diastolic and systolic blood pressure and HDL cholesterol, and with decreasing levels of LDL cholesterol and fibrinogen with no apparent threshold effect (Figure 3). Also among women, the association between alcohol intake and nonfasting triglycerides was significantly U-shaped.
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Probability value for trend for alcohol intake more than 21 drinks per week for men. 
Probability value for U-shape.Among men, alcohol was statistically significantly associated with increasing levels of diastolic and systolic blood pressure but only for alcohol intake of 21 or more drinks/wk. Also among men, alcohol was associated with decreasing levels of LDL cholesterol, but again, only for alcohol intake of 21 or more drinks/wk. There appeared to be a U-shaped association between alcohol intake and nonfasting triglycerides, but it was not statistically significant (P=0.23). Alcohol was statistically significantly associated with increasing levels of HDL cholesterol and with decreasing levels of fibrinogen with no apparent threshold effect among men.
ADH1B and ADH1C genotypes were not consistently associated with any of these cardiovascular risk factors among women or men (Table 3). There was no sign of interaction between ADH1C and alcohol intake on any of the cardiovascular biochemical risk factors (all P values >0.05).
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Discussion |
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In this general population study, we found that increasing alcohol intake was associated with a lower risk of MI and that amount of weekly alcohol from none to low through moderate and excessive intake was associated with stepwise increasing levels of diastolic and systolic blood pressure and HDL cholesterol, with stepwise decreasing levels of LDL cholesterol and fibrinogen, and with a U-shaped curve for nonfasting triglycerides. In contrast, ADH1B and ADH1C genotypes were not associated with risk of MI or with cardiovascular risk factors, and there was no indication that associations between alcohol intake and MI or alcohol intake and cardiovascular risk factors were modified by genotype.
A moderate alcohol intake is consistently shown to be associated with a decrease in risk of coronary heart disease.4 The maximal benefit seem to be obtained at 1 to 2 drinks per day for women and 2 to 3 drinks per day for men; for higher amounts of alcohol intake, there seem to be no further gain and some studies have even reported an increase in risk, indicating a J-shaped association between alcohol intake and coronary heart disease.4
The beneficial effect of alcohol is primarily thought to be mediated through an increase in HDL and a decrease in fibrinogen.7 For these 2 cardiovascular risk factors, we observed that increasing alcohol intake was associated with increasing HDL cholesterol and decreasing fibrinogen with no threshold, ie, even low amounts of alcohol intake was associated with increasing HDL and decreasing fibrinogen. These findings are consistent with the above mentioned effects of alcohol intake in the low-to-moderate range on the risk of coronary heart disease. We also observed that alcohol intake at higher levels (>14/21 drinks/wk for women/men) was associated with higher diastolic and systolic blood pressure and with increased level of nonfasting triglycerides, which on the other hand is associated with increased cardiovascular risk34,35 and in support of a J-shaped association between alcohol intake and risk of coronary heart disease.
If the effect of alcohol on coronary heart disease is modified by variations in ADH genes it really comes down to the question of whether the risk is lower among ADH1C · 2/2 (slow metabolizers) than among ADH1C · 1/1 (fast metabolizers) among light-to-moderate drinkers but similar among nondrinkers. Initially, results in American physicians by Hines et al17 indicated that this is so (interaction, P=0.01; Table 4). However, the relative risk of 0.14 (95% CI, 0.04 to 0.45) was based on only 5 cases and 37 controls with the ADH1C · 2/2 genotype (slow metabolizers) in the highest alcohol category drinking (
8 drinks/wk); for lower alcohol intake there seemed to be no difference in risk of MI according to genotype. Another study also found a significant interaction (P=0.02) between alcohol intake and the ADH1C genotype, but only after performing post hoc regrouping of the alcohol categories, and in contrast to the previous report,17 the lower risk was found among individuals with the lowest alcohol intake (0.7 to 2 drinks/wk).18 In yet other studies, there was no significant interaction between alcohol intake and the ADH1C genotype (Table 4).19–21 Finally, our study which is the largest so far could not confirm either of the previous findings; our post hoc power calculations showed that we had 97% power to pick up a ADH1C-alcohol interaction of a size similar to what was found in the Hines study.17 This further supports the overall conclusion that the association between alcohol intake and risk of coronary heart disease is not modulated by the ADH1C genotype.
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Previously, we showed that ADH1B and ADH1C genotypes were associated with amount of alcohol intake and with risk of heavy drinking (participants with genotypes coding for slow alcohol degradation were drinking more and had higher risk of heavy drinking; for ADH1C, however, these effects were only modest). Hence, individuals with genotypes coding for slow alcohol degradation have higher blood alcohol concentrations due to both the lower activity of the resulting enzyme and to a higher alcohol intake. These effects both stem directly from the genotype and should therefore not be separated.
A limitation of our results is that never-drinkers could not be separated from ex-drinkers and the nondrinking category may therefore contain some former alcoholics who due to their former heavy drinking have preexisting illness. This could lead to an apparent inverse association between alcohol intake and MI. However, analyses of alcohol intake and cardiovascular biochemical risk factors (diastolic and systolic blood pressure, HDL and LDL cholesterol, nonfasting triglycerides, and fibrinogen) showed that the level of the respective risk factor in the nondrinking category were in accordance with an overall dose-response shaped curved between alcohol intake and the cardiovascular risk factor, indicating that accumulation of former heavy drinkers in this category is not a major problem.
Limitations further include that information on alcohol intake was obtained by self-report and has not been validated. However, associations between increasing alcohol intake and increasing levels of biomarkers of alcohol intake such as alanine aminotransferase, aspartate aminotransferase, and 
-glutamyl transpeptidase has previously been observed within this cohort.36 Also, because we studied whites only, our results may not necessarily apply to other ethnic groups.
Our study had several strengths. First of all, sample size is large and the wide range of alcohol intake provided statistical power to study effects of low-to-moderate as well as excessive alcohol consumption on levels of cardiovascular risk factors and risk of MI. Furthermore, participants were men and women all from the general population of Danish descent. Hence, population stratification is unlikely to have affected our results. We had information on several different cardiovascular risk factors, which were obtained objectively from the study participants. Hence, it is unlikely that these measures are differentially biased according to alcohol intake or genotype.
In summary, we observed that increasing alcohol intake associated with decreasing risk of MI, decreasing LDL cholesterol and fibrinogen, increasing diastolic and systolic blood pressure and HDL cholesterol, and with U-shaped nonfasting triglycerides. These associations were not modified by ADH1B and ADH1C genotypes.
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Acknowledgments |
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We thank to the participants in the Copenhagen City Heart Study for their outstanding cooperation.
Sources of Funding
This research was supported in part by the Danish Graduate School of Public Health, the Danish Heart Foundation, Chief Physician Johan Boserup and Lise Boserup Foundation, the Health Insurance Foundation, the Ministry of the Interior and Health, the Danish Cancer Society, and the Danish National Board of Health.
Disclosures
None.
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