![]() |
|
|
German Institute of Human Nutrition, Potsdam-Rehbruecke, Group of Energy Metabolism, D-14558 Nuthetal, Germany
2To whom correspondence should be addressed. E-mail: klaus{at}mail.dife.de.
| ABSTRACT |
|---|
|
|
|---|
KEY WORDS: low carbohydrate diets energy metabolism macronutrients indirect calorimetry
Obesity is increasing worldwide and dietary fat is considered to be one of the important environmental factors contributing to the obesity epidemic (1,2). Fat content is one of the main factors influencing the energy density of diets, and an increase in energy density was shown to result in passive overconsumption in humans, which in turn promotes the development of obesity (3,4). However, the role of dietary fat in human obesity is also subject to debate (5). Animal studies demonstrated the development of obesity and diabetes-related traits in certain strains of rats and mice consuming high-fat diets ad libitum. One widely used model for obesity studies is the C57BL/6 mouse, especially in an exploration of the interplay between genetic background and environmental factors (6). C57BL/6 mice are highly susceptible to the development of diet-induced obesity (DIO)3 ; they are also prone to develop diabetes-related traits when DIO is manifest (7,8). When weaned onto a high-fat, high-sucrose diet, they develop hyperglycemia and hyperinsulinemia, for which fat was found to be the important stimulus, independent of energy intake (911). Although it is clear from these studies that dietary fat is an important factor, little attention has been paid to the role of the protein:CHO ratio and its interaction with dietary fat in the development of obesity and diabetes-related traits. In addition, it is still not well established whether hyperphagia alone or also reduced energy expenditure (EE) causes the development of obesity in rats and mice fed high fat diets. Many experimental approaches suffer from the problem that not only is dietary fat content changed, but also other dietary components compared with standard diets. Most commercial suppliers use different sources of macronutrients for standard and high-fat diets; this affects diet digestibility and also alters the macronutrient quality in addition to quantity. A further problem is that many commercial high-fat diets have a reduced proportion of energy as protein. This could result in increased food intake to ensure appropriate amino acid supply. The occurrence of hyperphagia under these conditions could thus be related to the protein rather than to the fat content of the diet. To examine in detail the role of the different macronutrients in the development of obesity, it is therefore necessary to employ diets with identical macronutrient sources but varied macronutrient ratios. Therefore, the aim of this study was to investigate the effect of 2 defined, semisynthetic, high-fat, isoenergetic diets with different protein:CHO ratios on the development of obesity, energy metabolism, and glucose homeostasis in C57BL/6J mice compared with a low-fat diet composed of the same ingredients.
| MATERIALS AND METHODS |
|---|
|
|
|---|
Diets. During the intervention mice were fed purified diets with different macronutrient compositions (Table 1). Dietary components were as described previously (12), and diets were freely available in pellet form. The metabolizable energy density of the diets was calculated according to the following macronutrient energy contents (kJ/g): casein, 15.7; carbohydrate, 16; and fat, 38. The 2 high-fat diets, low- and high-carbohydrate (LC and HC, respectively) did not differ in fat content and energy density. The control diet was a low-fat diet with CHO content (energy %) matched to the HC-diet.
|
Insulin tolerance test. Insulin sensitivity was tested after 70 d of dietary intervention by i.p. injection of insulin (Actrapid, 1.5 U/g body wt), as described previously (14). Glucose concentration was determined in blood from the tail at 0, 15, 30, and 60 min after insulin injection.
Energy expenditure. EE was measured by indirect calorimetry in individual mice, as described earlier (1315), using an open respirometric system (gas analyzers: Magnos 16 and Uras 14, Hartmann & Braun). Measurements were performed during wk 8 or 9 of the intervention. Mice were unrestrained and had free access to their respective diets and water during the measurement. The respiratory quotient (RQ = VCO2:VO2) and EE (kJ/d) were calculated as described previously (16). Measurements were performed at 6-min intervals over a 23-h period. For resting energy expenditure (REE), the mean of the 10 lowest individual measurements for each mouse was used.
Statistical analysis. Results are given as means ± SEM. Statistical significance was assessed by ANOVA (factorial or repeated measurements when appropriate) followed by least significant difference post-hoc test (Statview 4.5 for Apple Macintosh, Abacus Concepts). Differences were considered significant at P < 0.05.
| RESULTS |
|---|
|
|
|---|
|
|
|
EE was measured after 89 wk of dietary intervention when body-weight differences were already established. Weight-specific EE did not differ among the groups (Table 2). The daily pattern of EE, which reflects activity patterns, was also similar among the groups (Fig. 3A). Total energy expenditure (TEE) over 24 h was greater in the HC group than in the other groups, due exclusively to greater body weight. When normalized for body weight, TEE as well as REE did not differ among the groups (Table 2). The respiratory quotient (RQ) is indicative of the overall substrate oxidation; i.e., lipid oxidation results in an RQ close to 0.7, whereas carbohydrate oxidation has an RQ of 1.0 (17). The RQ was similar in all groups during daytime (i.e., inactivity period) but differed among the groups at night, i.e., during the activity and feeding period (Fig. 3B). In the control group, nighttime RQ values were close to 1, reflecting almost exclusive carbohydrate oxidation (Table 2). The lowest RQ values (i.e., highest fat oxidation rates) were in the LC group. They were greater in the HC group, and in this group, the nighttime RQ was less than that of controls (Table 2).
|
|
| DISCUSSION |
|---|
|
|
|---|
Certain diets promote dietary hyperphagia in humans and also in rodent models (18,19). In human studies, it was reported that an increase in the dietary fat content (i.e., increased energy density) led to so-called passive overconsumption because the amount of food eaten did not change (4,20). However, it was shown in rats that high-fat diets can also enhance daily energy intake and weight gain at least in part via a mechanism that is unrelated to energy density (21). In the present study, passive overconsumption was apparent in the LC group, which consumed the same amount of food as the control group. In the HC group, on the other hand, early active hyperphagia was evident in addition to the continuous passive overconsumption. Interestingly, this active hyperphagia was transient and disappeared almost completely after
3 wk, confirming earlier studies in rats (22,23). Thus, it is clear that it is not high fat alone but rather the combination of high fat with high CHO that leads to this transient overfeeding. Human studies also suggest that energy density affects food intake only in the short term, whereas in the long term, these effects are modulated and compensation occurs (3). The mechanisms leading to the observed initial hyperphagia with consumption of a high-fat, high-CHO diet are not clear. This hyperphagia can be attributed to increased palatability, possibly related to distinct sensory properties of fat (4). Because this has been observed in humans as well as in rats and mice, it is reasonable to assume the existence of common physiological mechanisms that underlie this active overfeeding.
It is interesting to note that even in the long term, the mice did not compensate for the changes in dietary energy density irrespective of the diet composition. It remains to be established whether this is unique to the strain of mice used or a general phenomenon. Using another mouse strain (FVB/N mice), we also found no compensation in food intake when mice were fed a macronutrient choice diet compared with a standard rodent diet. However, unlike the C57BL/6J mice used here, FVB/N mice did not become obese despite an increased energy intake, thus indicating a decreased energy efficiency (14).
Low-CHO (high-fat) diets have recently gained attention in the treatment of obesity (24,25). Although such diets have been popular for a long time, only in the past few years have randomized trials evaluated the long-term efficacy of such diets. The weight-reducing properties of such diets were similar to those of conventional studies (2628); i.e., the weight-reducing effect of low-CHO diets is due mainly to a decreased energy intake, possibly caused by the higher satiating capacity of protein (25). Nevertheless, it was proposed that part of the weight-reducing effect of a high-fat, high-protein diet could be due to increased diet-induced thermogenesis caused by the high protein content (29). The present study does not support this hypothesis, at least not in the long term. After several weeks of feeding, EE did not differ among the groups and overall energy intake could explain >80% of the differences in final body weight. This strongly suggests that long-term body-weight gain is determined mainly by energy intake, irrespective of the macronutrient composition. In a previous study, we observed an increase in nighttime oxygen consumption in rats fed high-protein diets for 8 wk, but there was no effect on TEE. Interestingly, net fat oxidation increased with higher amounts of dietary protein although the dietary fat content was similar (16). In the present study, RQ was significantly reduced in the LC group compared with the HC group, which is also suggestive of an increased fat oxidation rate.
Human intervention trials suggest that weight-reducing diets with increased protein content may have a more favorable health outcome than similar low-protein diets in the long term (3032). Layman and colleagues (31) demonstrated that consumption of a diet with increased protein and a reduced CHO:protein ratio stabilized blood glucose during nonabsorptive periods and reduced the postprandial insulin response. It was suggested that weight-loss diets with decreased CHO and increased protein levels provide metabolic advantages, possibly due to the unique effects of leucine on muscle protein synthesis and insulin signaling (33). From the present study, it becomes clear that even with ad libitum consumption, an increase in protein:CHO ratio in a high-fat diet beneficially affects glucose homeostasis; i.e., mice fed high-protein diets (LC group) had lower nonfasting glucose levels and improved insulin sensitivity compared with the HC group. It is somewhat surprising that control mice also were insulin resistant; however, it should be noted that the mice were
1 y old at the end of the experiments, making it possible that this was age related. Because the control and HC diets had similar high-protein contents, the improvement in insulin sensitivity in mice consuming the HC diet is most probably due to the decreased CHO content.
This study shows that increasing the protein:CHO ratio in a high-fat diet delayed but did not prevent development of adiposity in C57BL/6J mice. Obesity development was due to passive overconsumption of energy and was further worsened by an initial active hyperphagia when a high-fat, high-CHO diet was fed. However, an increase in the protein:CHO ratio in a high-fat diet improved glucose homeostasis, indicating that a combination of high fat and high CHO is responsible for the development of some of the traits related to metabolic syndrome in mice. Thus, the detrimental health effects of a high-fat diet cannot be attributed to fat alone; rather, they result from an interaction of the macronutrients. Further studies are warranted to assess health effects that relate not only to macronutrient quantities but also to the quality of the different macronutrients.
| ACKNOWLEDGMENTS |
|---|
| FOOTNOTES |
|---|
3 Abbreviations used: CHO, carbohydrates; DIO, diet induced obesity; HC, high carbohydrate; LC, low carbohydrate; EE, energy expenditure; REE, resting energy expenditure; QMR, quantitative magnetic resonance; RQ, respiratory quotient; TEE, total energy expenditure. ![]()
Manuscript received 22 February 2005. Initial review completed 9 April 2005. Revision accepted 20 May 2005.
| LITERATURE CITED |
|---|
|
|
|---|
1. Peters, J. C. (2003) Dietary fat and body weight control. Lipids 38:123-127.[Medline]
2. Bray, G. A., Paeratakul, S. & Popkin, B. M. (2004) Dietary fat and obesity: a review of animal, clinical and epidemiological studies. Physiol. Behav. 83:549-555.[Medline]
3. Westerterp-Plantenga, M. S. (2004) Effects of energy density of daily food intake on long-term energy intake. Physiol. Behav. 81:765-771.[Medline]
4. Stubbs, R. J. & Whybrow, S. (2004) Energy density, diet composition and palatability: influences on overall food energy intake in humans. Physiol. Behav. 81:755-764.[Medline]
5. Willett, W. C. (2002) Dietary fat plays a major role in obesity: no. Obes. Rev. 3:59-68.[Medline]
6. Collins, S., Martin, T. L., Surwit, R. S. & Robidoux, J. (2004) Genetic vulnerability to diet-induced obesity in the C57BL/6J mouse: physiological and molecular characteristics. Physiol. Behav. 8:243-248.
7. Kobayashi, M., Ohno, T., Tsuchiya, T. & Horio, F. J. (2004) Characterization of diabetes-related traits in MSM and JF1 mice on high-fat diet. Nutr. Biochem. 15:614-621.
8. de Fourmestraux, V., Neubauer, H., Poussin, C., Farmer, P., Falquet, L., Burcelin, R., Delorenzi, M. & Thorens, B. (2004) Transcript profiling suggests that differential metabolic adaptation of mice to a high fat diet is associated with changes in liver to muscle lipid fluxes. J. Biol. Chem. 279:50743-50753.
9. Surwit, R. S., Feinglos, M. N., Rodin, J., Sutherland, A., Petro, A. E., Opara, E. C., Kuhn, C. M. & Rebuffe-Scrive, M. (1995) Differential effects of fat and sucrose on the development of obesity and diabetes in C57BL/6J and A/J mice. Metabolism 44:645-651.[Medline]
10. Black, B. L., Croom, J., Eisen, E. J., Petro, A. E., Edwards, C. L. & Surwit, R. S. (1998) Differential effects of fat and sucrose on body composition in A/J and C57BL/6 mice. Metabolism 47:1354-1359.[Medline]
11. Petro, A. E., Cotter, J., Cooper, D. A., Peters, J. C., Surwit, S. J. & Surwit, R. S. (2004) Fat, carbohydrate, and calories in the development of diabetes and obesity in the C57BL/6J mouse. Metabolism 53:454-457.[Medline]
12. Daenzer, M., Ortmann, S., Klaus, S. & Metges, C. C. (2002) Prenatal high protein exposure decreased energy expenditure and increased adiposity in young rats. J. Nutr. 132:142-144.
13. Klaus, S., Rudolph, B., Dohrmann, C. & Wehr, R. (2005) Expression of uncoupling protein 1 in skeletal muscle decreases muscle energy efficiency and affects thermoregulation and substrate oxidation. Physiol. Genomics 21:193-200.
14. Ortmann, S., Prinzler, J. & Klaus, S. (2003) Self-selected macronutrient diet affects energy and glucose metabolism in brown fat-ablated mice. Obes. Res. 11:1536-1544.[Medline]
15. Ortmann, S., Kampe, J., Gossel, M., Bickel, M., Geisen, K., Jähne, G., Lang, H. J. & Klaus, S. (2004) The novel anti-obesic HMR1426 reduces food intake without affecting energy expenditure in rats. Obes. Res. 12:1290-1297.[Medline]
16. Petzke, K. J., Friedrich, M., Metges, C. C. & Klaus, S. (2004) Long-term dietary high protein intake up-regulates tissue specific gene expression of uncoupling proteins 1 and 2 in rats. Eur. J. Nutr. DOI:10.1007/s00394004-05454 [Epub ahead of print].
17. Jequier, E., Acheson, K. & Schutz, Y. (1987) Assessment of energy expenditure and fuel utilization in man. Annu. Rev. Nutr. 7:187-208.[Medline]
18. Ramirez, I., Tordoff, M. G. & Friedman, M. I. (1989) Dietary hyperphagia and obesity: what causes them?. Physiol. Behav. 45:163-168.[Medline]
19. Warwick, Z. S. (1996) Probing the causes of high-fat diet hyperphagia: a mechanistic and behavioral dissection. Neurosci. Biobehav. Rev. 20:155-161.[Medline]
20. Prentice, A. M. (1998) Manipulation of dietary fat and energy density and subsequent effects on substrate flux and food intake. Am. J. Clin. Nutr. 67(suppl. 3):535S-541S.[Abstract]
21. Warwick, Z. S., Synowski, S. J. & Bell, K. R. (2002) Dietary fat content affects energy intake and weight gain independent of diet caloric density in rats. Physiol. Behav. 77:85-90.[Medline]
22. Naim, M., Brand, J. G., Kare, M. R. & Carpenter, R. G. (1985) Energy intake, weight gain and fat deposition in rats fed flavored, nutritionally controlled diets in a multichoice ("cafeteria") design. J. Nutr. 115:1447-1458.
23. Ramirez, I. (1991) High-fat diets stimulate transient hyperphagia whereas wet diets stimulate prolonged hyperphagia in Fischer rats. Physiol. Behav. 49:1223-1228.[Medline]
24. Acheson, K. J. (2004) Carbohydrate and weight control: where do we stand?. Curr. Opin. Clin. Nutr. Metab. Care 7:485-492.[Medline]
25. Astrup, A., Meinert Larsen, T. & Harper, A. (2004) Atkins and other low-carbohydrate diets: hoax or an effective tool for weight loss?. Lancet 364:897-899.[Medline]
26. Foster, G. D., Wyatt, H. R., Hill, J. O., McGuckin, B. G., Brill, C., Mohammed, B. S., Szapary, P. O., Rader, D. J., Edman, J. S. & Klein, S. (2003) A randomized trial of a low-carbohydrate diet for obesity. N. Engl. J. Med. 348:2082-2090.
27. Brinkworth, G. D., Noakes, M., Keogh, J. B., Luscombe, N. D., Wittert, G. A. & Clifton, P. M. (2004) Long-term effects of a high-protein, low-carbohydrate diet on weight control and cardiovascular risk markers in obese hyperinsulinemic subjects. Int. J. Obes. Relat. Metab. Disord. 28:661-670.[Medline]
28. Stern, L, Iqbal, N., Seshadri, P., Chicano, K. L., Daily, D. A., McGrory, J., Williams, M., Gracely, E. J. & Samaha, F. F. (2004) The effects of low-carbohydrate versus conventional weight loss diets in severely obese adults: one-year follow-up of a randomized trial. Ann. Intern. Med. 140:778-785.
29. Westerterp, K. R. (2004) Diet induced thermogenesis. Nutr. Metab. 1:5.
30. Layman, D. K., Shiue, H., Sather, C., Erickson, D. J. & Baum, J. (2003) Increased dietary protein modifies glucose and insulin homeostasis in adult women during weight loss. J. Nutr. 133:405-410.
31. Layman, D. K., Boileau, R. A., Erickson, D. J., Painter, J. E., Shiue, H., Sather, C. & Christou, D. D. (2003) A reduced ratio of dietary carbohydrate to protein improves body composition and blood lipid profiles during weight loss in adult women. J. Nutr. 133:411-417.
32. Brinkworth, G. D., Noakes, M., Parker, B., Foster, P. & Clifton, P. M. (2004) Long-term effects of advice to consume a high-protein, low-fat diet, rather than a conventional weight-loss diet, in obese adults with type 2 diabetes: one-year follow-up of a randomised trial. Diabetologia 47:1677-1686.[Medline]
33. Layman, D. K. (2004) Protein quantity and quality at levels above the RDA improves adult weight loss. J. Am. Coll. Nutr. 23(suppl. 6):631S-636S.
This article has been cited by other articles:
![]() |
Y. Katterle, S. Keipert, J. Hof, and S. Klaus Dissociation of obesity and insulin resistance in transgenic mice with skeletal muscle expression of uncoupling protein 1 Physiol Genomics, February 19, 2008; 32(3): 352 - 359. [Abstract] [Full Text] [PDF] |
||||
![]() |
V. Leray, B. Siliart, H. Dumon, L. Martin, R. Sergheraert, V. Biourge, and P. Nguyen Protein Intake Does Not Affect Insulin Sensitivity in Normal Weight Cats J. Nutr., July 1, 2006; 136(7): 2028S - 2030S. [Full Text] [PDF] |
||||
![]() |
D. K. Layman and D. A. Walker Potential Importance of Leucine in Treatment of Obesity and the Metabolic Syndrome J. Nutr., January 1, 2006; 136(1): 319S - 323S. [Abstract] [Full Text] [PDF] |
||||
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||