European Heart Journal Advance Access originally published online on June 13, 2006
European Heart Journal 2006 27(18):2170-2176; doi:10.1093/eurheartj/ehl086
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Serum gamma-glutamyltransferase predicts non-fatal myocardial infarction and fatal coronary heart disease among 28 838 middle-aged men and women
1 Department of Preventive Medicine, School of Medicine, Kyungpook National University, 1, 01 Dongin-dong, Jung-gu, Daegu, South Korea 700-422
2 Department of Public Health, University of Helsinki, Finland
3 Department of Epidemiology and Health Promotion, National Public Health Institute, Finland
4 Division of Epidemiology, School of Public Health, University of Minnesota, Minneapolis, MN, USA
5 Department of Nutrition, University of Oslo, Oslo, Norway
6 School of Public Health, University of Tampere, Finland
7 Department of Health and Functional Capacity, National Public Health Institute, Finland
8 South Ostrobothnia Central Hospital, Seinäjoki, Finland
Received 22 March 2006; revised 15 May 2006; accepted 19 May 2006; online publish-ahead-of-print 13 June 2006.
* Corresponding author. Tel: +82 53 420 6960; fax: +82 53 425 2447. E-mail address: lee_dh{at}knu.ac.kr
See page 2145 for the editorial comment on this article (doi:10.1093/eurheartj/ehl151)
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Abstract |
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Aims Serum gamma-glutamyltransferase (GGT) concentration may be involved in atherosclerosis. This study examined if serum GGT predicted coronary heart disease (CHD), especially differentiating non-fatal myocardial infarction (MI) and fatal CHD event, among the general population or participants with type-2 diabetes.
Methods and results A prospective study of 28 838 Finnish men and women aged 25–74 years was performed (1467 incident CHD cases; a median follow-up time of 11.9 years). Serum GGT cutpoints were the 25th, 50th, 75th, and 90th sex-specific percentiles. After adjustment for known cardiovascular risk factors, compared with the lowest GGT category, hazard ratios (HR) were 1.15, 1.25, 1.27, and 1.57 among men and 1.03, 1.22, 1.32, and 1.44 among women in other four GGT categories (P for trend <0.01, respectively). However, stronger associations were observed among subjects aged <60 and among alcohol drinkers. The strength of association was similar for non-fatal MI and for fatal CHD. Among subjects with type-2 diabetes, the corresponding adjusted HRs were 1.29, 1.57, 1.88, and 1.78 (P trend=0.03, men and women combined).
Conclusion This study suggests an independent mechanism linking serum GGT to CHD among general population. Even though the strength of association appeared to be modest among all subjects, stronger associations were observed among subjects aged <60 and among alcohol drinkers. Especially, measurement of serum GGT among type-2 diabetics may be helpful to predict the future risk of CHD.
Key Words: Gamma-glutamyltransferase • Myocardial infarction • Coronary heart disease • Diabetes • Oxidative stress
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Introduction |
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Gamma-glutamyltransferase (GGT) activity, normally found in serum as well as in the plasma membrane of virtually all cells except erythrocytes, catalyzes the first step in the degradation of extracellular glutathione (GSH), allowing for precursor amino acids to be assimilated and reutilized for intracellular GSH synthesis.1 Thus in this way, GGT activity favours the cellular supply of GSH, the most important non-protein antioxidant of the cell. However, there is also clear evidence that the degradation of GSH can play a pro-oxidant role in selected conditions; low density lipoprotein (LDL) oxidation through GSH/GGT-dependent iron reduction has been suggested as a potential mechanism in atherosclerosis.2 Experimental work has documented that GGT activity is present in atherosclerotic coronary plaques.3
Consistent with experimental findings, several prospective studies have found that serum GGT predicted non-fatal myocardial infarction (MI) or cardiac mortality, especially among patients with previous coronary events.4–6 Recently, two large prospective cohort studies based on general populations from two European countries showed that serum GGT had a graded positive association with mortality or incidence of coronary heart disease (CHD).7,8 However, the strengths of associations were substantially different between the two studies. In the study with the outcome of non-fatal MI or fatal CHD event (46.7% of total events were non-fatal MI),8 the strength of association was quite strong, whereas in the study with the outcome of mortality from acute and subacute forms of CHD,7 it was modest and even not significant among men. Taken together, these two studies suggest that serum GGT may predict non-fatal MI more strongly than fatal CHD.7,8 As one criticism about using serum GGT in a clinical setting is how much additional value beyond the traditional CVD risk factors serum GGT has in predicting CHD, the strength of association is an important issue.
This study addressed whether the strength of association of serum GGT with CHD in the general population differed depending on whether the case was non-fatal or fatal. Moreover, as serum GGT predicted the risk of microalbuminuria among patients with type-2 diabetes,9 it may also be interesting to examine whether serum GGT predicts the risk of CHD, a major complication of type-2 diabetes, among patients with type-2 diabetes. Therefore, we performed a prospective study to determine whether serum GGT is an independent predictor of incident non-fatal MI and fatal CHD events among middle-aged Finnish men and women or among participants with type-2 diabetes. We also studied if serum GGT could predict the risk of fatal CHD event among subjects with a history of MI at baseline.
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Methods |
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Study population
Baseline risk factor surveys were carried out in the Kuopio and North Karelia provinces in eastern Finland and in the Turku-Loimaa area in southwestern Finland, in 1982, 1987, 1992, and 1997. The Helsinki capital area was included in the survey in 1992 and 1997 and Oulu province in northern Finland in 1997. In each study year, the sample was randomly drawn from the population aged 25–64 years and was stratified so that in each area at least 250 subjects were chosen from both genders and each 10-year age group, according to the international WHO MONICA (MONItoring trends and determinants in CArdiovascular disease) project protocol.10 In 1997, an additional sample of subjects aged 65–74 years were recruited. The surveys were independent, i.e. study subjects were chosen from the population randomly for each survey and only the risk factor findings from their first survey was included when participants were involved in more than one survey. The study was conducted according to the national data protection legislation, the ethical rules of the Finnish National Public Health Institute, and the rules and principles of the Helsinki Declaration. In the present study, the data from the five areas and the four study years were combined. The participation rate was 75% among men and 82% among women in the pooled data set.11 Of 29 890 participants, 971 were excluded from analyses because they reported the history of MI at baseline. Another 81 participants were excluded because of missing data on GGT. A total of 13 811 men and 15 027 women were included in the present analyses. In the fully adjusted models, 13 802 men and 15 016 women were included due to missing values on some covariates in the rest of subjects.
Measurements
Alcohol drinking, smoking status, physical activity, and diabetes diagnosed by a physician prior to the baseline were assessed with a set of standardized questions in a self-administered questionnaire mailed to the participants in advance. Smoking status was categorized as regular current smokers and former or never smokers. Alcohol drinking was assessed on the basis of the self-reported number of drinks consumed during the previous week. Physical activity was measured by asking whether the participant performed leisure time physical activity at least 20–30 min two times or more per week.
At the survey site, specially trained research nurses measured height, weight, and blood pressure using the standardized WHO MONICA protocol.12 Height and weight were measured in light clothing and without shoes. Height was rounded to the nearest 1 cm and weight to the nearest 100 g. Systolic and diastolic blood pressures were measured twice, and the mean of these measurements was used in the analyses. Body mass index (BMI, kg/m2) was used as a measure of relative body weight. A venous blood specimen was taken for biochemical measurements; fasting was not required for all surveys.
GGT, total, and high-density lipoprotein cholesterol were determined from fresh serum samples. GGT was determined using a kinetic method (J.T. Baker Chemicals B.V., Denventer, Holland or Oy Medix Biochemica Ab, Kauniainen, Finland) at 37°C, based on the recommendation of the Committee on Enzymes of the Scandinavian Society for Clinical Chemistry and Clinical Physiology (1982, 1987, and 1992) or the European Committee for Clinical Laboratory Standards (1997). All GGT analyses were conducted in the same central laboratory in the National Public Health Institute in Helsinki, Finland. HDL-cholesterol was measured after precipitation of apolipoprotein B-containing lipoproteins with dextran sulphate and magnesium chloride. Total and high-density lipoprotein (HDL) cholesterol levels were determined by an enzymatic method (CHOD-PAP, Boehringer Mannheim, Mannheim, Germany).
Fatal CHD events (410–414 in the ICD 8 and 9 classifications and I20–I25 in the ICD 10 classification) as well as non-fatal MI events (410–411 and I21–I22, I24) (according to the criteria used in the FIN-MONICA MI Register Study) were included in the present study. Non-fatal MI events were derived from the National Hospital Discharge Register, which have shown good validity in Finland.13 CHD mortality data were obtained from the Central Statistical Office of Finland based on death certificates. The diagnostic criteria for these events have been published.14 At the National Public Health Institute, the data were further cross-checked with these two registers for completeness. Because of practically free and universal health care system in Finland, the mortality and hospital discharge registers cover virtually the entire Finnish population and thus no loss during the follow-up existed.
Statistical analyses
Analyses were separately performed in men and women. Serum GGT levels were classified into five groups using the 25th, 50th, 75th, and 90th percentiles as cutpoints (quartiles with the top quartile split), which were used in our previous study with the same dataset on the association between serum GGT and type-2 diabetes.15 Analyses of serum GGT in quintiles did not yield materially different results. The cutpoints were 16, 24, 38, and 64 U/L among men (normal range: 
50 U/L) and 10, 14, 20, and 32 U/L among women (normal range: 40 U/L) for the categories of GGT used, respectively. For calculation of the incidence density, length of follow-up was calculated as days from the baseline examination to the date of onset of non-fatal MI or fatal CHD event diagnosis (cases), to death from other causes based on the Mortality Register of Statistics Finland (censored cases) or to the end of the follow-up at 31 December 2003 (non-cases).
Cox proportional hazard models were used to calculate multivariable-adjusted hazard ratios (HRs), using the PHREG procedure of the SAS statistical package. Tests for trend were across the median GGT value in each category. Covariates, selected a priori in four models as specified in the tables, were the baseline values of age, study year, study area, BMI, alcohol consumption, cigarette smoking, physical activity, systolic blood pressure (SBP), serum total cholesterol, HDL-cholesterol, and history of diabetes. In each model, variables were entered simultaneously. The proportional hazards assumption was satisfied based on log minus log plots for category of serum GGT. The final multivariable model was validated by plotting the residuals against the fitted values and testing the goodness-of-fit.
We repeated these analyses for non-fatal MI and fatal CHD events as separate outcome variables and also in two subgroups: subjects with history of diabetes at baseline or subjects with history of previous acute MI at baseline. In addition, we performed stratified analyses by age at 60 years and status of alcohol consumption as a previous study reported a stronger relationship of serum GGT among subjects <60 years and serum GGT has been conventionally used as a marker of alcohol consumption.7 In subgroup analyses, as the associations between serum GGT and incident CHD were similar between men and women, we presented results combining men and women.
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Results |
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In total, 1467 incident CHD events were registered during a median follow-up time of 11.9 years (interquartile range: 6.9–20.3). At baseline, serum GGT was related to most cardiovascular risk factors (Table 1). Age, alcohol consumption, cigarette smoking, BMI, SBP, and DBP were positively associated with baseline serum GGT level in both men and women. Total cholesterol showed a positive association with baseline GGT level among men only, whereas HDL-cholesterol showed an inverse association with it among women only. HDL-cholesterol in men and total cholesterol in women showed U-shaped associations with serum GGT.
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Compared with the lowest baseline GGT category, the age-adjusted HRs for incident CHD events adjusted for age were 1.31, 1.56, 1.75, and 2.27 among men and 1.13, 1.49, 1.81, and 2.14 among women in the other four GGT categories, respectively (test for trend P<0.01 in both men and women) (Table 2). Additional adjustment for other cardiovascular risk factors (BMI, alcohol consumption, cigarette smoking, physical activity, SBP, total cholesterol, HDL-cholesterol, and history of diabetes) attenuated this relationship, but GGT still remained an independent risk factor for incident CHD events among both genders; multivariable-adjusted HRs were 1.00, 1.15, 1.25, 1.27, and 1.57 (test for trend P<0.01) among men, and 1.00, 1.03, 1.22, 1.32, and 1.44 (test for trend P<0.01) among women in the five GGT categories, respectively. When we separately analyzed non-fatal MI and fatal CHD events, similar associations were observed with the outcome of non-fatal MI as well as with the outcome of fatal CHD event (Table 3).
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When stratified by age at 60 years, the relationship of serum GGT was only observed among subjects <60 years (P for interaction <0.01). After stratification by alcohol drinking, the association between serum GGT and incident CHD was observed in both non-drinkers and drinkers (Table 4). However, the association tended to be stronger among drinkers than non-drinkers (P for interaction=0.07). On the other hand, the incidence of CVD events among drinkers was lower than that in non-drinkers in each category of serum GGT.
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In addition, serum GGT predicted the future risk of CHD events among 1120 men and women with a history of diabetes at baseline (3.9% of all study subjects) with sex- and multivariable-adjusted HRs of 1.00, 1.29, 1.57, 1.88, and 1.78 (P for trend=0.03) (Table 5). The findings were somewhat less clear among 971 patients with a history of acute MI, who were excluded from the other analyses, in that the association found with serum GGT was not graded with fatal CHD; sex- and multivariable-adjusted HRs of 1.00, 1.57, 1.26, 1.36, and 1.59 (P for trend=0.17) (Table 5). However, when we dichotomized serum GGT into <25th vs.
25th percentiles, sex- and multivariable-adjusted HR for fatal CHD was 1.45 (95% CI: 1.04–2.04).
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Discussion |
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In several previous prospective cohort studies with unselected populations or patients with a history of MI, high levels of serum GGT predicted CVD events or CHD mortality after adjusting for other known CVD risk factors as well as alcohol consumption.4–8 This prospective cohort study also presented a positive association of serum GGT with the risk of CHD, showing in a single dataset that this elevated risk is present for both non-fatal MI and fatal CHD events and exists in both men and women, especially those with age <60 and alcohol drinkers. Despite a general consistency in finding statistical significance of CHD risk elevated in those with high normal GGT, strength of association varied between studies. Relative risks may be important in deciding whether measurement of serum GGT would be useful in clinical practice. In our study (number of study subjects: 28 838) and the prospective study from Austria (number of study subjects: 163 944),7 the strength of association was relatively modest, but the small study from Germany (number of study subjects: 1878)8 showed a stronger association. As the major difference between the previous two studies7,8 appeared to be whether non-fatal MI was included in the outcome or not, we separately evaluated the association of serum GGT with non-fatal MI and fatal CHD events. However, we found no risk difference between non-fatal MI and fatal CHD events. The other difference among three studies was whether subjects with angina or history of MI at baseline were excluded or not. The study from Germany8 excluded subjects with history of MI or angina, but our study excluded only subjects with history of MI because information on history of angina was not available. On the other hand, the study from Austria7 did not exclude subjects with history of MI or angina. As the baseline risk in the study population is lower by excluding participants with angina in addition to those with MI, the stronger association shown in the German study may be partly explained by the difference in the exclusion criteria.
In addition, this study showed that serum GGT was positively associated with CHD among subjects with diabetes at baseline; the strength of association was somewhat stronger than in the general population. However, the association among subjects with a history of acute MI at baseline was not as strong as among subjects with diabetes.
Our study together with other studies suggests that an independent mechanism may link GGT to CHD, beyond its strong associations with known CVD risk factors. Serum GGT also significantly contributed to the estimated risk of CVD mortality as determined by a new risk scoring system for CVD risk in clinical practice in Europe developed by the SCORE project group,16 independent of the major risk factors for CVD mortality.17 Compared with known CVD risk factors such as smoking or serum cholesterol, however, the strength of the association appeared to be modest.
While previous studies report greater prognostic value of serum GGT on the risk of CHD among subjects with prevalent heart problems when compared with subjects without,4,6 the prognostic value of serum GGT in this study seemed to be clearest among subjects with diabetes at baseline. Among subjects with a history of MI, serum GGT levels were elevated in subjects who had another CHD event and the association with serum GGT was significant when it was dichotomized into values <25th vs. >25th percentile, but it did not show a dose-response relation. This may be related to the variety of clinical conditions among subjects with history of acute MI, despite adjustment for known CVD risk factors.
In our previous study with largely the same FIN-MONICA dataset,15 serum GGT within its reference range had a strong dose-response relation with incident type-2 diabetes in both men and women, the risk in the highest category being about five times higher than that of the lowest category. This study extends that finding, showing that serum GGT also predicts CHD complications among diabetic patients. However, the strength of association with CHD was weaker than that with the risk of diabetes. Ruttmann et al.7 suggested cut-off values of serum GGT which were related to the increased risk of CVD mortality through analyses of sensitivities and specificities for selected threshold values of GGT, but in our study serum GGT showed graded associations with various clinical outcomes or CVD risk factors. It suggests that setting any artificial cutpoints to divide normal vs. abnormal GGT in this respect may lose information and therefore not be appropriate. In addition, in the CARDIA study with young white and black men and women, serum GGT levels within its reference range positively predicted the future risk of microalbuminuria among subjects with hypertension or diabetes.9 Thus, our current and previous studies consistently suggest that serial measurement of serum GGT among diabetic patients may be useful to predict the risk of complications in diabetic patients.
In this study, the stronger association of serum GGT with incident CHD observed in alcohol drinkers, compared with non-drinkers, may need further discussion as serum GGT has been conventionally used as an objective indicator of excess alcohol consumption. This observation led us to suspect that the strong association between serum GGT and non-fatal MI or fatal CHD event in the Germany study8 may be partly explained by the high proportion of alcohol drinkers among study subjects; about 80% of study subjects were drinkers. Interestingly, we reported a similar interaction between serum GGT and alcohol consumption with the risk of hypertension.18 The dose-response relationship generally seen is that the mean GGT increases as the amount of self-reported alcohol consumption increases.19 Nevertheless, a wide variation in GGT levels exists among subjects who report the same amount of alcohol consumption.19 Our results may be related to the inaccuracy of information on self-reporting alcohol consumption; drinkers with low serum GGT might drink less alcohol than drinkers with high serum GGT. However, under this interpretation, it may be difficult to explain the dose-response relation of serum GGT across all categories with CHD risk because moderate alcohol consumption is usually associated with decreased CHD risk. Furthermore, it should be noted that the graded association between GGT levels and CHD was similar in both sexes, and yet Finnish women reported much lower amounts of alcohol drinking when compared with men, despite the range of GGT in women was by far lower than in men. Rather than this interpretation, our results may suggest that subjects whose serum GGT increases after alcohol consumption may be more susceptible to the risk of CHD than subjects who do not increase serum GGT after the same amount of alcohol consumption. At present, it is unclear which factors can influence inter-individual variation in the changes of serum GGT after alcohol consumption. Genetic factors may explain elevation of serum GGT after alcohol consumption.20 Further studies on factors which influence increases of serum GGT after alcohol consumption may be helpful to elucidate the mechanism of serum GGT affecting atherosclerosis.
Compelling evidence for the importance of inflammation and atherosclerosis at both the basic and clinical level has evolved in parallel.21,22 In this context, the finding in the CARDIA study that serum GGT predicted future concentrations of inflammation markers such as C-reactive protein or fibrinogen in a dose-response manner could be of substantial interest.23 This finding was also confirmed in the NHANES representative sample of the US population.24 In addition, serum GGT predicted the future levels of F2-isoprostanes, an oxidative damage product of arachidonic acid in the CARDIA subjects.23 These associations suggest that graded higher serum GGT activity was associated with both inflammation and oxidative stress, both of which are proposed as key mechanisms of atherosclerosis.
In conclusion, even after adjusting for known CVD risk factors, there was a modest dose-response relation between serum GGT levels and the risk of both non-fatal MI and fatal CHD event. However, this relation was more pronounced among subjects aged <60, alcohol drinkers, and those with type-2 diabetes at baseline. The determination of serum GGT, usually considered as a marker of alcohol consumption or hepatobiliary diseases but equally considered as a marker of oxidative stress, may have important clinical implications for prediction of CHD, diabetes, and complications among diabetics, identifying a subset at high risk of events who require specific and enhanced therapeutic effort.
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Acknowledgements |
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This study is funded by Academy of Finland, Research Council for Health (Grant Nos. 46558, 53585, 108297, 204274, 205657), YALTA (Grant No. NIH/NHLBI R01 HL53560), and the Korea Health 21 R&D Project, Ministry of Health & Welfare, Republic of Korea. (A050349).
Conflict of interest: none declared.
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