Clinical Chemistry Siemens Point of Care - Urinalysis
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
 QUICK SEARCH:   [advanced]


     


Clinical Chemistry 51: 360-367, 2005. First published December 2, 2004; 10.1373/clinchem.2004.040477
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
clinchem.2004.040477v1
51/2/360    most recent
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via ISI Web of Science (12)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Olivieri, O.
Right arrow Articles by Corrocher, R.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Olivieri, O.
Right arrow Articles by Corrocher, R.
Related Collections
Right arrow Lipids, Lipoproteins, and Cardiovascular Risk Factors
(Clinical Chemistry. 2005;51:360-367.)
© 2005 American Association for Clinical Chemistry, Inc.


Lipids, Lipoproteins, and Cardiovascular Risk Factors

Apolipoprotein C-III, n-3 Polyunsaturated Fatty Acids, and "Insulin-Resistant" T–455C APOC3 Gene Polymorphism in Heart Disease Patients: Example of Gene-Diet Interaction

Oliviero Olivieri1,a, Nicola Martinelli1, Marco Sandri1, Antonella Bassi2, Patrizia Guarini1, Elisabetta Trabetti3, Francesca Pizzolo1, Domenico Girelli1, Simonetta Friso1, Pier Franco Pignatti3 and Roberto Corrocher1

1 Unit of Internal Medicine, Department of Clinical and Experimental Medicine, 2 Institute of Clinical Chemistry, and 3 Section of Biology and Genetics, Department of Mother and Child and Biology-Genetics, University of Verona, Verona, Italy.

aAddress correspondence to this author at: Dipartmento Medicina Clinica e Sperimentale, Cattedra di Medicina Interna, Università di Verona, Policlinico Borgo Roma, 37134 Verona, Italy. Fax 39-45-580111; e-mail oliviero.olivieri{at}univr.it.


   Abstract
Top
Abstract
Introduction
Patients and Methods
Results
Discussion
References
 
Background: Apolipoprotein C-III (apo C-III) is a marker of cardiovascular disease risk associated with triglyceride (TG)-rich lipoproteins. The T–455C polymorphism in the insulin-responsive element of the APOC3 gene influences TG and apo C-III concentrations. Long-chain n-3 polyunsaturated fatty acids (PUFAs) contained in fish have well-known apo C-III-lowering properties.

Methods: We investigated the possibility of an interactive effect between the APOC3 gene variant and erythrocyte n-3 PUFAs, suitable markers of dietary intake of fatty acids, on apo C-III concentrations in a population of 848 heart disease patients who had coronary angiography.

Results: In the population as a whole, apo C-III concentrations were significantly inversely correlated with total erythrocyte PUFAs, but the correlation was not significant when only –455CC homozygous individuals were taken into account. In the total population and in subgroups with the –455TT and –455CT genotypes, the relative proportions of individuals presenting with increased apo C-III (i.e., above the 75th percentile value calculated on the entire population after exclusion of individuals taking lipids-lowering medications) decreased progressively as the n-3 PUFA and docosahexaenoic acid concentrations increased. The opposite situation was observed in the homozygous –455CC subgroup, in whom increasing erythrocyte n-3 PUFA and docosahexaenoic acid concentrations were associated with higher proportions of individuals with high apo C-III. A formal interactive effect between genotype and n-3 PUFAs was confirmed even after adjustment for possible confounding variables [age, sex, body mass index, smoking, coronary artery disease (CAD)/CAD-free status, or use of lipid-lowering medications] by logistic models.

Conclusion: Patients homozygous for the –455C APOC3 variant are poorly responsive to the apo C-III-lowering effects of n-3 PUFAs.


   Introduction
Top
Abstract
Introduction
Patients and Methods
Results
Discussion
References
 
The metabolism of circulating particles rich in triglycerides (TGs)1 is strongly affected by their content in apolipoprotein C-III (apo C-III), a component that inhibits the lipoprotein lipase-induced hydrolysis of these particles (1), and their apo E-mediated hepatic uptake (2). In recent years, clinical evidence supported the role of apo C-III and TG-rich lipoproteins in coronary artery disease (CAD) (3)(4)(5)(6)(7)(8)(9), suggesting that the apo C-III concentration is a reliable marker for lipoprotein concentration-associated CAD risk.

Different genetic and acquired factors influence serum apo C-III concentrations (10). Several polymorphic variants have been described in the APOC3 gene promoter, affecting protein transcription and synthesis (11); among them, promoter variants at positions –455 and –482 have been studied more extensively because of their altered affinity for the nuclear transcription factors that mediate the insulin response (12). APOC3 is transcriptionally down-regulated by insulin concentrations (13), but the presence of mutant sequences seems to reduce the inhibitory modulation of the hormone ("insulin resistance" at the gene level) (12).

Dietary factors, such as the consumption of long-chain n-3 polyunsaturated fatty acids (PUFAs) contained in fish and fish oil, have been also described to affect serum apo C-III concentrations through a mechanism similar to that exerted by fibrate lipid-lowering medications, which involves the activation of specific nuclear receptors, i.e., the so-called "peroxisome proliferator-activated receptor-{alpha}" (PPAR{alpha}) (14). APOC3 is one of the target genes transcriptionally down-regulated by PPAR{alpha} activation, thus contributing to the lipid- and lipoprotein-lowering properties of fish or fish oil intake (14). However, not all individuals within a population seem to gain the beneficial effects of a fish-rich diet. Genetic factors may render individuals differently susceptible as either "dietary responsive" or "dietary nonresponsive" (15).

Recently we reported that the T–455C variant on the APOC3 gene promoter is associated with increased TG and apo C-III concentrations (16)(17) and represents an independent susceptibility factor for CAD (16), particularly in the presence of metabolic syndrome (17). However, in patients with high dietary intake, n-3 PUFAs could act as mediating factors able to substantially reduce the "over time impact" of APOC3 gene variants.

The fatty acid (FA) content in the erythrocyte membrane reflects previous intake over a relatively long time period (months), and an analysis by gas chromatography can provide information on multiple FAs, an approach superior to traditional dietary assessment methods (18). For this reason, erythrocyte FAs are considered as suitable biological markers for dietary intake, particularly for nutritional epidemiology purposes.

Taking into account all of these considerations, we analyzed apo C-III concentrations, erythrocyte FA concentrations, and APOC3 genotypes with the aim of evaluating possible interactions among these factors in determining circulating apo C-III concentrations in a large cohort of heart disease patients examined as part of the Verona Heart Project.


   Patients and Methods
Top
Abstract
Introduction
Patients and Methods
Results
Discussion
References
 
study population
The details of the study have been reported previously (16). Briefly, we selected a total of 848 unrelated adult patients of both sexes who were recruited consecutively from those referred to the Institute of Cardiovascular Surgery or to the Cardiovascular-Hypertension Unit of the Department of Internal Medicine of the University of Verona in Italy and underwent coronary angiography (the Verona Heart Project). At the time of blood sampling, a complete clinical and pharmacologic history, including the presence or absence of the traditional CAD risk factors, was obtained. Of these patients, 590 had angiographically severe multivessel coronary atherosclerosis (CAD group), whereas 258 had normal coronary arteries (CAD-free) and underwent coronary angiography generally before surgical correction of valvular heart disease. Although CAD-free, these patients were therefore heart disease patients.

The study was approved by our Institutional Review Boards. Either written or oral informed consent was obtained from all patients.

biochemical analyses
Samples of venous blood were drawn from each patient in the free-living state, after an overnight fast. Serum lipids and the other common biochemical indices were measured as described previously (16). Apo A1, apo B, and apo E were measured by commercially available nephelometric immunoassays; antisera, calibrators, and the BNII nephelometer were from Dade Behring. Apo C-III was measured by a fully automated turbidimetric immunoassay. The reagent were obtained from Wako Pure Chemical Industries, and the procedure recommended by the manufacturer was implemented on a RxL Dimension Analyzer (Dade International Inc.). Imprecision was assessed on three pools of control sera with low, medium, and high concentrations of apo C-III. For the low, medium, and high concentrations, the intraassay CV was 1.8%, 2.0%, and 2.0%, respectively, and the interassay CV was 4.4%, 3.4%, and 2.3%.

mutation analysis
The APOC3 T–455C polymorphism was analyzed as described previously (16).

statistical analysis
All computations were performed with use of the STATA 8.0 statistical package (Stata Corp.). Distributions of continuous variables are reported as the mean (SD). Influences on apo C-III concentrations were first analyzed with log-transformed apo C-III concentrations as the variable of interest (outcome). Given the asymmetric and bimodal distribution of this variable (Fig. 1 ), gene-diet interaction effects were assessed by quantile regression models (19). Subsequently, interaction effects were analyzed by logistic models using as outcome the binary variable high apo C-III concentration (h-apo C-III), with the value 1 (and 0 otherwise) assigned to patients with an apo C-III concentration above than the 75th percentile of the apo C-III concentrations of the entire sample, after exclusion of the individuals taking lipid-lowering medications such as statins and/or fibrates (122 mg/L; see also Fig. 1 , dashed line).



View larger version (16K):
[in this window]
[in a new window]
 
Figure 1. Distribution of apo C-III concentrations in the study population.

Dashed line indicates the 75th percentile apo C-III value in the population as a whole after exclusion of individuals taking lipid-lowering medications.

In both quantile and logistic models, the explanatory variables were the APOC3 genotype (in the recessive model, a binary variable takes the value 1 for homozygous –455CC individuals and 0 otherwise), the erythrocyte FA concentration (continuous variable), and the product of the two preceding variables (interaction term). The set of independent variables contained the following potential confounders: gender, age, CAD/CAD-free status, use of lipid-lowering medications (statins or other medications, including fibrates), smoking, and body mass index (BMI) (10)(20). In the logistic models, the statistical significance of the interaction term was tested by the likelihood ratio test.


   Results
Top
Abstract
Introduction
Patients and Methods
Results
Discussion
References
 
The clinical features, the concentrations of the main erythrocyte FAs, and the T–455C allele and genotype frequencies of the patients, separated according to the diagnosis and considered as a whole, are summarized in Table 1 .


View this table:
[in this window]
[in a new window]
 
Table 1. Clinical and biochemical features of the study population (n = 848).

As expected, several features associated with cardiovascular risk were differently distributed between individuals with CAD or without CAD, including the T–455C genotypes (16). Because the aim of the study was to detect possible gene-diet interaction effects in the whole population, these differences were not the object of specific analyses [with this in mind, compare Refs. (16) and (17)], but CAD/CAD-free status was taken into account as a confounder in the final logistic models (see below).

Apo C-III concentrations in the total patient population showed a bimodal and asymmetric distribution (median value, 105 mg/L; skewness value, 1.83) with a long tail for the highest values, as shown in Fig. 1Up . For this reason, the variance-stabilizing logarithmic transformation of apo C-III was used in all subsequent analyses.

Total erythrocyte PUFAs were significantly correlated with log-transformed apo C-III concentrations [correlation coefficient ({rho}) = –0.12; 95% confidence interval (CI), –0.18 to –0.05]. When the analysis was performed on the subgroups based on genotype, correlations remained significant for the patients with the –455TT ({rho} = –0.12; 95% CI, –0.23 to –0.01) and –455TC ({rho} = –0.15; 95% CI, –0.24 to –0.05) genotypes and in the combined TT + TC subgroup ({rho} = –0.14; 95% CI, –0.21 to –0.06) but not in the –455CC homozygous individuals ({rho} = –0.02; 95% CI, –0.19 to 0.15). Following this observation, we based further analyses on the assumption of a recessive model of interaction (patients carrying or not carrying the gene variant in homozygosity).

We first analyzed the possible gene-diet interactions able to influence apo C-III concentrations by quantile regression models using 50th, 65th, 75th, and 85th percentiles of the log-transformed apo C-III concentrations. By this approach, statistically significant interactions emerged when we modeled the 75th (or greater) percentile. The proportion of h-apo C-III individuals was therefore considered as a binary variable of interest (see the section on statistical analysis), and it was analyzed in relation to the different (low, intermediate, high) FA concentrations categorized according the tertile distributions in the population as a whole (below the 33th, 33th–66th, and above the 66th percentile, respectively, after exclusion of patients taking lipid-lowering medications). Of note, h-apo C-III individuals were characterized by an unfavorable lipid profile (increased TG, total cholesterol, and LDL-cholesterol concentrations) despite being similar in age, BMI, gender, and smoking status to the remaining population (data not shown). The proportions of h-apo C-III patients, plotted vs erythrocyte total PUFA concentrations, in the total population are shown in Fig. 2A ; the corresponding distributions in the subgroups of individuals either carrying or not carrying the –455CC genotype are shown in Fig. 2 , B and C. Both in the total population and in patients with the –455TT or –455CT genotype, an increasing erythrocyte PUFA concentration was associated with a progressively minor proportion of h-apo C-III patients (Fig. 2 , A and B). This was not the case for –455CC homozygous individuals, in whom no substantial differences in the proportions of h-apo C-III patients were observed in connection with increasing total PUFA concentrations (Fig. 2C ). In addition, we observed a surprisingly opposite association when the erythrocyte concentrations of n-3 PUFAs or docosahexaenoic acid (C22:6) were considered rather than total PUFAs; the proportion of h-apo C-III patients was highest in the subgroup of –455CC individuals with increased intake rather than in the subgroups with low or medium intake of n-3 PUFAs or C22:6 (Fig. 3 ).



View larger version (14K):
[in this window]
[in a new window]
 
Figure 2. Erythrocyte PUFA concentrations and proportion of patients with high apo-C III concentrations in the total population (A) and in the APOC3 –455TT/–455TC (B) and –455CC (C) subgroups.

Patients with high apo C-III/total patients for each erythrocyte PUFA tertile are indicated.



View larger version (19K):
[in this window]
[in a new window]
 
Figure 3. Erythrocyte n-3 PUFA and C22:6 concentrations and proportion of patients with high apo-C III concentrations in the total population (A) and in the APOC3 –455TT/–455TC (B) and –455CC (C) subgroups.

Patients with high apo C-III/total patients for each erythrocyte n-3 PUFA or C22:6 tertile are indicated.

We analyzed the effects of n-3 PUFA concentrations and APOC3 genotype and their interaction on the risk of having or not having increased apo C-III concentrations (h-apo C-III) by appropriate logistic models after adjustment for possible confounding variables (gender, age, CAD/CAD-free status, use of lipid-lowering medications, smoking status, and BMI). Shown in Tables 2 and 3 are the models for erythrocyte total PUFA, n-3 PUFA, and C22:6 concentrations and APOC3 genotypes estimated on the whole population and on the subsample of patients not taking lipid-lowering medications, respectively. We observed a significant interaction between –455CC homozygosity and erythrocyte C22:6 concentrations in both samples; in contrast, the interaction between genotype and n-3 PUFA concentration was statistically significant in patients not taking lipid-lowering medications but not in the total population. When similarly tested, we found no statistically significant results for other FAs in the n-3 family (e.g., C20:5 and C18:3).


View this table:
[in this window]
[in a new window]
 
Table 2. Estimation of the logistic models on the entire population: Interaction effects between T–455C genotype (recessive model) and erythrocyte total PUFA, n-3 PUFA, and C22:6 concentrations on the risk of having or not having increased apo C-III concentrations.


View this table:
[in this window]
[in a new window]
 
Table 3. Estimation of the logistic models on the subsample of patients not taking lipid-lowering medications: Interaction effects between T–455C genotype (recessive model) and erythrocyte total PUFAs, n-3 PUFAs, and C22:6 concentrations on the risk of having or not having increased apo C-III concentrations.

To look for possible interactive effects on TG concentrations, we also applied the same statistical approach using either log-transformed TG concentrations or the proportion of patients with higher TG values (at or above the 75th percentile of the entire population after exclusion of patients taking lipid-lowering medications) as the dependent variable. However, we observed no statistically significant interactions between erythrocyte FA concentrations and APOC3 genotype.


   Discussion
Top
Abstract
Introduction
Patients and Methods
Results
Discussion
References
 
Diet may influence the circulating lipoproteins in genetically predisposed individuals differently, but the determinants of this variability remain largely unknown (15). The results of the present study identify a different susceptibility to the apo C-III-lowering effects of a diet rich in n-3 PUFAs of fish origin in individuals carrying a polymorphic "insulin-resistant" variant on the APOC3 gene promoter. We observed a significant gene-diet interaction between homozygosity for the APOC3 –455C variant and erythrocyte n-3 PUFA or erythrocyte C22:6 concentrations. In the majority of the population (~85%), i.e., in individuals not carrying the –455CC genotype, increasing concentrations of these FAs in erythrocyte membranes were associated with a lower probability of having high concentrations of apo C-III; the finding was particularly clear in the subgroup of patients not receiving lipid-lowering treatment (Table 3Up ). Such an association not only disappeared but had an opposite trend in –455CC homozygotes (Fig. 3CUp ). Despite statistical significance and biological coherence of the interaction reported, our findings should be viewed with some caution, taking into account the limitation that our statistical interactions are based on a relatively small number of participants and that we looked at several aspects of apo C-III distribution before concluding that there was a threshold effect.

To the best of our knowledge, this is the first report showing an APOC3 gene-diet interaction on apo C-III concentrations. Only a few studies have investigated the relationship between APOC3 gene polymorphisms and FA intake in determining the concentrations of plasma lipids, but the consequences on the protein product of that gene, i.e., the apo C-III values, have never been analyzed.

In 1996, Humphries et al. (21) reported that the APOC3 C–1100T polymorphism affects the consistency and magnitude of changes in plasma cholesterol in response to a diet high in polyunsaturated fats. In a study by Lopez-Miranda et al. (22), the SstI polymorphism, which arises from a cytosine-to-guanosine substitution in the 3'-untranslated region of the APOC3 gene, was shown to be associated with the changes in total and LDL-cholesterol induced by a diet rich in monounsaturated FAs. The same polymorphic variant was also reported to interact with smoking in determining plasma lipid responses to dietary changes (23). More recently, Brown et al.(24) demonstrated that a diet low in saturated fat, compared with a diet rich in saturated fat, was associated with a beneficial lipid profile (lower concentrations of apo B, total cholesterol, and LDL-cholesterol) only among individuals homozygous for of the APOC3 promoter 455T-625T polymorphism, whereas carriers of the APOC3 455C-625del allele were not responsive to a similar diet. Although different in study design, the report by Brown et al. (24), which is the only one reporting on the same APOC3 gene polymorphism as in our study, suggested that carriers of the APOC3 455C-625del allele receive no evident benefit from a diet poor in saturated FAs (and, as a necessary consequence, rich in unsaturated FAs). Unfortunately, data on apo C-III concentrations were not available in the report by Brown et al. (24) so that comparison with our findings can only be indirect.

Our results are consistent with the in vitro experimental evidence of an apo C-III-lowering effect generally exerted by n-3 FAs (14). This effect was attributable mainly to docosahexaenoic acid, the quantitatively most relevant FA of the n-3 family in our patients. The mechanism by which this FA acts on apo C-III production is not completely clear because the in vitro demonstration of activation of PPAR{alpha} receptors as a necessary step to lower apolipoprotein synthesis has recently been refuted by the results of a study on PPAR{alpha}-deficient animals (25). Our data concerning the insulin-resistant –455C APOC3 gene variant in humans support the hypothesis that n-3 FAs may interfere with the mechanism of APOC3 gene transcription and that it may be mediated to some extent by insulin or by nuclear factors operating on the APOC3 insulin-responsive element on the gene promoter. However, the matter is complex because individuals homozygous for –455C, –482T on the insulin-responsive element of the APOC3 gene should have lower insulin secretion after an oral glucose test (26). Although in our patients fasting insulin concentrations were not genotype related (17), a decreased incremental insulin response to physiologic stimuli could over time affect APOC3 gene transcription and apolipoprotein synthesis. Further studies are necessary to better clarify this point.

In combination with other positive biological effects, the hypolipidemic properties of n-3 PUFAs have been pharmacologically exploited to reduce CAD risk, and fish oil capsules are now recognized as useful medications in TG-associated dyslipidemia (27). For this reason, the conclusions derived from the present study may be of pharmacogenomic interest. The sample of heart disease patients recruited in the Verona Heart Project was not representative of the general population because many patients were males affected by CAD. The validity of our conclusions is therefore limited to this specific clinical setting, and it needs to be confirmed in a healthy population. In interpreting these results, however, it is important to emphasize that this is not a case-control study between CAD and CAD-free patients, but rather an analysis of interactions in a population in which CAD/CAD-free status is one of the confounders. Adjustment for possible confounding variables (including CAD/CAD-free status) did not modify the results of the interaction models, supporting the view that the relationship between apo C-III concentrations, erythrocyte n-3 PUFA concentrations, and genotype is independent of the concurrent modifiers. Moreover, because the only firmly established therapeutic recommendation for n-3 PUFA supplementation is for patients with documented CAD (27), such as those enrolled in the present study, the value of the present results could be of clinical relevance.

Although this is not an intervention study, there is no logical reason to presume that dietary intake of n-3 PUFAs or fish oil capsules would yield qualitatively different effects. On the contrary, quantitative differences may play a role because the amounts of PUFAs ingested in fish oil capsules are generally much higher than those consumed in the diet. For example, the difference between the lowest and highest tertiles of the erythrocyte n-3 PUFA distribution in our population was 17–18%, whereas in intervention studies the corresponding difference between controls and treatment groups was 300–400%, depending on the duration and dose of n-3 PUFA supplementation (28)(29). The inconsistency for an interactive diet-genotype effect on TG concentrations could be explained by this aspect, considering that a quantitatively more relevant change in n-3 PUFA intake is necessary to observe significant TG-lowering effects independently from any genetic influence (27).

In this respect, the beneficial n-3 PUFA effects could have been under- or overrated in the past, depending on the relative proportions of genetically nonresponsive individuals present in the different populations treated with fish oil capsules. Similarly, it is possible that in genetically selected patients, the advantages achieved by n-3 PUFA supplementation may in the future be shown to be even bigger than the effects demonstrated to date. Further genotype-tailored studies will be necessary to evaluate this possibility.


   Acknowledgments
 
This work was supported by grants from the Ministry of University and Scientific and Technological Research, the Veneto Region Department of Health, and the Cariverona Foundation.


   Footnotes
 
1 Nonstandard abbreviations: TG, triglyceride; apo, apolipoprotein; CAD, coronary artery disease; PUFA, polyunsaturated fatty acid; PPAR{alpha}, peroxisome proliferator-activated receptor-{alpha}; FA, fatty acid; h-apo C-III, high apolipoprotein C-III; BMI, body mass index; and CI confidence interval.


   References
Top
Abstract
Introduction
Patients and Methods
Results
Discussion
References
 

  1. McConathy WJ, Gesquiere JC, Bass H, Tartar A, Fruchart JC, Wang CS. Inhibition of lipoprotein lipase activity by synthetic peptides of apolipoprotein C-III. J Lipid Res 1992;33:995-1003.[Abstract]
  2. Ginsberg HN, Le NA Goldberg, IJ Gibson, JC Rubinstein A, Wang-Iverson P, et al. Apolipoprotein B metabolism in subjects with deficiency of apolipoproteins CIII and AI. Evidence that apolipoprotein CIII inhibits catabolism of triglyceride-rich lipoproteins by lipoprotein lipase in vivo. J Clin Invest 1986;78:1287-1295.
  3. Blankenhorn DH, Alaupovic P, Wickham E, Chin HP, Azen SP. Prediction of angiographic change in native human coronary arteries and aortocoronary bypass grafts. Lipid and nonlipid factors. Circulation 1990;81:470-476.[Abstract/Free Full Text]
  4. Hodis HN, Mack WJ, Azen SP, Alaupovic P, Pogoda JM, LaBree L, et al. Triglyceride and cholesterol-rich lipoproteins have a differential effect on mild/moderate and severe lesion progression as assessed by quantitative coronary angiography in a controlled trial of lovastatin. Circulation 1994;90:42-49.[Abstract/Free Full Text]
  5. Mack WJ, Krauss RM, Hodis HN. Lipoprotein subclasses in the monitored atherosclerosis regression study (MARS). Treatment effects and relation to coronary angiographic progression. Arterioscler Thromb Vasc Biol 1996;16:697-704.[Abstract/Free Full Text]
  6. Luc G, Fievet C, Arveiler D, Evans AE, Bard JM, Cambien F, et al. Apolipoproteins C-III and E in apo B- and non-apo B-containing lipoproteins in two populations at contrasting risk for myocardial infarction: the ECTIM study. J Lipid Res 1996;37:508-517.[Abstract]
  7. Thompson GR. Angiographic evidence for the role of triglyceride-rich lipoproteins in progression of coronary artery disease. Eur Heart J 1998;19:H31-H36.
  8. Sacks FM, Alaupovic P, Moye LA, Cole TG, Sussex B, Stampfer MJ, et al. VLDL, apolipoproteins B, CIII, and E, and risk of recurrent coronary events in the cholesterol and recurrent events (CARE) trial. Circulation 2000;102:1886-1892.[Abstract/Free Full Text]
  9. Lee S-J, Campos H, Moye LA, Sacks FM. LDL particles containing apolipoprotein CIII are independent risk factors for coronary events in diabetic patients. Arterioscler Thromb Vasc Biol 2003;23:853-858.[Abstract/Free Full Text]
  10. Tilly P, Sass C, Vincent-Viry M, Aguillon D, Siest G, Visvikis S. Biological and genetic determinants of serum apo C-III concentration: reference limits from the Stanislas cohort. J Lipid Res 2003;44:430-436.[Abstract/Free Full Text]
  11. Dammerman M, Sandkuijl LA, Halaas JL, Chung W, Breslow JL. An apolipoprotein CIII haplotype protective against hypertriglyceridemia is specified by promoter and 3' untranslated region polymorphisms. Proc Natl Acad Sci U S A 1993;90:4562-4566.[Abstract/Free Full Text]
  12. Li WW, Dammerman M, Smith JD, Metzger S, Breslow JL, Leff T. Common genetic variation in the promoter of the human apo CIII gene abolishes regulation by insulin and may contribute to hypertriglyceridemia. J Clin Invest 1995;96:2601-2605.
  13. Chen M, Breslow JL, Li W, Leff T. Transcriptional regulation of the apo C-III gene by insulin in diabetic mice: correlation with changes in plasma triglyceride levels. J Lipid Res 1994;35:1918-1924.[Abstract]
  14. Schoonjans K, Staels B, Auwerx J. Role of the peroxisome proliferator-activated receptor (PPAR) in mediating the effects of fibrates and fatty acids on gene expression. J Lipid Res 1996;37:907-925.[Abstract]
  15. Ye SQ, Kwiterovich PO, Jr. Influence of genetic polymorphisms on responsiveness to dietary fat and cholesterol. Am J Clin Nutr 2000;72(Suppl):1275S-1284S.[Abstract/Free Full Text]
  16. Olivieri O, Stranieri C, Bassi A, Zaia B, Girelli D, Pizzolo F, et al. Apolipoprotein CIII gene polymorphisms and risk of coronary artery disease. J Lipid Res 2002;43:1450-1457.[Abstract/Free Full Text]
  17. Olivieri O, Bassi A, Stranieri C, Trabetti E, Martinelli N, Pizzolo F, et al. Apolipoprotein CIII, metabolic syndrome and risk of coronary artery disease. J Lipid Res 2003;44:2374-2381.[Abstract/Free Full Text]
  18. Arab L, Akbar J. Biomarkers and the measurement of fatty acids. Public Health Nutr 2002;5:865-871.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
  19. Koenker R, Bassett G. Regression quantiles. Econometrica 1978;46:33-50.[CrossRef][Web of Science]
  20. Waterworth DM, Talmud P, Bujac SR, Fisher RM, Miller GJ, Humphries SE. Contribution of apolipoprotein C3 gene variants to determination of triglyceride levels and interaction with smoking in middle-aged men. Arterioscler Thromb Vasc Biol 2000;20:2663-2669.[Abstract/Free Full Text]
  21. Humphries SE, Talmud P, Cox C, Sutherland W, Mann J. Genetic factors affecting the consistency and magnitude of changes in plasma cholesterol in response to dietary challenge. QJM 1996;89:671-680.[Abstract]
  22. Lopez-Miranda J, Jansen S, Ordovas JM, Salas J, Marin C, Castro P, et al. Influence of the SstI polymorphism at the apolipoprotein C-III gene locus on the plasma low-density-lipoprotein-cholesterol response to dietary monounsaturated fat. Am J Clin Nutr 1997;66:97-103.[Abstract/Free Full Text]
  23. Perez-Martinez P, Gomez P, Paz E, Marin C, Gavilan Moral E, Lopez-Miranda J, et al. Interaction between smoking and the SstI polymorphism of the apo C-III gene determines plasma lipid response to diet. Nutr Metab Cardiovasc Dis 2001;11:237-243.[Web of Science][Medline] [Order article via Infotrieve]
  24. Brown S, Ordovas JM, Campos H. Interaction between the APOC3 gene promoter polymorphisms, saturated fat intake and plasma lipoproteins. Atherosclerosis 2003;170:307-313.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
  25. Dallongeville J, Baugé E, Tailleux A, Peters JM, Gonzalez FJ, Fruchart JC, et al. Peroxisome proliferator-activated receptor {alpha} is not rate-limiting for the lipoprotein-lowering action of fish oil. J Biol Chem 2001;276:4634-4639.[Abstract/Free Full Text]
  26. Waterworth DM, Talmud PJ, Luan J, Flavell DM, Byrne CD, Humphries SE, et al. Variants in the APOC3 insulin responsive element modulate insulin secretion and lipids in middle-aged men. Biochim Biophys Acta 2003;1637:200-206.[Medline] [Order article via Infotrieve]
  27. Kris-Etherton PM, Harris WS, Lawrence JA. Fish consumption, fish oil, omega-3 fatty acids, and cardiovascular disease. Circulation 2002;106:2747-2757.[Free Full Text]
  28. Vidgren HM, Agren JJ, Schwab U, Rissanen T, Hanninen O, Uusitupa MI. Incorporation of n-3 fatty acids into plasma lipid fractions, and erythrocyte membranes and platelets during dietary supplementation with fish, fish oil, and docosahexaenoic acid-rich oil among healthy young men. Lipids 1997;32:697-705.[Web of Science][Medline] [Order article via Infotrieve]
  29. Katan MB, Deslypere JP, van Birgelen AP, Penders M, Zegwaard M. Kinetics of the incorporation of dietary fatty acids into serum cholesteryl esters, erythrocyte membranes, and adipose tissue: an 18-month controlled study. J Lipid Res 1997;38:2012-2022.[Abstract]



The following articles in journals at HighWire Press have cited this article:


Home page
Am. J. Clin. Nutr.Home page
N. Martinelli, D. Girelli, G. Malerba, P. Guarini, T. Illig, E. Trabetti, M. Sandri, S. Friso, F. Pizzolo, L. Schaeffer, et al.
FADS genotypes and desaturase activity estimated by the ratio of arachidonic acid to linoleic acid are associated with inflammation and coronary artery disease
Am. J. Clinical Nutrition, October 1, 2008; 88(4): 941 - 949.
[Abstract] [Full Text] [PDF]


This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
clinchem.2004.040477v1
51/2/360    most recent
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via ISI Web of Science (12)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Olivieri, O.
Right arrow Articles by Corrocher, R.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Olivieri, O.
Right arrow Articles by Corrocher, R.
Related Collections
Right arrow Lipids, Lipoproteins, and Cardiovascular Risk Factors


HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS