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Diet-Induced Weight Loss Is Associated with Decreases in Plasma Serum Amyloid A and C-Reactive Protein Independent of Dietary Macronutrient Composition in Obese Subjects

Departments of Medicine (Cardiology) (K.D.O.) and Laboratory Medicine (M.H.W.), University of Washington. Seattle, Washington 98195-6422; and Departments of Medicine (D.A.D.), Nursing (B.J.B.), Psychiatry (R.J.S.), and Pediatrics (J.B., S.D.), University of Cincinnati, Cincinnati, Ohio 45267

Address all correspondence and requests for reprints to: Kevin D. O’Brien, M.D., Division of Cardiology, Box 356422, University of Washington, 1959 Northeast Pacific Street, Seattle, Washington 98195-6422. E-mail: cardiac{at}u.washington.edu.

	Abstract

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Elevated levels of serum amyloid A (SAA) and C-reactive protein (CRP) have been associated with increased cardiovascular risk. Although levels of CRP decrease with weight loss, it is not known whether SAA decreases with weight loss or whether dietary macronutrient composition affects levels of either SAA or CRP. SAA and CRP levels were measured retrospectively on baseline and 3-month plasma samples from 41 obese (mean body mass index 33.63 ± 1.86 kg/m²) women completing a randomized trial comparing a low-fat diet (n = 19) and a very low-carbohydrate diet (n = 22). For the 41 participants, there were significant decreases from baseline to 3 months in both LogSAA (P = 0.049) and LogCRP (P = 0.035). The very low-carbohydrate dieters had a significantly greater decrease in LogSAA (P = 0.04), but their weight loss also was significantly greater (–7.6 ± 3.2 vs. –4.3 ± 3.5 kg, P < 0.01). In this study, the decreases in inflammatory markers correlated significantly with weight loss (r = 0.44, P = 0.004 vs. LogSAA and r = 0.35, P = 0.03 vs. LogCRP). Also, change in LogSAA correlated with change in insulin resistance (r = 0.35, P = 0.03). Thus, in otherwise healthy, obese women, weight loss was associated with significant decreases in both SAA and CRP. These effects were proportional to the amount of weight lost but independent of dietary macronutrient composition.

	Introduction

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IN THE UNITED STATES, there has been a staggering 70% increase in the prevalence of obesity in the last decade (1, 2). The U.S. age-adjusted prevalence of obesity may be as high as 30.5% in adults (3) and over 15% in children between the ages of 6 and 19 yr (4). Because current strategies for weight loss are not successful in the majority of subjects, a number of alternative weight loss diets have been promoted outside the medical mainstream. Of these, the best-known are regimens with severe restriction of carbohydrates (5). Despite their popularity, there has been almost no formal testing of the efficacy of these diets (6). In addition, concern has been raised as to whether very low-carbohydrate diets might adversely affect cardiovascular risk factors, such as plasma lipids (7).

One consequence of obesity that may contribute to morbidity and mortality is an increase in levels of serum inflammatory markers, such as C-reactive protein (CRP) and serum amyloid A (SAA) (8, 9, 10, 11, 12, 13, 14). SAA is an inflammatory protein that is carried in the plasma on primarily high-density lipoprotein (HDL) particles (15, 16), and SAA levels are increased by dietary cholesterol feeding in mice (17). The exact mechanisms linking obesity to inflammatory markers are not clear, but it has been suggested that release of proinflammatory cytokines from adipose tissue is the primary connection (9). Increased levels of CRP have been associated with increased insulin resistance, which is strongly associated with obesity and also is thought to be caused in part by adipocyte-released cytokines (8, 9, 13, 14). Furthermore, high-fat, high-cholesterol diets have been shown to increase SAA levels in animal models, suggesting that diet also may contribute to obesity-related elevations in inflammatory markers (17). Importantly, increased levels of both CRP and SAA have been associated with increased cardiovascular risk (18, 19), although it is a matter of some debate as to whether their predictive power is independent of cholesterol levels and other risk factors, such as the metabolic syndrome (20, 21, 22, 23).

Recently, studies using low-fat, high-carbohydrate diets have demonstrated that weight loss is associated with decreases in CRP levels (12, 13, 14). However, no studies have examined the effects of weight loss on SAA levels in humans. Furthermore, no studies have examined the influence of the macronutrient composition of weight loss diets on levels of either CRP or SAA.

We hypothesized that very low-carbohydrate diets, which have a high proportion of calories from fat, would increase plasma CRP and SAA levels in humans. Accordingly, we compared the effects of 3-month dietary interventions with either a low-fat diet or a very low-carbohydrate diet on CRP and SAA levels in 41 obese women.

	Subjects and Methods

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Participants

We recently reported the results of a randomized trial comparing low-fat and very low-carbohydrate diets in 42 obese women (24). Inclusion criteria were age 18 yr or older, moderate obesity (body mass index of 30–35), and a stable weight over the preceding 6 months (no weight loss or gain > 10% of their body weight). Exclusion criteria were the presence of cardiovascular disease; untreated hypertension, diabetes, hypothyroidism, substance abuse; pregnancy; or lactation. All participants gave written, informed consent for participation in the study, which was approved by the University of Cincinnati Institutional Review Board. Of the 42 participants, stored, frozen plasma samples obtained at baseline and 3 months were available from 41 (mean age 43.73 ± 7.72 yr; mean body mass index 33.63 ± 1.86 kg/m²; mean percent body fat 41.36 ± 3.22%).

Among these 41 participants, 19 had followed a low-fat diet, corresponding to an American Heart Association Step 1 diet. These subjects had been advised to intentionally restrict their caloric intake to approximately 1200 kcal/d. The remaining 22 participants had been randomized to a very low-carbohydrate diet, similar to the one promoted by Atkins (5). Subjects assigned to the very low-carbohydrate diet did not follow a prescribed restriction in caloric intake. Instead, they were advised to limit daily carbohydrate intake to 20 gm/d for the first 2 wk, with urinary dipstick self-testing for ketones to confirm that ketosis had been induced. After the second week, participants were allowed to increase their daily carbohydrate intake up to 60 gm/d so long as urinary dipstick self-testing confirmed continued ketosis. Caloric intake and the macronutrient composition of the diets were determined by 3-d food records kept by the subjects before, and weekly after, starting the diet. The diet records had been analyzed using Nutritionist V (First Data Bank, San Bruno, CA).

CRP and SAA assays

Plasma CRP and SAA levels were determined by highly sensitive, nephelometric assays (Behring Diagnostics, Deerfield, IL, and Liederbach, Germany). For the CRP assay, the lower limit of detection was 0.2 mg/dl and the coefficient of variation was 5–9%. For the SAA assay, the lower limit of detection was 0.8 mg/dl and the coefficient of variation was 4–8%.

Determination of basal insulin resistance

Mean fasting insulin and glucose values were calculated from three samples drawn at 5-min intervals. Basal insulin resistance was calculated from fasting insulin and glucose values using the homeostasis model assessment (HOMA) method (25, 26).

Statistical analyses

Continuous variables were compared by one-way ANOVA. The distributions of CRP and SAA values were highly skewed, so baseline and 3-month values were log transformed. However, because the log-transformed values still were not normally distributed, nonparametric tests were used in the analyses. Baseline and 3-month CRP, SAA, LogCRP, and LogSAA values were compared for all participants using the Wilcoxon matched pairs test. Changes in LogCRP and LogSAA values for each person were calculated and the effects of the two diets compared using the Mann-Whitney U test. Pearson correlation coefficients were calculated to quantify the relationships between changes in LogCRP or LogSAA and changes in weight or insulin resistance; in each case a linear relationship was confirmed by the runs test. Statistical analyses were performed using the GraphPad Prism (version 3.03) and InStat (version 3.05) programs (GraphPad Software, Inc., San Diego, CA).

	Results

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Changes in body weight, blood pressure, lipids, and insulin resistance

Baseline body weights were similar in the women randomized to the very low-carbohydrate and low-fat groups (91.1 ± 8.4 vs.± 92.3 ± 6.2 kg, P = 0.62), but weight loss was substantially greater in the very low-carbohydrate group (–7.6 ± 3.2 vs. –4.3 ± 3.5 kg, P < 0.01). In this 41-patient subset of the original study population (24), there were no significant differences between the low-fat and very low-carbohydrate diet groups with regard to change in either systolic (P = 0.22) or diastolic blood pressure (P = 0.06). Similarly, changes in total cholesterol (P = 0.12), low-density cholesterol (LDL) cholesterol (P = 0.76), and HDL cholesterol (P = 0.98) were similar in the low-fat and very low-carbohydrate groups. There was a significantly greater decrease in triglyceride levels in the very low-carbohydrate group, compared with the low-fat dieters (–7.5 ± 30.3 vs. –56.3 ± 51.1 mg/dl, P < 0.001). Insulin resistance (HOMA units) decreased significantly from baseline to 3 months in both the low-fat (5.3 ± 2.2 vs. 4.1 ± 2.8, P < 0.03) and very low-carbohydrate (4.5 ± 2.1 vs. 2.9 ± 1.9, P < 0.03) groups, and the magnitude of these changes did not differ significantly between the two diet groups (P = 0.49).

Dietary intervention and inflammatory markers

For all participants, the median [interquartile range (IQR)] CRP level was 3.45 (1.70, 7.45) mg/liter at baseline and 2.40 (1.35, 7.35) mg/liter after 3 months of diet (P = 0.09, Fig. 1A). However, 3 months of dietary intervention was associated with a significant, 24% reduction in median (IQR) LogCRP values from 0.54 (0.26, 0.88) to 0.41 (0.15, 0.88) (P = 0.035, Fig. 1B).

View larger version (27K): [in this window] [in a new window]   FIG. 1. Dietary intervention is associated with decreases in LogCRP and LogSAA levels. Data are graphed either as scatterplots, in which median values are indicated by a horizontal line (A and C) or as box and whisker plots (B and D), which show median (center line of box), 75th and 25th percentiles (upper and lower bounds of the box), and 90th and 10th percentile values (upper and lower whiskers). A and B, CRP change for all participants. For all 41 participants in the study, the change in CRP levels from baseline to 3 months did not reach significance (A), but LogCRP levels decreased significantly from baseline to 3 months (P = 0.035). C and D, SAA change for all participants. Similarly, the change in SAA levels from baseline to 3 months did not reach significance (C), but LogSAA levels decreased significantly from baseline to 3 months (D, P = 0.049).

Effects of diets on inflammatory markers

Median (IQR) decreases in LogCRP did not differ significantly between the very low-carbohydrate group [–0.16 (–0.39, 0.09)] and the low-fat diet group [–0.02 (–0.12, 0.08)] (P = 0.20, Fig. 2A). However, the median reduction in LogSAA was significantly greater for the very low-carbohydrate diet group [–0.10 (–0.28, 0.02)] than for the low-fat diet group [–0.02 (–0.10, 0.15)] (P = 0.04, Fig. 2B).

View larger version (15K): [in this window] [in a new window]   FIG. 2. CRP and SAA changes by diet group. A, CRP change by diet group. There was no significant difference in the decreases in LogCRP levels for the low-carbohydrate group, compared with the low-fat group over 3 months (P = 0.20). B, SAA change by diet group. The decrease in LogSAA levels over 3 months was significantly greater for the low-carbohydrate group, compared with the low-fat group (P = 0.04).

Correlation of changes in body weight and insulin resistance with changes in LogCRP and LogSAA

Changes in LogCRP and LogSAA were highly correlated (r = 0.68, P < 0.0001, Fig. 3A). However, there was no correlation between changes in body weight and insulin resistance among the 41 subjects (r = 0.18, P = 0.28, Fig. 3B). For the 41 participants, weight change was significantly correlated with changes in LogCRP (r = 0.34, P = 0.03, Fig. 4A) and LogSAA (r = 0.44, P = 0.004, Fig. 4B). Change in basal insulin resistance did not correlate with change in LogCRP (r = 0.07, P = 0.66, Fig. 4C). However, change in basal insulin resistance did correlate with change in LogSAA (r = 0.32, P = 0.04, Fig. 4D).

View larger version (14K): [in this window] [in a new window]   FIG. 3. Correlation between changes in CRP and SAA level and lack of correlation between changes in body weight and insulin resistance. For each comparison the regression line is shown (solid line) along with its 95% confidence intervals (dotted curves). A, Change in CRP vs. change in SAA. Changes in LogCRP and LogSAA levels were highly correlated (n = 41). B, Change in body weight and change in insulin resistance. In contrast, body weight change and insulin resistance change were not correlated (n = 40).

View larger version (26K): [in this window] [in a new window]   FIG. 4. Relationships of changes in CRP or SAA to changes in body weight and insulin resistance. For each comparison the regression line is shown (solid line) along with its 95% confidence intervals (dotted curves). A, Change in CRP vs. change in weight. For the 41 participants, there was a significant correlation between change in LogCRP and change in body weight (r = 0.34, P = 0.03). B, Change in SAA vs. change in weight. Similarly, for the 41 participants, there was a highly significant correlation between change in LogSAA and change in body weight (r = 0.44, P = 0.004). C, Change in CRP vs. change in insulin resistance. For 40 participants with basal insulin and glucose levels, there was no relationship between change in LogCRP and change in insulin resistance, as calculated by HOMA (r = 0.07, P = 0.66). D, Change in SAA vs. change in insulin resistance. In contrast, there was a significant correlation between change in LogSAA and change in insulin resistance (r = 0.32, P = 0.04).

In addition, we compared changes in weight over 3 months with changes in systolic blood pressure, diastolic blood pressure, triglycerides, total cholesterol, LDL cholesterol, and HDL cholesterol for all 41 participants (Table 1). Significant correlations were found between weight loss and reductions in systolic blood pressure (r = 0.37, P = 0.02), diastolic blood pressure (r = 0.39, P = 0.01), and triglycerides (r = 0.39, P = 0.01). No correlations were found between change in weight and changes in total, LDL, or HDL cholesterol. Slopes of the regression lines demonstrated that for each kilogram of weight lost, systolic blood pressure decreased by 1.1 ± 0.4 mm Hg, diastolic blood pressure decreased by 0.9 ± 0.3 mm Hg, and triglycerides decreased by 5.2 ± 2.0 mg/dl. Thus, these findings confirm that weight loss is associated with favorable changes in more traditional cardiovascular risk factors as well as in inflammatory markers and insulin resistance.

	Discussion

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The most likely explanation for the greater decrease in SAA in the very low-carbohydrate diet group is that participants on the very low-carbohydrate diet lost significantly more weight than did those on the low-fat diet over the 3 months of observation. This possibility is supported by the observations that reductions in both LogCRP and LogSAA correlated significantly with weight loss in the 41 participants of the present study. In addition, a previous 3-month dietary intervention study in obese women (12) reported reductions in mean weight (–7.9 kg) and mean CRP level (–26%) with a low-fat diet that were similar to the reductions in mean weight (–7.5 kg) and median CRP level (–24%) achieved with the very low-carbohydrate diet in the present study. Taken together, these observations suggest that weight loss, rather than macronutrient composition, may be the primary determinant of changes in inflammatory markers during dietary intervention in obese women.

Because high-fat, high-cholesterol diets increase SAA levels in particular (17) and inflammation in general (17, 27) in animal models, it also was surprising that the high-fat, very low-carbohydrate diet was not associated with increased CRP and SAA levels. One possible explanation for this finding is that obesity and/or insulin resistance influence an individual’s susceptibility to adverse changes in plasma inflammatory markers in response to dietary cholesterol. For example, a recent study, performed in weight-stable subjects, demonstrated that 1 month of cholesterol feeding increased total and LDL cholesterol levels to a much greater degree in lean, insulin-sensitive subjects than in subjects that were either lean but insulin resistant or obese and insulin resistant (28). Thus, it is possible that the obese subjects in the present study were less sensitive to adverse effects of dietary cholesterol feeding.

An interesting additional finding of this study was the correlation between improvement in insulin resistance and decrease in SAA levels. This relationship was not simply a function of weight loss because changes in insulin resistance and body weight were not correlated. Previous studies have shown that changes in CRP levels correlate with changes in insulin resistance (13, 14), but we were unable to demonstrate this relationship in the present study, possibly related to small sample size, differences in the method of determination of insulin resistance, and/or inclusion of insulin-sensitive as well as insulin-resistant participants. For example, our study measured insulin resistance by the HOMA method (25), which measures basal, rather than glucose-stimulated, insulin resistance (26), whereas previous studies used measurements of glucose-stimulated insulin resistance (13, 14). Moreover, McLaughlin et al. (14) recently have shown that with weight loss, CRP levels are decreased only in insulin resistant, but not in insulin-sensitive, obese subjects. Thus, the relationship between CRP change and insulin resistance change could have been masked in our study by the inclusion of insulin-sensitive subjects, in whom the relationship between CRP change and insulin resistance change is not present. However, our study did find a significant correlation between change in basal insulin resistance and change in SAA levels. This raises the possibility that SAA levels maybe more sensitive to change in basal insulin resistance than are CRP levels.

There was no influence of oral sex steroid hormones on dietary responses for either SAA or CRP. At baseline, median (IQR) CRP levels were higher in hormone users [6.75 (3.45, 15.35)] than nonusers [2.10 (1.30, 4.20)] (P = 0.0005), a relationship that has been well documented (29). However, in contrast to a recently published report (30), we were not able to demonstrate a significant difference in baseline median (IQR) SAA levels between oral hormone users [5.60 (2.45, 11.55)] and nonusers [5.00 (2.95, 6.55)] (P = 0.41).

Finally, the results demonstrate significant correlations of weight loss with favorable changes in more traditional cardiovascular risk factors, such as blood pressure and plasma triglycerides. The blood pressure changes were particularly striking because, as a group, these participants were normotensive at baseline (mean ± SD baseline systolic blood pressure: 116 ± 13 mm Hg and mean ± SD baseline diastolic blood pressure: 77 ± 11 mm Hg). A recent metaanalysis reemphasized the importance of blood pressure as a cardiovascular risk factor by demonstrating that, in subjects aged 40–69 yr, each 10 mm Hg difference in usual diastolic blood pressure is associated with a greater than 2-fold difference in rates of death from either stroke or ischemic heart disease (31). In addition, two recent studies have shown that, in insulin-resistant individuals, modest weight loss is associated with a substantial reduction in risk for developing diabetes (32, 33). Our study confirms the beneficial effects of weight loss on blood pressure and insulin resistance and extends this benefit to the inflammatory markers, SAA and CRP.

In summary, 3-month dietary intervention was associated with significant reductions in the inflammatory markers, CRP and SAA. These changes in inflammatory markers correlated with changes in body weight, and the SAA change also correlated with change in insulin resistance. The magnitude of reductions in weight and SAA levels was significantly greater with the very low-carbohydrate diet. However, the clinical choice of a weight loss diet includes a variety of factors. Concerns about the long-term safety of very low-carbohydrates remain and will need to be assessed carefully. These findings suggest that longer-term studies of with very low-carbohydrate diets are warranted.

	Acknowledgments

 
The authors thank Karen Fowler for expert assistance in manuscript preparation and Maggie Mayes for expert technical assistance.

	Footnotes

 
This work was supported in part by the American Heart Association Grant-in-Aid, University of Cincinnati General Clinical Research Center (M01 RR08084), University of Washington Clinical Nutrition Research Unit (National Institutes of Health Grant DK35816), and National Institutes of Health Grants DK54263, DK56863, and HL30086.

First Published Online January 25, 2005

Abbreviations: CRP, C-reactive protein; HDL, high-density lipoprotein; HOMA, homeostasis model assessment; IQR, interquartile range; LDL, low-density cholesterol; SAA, serum amyloid A.

Received May 28, 2004.

Accepted January 19, 2005.

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Top Abstract Introduction Subjects and Methods Results Discussion References

 

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