CLINICAL RESEARCH: ATHEROSCLEROSIS
High Serum Cholesteryl Ester Transfer Rates and Small High-Density Lipoproteins Are Associated With Young Age in Patients With Acute Myocardial Infarction
Marianne Zeller, PhD*,
David Masson, PharmD, PhD ,||,
Michel Farnier, MD, PhD ,
Luc Lorgis, MD ,
Valérie Deckert, PhD,
Jean-Paul Pais de Barros, PhD,
Catherine Desrumaux, PhD,
Pierre Sicard, MSc*,
Jacques Grober, PhD,
Denis Blache, PhD,
Philippe Gambert, MD, PhD,||,
Luc Rochette, PharmD, PhD*,
Yves Cottin, MD, PhD and
Laurent Lagrost, PhD,*
* Laboratory of Cardiovascular and Experimental Physiopathology and Pharmacology, IFR Santé STIC, Dijon, France
INSERM U866, University of Burgundy, Dijon, France
Point Médical, Dijon, France
Department of Cardiology, University Hospital, Dijon, France
|| Department of Medical Biochemistry, University Hospital, Dijon, France.
Manuscript received January 12, 2007;
revised manuscript received June 8, 2007,
accepted June 11, 2007.
* Reprint requests and correspondence: Dr. Laurent Lagrost, INSERM U866, Medical School, 7 bld Jeanne d’Arc, 21079 Dijon Cedex, France. (Email: laurent.lagrost{at}u-bourgogne.fr).
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Abstract
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Objectives: Our aim was to characterize cholesteryl ester transfer protein (CETP) activity in the early phase of acute myocardial infarction (MI).
Background: Cholesteryl ester transfer protein catalyzes the transfer of cholesteryl esters from high-density lipoprotein (HDL) donors to apolipoprotein B-containing lipoprotein acceptors.
Methods: The CETP concentration, lipid profiles, and the rate of cholesteryl ester transfer (CET) from a tracer dose of radiolabeled HDL toward endogenous lipoproteins were determined within 24 h after symptom onset.
Results: Among 347 patients with first MI, CETP concentration, triglycerides, and non–HDL-cholesterol increased across tertiles of the CET rate, whereas HDL-cholesterol, HDL, and LDL sizes decreased gradually. Among lipoprotein donors and acceptors, the best predictors of the CET rate were HDL2b and non–HDL-cholesterol, respectively. Mean age at first MI was 8.5 years lower in the patients from the highest CET tertile than in those in the lowest CET tertile. Diagonal stratification according to both non–HDL-cholesterol and HDL2b tertiles revealed that patients in the highest CET group were 18 years younger than patients in the lowest CET group. Parameters of the high CETP mass/high non–HDL-cholesterol/low HDL2b triad were independently associated with the CET rate.
Conclusions: In patients with acute MI, high CET rates are characterized by the presence of the high CETP mass/high non–HDL-cholesterol/low HDL2b triad. The association of high CET rates with young age at first MI lends support to a significant contribution of CETP to the accelerated progression of disease among asymptomatic patients.
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Abbreviations and Acronyms
| | apoB = apoliprotein B | | BMI = body mass index | | CET = cholesteryl ester transfer | | CETP = cholesteryl ester transfer protein | | CHD = coronary heart disease | | HDL = high-density lipoprotein | | ICD = International Classification of Diseases | | LDL = low-density lipoprotein | | MI = myocardial infarction | | VLDL = very-low-density lipoproteins |
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Plasma cholesteryl ester transfer protein (CETP) catalyzes the exchange of cholesteryl esters and triglycerides between circulating lipoproteins, leading to the net mass transfer of cholesteryl esters from antiatherogenic high-density lipoproteins (HDL) to proatherogenic apolipoprotein (apo) B-containing lipoproteins (very-low-density lipoproteins [VLDL] and low-density lipoproteins [LDL]). Although the reduction in plasma neutral lipid transfer activity, as a result of either CETP gene mutation (1) or CETP inhibition (2), is known to produce a major yet unrivaled increase in HDL-cholesterol, its impact on atherosclerosis prevention still remains a matter of debate. In particular, animal studies have provided a mixed picture (3). Whether modulation of CETP is beneficial or deleterious in the prevention or treatment of cardiovascular disease has recently come to the fore, because an excess of deaths and cardiovascular events has been found in high-risk patients from the ILLUMINATE (Investigation of Lipid Level management to Understand its iMpact IN ATherosclerotic Events) study receiving the CETP inhibitor torcetrapib (3). This outcome was rather unexpected, at least in the light of 3 distinct but complementary observations. First, elevated CETP mass and activity had been reported in patients with a history of myocardial infarction (MI) (4) in whom CETP-mediated decreases in the levels of large LDL and HDL subfractions correlated with cardiovascular risk (5,6). Second, CETP-deficient subjects with high HDL-cholesterol have a lower incidence of coronary heart disease (CHD) than subjects with normal CETP activity (7), whereas subjects with high CETP concentrations have an increased risk for future CHD (8). Third, CETP was reported to relate to the progression of atherosclerosis in high-risk populations (9–11). It remains plausible that torcetrapib was harmful in the ILLUMINATE study not because of its impact on the lipoprotein profile but because of uncontrolled molecule-specific adverse effects (12–14). Based on these observations, the hypothesis of a predominant adverse effect of CETP still deserves attention, at least in high-risk populations.
An independent yet unexplored way to answer the question of the role of CETP in cardiovascular disease would be to assess further whether elevated CETP activity was associated with a younger age at first MI onset. To this end, CETP concentrations and cholesteryl ester transfer (CET) rates were measured in patients with acute MI at the very early phase, during which changes in lipids and CET rates are minimal (15,16). The hallmarks of elevated CET rates, including high triglycerides and small LDL and HDL were determined.
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Methods
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Patients.
From April 2004 to December 2005, all of the consecutive patients hospitalized in the coronary care unit of the University Hospital of Dijon for acute MI and fulfilling the inclusion criteria were included. Eligible patients were identified during the index admission, and medical records were reviewed on an ongoing basis after appropriate consent had been obtained. The hospital list of discharged patients was systematically reviewed to validate a posteriori eligible cases with the use of the International Classification of Diseases (ICD)-9 codes 410 and 411 and the corresponding codes in ICD-10. Standardized definitions for MI, patient-related variables and clinical outcomes were used. Patients were enrolled if they were age 18 years or older and admitted to the center within 24 h of the onset of symptoms with a suspected diagnosis of MI. Patients with a history of cardiovascular disease (prior MI, documented CHD, or peripheral arterial disease) were excluded from the main analysis. However, they were included in a subsidiary analysis to ascertain whether the observations applied to the whole population of patients hospitalized for MI. A final diagnosis of MI was made in the presence of serial increases in serum biochemical markers of cardiac necrosis, associated with typical electrocardiographic changes and/or typical symptoms (17).
Patients’ characteristics, cardiovascular risk factors, chronic therapy, and medical history were collected prospectively, along with baseline clinical data. The cases were ascertained by the prospective collection of consecutive admissions. The study complied with the Declaration of Helsinki and was approved by the ethics committee of the Centre Hospitalier Universitaire de Dijon. Each patient gave written informed consent before participation.
Biochemical analyses.
Fasting blood samples were collected in glass tubes on the morning after admission. Median (interquartile range [IQR]) time from symptom onset to blood sampling was 16 (8 to 30) h. Patients sampled after 24 h (34%) were taken into account in the analysis. Serum total cholesterol, triglyceride, and HDL-cholesterol concentrations were determined on a Dimension Xpand (Dade Behring, Marburg, Germany) using enzymatic methods. Non–HDL-cholesterol was calculated by subtracting HDL-cholesterol from total cholesterol. The LDL cholesterol was calculated according to the Friedewald formula. The CETP concentration was measured by a specific enzyme-linked immunosorbent assay with TP1 anti-CETP antibodies (18). Serum CET activity was determined from 3H-CE-HDL toward endogenous serum apoB-containing lipoproteins (19–21). The CET rates are expressed in nmoles cholesteryl esters transfered per ml serum per hour. The size distribution of lipoproteins was analyzed by electrophoresis on Spiragel 1.5% to 25.0% (Spiral, Couternon, France) (22). The relative proportions of serum HDL subfractions (HDL2b, 9.71 to 12.90 nm; HDL2a, 8.77 to 9.71 nm; HDL3a, 8.17 to 8.77 nm; HDL3b, 7.76 to 8.17 nm; and HDL3c, 7.21 to 7.76 nm) were obtained by determining the relative areas under the scan curve and by relating them to the total area corresponding to the entire serum HDL fraction (22).
Statistical analysis.
Data are shown as mean ± SD or median (IQR), as appropriate, and qualitative data are presented as frequencies. Dichotomic data were compared by the chi-square test for trends across tertiles and by the chi-square test for comparison between 2 groups. For continuous variables, the normality of distribution was checked by the Kolmogorov-Smirnov test. In our dataset, only total cholesterol, CETP concentration, HDL2b, and HDL3b were non-normally distributed. Log-transformation of the skewed data was used for univariate (Pearson correlation and Student t test) and multivariate (multiple linear regression) analyses for prediction of the CET rate. For all of the other analyses, nonparametric tests for skewed data or parametric tests for normally distributed values were performed on untransformed values. For 2-group comparisons, values were tested by either the Mann-Whitney rank-sum test or the Student t test. For the tests across tertiles, we performed either the Kruskal-Wallis 1-way analysis of variance by rank or 1-way analysis of variance as appropriate. Univariate relationships between the CET rate, as a dependent variable, and clinical parameters were analyzed by either the Student t test for binary variables (gender, history of diabetes, hypertension, smoking, fibrate) or by the Pearson correlation test for continuous variables (age, BMI, blood lipid parameters). Multiple linear regression analysis (models 1 and 2) were performed with the CET rate as a dependent variable. Variables entered into the models were those with a significant relationship (p < 0.05) with the dependent variable in univariate analysis. Model 1 included age, gender, smoking, fibrate, triglycerides, CETP concentration, non–HDL-cholesterol, and HDL. Model 2 included age, gender, smoking, fibrate, triglycerides, CETP concentration, non–HDL-cholesterol, and HDL2b. The assumption of linearity for continuous independent variables and constant variance of the standardized residuals were assessed by plotting the residuals against fitted values. Two-sided p values of  0.05 were considered to be statistically significant.
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Results
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Characteristics of patients.
Table 1
presents the characteristics of the patients without a history of cardiovascular disease (n = 347), classified according to tertiles of serum CET rates (low, medium, and high). Gender, hypertension, and diabetes, as well as hypolipidemic therapy (including statins and fibrates) were similar for all tertiles. The proportion of current smokers increased gradually across the tertiles, with one-quarter in the lowest to almost one-half in the highest tertile. Strikingly, age at first MI markedly decreased across tertiles: mean age in the highest tertile was 8.5 years lower than that in the lowest (p < 0.001) (Table 1).
Serum lipid parameters.
Serum values did not differ significantly whether admission to hospital was within the first or the second half of the 24-h period after symptom onset, in particular for CET rates (8.31 ± 2.54 nmol/ml/h vs. 7.93 ± 3.56 nmol/ml/h, respectively; p = 0.553). This indicates that the time of sampling when performed early (<24 h) after hospital admission did not constitute a confounding parameter in the present study. The 2.2-fold increase in the CET rate between the low and the high subgroups was associated with a moderate but significant rise in plasma CETP concentration (Table 2). Striking increases in the triglycerides-to-LDL-cholesterol and triglycerides-to-HDL-cholesterol ratio were observed from the lowest to the highest tertile of the CET rates. These changes were accompanied by concomitant decreases in HDL-cholesterol concentrations (p < 0.001 in all cases).
Lipoprotein size distribution.
The relative abundance of the small-sized HDL3a, HDL3b, and HDL3c subpopulations increased gradually across tertiles of the CET rates (Table 2). This occurred at the expense of the large HDL2 subpopulations, mainly HDL2b, which were 35% lower in the high tertile than in the low. At the same time, a slight decrease in mean LDL diameter was observed (Table 2).
Factors associated with CET rate.
Spearman correlation showed an inverse relationship between the serum CET rate and HDL-cholesterol concentration, but a positive relationship between the CET rate and both non–HDL-cholesterol and triglyceride concentrations (Table 3). Compared with correlations of CET rates with other parameters, a slightly higher correlation coefficient was observed with the triglycerides-to-HDL-cholesterol ratio, which combines donor and acceptor lipoprotein parameters (Table 3). As a result of changes in lipid fluxes between HDL and apoB-containing lipoproteins, the CET rate correlated with the size of both LDL and HDL. Among lipoprotein donor parameters, HDL2b showed the strongest correlation with CET rates. Among lipoprotein acceptor parameters, non–HDL-cholesterol was the best predictor of the CET rate (Table 3).
The associations between patient characteristics, lipid parameters, and the CET rate are shown in Table 4. Univariate analysis revealed that the CET rate was related to age, gender, smoking, fibrate therapy, lipoprotein parameters and CETP concentration. Multivariate analysis was then performed by including variables with significant relationships in univariate analysis, and 2 models were built including either HDL-cholesterol (model 1) or HDL2b (model 2) as lipoprotein donors. The HDL2b, CETP mass concentration, and non–HDL-cholesterol were strong and independent predictors of the CET rate. Moreover, the non–HDL-cholesterol/CETP mass/HDL2b combination better predicted the CET rate than did the non–HDL-cholesterol/CETP mass/HDL-cholesterol combination (r2 = 0.51 vs. r2 = 0.33, respectively). When LDL cholesterol was used instead of non–HDL-cholesterol in multiple linear regression analysis, the regression coefficient (SE) was 0.327 (0.083; p < 0.001) instead of 0.394 (0.104; p < 0.001) in model 1 and 0.357 (0.066; p < 0.001) instead of 0.438 (0.851; p < 0.001) in model 2, respectively. Overall, r2 in model 1 and model 2 was similar when using either LDL cholesterol or non–HDL-cholesterol in the analysis (model 1: r2 = 0.335 vs. r2 = 0.327; model 2: r2 = 0.534 vs. r2 = 0.512, respectively).
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Table 4 Univariate and Multivariate Analyses for the Association Between the CET Rate, as a Dependent Variable, and Patients’ Characteristics or Lipid Parameters
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Age at first MI and CET rate.
Among MI patients, age at first MI onset correlated positively with antiatherogenic HDL-related parameters, but negatively with cardiovascular risk factors such as total cholesterol, non–HDL-cholesterol, and triglycerides (Table 5). The correlation coefficient of the serum CET rate with the triglycerides-to-HDL-cholesterol ratio was only slightly higher than that obtained with either parameter alone (Table 5). By multiple linear regression, age at first MI as a dependent variable was predicted from a linear combination of triglycerides and CET rates as independent variables (regression coefficients [SE] –3.17 [0.89; p < 0.001] and –0.56 [0.28; p = 0.045], respectively).
Diagonal stratification according to both non–HDL-cholesterol and HDL2b tertiles is shown in Figure 1. The lowest CET rates were found in patients with the lowest non–HDL-cholesterol and the highest HDL2b levels, whereas the highest CET rates were found in patients with the highest non–HDL-cholesterol and the lowest HDL2b levels. Most strikingly, in patients with the highest CET rate (11.95 ± 3.97 nmol/ml/h), the age at first MI was on average 18 years lower than that in patients with the lowest CET rate (5.65 ± 2.32 nmol/ml/h [p < 0.001]; 54 ± 14 years vs. 72 ± 12 years [p < 0.001]) (Fig. 1).
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Figure 1 The Highest CET Rates Are Found Among the Youngest Patients With First MI
Patients without a history of coronary artery disease (n = 347) were divided into tertiles of both non–high-density lipoprotein-cholesterol (HDL-c) and HDL2b. The highest cholesteryl ester transfer (CET) rate (nmol/ml/h) was observed in patients with the lowest HDL2b levels and the highest non–HDL-c levels. Numbers at the top of each bar represent mean age to first myocardial infarction (MI) (years). The subgroup with the highest CET rate contains the youngest patients, with an 18-year difference from the subgroup with the lowest CET rate (p < 0.001). Non–HDL-c (mg/dl) tertiles: low <141, medium 142 to 180, and high >181. HDL2b (%) tertiles: low <14.48, medium 14.50 to 20.61, and high >20.72.
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Current smoking and abnormal blood lipids are the 2 main features of young patients with acute MI. Moreover, hypolipidemic treatments (statins and fibrates) may influence CET rates through modifications in the concentrations of CETP and lipoprotein donors and acceptors. When smokers were excluded from the analysis, the CET rate in patients with the lowest non–HDL-cholesterol and the highest HDL2b tertiles was still approximately one-half that of patients with the highest non–HDL-cholesterol and the lowest HDL2b tertiles (n = 228; 5.47 ± 2.13 nmol/ml/h and 10.59 ± 3.31 nmol/ml/h, respectively; p < 0.001). In the nonsmoking population, age at first MI in patients with the lowest CET rate was 10 years higher than that in patients with the highest CET rate (74 ± 11 years and 64 ± 13 years, respectively; p = 0.007). When patients treated with hypolipidemic drugs were excluded from the analysis, comparison of CET rates still showed a significant difference between the lowest non–HDL-cholesterol/highest HDL2b group and the highest non–HDL-cholesterol/lowest HDL2b group (n = 287; 5.72 ± 2.53 nmol/ml/h and 12.79 ± 3.91 nmol/ml/h, respectively; p < 0.001). Again, age at first MI in the lowest CET rate tertile was 18 years higher than in the highest CET rate tertile (71 ± 13 years and 53 ± 13 years, respectively; p < 0.001). A significant relationship between the CET rate and age at MI onset was observed whether patients with prior MI, documented CHD, or peripheral vascular disease (n = 132) were included (r = –0.202; p < 0.001; n = 479) or were not included (r = –0.261; p < 0.001; n = 347) in the analysis.
Gender and CET rate.
There was a trend toward a lower proportion of women in the high-CET group (Table 1), despite higher CETP levels in women than in men (Table 4). Thus, it was important to establish that the relationship observed between lipid parameters and age at MI onset did not relate to differences in the gender distribution across CET tertiles. Table 6
shows blood lipid parameters in men and women. Women were older than men. They had higher levels of HDL-cholesterol and large HDL and lower CET rates and triglycerides-to-HDL-cholesterol ratios. Significant negative correlations between CET rates and age at first MI were found in both men and women, with an even stronger negative correlation in women despite a smaller sample size (men: r = –0.188; p < 0.005; n = 253; women: r = –0.317; p < 0.001; n = 94).
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Discussion
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The present study specifically addressed an important yet unanswered question: Are the highest levels of CETP associated with a younger age among patients with first MI? The CET rates between HDL and apoB-containing lipoproteins have been characterized for the first time at the early phase of acute MI. Our findings demonstrate that the highest rates of CET are found among the youngest MI patients, even when smokers, patients treated with hypolipidemic drugs, or patients with prior cardiovascular disease were taken into account in the analysis. In addition, concordant conclusions were drawn irrespective of gender. Aging has been shown to be accompanied by elevations in plasma cholesterol and triglycerides, and by decreases in HDL-cholesterol and LDL size in healthy men and women (23–28). In contrast, in the present study age at MI onset correlated positively with HDL-cholesterol and HDL size, but negatively with triglycerides and non–HDL-cholesterol. Thus, lipoprotein changes did not relate to the aging process per se, and findings should not be interpreted in terms of aging but rather of time to MI onset. Our data further support the hypothesis that elevated CETP activity may actually provide a clue to the previously reported association of high plasma triglyceride and low HDL-cholesterol levels with premature CHD (29). As an extension to recent studies in which high CETP levels were associated with faster progression of atherosclerosis (9,11), the present observations lend further support of the hypothesis of a relationship between a high serum CET rate and the earlier disease onset among patients undergoing MI.
The controversy on the proatherogenic or antiatherogenic property of CETP is based on the fact that its activity might be highly dependent on the metabolic context. When associated with the high VLDL/low HDL/small lipoprotein triad, CETP might act as a harmful proatherogenic factor that accelerates cholesteryl ester flux from antiatherogenic HDL to the accumulating triglyceride-rich apoB-containing lipoproteins. Indeed, CETP has been found to increase the risk for future CHD, but only in individuals with an accumulation of triglyceride-rich VLDL1 acceptors (8). In contrast, when clearance of VLDL and LDL is optimal, CETP might no longer act as a proatherogenic factor, and may provide an alternative pathway for HDL cholesteryl esters to be removed from the bloodstream. When apoB-containing lipoprotein clearance was accelerated by treatment with statins, the B1B1 Taq1B genotype with high CETP levels was not accompanied by an elevation in CHD risk (30). An inverse relationship was even found between the level of CETP expression and the progression of CHD (31) or the number of cardiovascular events (32) in statin-treated patients. Although CETP concentration is a major determinant of CET activity in vivo, its activity is also dependent on lipoproteins. In an attempt to assess the combined effects of CETP concentration and the level and composition of lipoproteins in a comprehensive way, the rate of CET from a tracer dose of HDL toward endogenous lipoprotein particles was measured in total serum in the present study. Our data also revealed that MI patients were heterogeneous for both CETP activity and lipoprotein profile. Compared with the lower tertiles, the high CET rate group combined elevated CETP and high triglyceride levels. These observations are in agreement with a recent study that showed a synergistic contribution of CETP and triglycerides to an increased risk of future CHD in apparently healthy individuals (8). The CET assay used in the present study is assumed to closely reflect the in vivo situation, in particular with regard to a key role of triglyceride-rich lipoproteins and CETP in driving cholesteryl esters out of HDL, resulting in shrinkage of the particles (9,33–35). Accordingly, LDL and HDL shifted toward small-sized particles in the high-CET group, providing further support to the hypothesis that elevated CET rates were present before the index event. Because serum residence times of LDL and HDL are a few days (36,37), LDL and HDL size distributions can be considered as remnant parameters and, as for standard lipid parameters, most likely reflect pre-MI values. The relative abundance of small LDL and HDL particles could therefore be considered as an integrative marker of CETP activity. That small HDL size per se might directly account for higher CET rates is excluded, because earlier studies in CETP transgenic animals (38) and in CETP-deficient patients (1) would have predicted preferential interaction of CETP with large rather than small HDL. Overall, and as predicted from mechanistic studies (34), the size reduction in LDL and HDL in patients with a high CET rate was likely to be driven by the high CETP/high triglyceride combination. Our data shed light on the complex association of small LDL and HDL with the risk of MI (5,6). Moreover, the opposite correlations of the CET rate with either HDL3 or HDL2 subpopulations further support the direct role of a high CET rate in producing small HDL at the expense of large HDL. In addition, the present study suggests that the HDL2b subfraction, rather than LDL size might be a reliable sensor of both high CET activity and increased risk of MI in young patients. In this respect, the high CETP/high non–HDL-cholesterol/low HDL2b triad arises as the best predictor of an elevated CET rate. Whereas triglycerides are probably a more potent driving factor of CETP activity than non-HDL particles, most of the triglycerides are more rapidly hydrolyzed in the blood stream, accounting for the higher predictive value of the more stable non–HDL-cholesterol in the triad.
Study limitations.
As suggested by earlier studies, lipoprotein-related parameters may vary over the few days after MI and thus constitute a potential confounding factor. However, earlier reports indicated that lipid changes in response to inflammation are only minor within the first 24 h of MI (15,16), leading us to systematically proceed to blood sampling the day following the admission. Mean CET rates in patients admitted in the second part of the period studied, that is 12 to 24 h after MI, did not differ significantly from those admitted earlier. Finally, the relationship between small lipoproteins and high CET rate reported here is consistent with the expected trend. Thus, it can be assumed that in the present study measurement of lipoprotein parameters at the early phase of acute MI approximates accurately and in a retrospective manner the chronic pre-MI lipoprotein profile.
Although the present study focused on first MI patients, a significant correlation between the CET rate and age at MI onset was still observed when patients with prior MI, documented CHD or peripheral vascular disease were added into the analysis. Thus, the conclusions of the present study might be extended beyond the population of patients presenting with first MI.
Finally, although the observations of this study apply only to patients who were hospitalized at the University Hospital of Dijon and who survived acute MI until blood sampling, they could be generalized, because the population studied here shows the main features of contemporary MI registries such as GRACE (Global Registry of Acute Coronary Events) (39) and NRMI (National Registry of Myocardial Infarction) (40), in particular regarding age, gender, and risk factors. In all cases, early in-hospital mortality (within 24 h) was below 10%.
Although the method used to determine the CET rate can be considered to be a valuable estimate of CETP activity in vivo, it is highly dependent on triglyceride concentrations in the medium. Furthermore, both CET rate and triglycerides were found to independently predict age at first MI. Thus, it remains plausible that high triglycerides, in addition to high CET rate, might have contributed to the observed relationship between CET rate and age. The causal relationship between CETP activity and premature MI needs to be further investigated.
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Conclusions
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The present study lends further support to the existence of a direct link between high CETP activity and the progression of CHD in humans, suggesting that the faster development of atherosclerosis in patients with elevated CETP activity could eventually translate into a younger age at the first acute coronary event.
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Acknowledgments
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The authors are grateful to Frédéric Vincent, Hélène Laplanche, Aline Jeannin, Anne-Cécile Lagrost, and Philip Bastable for their technical assistance.
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Footnotes
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Supported by INSERM, Université de Bourgogne, Centre Hospitalier Universitaire de Dijon, Agence Nationale de la Recherche, Société Française de Cardiologie, Fédération Française de Cardiologie, ALFEDIAM, Fondation de France, Association de Cardiologie de Bourgogne, Union Régionale des Caisses d’Assurance Maladie de Bourgogne (URCAM), and Agence Regionale d’Hospitalisation (ARH) de Bourgogne.
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