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3 Department of Human Nutrition, Faculty of Life Sciences, University of Copenhagen, Copenhagen, Denmark; 4 Clinical Nutrition and Metabolism, Department of Public Health and Caring Sciences, Faculty of Medicine, Uppsala University, Uppsala, Sweden; 5 Faculty of Agricultural Sciences, University of Aarhus, Aarhus, Denmark; and 6 Biochemistry and Nutrition Group, BioCentrum-DTU, Technical University of Denmark, Lyngby, Denmark
* To whom correspondence should be addressed. E-mail: mrf{at}life.ku.dk.
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ABSTRACT |
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 TOP ABSTRACT IntroductionSubjects and MethodsResultsDiscussionLITERATURE CITED |
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concentration compared with the control, P < 0.0001. We observed no other significant differences in the effect of the interventions diets. In conclusion, when given as part of a diet rich in butter, a mixture of CLA isomers increased lipid peroxidation but did not affect risk markers of cardiovascular disease, inflammation, or fasting insulin and glucose concentrations.
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Introduction |
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TOPABSTRACTIntroductionSubjects and MethodsResultsDiscussionLITERATURE CITED |
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160 mg/d (1), whereas intake of other CLA isomers from natural foods is negligible. Following the discovery of CLA in 1987 as an anticarcinogenic substance (2), CLA has also been found to improve insulin sensitivity in rats (3,4) and reduce fatty streak formation (5,6). However, results from human studies of CLA's effect on traditional risk markers of atherosclerosis and diabetes are ambiguous. The majority of studies do not show any effect on total, LDL, or HDL cholesterol or triacylglycerol (TAG) concentration (7–11), but one study found that a CLA mixture reduced the LDL:HDL cholesterol ratio as well as increased HDL cholesterol (12), whereas an increase in the LDL:HDL cholesterol ratio and decreased HDL cholesterol have also been reported (13,14). With regard to insulin sensitivity and diabetes risk, many have found no effect of the CLA fatty acid (FA) on fasting serum glucose or insulin (7,15–18), but both decreased plasma insulin (19) and reduced insulin sensitivity (12,14) have been reported. A potential inhibitory effect of CLA on plaque formation, as found in animal studies, might be related to other risk factors than the blood lipids. New risk markers of interest include C-reactive protein (CRP), a marker of inflammation, which is strongly correlated to cardiovascular disease (CVD) (20), as well as hemostatic markers such as plasminogen inhibitor activator 1 (PAI-1), which is also associated with risk of CVD and insulin sensitivity (21–23). In addition, markers of oxidative stress are relevant, because increased oxidative stress is seen in conditions associated with CVD, e.g. diabetes (24,25), hypercholesterolemia (26), and in smokers (27,28). The urinary excretion of 8-iso-prostaglandin F2 (8-iso-PGF2) is a marker of free radical-catalyzed, nonenzymatic peroxidation of arachidonic acid (20:4 (n-6)) and is also thought to be a reliable in vivo marker of oxidative stress (29,30). The proportion of c9,t11-CLA in bovine milk fat can be increased through feeding procedures (31–33) and we therefore found it relevant to examine the effect of CLA when given as part of a diet rich in milk fat to mimic a real-life situation with dairy products naturally high in CLA. However, changing the feeding regime results in overall changes in the milk composition, so to match the test fats as closely as possible, we examined the effect of a commercial CLA mixture incorporated into foods rich in butter, as a source of milk fat, on both traditional and new risk markers of atherosclerosis, insulin, and glucose concentrations, as well as in vivo lipid peroxidation.
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Subjects and Methods |
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TOPABSTRACTIntroductionSubjects and MethodsResultsDiscussionLITERATURE CITED |
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Subjects. To obtain a homogenous group of subjects, and given that men traditionally have been accepted to have a slightly higher absolute risk of developing CVD, only men were recruited as subjects in this study. The recruitment was conducted by advertising in local newspapers and at universities near the department. Exclusion criteria were: BMI > 30 kg/m2, smoking, hypertension, atherosclerotic disease, regular use of medication, or >10 h/wk of heavy exercise. Baseline characteristics of the 38 men who completed the study did not differ between the groups (Table 1). All men were apparently healthy as indicated by a medical questionnaire. All subjects were instructed to maintain the same level of physical activity throughout the study. The subjects' habitual diet was assessed by a 4-d weighed-food record. The mean habitual energy intakes before the intervention were 15.1 MJ/d (range, 9–18 MJ/d); 13% (9–18%) of the energy was from protein, 54% (40–70%) was from carbohydrates, and 29% (18–42%) was from fat. The 2 groups' habitual dietary intake did not differ.
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5% was from protein, 35% from carbohydrates, and 60% (115 g) from fat and replaced most of the habitual fat consumption. On the basis of the first 4-d weighed food records, the subjects were instructed in how to change their diet to consume the test foods without increasing the total fat content of their diet. We tested adherence to the dietary advice by assessing each subject's diet from another 4-d weighed food record in wk 2 of the intervention. If the dietary registration in wk 2 showed increased energy intake together with increased bodyweight (> 1 kg), we instructed the subjects to reduce their fat intake from other food sources than the test foods. All dietary records were evaluated by trained dieticians and if amounts or proportions of foods were not stated precisely and clarification with subjects was not possible, the dietary record was rejected.
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We assessed plasma LDL and HDL concentrations by enzymatic colorimetric procedure (LDL cholesterol-plus and HDL cholesterol-plus second generation kits; Roche) using a Cobas Mira Plus analyzer (Roche Diagnostic). We measured cholesterol and TAG concentrations in plasma by using enzymatic procedures (CHOD-PAP and GPO-PAP, respectively; Roche) using a Cobas Mira Plus analyzer. The CV% were 1.5, 1.1, 1.0, and 1.1 for LDL, HDL, and total cholesterol, and TAG, respectively.
We measured the plasma CRP concentrations by enhanced turbidimetric immunoassay [CRP-Latex (II) x 2 Seiken; Denka Seikan] using a Cobas Mira Plus analyzer (CV% = 4.1). We assessed plasma factor VII coagulation activity (FVII:c) in a 1-stage clotting assay and expressed the activity relative to an activity of 100 by using a 3-point standard curve (CV% = 2.0). Additional details were described previously (38,39). The concentration of PAI-1 (µg/L) in plasma was analyzed via an enzymatic immunoassay procedure (TintElize PAI-1 kit; Biopool) and quantified with a SLT Rainbow Scanner (SLT laninstruments) (CV% = 1.9).
Insulin concentrations were measured in serum with a solid phase, 2-site fluoroimmunometric assay (Auto Delfia Insulin kit B080–101; Wallac) and the Auto Delfia system 1235 514 (CV% = 2.9). We measured glucose concentrations with a hexokinase endpoint procedure in serum (Glucoquant Glucose/HK kit; Roche Diagnostics) using a Cobas Mira Plus analyzer (CV% = 1.2). We calculated the homeostasis model of assessment ratio (HOMA-R), an index of insulin resistance, from the fasting concentrations of glucose and insulin, from the following equation: (glucose mmol/L x insulin pmol/L)/22.5 (40).
Lipid peroxidation.
The subjects collected urine for 24 h before and after the intervention period. We recorded the volume and density and the samples were stored at –80°C until they were analyzed for free 8-iso-PGF2 using a specific and validated radioimmunoassay as described elsewhere (41). We adjusted the urine concentrations of 8-iso-PGF2 for total 24-h urine volume.
Statistics.
We used a mixed model ANCOVA to compare the effects of the CLA-rich and control foods and used the respective baseline values as covariates and the analyses were thus adjusted for the baseline values of each variable. We set fixed effects to type of test food (rich in CLA or control) and baseline values and random factor to subject ID number. Because the results presented here are part of a study compromising 3 interventions groups, the statistical analysis included all groups. When we detected significant effects (P < 0.05), we used the Tukey-Kramer test for a post hoc pair-wise comparison of the groups. When necessary, we log transformed the values to normalize the distribution of residual and to obtain variance homogeneity. Statistical tests were subsequently performed on the transformed data. Transformation was necessary for the proportion of c9,t11-CLA in TAG and PL, the ratio of total cholesterol:HDL cholesterol, and the concentrations of HDL cholesterol, TAG, CRP, 8-iso-PGF2, and glucose. Baseline BMI was included in the model initially because it was a stratification parameter, but it had no influence on the results and was therefore removed again. We determined Pearson correlation coefficients from pair-wise correlations of 
values (end-start values). We performed correlation analysis between variables where a treatment effect was found and the values for c9,t11- and t10,c12-CLA in lipid classes and values for all outcome variables. Unless stated otherwise, we calculated correlations from n = 38. A 2-tailed P-value of < 0.05 was considered significant. SAS statistical software (version 8.2; SAS Institute) was used for all statistical analyses. We have presented all baseline measures as means ± SD and all outcome measures as least-squares means (LSmeans; adjusted for baseline values) ± SEM.
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Results |
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TOPABSTRACTIntroductionSubjects and MethodsResultsDiscussionLITERATURE CITED |
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Dietary intake and bodyweight. We excluded 6 food records (2 from the CLA group and 4 from the control group) from wk 2 of the intervention from the analysis. The CLA group reported an 18% higher energy intake during wk 2 of the intervention (16.2 ± 2.2 MJ/d) compared with the control group (13.7 ± 3.7 MJ/d; P = 0.002). The CLA group had a 30% higher intake of PUFA (1.2 ± 0.1 g/MJ) than the control group (0.9 ± 0.1 g/MJ; P = 0.04), which corresponded to the difference in FA composition of the test foods. The distribution (g/MJ) of protein (6.1 ± 0.3 vs. 5.9 ± 0.3), carbohydrates (24.5 ± 0.8 vs. 26.8 ± 0.8), total fat (11.8 ± 0.4 vs. 11.1 ± 0.4), SFA (6.9 ± 0.5 vs. 6.4 ± 0.5), and monounsaturated fat (2.9 ± 0.1 vs. 2.5 ± 0.1) did not differ between the groups. We found no significant changes in bodyweight during (data not shown) or at the end of the intervention period (Table 3).
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The effects of the types of test foods on plasma total, LDL, or HDL cholesterol concentration, the total cholesterol:HDL cholesterol ratio, and TAG, CRP, FVII:c, or PAI-1 concentrations did not differ (Table 3). The control group had a high baseline CRP concentration, which was caused by 2 outliers (3.17 and 4.35 mg/L). Although the concentrations were not >10 mg/L, the generally accepted cut-off concentration indicating acute and not chronic inflammation, we repeated the statistical analysis without the outliers. The baseline values in the control group were then 0.46 ± 048 mg/L (mean ± SD) and the adjusted CRP concentrations after the intervention for the CLA and control group were 0.32 ± 0.07 and 0.24 ± 0.05 (LSmeans ± SEM), respectively. Without the outliers, the CRP concentration between the groups still did not differ either at baseline (P = 0.330) or after the intervention (P = 0.735).
The effects of the test foods on fasting serum insulin or glucose concentrations or the insulin sensitivity when assessed using the HOMA-R index did not differ (Table 3).
Lipid peroxidation.
The CLA-rich foods resulted in 83% higher urinary excretion of in vivo marker of lipid peroxidation 8-iso-PGF2 compared with the control foods (P = 0.002) (Table 3).
Correlation analysis.
The change in the urinary excretion of 8-iso-PGF2 was positively correlated with the change in the proportion of c9,t11-CLA in plasma CE (r = 0.38; P = 0.018) and plasma PL (r = 0.47; P = 0.003) and with that of t10,c12-isomer in plasma CE (r = 0.45; P = 0.005) and plasma PL (r = 0.52; P = 0.009).
The urinary excretion of 8-iso-PGF2 was positively correlated to CRP concentration (r = 0.37; P = 0.024).
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Discussion |
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TOPABSTRACTIntroductionSubjects and MethodsResultsDiscussionLITERATURE CITED |
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The main result of the study was the 83% higher concentration of urinary 8-iso-PGF2 in the CLA group compared with the control group after the intervention. This increase is consistent with the results of other studies (8,15,44). We also found a significant correlation between the changes in the proportions of the CLA isomers in plasma CE and PL and the changes in 8-iso-PGF2 excretion. 8-Iso-PGF2 is a specific metabolite of arachidonic acid and an indicator of free radical-induced, nonenzymatically lipid peroxidation in vivo (45), which is considered to be a reliable and clinically relevant in vivo marker of oxidative stress (29,30).
Originally, CLA was hypothesized to reduce the risk of CVD, based on the fatty streak prevention and reduction in rodents (5,6), but we found no difference between the groups in plasma total, LDL, or HDL cholesterol concentrations or the TAG concentration, consistent with the majority of CLA studies (7,9–11,18,44,46). However, both lower and higher LDL:HDL ratios and lower and higher circulating plasma HDL cholesterol concentrations have been reported (12–14, 47). The discrepancy between the results may be caused by differences in study design and subjects. With regard to the newer risk markers of CVD, the effects of the foods on inflammatory or hemostatic risk markers did not differ. The higher plasma CRP concentration in the control group at baseline was caused by 2 outliers; excluding those from the statistical analysis did not change the overall result but did provide more homogenous baseline values. Other studies have found that a CLA mixture both increased CRP concentration (48,49) and, like our results, had no effect on the marker (12,15). There is no obvious explanation for the discrepancy between the results in these studies, because study design and subjects did not differ. We found that the change in urinary 8-iso-PGF2 was positively correlated to the change in CRP concentration, which has also been found by other studies (50,51). Other markers of inflammation have also been examined, e.g. 4 studies found that CLA increased the leukocyte count (46,48,52), an indicator of inflammation associated with increased CVD risk (53). Plasma interleukin-6, like CRP, has both increased (48) and not been affected by a CLA mixture (12). Thus, the effect of CLA on low-grade inflammation in humans is not clear but may tend to increase.
The effect of CLA on other hemostatic markers has only been investigated sparsely. CLA has been found to reduce the fibrinogen concentrations compared with a control (12) and an in vitro study found that CLA (both c9,t11- and t10,c12-CLA and a mixture of these isomers) inhibited platelet aggregation (54). Consistent with our finding, one study found that the effect of a CLA mixture and a control on PAI-1 concentrations did not differ (7). Thus, at this point it is difficult to ascertain whether CLA affects PAI-1, the main regulator of fibrinolysis. Considering the inconsistent results on risk markers of CVD, it is not clear whether the increase in isoprostane excretion after CLA is of clinical significance per se, although an increase in lipid peroxidation is not considered beneficial due to the association with CVD-related conditions.
The CLA-rich foods did not affect fasting serum glucose, insulin, or the calculated HOMA-R differently than the control foods index in this study, which is consistent with findings from studies examining both a mixture and the c9,t11- and t10,c12 isomers alone (7,15–17). However, other studies have reported increased plasma glucose or reduced insulin sensitivity from a CLA mixture and the t10,c12 isomer alone on insulin sensitivity in diabetic patients or men with metabolic syndrome (11,12,50). Thus, these results indicate that health status may influence the response to CLA supplementation. Two studies have observed increased plasma and urinary concentrations of 8-iso-PGF2 in diabetic patients (24,25), which may indicate an association between increased lipid oxidation and diabetes, but the impact of this on the risk of diabetes is not yet established.
The difference between the results in human and animal studies may be caused by differences in the dose of CLA administered. The amount of CLA administered in this study was similar to those in other human studies (7,10,55), which ranged from 1.5 g/d (16) to 6.4 g/d (48). In animal studies, the dose may be up to 10 times higher; thus, the effect of the FA is likely to be more pronounced. Furthermore, differences in metabolic rate and species differences are also often responsible for the different results.
One concern about our study was the large daily amount of fat from the test foods, because a high intake of fat may influence the risk markers of interest. However, the amount corresponded to the average daily intake in young Danish men (19–34 y) in 1995 (56) and substituted most of the subjects' habitual fat intake. The subjects in the CLA group reported increased energy intake compared with the control group. The reason for the increased energy intake is not clear, because the energy content and macronutrient composition of the test foods were similar and the intervention was double-blinded. However, most importantly, body weight between the 2 groups did not differ before or after the intervention; therefore, the increased energy intake may not have influenced the indicators of risk. However, another concern in the present study is that plasma total and LDL cholesterol concentrations increased during the intervention in both groups. This may have been caused by the amount of SFA in the test foods, especially myristic and palmitic acid, because these have been demonstrated to increase total and LDL cholesterol concentrations (57). Thus, the content of SFA may have masked any effect of CLA on the blood lipids and maybe also on other risk markers, i.e. FVII:c and HOMA-R, which also increased in both groups during the intervention.
We were unable to estimate the contribution of CLA from foods other than the test foods. CLA is naturally found in foods with a high content of SFA (e.g. dairy and meat products) and the SFA intake did not differ. Therefore, we find it reasonable to assume that there were no differences between the groups in the CLA contribution from other foods. Furthermore, the estimated intake of CLA in the Swedish population is 160 mg/d (1); thus, any differences in CLA intake from the subjects' own diet would likely be too small to interfere with our intervention. We did observe an expected higher intake of PUFA in the CLA group compared with the control group during the intervention, because CLA was categorized as PUFA when calculating the FA intake from the dietary records.
In conclusion, a mixture of c9,t11- and t12,c10-CLA administered as part of a diet rich in butter increases lipid peroxidation but does not affect the plasma total, LDL, and HDL cholesterol and TAG concentrations, or inflammatory and hemostatic risk markers, nor does it affect fasting insulin and glucose concentrations or an index of insulin sensitivity in healthy young men. Thus, this study confirms previous findings of the effect of a CLA mixture in humans on lipid peroxidation and contributes to elucidating the effect on risk markers of CVD.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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2 Author disclosures: M. Raff, T. Tholstrup, S. Basu, P. Nonboe, M. T. Sørensen, and E. M. Straarup, no conflicts of interest.
7 Abbreviations used: CE, cholesterol ester; CLA, conjugated linoleic acid; c9,t11-CLA, cis 9, trans 11 CLA; CRP, C-reactive protein; CVD, cardiovascular disease; 8-iso-PGF2, 8-iso-prostaglandin F2; FA, fatty acid; FVII:c, factor VII coagulation activity; HOMA-R, homeostasis model of assessment ratio; LSmeans: least-squares means; PAI-1, plasminogen activator inhibitor 1; PL, phospholipid; TAG, triacylglycerol; t10,c12-CLA, trans 10, cis 12 CLA.
Manuscript received 13 March 2007. Initial review completed 3 April 2007. Revision accepted 18 December 2007.
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LITERATURE CITED |
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