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Abstract

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

Obesity-related hepatic steatosis is a major risk factor for metabolic and cardiovascular disease. Fat reduced hypocaloric diets are able to relieve the liver from ectopically stored lipids. We hypothesized that the widely used low carbohydrate hypocaloric diets are similarly effective in this regard. A total of 170 overweight and obese, otherwise healthy subjects were randomized to either reduced carbohydrate (n = 84) or reduced fat (n = 86), total energy restricted diet (−30% of energy intake before diet) for 6 months. Body composition was estimated by bioimpedance analyses and abdominal fat distribution by magnetic resonance tomography. Subjects were also submitted to fat spectroscopy of liver and oral glucose tolerance testing. In all, 102 subjects completed the diet intervention with measurements of intrahepatic lipid content. Both hypocaloric diets decreased body weight, total body fat, visceral fat, and intrahepatic lipid content. Subjects with high baseline intrahepatic lipids (>5.56%) lost ≈7-fold more intrahepatic lipids compared with those with low baseline values (<5.56%) irrespective of diet composition. In contrast, changes in visceral fat mass and insulin sensitivity were similar between subgroups, with low and high baseline intrahepatic lipids. Conclusion: A prolonged hypocaloric diet low in carbohydrates and high in fat has the same beneficial effects on intrahepatic lipid accumulation as the traditional low-fat hypocaloric diet. The decrease in intrahepatic lipids appears to be independent of visceral fat loss and is not tightly coupled with changes in whole body insulin sensitivity during 6 months of an energy restricted diet. (HEPATOLOGY 2011)

Excessive hepatic fat content contributes to obesity-associated metabolic disease.1-3 Indeed, the amount of intrahepatic lipids (IHL) is an important determinant for whole-body and tissue-insulin sensitivity,2, 4 independent of total body or visceral fat.5, 6 Moreover, excessive hepatic fat accumulation predisposes to nonalcoholic steatohepatitis, which may progress to cirrhosis and hepatic cancer.7 Therefore, interventions reducing hepatic fat content address the root cause for both obesity-associated metabolic and liver disease. Lifestyle interventions including hypocaloric diets are a cornerstone for obesity management because diet-induced weight loss improves insulin action8, 9 and reduces type 2 diabetes mellitus incidence.10 Moreover, weight reduction through caloric restriction improved hepatic steatosis.11, 12 In addition to energy balance, macronutrient composition may affect liver fat content. Excessive fat ingestion is a commonly applied model to induce hepatic steatosis in laboratory animals.13 Indeed, short-term high-fat feeding increased hepatic fat content in rodents14 and in human subjects.15-17 The response involves lipogenic transcription factor activation and increased dietary lipid delivery.14 On the other hand, low-fat hypocaloric dieting reduced hepatic fat content in obese subjects.8 Excessive carbohydrate ingestion also increased hepatic fat in human subjects.18 Yet carbohydrate and fat feeding differentially regulates genes involved in hepatic lipogenesis, fatty acid uptake, and fat oxidation.19 We determined whether or not a reduced carbohydrate diet is as effective in reducing hepatic lipid content in obese individuals as a low-fat hypocaloric diet. The issue is clinically relevant because low-carbohydrate hypocaloric diets are popular in the treatment of obesity.20

Patients and Methods

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

Patients.

We randomized 170 overweight and obese otherwise healthy subjects (135 women, 35 men) in our study. All subjects completed a comprehensive medical evaluation including a dietary record for 7 consecutive days before study participation. They ingested no medications. Subjects reporting more than 2 hours of physical activity per week assessed with a physical activity record over 7 consecutive days were excluded. Physical activity was defined as any scheduled exercise training performed by the subjects during the 7 days.We also excluded subjects consuming >20 g/day of alcohol, with type 2 diabetes, acute or chronic infections, any diseases requiring treatment, and pregnant or nursing women. Subjects were advised to continue their current physical activity level throughout the study. This study was carried out in accordance with the Declaration of Helsinki and current guidelines of good clinical practice. Our Institutional Review Board approved the study and written informed consent was obtained before entry.

Study Design.

This was a prospective, randomized study conducted in an academic clinical research center between March 2007 and June 2010. The data were generated as part of the B-SMART study (ClinicalTrials.gov Identifier: NCT00956566), which compared weight loss and associated metabolic and cardiovascular markers with reduced carbohydrate and reduced fat hypocaloric diets. Subjects underwent thorough anthropometric, metabolic, and exercise testing before and after 6 months on a hypocaloric diet with either reduced carbohydrate or reduced fat content. Except for the dieticians, study nurses and physicians were blinded for the treatment assignment. For allocation of the subjects, a computer-generated list of random numbers was used. The randomization sequence was created using SPSS 18 (Chicago, IL) statistical software and subjects were assigned to reduced carbohydrate or reduced fat diet with a 1:1 allocation using random block sizes of 2, 4, and 6. Study nurses and physicians screening and enrolling volunteers were blinded for the randomization sequence.

After randomization, subjects provided a baseline 7-day food protocol, which was analyzed for macro- and micronutrient content including fatty acid composition using Optidiet (V3.1.0.004, GOE, Linden, Germany) a professional analysis software that is based on nutritional content of food as provided by the German National Food Key. Individual recommendations for energy intake were calculated as follows: total energy content of the baseline food protocol was reduced by 30% (to a minimum of 1,200 kcal/day) to ensure significant weight reduction. In addition to the reduced energy intake, nutrition counseling aimed at achieving a daily macronutrient content ≤90 g carbohydrates, 0.8 g protein per kg body weight, and a minimum of 30% fat in the reduced carbohydrate group, and a fat content of ≤20% of total energy intake, 0.8 g protein per kg body weight, and the remaining energy content provided by carbohydrates in the reduced fat group. All participants attended either reduced carbohydrate or reduced fat weekly group sessions run by nutritionists throughout the 6-month weight reduction program, providing background information on healthy food choices for each group. Blinding of participants for the allocated dietary intervention was impossible. In addition, individual nutritional counseling by a nutritionist including analysis of a 7-day food protocol took place every 2 months during the 6-month intervention, to address individual questions, and to monitor adherence to the diet.

Anthropometric and Metabolic Evaluation.

After an overnight fast, we determined body weight, waist circumference, and height in a standardized fashion.21 During an oral glucose load (75 g glucose/500 mL), we obtained blood samples at baseline and 15, 30, 45, 60, 90, and 120 minutes after glucose ingestion to measure glucose and insulin. We assessed lean body and fat mass by bioimpedance analysis (BIA 5 series, Denner, Feldmeilen, Switzerland). After another overnight fast, subjects underwent imaging studies and physical fitness testing.

Abdominal and Liver Fat Quantification.

Abdominal subcutaneous and visceral fat mass as well as liver fat content were measured as described.1 For further information, see the Supporting Information.

Incremental Exercise Test.

Subjects were submitted to a stepwise incremental exercise test on a bicycle ergometer to determine maximal oxygen uptake as outlined in the Supporting Information.

Biochemical Measurements and Calculations.

Glucose (mmol/L), insulin (μU/mL), lipoproteins, alanine aminotransferase (ALT [U/L]), and aspartate aminotransferase (U/L) were determined by standard methods in a certified clinical chemistry laboratory. Insulin resistance was estimated by homeostasis model assessment index (HOMA). HOMA was calculated from fasting insulin and glucose by (insulin [μU/mL] × glucose [mmol/L])/22.5).22 Impaired glucose tolerance was defined as 2-hour glucose values during the oral glucose tolerance test (OGTT) of ≥140 mg/dL.23 Whole body insulin sensitivity was calculated by the composite insulin-sensitivity index (C-ISI).24 C-ISI = 10,000/√[(FPG×FPI) × (G×I)], where FPG and FPI are fasting plasma glucose (mg/dL) and fasting plasma insulin (μU/mL), respectively, and G (mg/dL) and I (μU/mL) are the mean glucose and mean insulin concentration during the 2-hour OGTT. Hepatic insulin resistance and β-cell function/secretion (insulinogenic index) were also estimated.25 The hepatic insulin resistance index was calculated from the OGTT. The approach has been validated in nondiabetic subjects against euglycemic insulin clamp testing in combination with tritiated glucose.26 The insulinogenic index was computed as the serum insulin increment in the first 30 minutes of the OGTT divided by the corresponding glucose increment (ΔI30/ΔG30), which is correlated with beta-cell function derived from frequently sampled intravenous glucose tolerance testing.27 Before and after diet serum high sensitive-C-reactive protein (CRP) (in μg/mL), total and high molecular weight adiponectin (both μg/mL), and fetuin-A (in ng/mL), were measured by sandwich enzyme-linked immunosorbent assay (ELISA) with the following characteristics: hs-CRP (BioVendor, Heidelberg, Germany; #RH961CRP01HR), intraassay coefficient of variation (CV) 3.8%, and interassay CV 5.2%. Adiponectin (ALPCO Immunoassays, Salem, NH; #47-ADPHU-E01), intraassay CV between 5.1% and 9.8% for the different multimeres and interassay CV between 4.8% and 6.5%. Fetuin-A (BioVendor, Heidelberg, Germany; #RD191037100), intraassay CV 4.9% and interassay CV 5.7%. Transforming growth factor beta1 (TGF-β1) ELISA kits were purchased from Biovendor and used according to the manufacturer's protocol. Samples were measured in duplicate. The intra- and interassay CVs for the ELISA were 5.1% and 8.4%, respectively. Soluble human intermediate filament protein fragments of cytokeratin 18 were measured with the M30-Apoptosense ELISA from Peviva AB (Bromma, Sweden) in strict accordance with the manufacturer's protocol. Intraassay coefficient of variation was 3.1% and interassay coefficient of variation was 5.2% in a pooled control plasma sample from our laboratory.

Sample Size and Statistical Analysis.

The B-SMART study had the primary goal to compare weight loss with reduced fat and reduced carbohydrate hypocaloric diets. Overall, we expected a 5%-10% weight loss from baseline within 6 months with a 3% greater body weight reduction from baseline in the reduced carbohydrate compared with the reduced fat group. The secondary goal was to examine associated cardiovascular and metabolic markers. To allow for a meaningful analysis of these secondary goals, we included enough patients to have at least 50 patients in each group complete the 6-month weight loss phase. With 50 patients in each group, the study had a 95% statistical power to show a 3% difference in weight loss from baseline between groups (alpha = 0.05, two-sided). For changes in body weight, measured every month during diet, we additionally performed an intention to treat with last observation carried forward analysis. Because magnetic resonance imaging and spectroscopy was only conducted in patients finishing the 6-month weight loss phase, the statistical analysis is restricted to completers. No interim analysis was planned.

Differences in the response to dietary interventions were analyzed using unpaired t tests. For subgroup analysis at baseline, we applied one-way analysis of variance (ANOVA) with Bonferroni post-hoc tests. To test for interactions between diet groups over the 6-month period (diet × time), we used a two-way ANOVA for repeated measures. Univariate associations between parameters were tested using Pearson's correlation coefficient. All statistical analyses were performed with SPSS 18. Significance was accepted at P < 0.05. Unless otherwise stated, values are given as mean ± standard deviation (SD).

Results

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

Enrolment began in March 2007 and the study ended in June 2010. Of 170 randomized subjects, 102 completed the dietary intervention phase and were included in the statistical analysis (Fig. 1). Similar proportions of subjects in each group completed the study (65% in the reduced carbohydrate and 60% in the reduced fat group). In subjects not completing the study, the time to discontinuation was 3.1 ± 1.6 months in the reduced carbohydrate and 3.2 ± 1.4 months in the reduced fat group (P = not significant [n.s.]). Both groups were well matched for gender, age, body weight, body mass index, blood lipid profiles, glucose metabolism, and cardiorespiratory fitness. Table 1 shows baseline characteristics in both intervention groups separately for subjects with normal and elevated intrahepatic fat content.

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Figure 1. Patient disposition.

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Table 1. Clinical Characteristics of Subjects Randomized to Reduced Carbohydrate or Reduced Fat Diets and Subdivided by Intrahepatic Lipid Content
 Reduced CarbohydrateReduced Fat
Normal IHLHigh IHLNormal IHLHigh IHL
  • IHL: intrahepatic lipids, HOMA: homeostasis model assessment index, C-ISI: composite insulin sensitivity index, ALT: alanine aminotransferase, AST: aspartate aminotransferase, hs-CRP: highly sensitive c-reactive protein, TGF-β1: transforming growth factor beta 1.

  • *

    P < 0.05,

  • **

    P < 0.01: significantly different between normal and high IHL within the same diet group, no significant differences were detected between diets within the same IHL subgroup, all analyzed by one-way ANOVA with Bonferroni post-hoc tests, data are mean ± SD.

  • Subjects with abdominal obesity (waist circumference: men ≥102 cm, women ≥88 cm).21

  • Subjects with impaired glucose tolerance (2-hour value in the OGTT ≥140 mg/dL).23

n (men/women)32 (3/29)20 (5/15)23 (2/21)27 (8/19)
Age, yrs42 ± 945 ± 844 ± 946 ± 9
Bodyweight, kg89 ± 1299 ± 1788 ± 1496 ± 19
Body mass index, kg/m232.0 ± 3.335.6 ± 4.7*31.9 ± 3.933.9 ± 3
Waist circumference, cm97.7 ± 8.7107.6 ± 13.4*97.2 ± 10.0105.4 ± 11.8*
Abdominal obese (men/women), n2/214/141/165/17
Blood lipids    
 Triglycerides, mmol/L1.01 ± 0.391.36 ± 0.571.12 ± 0.531.27 ± 0.71
 Cholesterol, mmol/L4.7 ± 0.65.1 ± 0.74.9 ± 0.94.9 ± 1.0
 HDL, mmol/L1.4 ± 0.31.7 ± 1.11.6 ± 0.71.2 ± 0.3
 LDL, mmol/L2.8 ± 0.53.1 ± 0.83.1 ± 0.93.2 ± 0.9
 Rree fatty acids, mmol/L0.59 ± 0.180.73 ± 0.18*0.61 ± 0.190.61 ± 0.18
Glucose metabolism    
 Fasting insulin, μU/mL6.0 ± 3.59.4 ± 6.3*6.3 ± 3.37.4 ± 4.1
 Fasting glucose, mg/dL91.5 ± 17.195.5 ± 23.394.1 ± 8.295.9 ± 7.8
 HOMA, arbitrary unit1.3 ± 0.92.3 ± 1.9*1.5 ± 0.81.8 ± 1.0
 C-ISI, arbitrary unit6.1 ± 2.64.2 ± 1.8*5.9 ± 2.44.7 ± 1.9
 Hepatic insulin resistance969 ± 5351,670 ± 1,379*1,156 ± 7681,813 ± 1,405*
 Insulinogenic index, μUINS/gGLU85 ± 4598 ± 6583 ± 45108 ± 66
 Impaired glucose tolerance,n12131114
Biochemical parameters    
 ALT, U/L19.3 ± 8.424 ± 9.621.6 ± 9.334.8 ± 17.4*
 AST, U/L26.7 ± 11.924.6 ± 6.426.8 ± 17.737.1 ± 24.8
 Total adiponectin, μg/mL6.3 ± 2.25.7 ± 1.87.1 ± 3.65.4 ± 2.2
 Adiponectin (HMW), μg/mL3.1 ± 1.62.8 ± 1.33.7 ± 3.22.4 ± 1.4
 Fetuin-A, ng/mL250 ± 64247 ± 91230 ± 68269 ± 76
 hs-CRP, μg/mL1.3 ± 1.11.7 ± 0.91.3 ± 0.61.9 ± 1.3
 Cytokeratin-18 fragments, U/L126 ± 54129 ± 52119 ± 43134 ± 46
 TGF-β1, ng/mL1.23 ± 1.971.55 ± 2.231.04 ± 1.381.79 ± 2.06
Abdominal adipose tissue    
 Intrahepatic lipids, %2.9 ± 1.114.9 ± 9.8**3.0 ± 1.115.3 ± 10.1**
 Visceral fat mass, kg1.3 ± 0.62.5 ± 1.4**1.4 ± 0.72.4 ± 1.0**
 Subcutaneous fat mass, kg9.4 ± 2.811.3 ± 3.99.5 ± 3.110.5 ± 3.5
 Cardiorespiratory fitness    
 VO2max, ml/min/kg22.9 ± 0.921.3 ± 0.823.1 ± 1.021.4 ± 0.9

As shown in Fig. 2, energy intake was reduced with both dietary interventions. The estimated reduction in energy intake was numerically but not significantly greater in the reduced carbohydrate (−25%) compared with the reduced fat group (−21%). Figure 2 also illustrates changes in fat and carbohydrate ingestion for both groups during dietary intervention. In the reduced fat group, fat ingestion was decreased (−50%), whereas carbohydrate (−8%) and protein ingestion (−3%) remained largely unchanged. In the reduced carbohydrate group we observed a moderate increase in protein intake (9%) in addition to the carbohydrate (−54%) and fat (−9%) changes. Figure 3 shows saturated fatty acid, and n-3 and n-6 polyunsaturated fatty acid ingestion before and on diet. Saturated and n-6 polyunsaturated fatty acids were ingested less during diet with reduced fat compared to reduced carbohydrate diet.

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Figure 2. Energy and macronutrient intake. Changes in energy and macronutrient intake during the 6-month study in response to the dietary protocols randomly assigned to subjects (triangles: reduced carbohydrate diet, circles reduced fat diet). Data are mean ± SEM, *P < 0.001 significantly different between reduced carbohydrate and reduced fat diet.

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Figure 3. Fatty acid intake. Amount of consumed saturated, polyunsaturated n-3 (n-3), and polyunsaturated n-6 (n-6) dietary fatty acids before and at the end of 6 months of reduced carbohydrate or reduced fat diet. Data are mean ± SEM, *P < 0.05, **P < 0.01 significantly different between baseline and after diet. §Significant time × group interaction for diet groups analyzed by two-way ANOVA. No significant differences were observed between groups at baseline.

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In an intention to treat analysis with last observation carried forward analysis, weight loss tended to be greater with reduced carbohydrates (95.0 ± 15.9 to 89.5 ± 15.9 kg; P < 0.001) compared to reduced fat diet (93.6 ± 17.3 to 89.4 ± 17.0 kg; P < 0.001) (P = 0.078 between interventions). In completers, weight loss after 6 months was similar in subjects assigned to a reduced carbohydrate compared to subjects assigned to a reduced fat diet (Table 2). The time course of weight loss during the intervention was similar in both groups (Fig. 4). During 6 months caloric restriction, intrahepatic fat decreased from 7.6 ± 8.2 to 4 ± 4.6% (−47%) in the reduced carbohydrate and from 9.6 ± 9.8 to 5.6 ± 6.4% (−42%) in the reduced fat group, (P = n.s. between interventions, P < 0.001 compared with baseline for both). Abdominal visceral fat mass decreased from 1.8 ± 1.1 to 1.4 ± 0.9 kg (−22%) with reduced carbohydrate and from 1.9 ± 1 to 1.5 ± 0.9 kg (−21%) with reduced fat diet (P = n.s. between interventions, P < 0.001 compared with baseline for both). Abdominal subcutaneous adipose tissue decreased from 10.2 ± 3.1 to 8.7 ± 3 kg (−15%) with reduced carbohydrate and from 10.1 ± 3.3 to 8.6 ± 2.9 kg (−15%) with reduced fat (P = n.s. between interventions, P < 0.001 compared with baseline for both). Total body fat% estimated by bioimpedance analysis decreased similarly for both interventions (reduced carbohydrate: 35.6 ± 6.4% before and 33.2 ± 7.2% after, P < 0.01; reduced fat: 36.4 ± 5.5% before and 33.5 ± 5.1% after, P < 0.001). Cardiorespiratory fitness expressed as maximum oxygen uptake did not change with diet in either group.

Table 2. Changes for Anthropometric and Biochemical Parameters After 6-Month Diet Compared to Baseline
 Reduced CarbohydratesReduced FatP-Value Diet × Time Interaction
  • ALT: alanine aminotransferase, AST: aspartate aminotransferase, hs-CRP: highly sensitive c-reactive protein, TGF-β1: transforming growth factor beta 1.

  • #

    P < 0.10;

  • *

    P < 0.05;

  • **

    P < 0.01: significantly different between baseline and follow-up within a diet analyzed with Student's t tests for paired samples; P-value in third column = diet x time interaction for reduced carbohydrate vs. reduced fat diet over the 6-month diet by two-way ANOVA. Data are mean ± SEM.

n5250 
Δ body weight, kg−7.5 ± 0.6**−6.5 ± 0.7**0.25
Δ body mass index, kg/m2−2.7 ± 0.2**−2.4 ± 0.2**0.34
Δ waist circumference, cm−6.2 ± 0.6**−5.6 ± 0.7**0.56
Blood lipids   
 Δ triglycerides, mmol/L−0.19 ± 0.06**−0.14 ± 0.08*0.53
 Δ free fatty acids, mmol/L0.03 ± 0.03−0.01 ± 0.030.62
 Δ total cholesterol, mmol/L−0.08 ± 0.09−0.45 ± 0.11**0.009
 Δ LDL, mmol/L−0.04 ± 0.07−0.33 ± 0.08**0.006
 Δ HDL, mmol/L−0.09 ± 0.1−0.1 ± 0.070.98
Glucose metabolism   
 Δ fasting insulin, μU/mL−2.6 ± 0.6**−1.8 ± 0.4**0.27
 Δ fasting glucose, mg/dL−6.1 ± 1.3**−5.2 ± 1.7**0.67
 Δ HOMA, arbitrary unit−0.61 ± 0.18**−0.43 ± 0.11**0.39
Biochemical parameters   
 Δ ALT, U/L−2.5 ± 1.3#−6.1 ± 2.2**0.14
 Δ AST, U/L−3.7 ± 1.7*−5.1 ± 2.7*0.42
 Δ adiponectin (total), μg/mL0.77 ± 0.22**0.34 ± 0.19#0.15
 Δ adiponectin (HMW), μg/mL0.68 ± 0.15**0.33 ± 0.12**0.08
 Δ fetuin-A, ng/mL−31 ± 12*−36 ± 11**0.76
 Δ hs-CRP, μg/mL−0.34 ± 0.19#−0.51 ± 0.16**0.47
 Δ cytokeratin-18 fragments, U/L−0.03 ± 4.2−1.5 ± 3.80.52
 Δ TGF-β1, ng/mL−0.89 ± 0.26**−0.37 ± 0.260.17
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Figure 4. Body weight changes. Changes in body weight in response to a hypocaloric diet reduced either in carbohydrates (triangles) or fat (circles) during the 6-month study. Note that body weight reduction was nearly identical between groups.

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We observed similar changes in fasting insulin and glucose concentration as well as HOMA index in both intervention groups (Table 2). Triglycerides, free fatty acids, and high-density lipoprotein (HDL)-cholesterol concentrations were also not significantly different after diet among groups. However, total- and high-density lipoprotein (LDL)-cholesterol decreased more in subjects on a reduced fat diet compared to the reduced carbohydrate diet (Table 2). Liver aminotransferases decreased numerically but not statistically more in the reduced fat group. Adiponectin, fetuin-A, and high sensitive CRP measurements showed similar response in both dietary groups (Table 2).

We next analyzed subjects according to their intrahepatic fat content at baseline. We observed a greater intrahepatic fat loss along with a greater reduction of ALT by trend for subgroups with high initial IHL content, irrespective of dietary macronutrient composition (Fig. 5, first and second panels). Furthermore, subjects with high baseline IHL also showed a better relative reduction in IHL (−50 ± 22% versus −31 ± 36 on reduced carbohydrate; −44 ± 20 versus −23 ± 49% on reduced fat; P < 0.05 for both). In contrast, similar responses occurred for visceral fat mass, insulin sensitivity (Fig. 5, third panel; Fig. 6, first panel) as well as fasting insulin, glucose, and HOMA index between subgroups.

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Figure 5. Response to diets in subjects with low and high IHL content. Changes in intrahepatic lipid content (IHL), alanine aminotransferase (ALT), and visceral adipose tissue (AT) after the 6-month study. Subjects were stratified according to low (<5.6%) and high (>5.6%) baseline IHL. Data are mean ± SEM, *P < 0.05, **P < 0.01 significant differences within subgroups from baseline to follow-up analyzed by Student's paired t test, and significant time × group interactions between low and high IHL subgroups analyzed by two-way ANOVA, #P < 0.10 different by trend. No significant changes were observed for subgroups with low or high IHL between diets.

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Figure 6. Changes in insulin sensitivity in subjects with low and high IHL content. Changes in whole body insulin sensitivity (composite insulin sensitivity index [C-ISI]), hepatic insulin resistance, and pancreatic insulin secretion (insulinogenic index [IGIS]) after the 6-month study. Subjects were stratified according to low (<5.6%) and high (>5.6%) baseline IHL. Data are mean ± SEM, *P < 0.05, **P < 0.01 significant differences within subgroups from baseline to follow up analyzed by Student's paired t test, and significant time × group interactions between low and high IHL subgroups analyzed by two-way ANOVA, #P < 0.10 different by trend. No significant changes were observed for subgroups with low or high IHL between diets.

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To assess influences of insulin sensitivity on the response to macronutrient composition, we stratified subjects into an insulin-sensitive and an insulin-resistant group using a predefined C-ISI cutoff of 4.5.28 The insulin-resistant group was heavier (95.9 ± 15.8 versus 90.1 ± 15.9 kg; P = 0.072) and showed higher IHL values (12.5 ± 11.9 versus 5.8 ± 6.3%; P < 0.01) compared with the insulin-sensitive group. Insulin-resistant subjects lost 7.9 ± 4.6 kg on the reduced carbohydrate and 7.8 ± 4.9 kg on the reduced fat diet (n.s.). Insulin sensitive subjects lost 7.2 ± 4.2 kg on the reduced carbohydrate and 5.2 ± 4.1 kg on the reduced fat diet (P = 0.075). IHL in insulin-resistant subjects decreased 6% ± 6.7% with reduced carbohydrates and 4.9% ± 4.8% with reduced fat (n.s.). In insulin-sensitive subjects, IHL decreased 2.1% ± 2.3% with the reduced carbohydrate and 3.3% ± 5.1% (n.s.) with the reduced fat diet.

When stratifying subjects for impaired glucose tolerance before diet those with impaired glucose tolerance had similar bodyweight (94.8 ± 15.8 versus 92.5 ± 13.7 kg), and higher IHL values (10.7 ± 9.4 versus 7.1 ± 6.2%; P = 0.05) compared with subjects with normal glucose tolerance. Bodyweight loss was similar in both groups regardless of the dietary intervention. IHL loss was not related to diet or glucose tolerance state (impaired glucose tolerance: reduced carbohydrates: Δ −4.8 ± 6.2%; reduced fat: Δ −4.0 ± 5.9%, both P < 0.01; normal glucose tolerance: reduced carbohydrates: Δ −2.4 ± 2.6%; reduced fat: Δ −3.2 ± 4.1%, both P < 0.01). Glucose tolerance improved only in subjects with impaired glucose tolerance regardless of diet.

Discussion

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

The main finding of our study is that IHL content decreased similarly in overweight and obese subjects assigned to moderately reduced carbohydrate or moderately reduced fat hypocaloric diets. The observation holds true for both subjects with low and subjects with elevated IHL content at baseline. Our findings provide insight in mechanisms regulating IHL in human subjects and may have a bearing on therapeutic decision-making.

Previous studies compared low-carbohydrate to low-fat hypocaloric diets. A meta-analysis including earlier trials revealed that low-carbohydrate diets appear to be at least as effective as low-fat diets in terms of weight loss.20 More recent trials showed advantages29 or no differences15 for reduced carbohydrate diets. However, most of these trials assessed changes in overall adiposity rather than fat distribution between adipose tissue depots and ectopic fat storage in the liver. The issue is relevant given the central role of intrahepatic fat in the pathogenesis of obesity-associated disease, such as insulin resistance and type 2 diabetes. Indeed, animal and human studies show that increasing dietary fat content predisposes to IHL accumulation and insulin resistance.13, 30

We observed virtually identical weight loss with reduced carbohydrate and reduced fat diets. Both groups adhered to their assigned interventions in terms of macronutrient content. Physical fitness is negatively correlated with IHL content.1 Dieticians reminded participants to keep physical activity constant throughout the study. Moreover, cardiorespiratory fitness did not change during either intervention. Thus, differences in fat distribution, lipoprotein metabolism, or glucose metabolism between interventions are mainly explained by macronutrient composition rather than differences in weight loss or physical fitness between groups. Abdominal visceral, abdominal subcutaneous, and IHL loss was similar with low-fat and low-carbohydrate diets. These observations suggest that over a 6-month period, success in losing visceral fat and IHL is primarily related to caloric restriction rather than macronutrient composition.

IHL is associated with metabolic disease including insulin resistance2, 4 independently of visceral fat.5, 6 Although the initial cellular signal in inducing hepatic lipid accumulation differs between excessive fat or carbohydrate ingestion, once insulin resistance develops, hyperinsulinemia promotes increased hepatic sterol regulatory element binding protein-1c (SREBP-1c) expression. SREBP-1c coordinately regulates transcription of key enzymes involved in lipogenesis.31 Moreover, insulin resistance in rodents and in human subjects changes the disposition of ingested carbohydrate away from skeletal muscle glycogen synthesis towards hepatic de novo lipogenesis.32 Thus, the beneficial effects of hypocaloric diets on IHL fat could be mediated in part through improved peripheral insulin resistance. Yet, whereas insulin-resistant subjects tended to lose more IHL compared with insulin-sensitive subjects, we did not observe a relevant interaction between insulin sensitivity and the response to macronutrient composition of the diet. We obtained similar results when we stratified our subjects for glucose tolerance. A recent clinical study in obese insulin-resistance subjects reported similar reductions in body weight and IHL after 11 weeks on a hypocaloric diet with either high or low carbohydrate content. However, the low carbohydrate diet was superior in improving hepatic insulin sensitivity.15 In our subjects an OGTT-derived index of hepatic insulin resistance, which has to be interpreted with caution, showed no significant interaction between macronutrient composition and improvements in hepatic insulin sensitivity during the 6-month intervention.

Approximately half of our subjects had an IHL content >5.6%, a value reported as “the upper limit of normal” for IHL with an increased risk of hepatic steatosis.33 Subjects exceeding this cutoff showed an ≈7-fold greater absolute reduction in IHL compared with subjects with normal IHL content. Remarkably, subjects with normal and with elevated IHL content showed similar improvements in glucose metabolism, even though the absolute reduction in IHL was much greater in the latter group. The observation may suggest that the improvement in glucose metabolism with dietary weight loss is not directly related to the quantity of mobilized IHL. The dynamics of fat mobilization may be more important in this regard. Possibly other mechanisms, such as reductions in abdominal visceral or subcutaneous adipose tissue, mediated the beneficial effect of dietary weight loss on glucose metabolism.34 Indeed, subjects with normal and with elevated IHL showed similar reductions in abdominal visceral adipose tissue.

We observed larger reductions in total- and LDL-cholesterol in the reduced fat compared with the reduced carbohydrate group. Yet triglycerides, HDL-cholesterol, and measures of insulin resistance responded similarly or improved more with reduced carbohydrate diets.20 Similar to another dietary intervention study,29 circulating total and high molecular weight adiponectin tended to increase more with reduced carbohydrate diet. These findings fuel the concern that macronutrient composition of hypocaloric diets could adversely affect cardiovascular and metabolic risk. However, the issue can only be sufficiently addressed in long-term studies with hard cardiovascular endpoints.

TGF-β1, which plays a critical role in the pathogenesis of liver fibrosis and hepatocellular carcinoma,35 was reduced 2-fold after reduced carbohydrate diet compared to reduced fat diet, which could indicate a potential advantage of carbohydrate-restricted diets on fibrogenesis. In our subjects, cytokeratin-18 fragments, which are markers of hepatocyte apoptosis,36 were in the normal range and did not change with either diet. The observation suggests that in most subjects obesity-associated IHL accumulation was not yet associated with ongoing hepatocyte apoptosis. Our results cannot be simply extrapolated to patients with more advanced liver disease.

The main limitation of our study is that a 6-month weight loss period may not be sufficiently long to observe influences of macronutrient content on IHL. An influence of macronutrient composition could be unmasked during weight stabilization or regain. Furthermore, our study does not exclude that more extreme changes in dietary fat and/or carbohydrate affect IHL in a weight-independent fashion. However, we suggest that the changes in macronutrient content in our study reflect typical Western dietary patterns. We controlled for fatty acid composition, which may affect IHL deposition. For example, transgenic restoration of omega-3 fatty acid tissue levels improved hepatic insulin sensitivity in mice fed a high-fat diet.37 We observed no changes for n-3 fatty acids during either diet. A reduction in n-6 fatty acid and more so saturated fatty acid ingestion in the reduced fat diet was unavoidable. Because we did not measure physical activity throughout the study, we cannot completely rule out an influence of an unrecognized change in physical activity on our outcomes.

We conclude that over a 6-month period, caloric restriction through reductions in dietary fat or carbohydrates achieved similar reduction in IHL content in nondiabetic overweight or obese subjects. Patients with elevated intrahepatic fat content showed a particularly large response. The improvement in IHL content was associated with a reduction in ALT. Thus, both types of diets are similarly useful in the prevention of obesity-associated hepatic fat accumulation, which is a major risk factor for metabolic disease, such as insulin resistance and type 2 diabetes, and nonalcoholic steatohepatitis.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

We thank Gritt Stoffels, Anke Strauss, and Elke Nickel-Sczcech for technical help with patient recruitment and study procedures. We also thank Andreas Busjahn for statistical advice.

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  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information
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Supporting Information

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

Additional Supporting Information may be found in the online version of this article.

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