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Clinical Chemistry 54: 154-162, 2008. First published November 12, 2007; 10.1373/clinchem.2007.095059
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Right arrow Lipids, Lipoproteins, and Cardiovascular Risk Factors
(Clinical Chemistry. 2008;54:154-162.)
© 2008 American Association for Clinical Chemistry, Inc.

Lipids, Lipoproteins, and Cardiovascular Risk Factors

Erythrocyte Fatty Acid Composition and the Metabolic Syndrome: A National Heart, Lung, and Blood Institute GOLDN Study

Edmond K. Kabagambe1,a, Michael Y. Tsai2, Paul N. Hopkins3, Jose M. Ordovas4, James M. Peacock5, Ingrid B. Borecki6 and Donna K. Arnett1

1 Department of Epidemiology, University of Alabama at Birmingham, School of Public Health, Birmingham, AL; 2 Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN; 3 Department of Internal Medicine, University of Utah, Salt Lake City, UT; 4 JM-USDA-HNRCA, Tufts University, Boston, MA; 5 Division of Epidemiology and Community Health, University of Minnesota, School of Public Health, Minneapolis, MN; 6 Division of Statistical Genomics, Department of Genetics, Washington University, School of Medicine, St. Louis, MO.

aAddress correspondence to this author at: Department of Epidemiology, University of Alabama at Birmingham, School of Public Health, Birmingham, AL 35294. Fax 1-205-934-8665; e-mail edmondk{at}uab.edu.


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Background: Different fatty acids may vary in their effect on the metabolic syndrome (MetS). We tested whether fatty acid classes measured in erythrocytes are associated with the MetS or its components.

Methods: Included were men [n = 497; mean (SD) age, 49 (16) years] and women [n = 539; age, 48 (16) years] from 187 families in a National Heart, Lung, and Blood Institute (NHLBI) family study of the Genetics of Lipid-Lowering Drugs and Diet Network (GOLDN) conducted in Utah and Minnesota. We used gas chromatography to measure erythrocyte fatty acids and obtained data on potential confounding variables from interviewer-administered questionnaires.

Results: The prevalence of the MetS as defined by the updated Adult Treatment Panel III criteria was 36.8% in Utah and 39.6% in Minnesota (P >0.05). In a multivariate model that included 4 fatty acid classes, covariates, and pedigree as a random effect, the odds ratios (95% confidence interval) for the MetS in the 1st, 2nd, 3rd, and 4th quartile of polyunsaturated fatty acids were 1.00, 0.72 (0.47–1.10), 0.67 (0.43–1.05), and 0.39 (0.24–0.64), respectively (P for trend = 0.0002). For the corresponding quartiles of saturated fatty acids, the odds ratios were 1.00, 1.19 (0.77–1.84), 1.48 (0.94–2.34), and 1.63 (1.01–2.63), respectively (P for trend = 0.03). Unlike n6 fatty acids, which showed an inverse association (P <0.05) with MetS, n3, trans, and monounsaturated fatty acids were not associated with the MetS (P >0.05). We observed significant correlations (P <0.05) between fatty acid classes, insulin, and components of the MetS.

Conclusions: Polyunsaturated fats are inversely associated with the MetS, whereas saturated fatty acids are positively associated with the MetS, probably through their effect on lipids, adiposity, insulin, and blood pressure.


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
Dietary fatty acids may have important effects on blood pressure, inflammation, insulin sensitivity, plasma glucose, and lipids, especially HDL cholesterol and triglycerides (1)(2)(3)(4)(5)(6)(7)(8). A high intake of saturated and trans fat is associated with an increase in triglycerides and LDL cholesterol (9), whereas cis-polyunsaturated fat lowers plasma triglycerides (10) and improves insulin sensitivity (11). The very-long-chain n3 fatty acids eicosapentaenoic acid and docosahexaenoic acid consistently lower plasma triglycerides (10)(12)(13) and, to a lesser extent, blood pressure (8), both of which are major components of the metabolic syndrome (MetS)1 . Although {alpha}-linolenic acid, a long-chain n3 fatty acid, is associated with a lower risk for cardiovascular disease (14)(15), it does not appear to alter the concentrations of plasma lipoproteins or their particle size (16). Linoleic acid, an n6 fatty acid and the most abundant polyunsaturated fatty acid in the human diet, can lower plasma glucose and LDL cholesterol (1)(17). n3 fatty acids contribute to membrane phospholipids, have anti-inflammatory properties (18)(19)(20), and are hypothesized to reduce abdominal adiposity, increase insulin sensitivity, and reduce the risk of the MetS (21)(22). Indeed, some recent studies (23)(24) have found associations between serum fatty acids and the MetS. Few studies have investigated the effects of dietary fat on the MetS, however, and results vary with age (25), smoking (26), and measurement error in dietary assessment, among other variables.

Compared with questionnaire-based assessments of fat intake, measurements of plasma or erythrocyte fatty acids may be a more stable biomarker for the medium-term intake (i.e., months) of dietary fat (27)(28)(29) and may be more suitable for comparing fatty acid classes with regard to their effect on diabetes, cardiovascular disease, and intermediate phenotypes. Indeed, a recent prospective study found a correlation between dietary and erythrocyte trans fatty acid contents (r = 0.44; P <0.01) (30). We are not aware of any published studies that have examined the composition of fatty acids in erythrocyte membranes and the MetS. We investigated whether the fatty acid composition in erythrocytes is related to the MetS or its components.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
study design and population
The study participants were 1 328 white men and women in the Genetics of Lipid-Lowering Drugs and Diet Network (GOLDN) family study, which consisted of 3-generation pedigrees in 2 genetically homogeneous centers in Minneapolis, MN, and Salt Lake City, UT. The GOLDN study is part of the Program for Genetic Interaction (PROGENI) Network, a group of NIH-funded family-intervention studies focusing on gene-environment interactions (31). The main aim of the GOLDN study is to characterize the genetic basis of the variable response of triglycerides in 2 environmental contexts, one that raises triglycerides (dietary fat), and one that lowers triglycerides (fenofibrate treatment). Men and women in this study participated in a 3-week open-label clinical trial that tested triglyceride responses to a high-fat milk shake before and after 3 weeks of treatment with 160-mg daily dose of micronized fenofibrate. After the screening visit (visit 1) and before the start of fenofibrate therapy, the study participants were asked to suspend their use of lipid-lowering drugs. Blood samples, lipid profiles, and anthropometric measurements were then taken (visit 2) before an orally administered fat challenge. The current analysis on the MetS uses baseline data (visit 2) consisting of anthropometric measurements, erythrocyte fatty acid profiles, plasma lipid profiles, physical activity, and other lifestyle variables that are collected in the period before an oral fat challenge and fenofibrate treatment.

data collection
Habitual dietary intake was assessed with the National Cancer Institute Diet History Questionnaire (32), and data on physical activity and other lifestyle variables, such as smoking and alcohol intake, were collected by means of an interviewer-administered questionnaire. Preprandial glucose and insulin concentrations were measured with colorimetric assays. The lipid profile (e.g., triglycerides, HDL cholesterol, LDL cholesterol, and total cholesterol) following at least 8 hours of fasting was measured by nuclear magnetic resonance techniques (31). Fatty acids in erythrocyte membranes were extracted with a mixture of chloroform and methanol (2:1, by volume), collected in heptane, and injected onto a Varian CP7420 100-m capillary column with a Hewlett-Packard 5890 gas chromatograph equipped with an HP6890A autosampler. The initial temperature of 190 °C was increased to 240 °C over 50 min to separate fatty acids from 12:0 through 24:1n9 (33).

statistical analysis
SAS Software version 9.1.3 (SAS Institute) was used for statistical analyses. From the 1 328 men and women in the GOLDN study, we excluded all individuals with a self-reported history of kidney disease, individuals with Graves disease, those in the top and lowest 1 percentiles of total energy intake, and those with missing data on major exposure variables and potential confounders. The final data set consists of information from 1 036 individuals in 187 families. The MetS was defined according to the National Cholesterol Education Program Adult Treatment Panel III criteria as updated in 2004 (34)(35). We tested the statistical significance of differences in the distribution of categorical variables according to MetS status with the Cochran–Mantel–Haenszel test after stratifying by field center; for continuous variables, we used the Mixed procedure in SAS with a mixed model that adjusted for the field center and the pedigree as a random effect.

We used ANOVA to test for associations between quartiles of fatty acid classes in erythrocytes, components of the MetS, and risk factors of cardiovascular disease (e.g., insulin, homeostatic model assessment of insulin resistance, LDL cholesterol, and LDL cholesterol particle sizes). In these analyses, the 4 fatty acid classes (saturated, monounsaturated, polyunsaturated, and trans fatty acids), age, sex, body mass index, smoking, alcohol intake, field center, hours spent viewing a TV or a computer (as a proxy for physical activity), total energy intake, and pedigree (as a random effect) were concurrently entered in the model.

The MetS as a dichotomous variable was the main outcome variable in a mixed multivariate model that simultaneously included all 4 fatty acid classes, potential confounders, and pedigree as a random effect. The covariates included in the final models were age (as quartiles), sex (men vs women), smoking (never, past, and current smokers), alcohol-intake status (current drinker vs noncurrent drinker), and hours spent on the TV or computer (as quartiles). Income and education did not change the models appreciably and were excluded from the final analyses. We used Proc Glimmix in the SAS package to fit multivariate mixed models with erythrocyte fatty acid classes, potential confounders, and pedigree as a random effect to study the relation between individual fatty acid classes and the components of the MetS. We estimated the odds ratios [95% confidence interval (CI)] for the MetS in the 1st, 2nd, 3rd, and 4th quartile of saturated fat, monounsaturated fat, polyunsaturated fat, trans fat, total n3, and n6 fat in erythrocytes. All 4 main fatty acid classes (saturated fat, monounsaturated fat, polyunsaturated fat, and trans fat) were entered in the models simultaneously. If total n3 and n6 fat was simultaneously included in the model with saturated, monounsaturated, and trans fatty acid variables, the total polyunsaturated fatty acid variable was excluded. To calculate the P for trend, we assigned the quartile median value of a given fatty acid class to each individual in the quartile. The resulting semicontinuous variables for each fatty acid class were entered in the model simultaneously.


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
characteristics of study participants
Table 1 summarizes the characteristics of the study participants by MetS status and field center. Although the men and women from the Minnesota field center were somewhat older and more likely to drink alcohol and smoke cigarettes than those in Utah, the participants in the 2 field centers were similar in most other respects. Thirty-eight percent of the study population had the MetS, and the prevalence in Utah (36.8%) was similar (P >0.05) to that in the Minnesota (39.6%) field center. Unlike the Utah field center, where the prevalence of the MetS in men (39.0%) was similar (P >0.05) to that in women (34.7%), the prevalence in Minnesota was significantly higher (P <0.05) in men (46.9%) than in women (32.9%). In the total study population, the proportions of people with 0, 1, 2, 3, 4, and 5 components of the MetS were 18.9%, 22.3%, 20.6%, 18.7%, 12.6%, and 6.9%, respectively.


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  		Table 1. Characteristics of the study participants by MetS status and field center.1

fatty acids in erythrocytes and components of METS
Trans and polyunsaturated fatty acids correlated well with the corresponding fatty acids in the diet, regardless of MetS status. Age and sex-adjusted Spearman correlation coefficients were 0.31 (P <0.0001) for trans fatty acids and 0.14 (P <0.0001) for polyunsaturated fatty acids. Saturated fat and monounsaturated fatty acids are synthesized in the body and, as expected, did not show good correlations with diet [Spearman r = –0.02 (P = 0.43) for saturated fat; r = –0.08 (P = 0.01) for monounsaturated fatty acids]. The fatty acid compositions of erythrocytes were similar in the 2 field centers (data not shown); thus, the data on the composition of fatty acid subtypes are shown according to MetS status but not by field center (Table 2 ). Compared with individuals without the MetS, the concentrations of saturated and monounsaturated fatty acids were significantly higher (P <0.05) among individuals with the MetS, whereas the concentrations of polyunsaturated and trans fatty acids were significantly lower (P <0.05) among individuals with the MetS. The ratio of total polyunsaturated fatty acids to saturated fatty acids (PS ratio) was significantly higher (P <0.0001) among individuals without the MetS than those with the MetS (Table 2 ).


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  		Table 2. Erythrocyte fatty acid composition by MetS status.1

In age- and sex-adjusted analyses, fatty acid classes showed significant correlations with components of the MetS, body mass index, insulin, LDL cholesterol concentration, and LDL cholesterol particle size (Table 3 ). Most associations between fatty acid classes in erythrocytes, components of the MetS, insulin, homeostatic model assessment of insulin resistance, LDL cholesterol concentration, and LDL cholesterol particle size remained significant, even after adjustment for several potential confounders (see Figs. 1 and 2 in the Data Supplement that accompanies the online version of this article at http://www.clinchem.org/content/vol?/issue? ]. The potential confounding variables we adjusted for were age, sex, body mass index, smoking, alcohol intake, field center, hours spent on the TV or computer, total energy intake, and pedigree as a random effect.


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  		Table 3. Age- and sex-adjusted Spearman correlations between fatty acid groups in erythrocytes and selected characteristics of the GOLDN study participants (n = 1 023).1

relation between fatty acid classes in erythrocytes and the METS
Table 4 shows odds ratios for the quartiles of fatty acid classes and the MetS. The odds ratios (95% CI) for the MetS in the 1st, 2nd, 3rd, and 4th quartiles for the polyunsaturated fatty acid class were 1.00, 0.72 (0.47–1.10), 0.67 (0.43–1.05), and 0.39 (0.24–0.64), respectively (P for trend = 0.0002). For the corresponding quartiles for saturated fat, the odds ratios were 1.00, 1.19 (0.77–1.84), 1.48 (0.94–2.34), and 1.63 (1.01–2.63), respectively (P for trend = 0.03). Monounsaturated and trans fatty acid classes were not associated with the MetS (P >0.05; Table 4 ). In a model with quartiles for the PS ratio, monounsaturated and trans fatty acid classes, and potential confounders (Table 4 ), the PS ratio was significantly inversely associated with the MetS (data not shown). The odds ratios (95% CI) for the MetS in the 1st, 2nd, 3rd, and 4th quartiles of the PS ratio were 1.00, 0.65 (0.43–0.98), 0.44 (0.29–0.68), and 0.34 (0.22–0.53), respectively (P for trend <0.0001). The median PS ratio was 0.91, 0.96, 0.99, and 1.05 for the 1st, 2nd, 3rd, and 4th quartiles of the PS ratio, respectively.


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  		Table 4. Odds ratios for fatty acid classes in erythrocytes and the metabolic syndrome among GOLDN study participants.

The odds ratios (95% CI) for the MetS in the 1st, 2nd, 3rd, and 4th quartiles of the n6 polyunsaturated fatty acid class were 1.00, 1.04 (0.68–1.59), 0.51 (0.32–0.81), and 0.35 (0.21–0.59), respectively (P for trend <0.0001). For n3 fatty acids, the odds ratios for the corresponding quartiles were 1.00, 1.45 (0.93–2.25), 1.10 (0.70–1.74), and 0.66 (0.39–1.10), respectively (P for trend = 0.03).

Because smoking can affect several of the components of the MetS, we investigated whether the above associations between fatty acid classes and the MetS would vary by smoking status (Table 5 ). The low number of current smokers (n = 76) in this study population precluded detailed analyses among current smokers. Thus, subgroup analyses were performed only with people who had never smoked and past smokers. As in the main analyses, polyunsaturated fatty acid class among never smokers was significantly (P <0.05) inversely associated with the MetS. No other significant associations (P <0.05) were detected in these subgroup analyses.


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  		Table 5. Odds ratios for fat subtypes and MetS stratified by smoking status.1


   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
In this cross-sectional family study that used erythrocyte fatty acids as biomarkers of intake (27)(29), we have shown that a high content of saturated fatty acids in erythrocytes is significantly (P <0.05) positively associated with the MetS and is independent of known risk factors such as smoking, alcohol intake, and physical activity. Total polyunsaturated fatty acid content, n6 fatty acids specifically, and the PS ratio were inversely associated with the MetS. We also observed small but significant associations between fatty acid classes and individual components of the MetS. For instance, a higher polyunsaturated fatty acid content in erythrocytes showed a significant (P <0.05) monotonic inverse association with triglycerides, systolic blood pressure, and waist circumference but a positive monotonic association with HDL cholesterol concentration and LDL cholesterol particle size. Although the individual correlations between fatty acid classes and the components of the MetS were small (r <0.25), the associations between fatty acid classes and the MetS as an aggregate variable were stronger than would be expected from the correlations between individual fatty acid classes and the components of the MetS. To our knowledge, this is the first large study (n = 1 036) to examine the relationship between erythrocyte membrane fatty acids and the MetS. Furthermore, our results are not likely to have been confounded by smoking, because our study population had very few current smokers (n = 76), especially in the Utah field center, and their exclusion from the analyses did not change the magnitude or direction of the associations (data not shown).

Studies on the relation between fatty acids and the MetS are still scarce. Most studies (23)(24)(25)(36) have assessed fatty acids in the diet or the plasma, thus making it difficult to directly compare these studies with our results. Nonetheless, our data are similar to those from the few studies in adolescents (24) and adults (23)(25)(37), in that these studies found higher concentrations of tissue polyunsaturated fatty acids, particularly linoleic acid, to be inversely associated with the MetS or some of its components. As in another study (25), total tissue n6 fatty acids (which are mainly linoleic acid and arachidonic acid) showed a significant inverse dose-dependent association with the MetS (P for trend <0.0001) and its components. This result is not surprising given that polyunsaturated fatty acids such as linoleic acid contribute to the regulation of the expression of genes involved in lipogenesis, fat oxidation, and lipid production, possibly contributing thereby to the MetS (20)(38)(39).

Our data are different from those of other investigators, who showed a strong inverse association between n3 fatty acids in plasma lipid esters (aggregated by the use of factor analysis) and the development of the MetS 20 years later (25). In our multivariate adjusted analyses, we did not find significant associations between total or individual n3 fatty acids and the MetS or most of its components. We did find a weak but significant inverse correlation only for n3 fatty acids and waist circumference (r = –0.07; P <0.05). n3 fatty acids showed a statistically significant inverse trend with MetS (P for trend = 0.03), but none of the comparisons between each of the top 3 quartiles and the lowest quartile were significant. These results were a surprise given that several recent studies have found inverse associations between {alpha}-linolenic acid (as well as other n3 fatty acids) and cardiovascular disease (14)(15) or the MetS (25). The reasons for this lack of association is not clear but may be due to lower amounts of n3 fatty acids in erythrocytes in our study population compared with other study populations (29)(37)(40). For instance, in the n3-supplementation trial by Riccardi et al. (37), the mean (SD) baseline proportions of eicosapentaenoic acid and docosahexaenoic acid in erythrocytes were 0.7% (0.1%) and 5.0% (0.4%) of the total fatty acids, respectively, whereas the corresponding proportions were 0.5% (0.3%) and 3.0% (0.9%) of the total fatty acids among our study participants without the MetS.

Unlike other studies on tissue fatty acids and the MetS, our study examined the association between trans fat and the MetS. Although we did not find a significant association between the class of total trans fatty acids and the MetS, we did find a significant inverse association (P <0.05) between trans fatty acids and HDL cholesterol. Because humans are unable to synthesize trans fatty acids in vivo, the trans fat in erythrocytes must have come from the diet, and dietary trans fat correlated well with erythrocyte trans fat (r = 0.31; P <0.0001). The inverse association observed between trans fatty acids and HDL cholesterol in this study and their association with dyslipidemia and cardiovascular disease in other studies (5)(30) underscores the importance of reducing the intake of trans fatty acids in the diet.

Unlike trans fatty acids and short-chain essential cis-polyunsaturated fatty acids, saturated and monounsaturated fatty acids in erythrocytes can come from both diet and in vivo biosynthesis, thus making them unsuitable as biomarkers of intake (29). This consideration is especially true for short-term intervention studies (25). Because of the cross-sectional nature of our study, we are unable to determine whether the observed associations are causal. Despite these limitations, the associations observed in our study are in close agreement with those from longitudinal studies in which the fatty acid composition of plasma lipid esters predicted the development of the MetS 20 years after the initial assessment (23).

The results from this study support the current recommendations to lower the intake of saturated and trans fatty acids and to increase the intake of polyunsaturated fatty acids as a goal for improving diet quality and lowering the risk for diabetes and cardiovascular disease. Because the composition of the fatty acids in tissues does not depend on diet alone, future studies are needed to determine the nondietary factors that might be associated with higher tissue concentrations of polyunsaturated fat and lower concentrations of saturated and trans fatty acids.


   Acknowledgments
 
Grant/funding Support: This study was funded by National Heart, Lung, and Blood Institute grant no. U01HL072524-04.

Financial Disclosures: None declared.

Acknowledgment: We are grateful to the staff of the GOLDN study for the assistance in data collection and management.


   Footnotes
 
1 Nonstandard abbreviations: MetS, metabolic syndrome; CI, confidence interval; PS ratio, ratio of total polyunsaturated fatty acids to saturated fatty acids.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

  1. Wijendran V, Hayes KC. Dietary n-6 and n-3 fatty acid balance and cardiovascular health. Annu Rev Nutr 2004;24:597-615.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
  2. Brady LM, Williams CM, Lovegrove JA. Dietary PUFA and the metabolic syndrome in Indian Asians living in the UK. Proc Nutr Soc 2004;63:115-125.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
  3. Brady LM, Lovegrove SS, Lesauvage SV, Gower BA, Minihane AM, Williams CM, Lovegrove JA. Increased n-6 polyunsaturated fatty acids do not attenuate the effects of long-chain n-3 polyunsaturated fatty acids on insulin sensitivity or triacylglycerol reduction in Indian Asians. Am J Clin Nutr 2004;79:983-991.[Abstract/Free Full Text]
  4. Minihane AM, Brady LM, Lovegrove SS, Lesauvage SV, Williams CM, Lovegrove JA. Lack of effect of dietary n-6:n-3 PUFA ratio on plasma lipids and markers of insulin responses in Indian Asians living in the UK. Eur J Nutr 2005;44:26-32.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
  5. Sacks FM, Katan M. Randomized clinical trials on the effects of dietary fat and carbohydrate on plasma lipoproteins and cardiovascular disease. Am J Med 2002;113(Suppl 9B):13S-24S.[CrossRef][Medline] [Order article via Infotrieve]
  6. Mozaffarian D, Pischon T, Hankinson SE, Rifai N, Joshipura K, Willett WC, Rimm EB. Dietary intake of trans fatty acids and systemic inflammation in women. Am J Clin Nutr 2004;79:606-612.[Abstract/Free Full Text]
  7. James MJ, Gibson RA, Cleland LG. Dietary polyunsaturated fatty acids and inflammatory mediator production. Am J Clin Nutr 2000;71:343S-348S.[Abstract/Free Full Text]
  8. Morris MC, Sacks F, Rosner B. Does fish oil lower blood pressure? A meta-analysis of controlled trials. Circulation 1993;88:523-533.[Abstract/Free Full Text]
  9. Hu FB, Manson JE, Willett WC. Types of dietary fat and risk of coronary heart disease: a critical review. J Am Coll Nutr 2001;20:5-19.[Abstract/Free Full Text]
  10. Marchioli R, Barzi F, Bomba E, Chieffo C, Di Gregorio D, Di Mascio R, et al. Early protection against sudden death by n-3 polyunsaturated fatty acids after myocardial infarction: time-course analysis of the results of the Gruppo Italiano per lo Studio della Sopravvivenza nell’Infarto Miocardico (GISSI)-Prevenzione. Circulation 2002;105:1897-1903.[Abstract/Free Full Text]
  11. Luo J, Rizkalla SW, Boillot J, Alamowitch C, Chaib H, Bruzzo F, et al. Dietary (n-3) Polyunsaturated fatty acids improve adipocyte insulin action and glucose metabolism in insulin-resistant rats: relation to membrane fatty acids. J Nutr 1996;126:1951-1958.[Abstract/Free Full Text]
  12. Finnegan YE, Minihane AM, Leigh-Firbank EC, Kew S, Meijer GW, Muggli R, et al. Plant- and marine-derived n-3 polyunsaturated fatty acids have differential effects on fasting and postprandial blood lipid concentrations and on the susceptibility of LDL to oxidative modification in moderately hyperlipidemic subjects. Am J Clin Nutr 2003;77:783-795.[Abstract/Free Full Text]
  13. von Schacky C. The role of omega-3 fatty acids in cardiovascular disease. Curr Atheroscler Rep 2003;5:139-145.[Medline] [Order article via Infotrieve]
  14. Baylin A, Kabagambe EK, Ascherio A, Spiegelman D, Campos H. Adipose tissue alpha-linolenic acid and nonfatal acute myocardial infarction in Costa Rica. Circulation 2003;107:1586-1591.[Abstract/Free Full Text]
  15. Hu FB, Stampfer MJ, Manson JE, Rimm EB, Wolk A, Colditz GA, et al. Dietary intake of alpha-linolenic acid and risk of fatal ischemic heart disease among women. Am J Clin Nutr 1999;69:890-897.[Abstract/Free Full Text]
  16. Harper CR, Edwards MC, Jacobson TA. Flaxseed oil supplementation does not affect plasma lipoprotein concentration or particle size in human subjects. J Nutr 2006;136:2844-2848.[Abstract/Free Full Text]
  17. Segal-Isaacson CJ, Carello E, Wylie-Rosett J. Dietary fats and diabetes mellitus: is there a good fat?. Curr Diab Rep 2001;1:161-169.[CrossRef][Medline] [Order article via Infotrieve]
  18. Weber PC, Leaf A. Cardiovascular effects of omega 3 fatty acids. Atherosclerosis risk factor modification by omega 3 fatty acids. World Rev Nutr Diet 1991;66:218-232.[Medline] [Order article via Infotrieve]
  19. Wang C, Chung M, Lichtenstein A, Balk E, Kupelnick B, DeVine D, et al. Effects of omega-3 fatty acids on cardiovascular disease. Evidence Report/Technology Assessment No. 94 (Prepared by Tufts-New England Medical Center Evidence-Based Practice Center under contract 290-02-0022) March 2004 Agency for Healthcare Research and Quality Rockville, MD. AHRQ publication no. 04-E009-2..
  20. Van den Heuvel JP. Diet, fatty acids, and regulation of genes important for heart disease. Curr Atheroscler Rep 2004;6:432-440.[Medline] [Order article via Infotrieve]
  21. Carpentier YA, Portois L, Malaisse WJ. n-3 fatty acids and the metabolic syndrome. Am J Clin Nutr 2006;83:1499S-1504S.[Web of Science][Medline] [Order article via Infotrieve]
  22. Bjerregaard P, Pedersen HS, Mulvad G. The associations of a marine diet with plasma lipids, blood glucose, blood pressure and obesity among the Inuit in Greenland. Eur J Clin Nutr 2000;54:732-737.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
  23. Warensjo E, Riserus U, Vessby B. Fatty acid composition of serum lipids predicts the development of the metabolic syndrome in men. Diabetologia 2005;48:1999-2005.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
  24. Klein-Platat C, Drai J, Oujaa M, Schlienger JL, Simon C. Plasma fatty acid composition is associated with the metabolic syndrome and low-grade inflammation in overweight adolescents. Am J Clin Nutr 2005;82:1178-1184.[Abstract/Free Full Text]
  25. Warensjo E, Sundstrom J, Lind L, Vessby B. Factor analysis of fatty acids in serum lipids as a measure of dietary fat quality in relation to the metabolic syndrome in men. Am J Clin Nutr 2006;84:442-448.[Abstract/Free Full Text]
  26. Eliasson B, Mero N, Taskinen MR, Smith U. The insulin resistance syndrome and postprandial lipid intolerance in smokers. Atherosclerosis 1997;129:79-88.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
  27. Baylin A, Campos H. The use of fatty acid biomarkers to reflect dietary intake. Curr Opin Lipidol 2006;17:22-27.[Medline] [Order article via Infotrieve]
  28. 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]
  29. Poppitt SD, Kilmartin P, Butler P, Keogh GF. Assessment of erythrocyte phospholipid fatty acid composition as a biomarker for dietary MUFA, PUFA or saturated fatty acid intake in a controlled cross-over intervention trial. Lipids Health Dis 2005;4:30.[CrossRef][Medline] [Order article via Infotrieve]
  30. Sun Q, Ma J, Campos H, Hankinson SE, Manson JE, Stampfer MJ, et al. A prospective study of trans fatty acids in erythrocytes and risk of coronary heart disease. Circulation 2007;115:1858-1865.[Abstract/Free Full Text]
  31. Corella D, Arnett DK, Tsai MY, Kabagambe EK, Peacock JM, Hixson JE, et al. The –256T>C polymorphism in the apolipoprotein A-II gene promoter is associated with body mass index and food intake in the genetics of lipid lowering drugs and diet network study. Clin Chem 2007;53:1144-1152.[Abstract/Free Full Text]
  32. . National Cancer Institute. Diet History Questionnaire, Version 1.0 2007 National Institutes of Health, Applied Research Program, National Cancer Institute .
  33. Cao J, Schwichtenberg KA, Hanson NQ, Tsai MY. Incorporation and clearance of omega-3 fatty acids in erythrocyte membranes and plasma phospholipids. Clin Chem 2006;52:2265-2272.[Abstract/Free Full Text]
  34. . National Cholesterol Education Program. Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation 2002;106:3143-3421.[Free Full Text]
  35. Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, et al. Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation 2005;112:2735-2752.[Free Full Text]
  36. Millen BE, Pencina MJ, Kimokoti RW, Zhu L, Meigs JB, Ordovas JM, D’Agostino RB. Nutritional risk and the metabolic syndrome in women: opportunities for preventive intervention from the Framingham Nutrition Study. Am J Clin Nutr 2006;84:434-441.[Abstract/Free Full Text]
  37. Riccardi G, Giacco R, Rivellese AA. Dietary fat, insulin sensitivity and the metabolic syndrome. Clin Nutr 2004;23:447-456.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
  38. Sampath H, Ntambi JM. Polyunsaturated fatty acid regulation of genes of lipid metabolism. Annu Rev Nutr 2005;25:317-340.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
  39. Jump DB, Botolin D, Wang Y, Xu J, Christian B, Demeure O. Fatty acid regulation of hepatic gene transcription. J Nutr 2005;135:2503-2506.[Abstract/Free Full Text]
  40. Jorgensen MH, Nielsen PK, Michaelsen KF, Lund P, Lauritzen L. The composition of polyunsaturated fatty acids in erythrocytes of lactating mothers and their infants. Matern Child Nutr 2006;2:29-39.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]



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