In adult animals and human subjects, body weight tends to remain within a relatively narrow range despite large day-to-day fluctuations in the amount of the food consumed. In spite of these observations, it has been noted that the incidence of obesity has increased worldwide. Prevalence studies in the Brazilian adult population have shown an epidemic increase in obesity, mostly among women from lower social strata (Instituto Nacional de Alimentação e Nutrição, 1991; Coitinho, Reference Coitinho1998; Florêncio, Reference Florêncio1998; Monteiro & Mondini, Reference Monteiro and Mondini1998). Although an improvement in economic conditions can partly explain such trends, other factors may also be important (Popkin & Bisgrove, Reference Popkin and Bisgrove1988).
Low dietary protein intake can be associated with hyperphagia (Colombo et al. Reference Colombo, Cervantes, Kokorovic, Pfister and Perritaz1992; White et al. Reference White, Dean and Martin1998), enhanced body fat content and plasma leptin levels (White et al. Reference White, Dean and Martin1998; Du et al. Reference Du, Higginbotham and White2000) and a number of adaptations, such as an enhanced BMR (Tulp et al. Reference Tulp, Krupp, Danforth and Horton1979), brown adipose tissue thermogenesis (Rothwell & Stock, Reference Rothwell and Stock1987) and lipogenesis of white adipose tissue (Heard & Turner, Reference Heard and Turner1967). Dramatic feeding behaviour and metabolic changes are also seen in lactation, as hyperphagia (Denis et al. Reference Denis, Williams and Vernon2003) and a decrease in BMR (Shetty, Reference Shetty1990), brown adipose tissue thermogenesis (Trayhurn, Reference Trayhurn1989) and lipogenesis of white adipose tissue (McNamara, Reference McNamara1995; Vernon & Pond, Reference Vernon and Pond1997), and act to meet the high energy demand for the production of milk.
The feeding pattern and metabolic changes verified in protein restriction and lactation correlate with equally profound alterations in the circulating levels of insulin and leptin (Vernon, Reference Vernon1989; Terada et al. Reference Terada, Yamakawa, Sugaya and Toyoda1998), two hormones involved in the regulation of food intake and energy expenditure, and might promote obesity. Therefore, in the present study, we evaluated whether protein restriction affected serum insulin and leptin levels and the role of these hormones on energy balance at peak lactation. To address this issue, we used lactating rats submitted to protein restriction during pregnancy and lactation, and examined the relationship between insulin and leptin levels and some predictory variables of obesity (energy intake and energy expenditure).
Materials and methods
Animals and diets
The present experiment followed the Brazilian College of Animal Experimentation adopted by the Federal University of Mato Grosso. Thirty-one female Wistar rats (90 d old) were supplied by the animal central care facility of the Federal University of Mato Grosso (Cuiabá, Brazil). Mating was performed by housing females with males overnight, and pregnancy was confirmed by the presence of sperm in vaginal smears. Virgin and pregnant females were separated at random and maintained from the first day of pregnancy until the 14th day of lactation with isocaloric diets containing 60 g protein/kg (low-protein diet) or 170 g protein/kg (control diet), as described in Table 1. Rats were divided in four groups on the first day of lactation: control non-lactating (CNL), control lactating (CL), low-protein non-lactating (LPNL) and low-protein lactating (LPL).
Composition (g/kg) of the normal and low-protein diets
† For the detailed composition, see Reeves et al. (Reference Reeves, Nielsen and Fahey1993).
The experimental period was from the first day until the 14th day of lactation, when the rats were given free access to food and water. They were kept under standard lighting conditions (12 h light–dark cycle; lights on 06.00 h) at a temperature of 24 ± 1°C. Food intake and body weight were monitored three times a week. Spontaneous delivery took place on day 22 of pregnancy, after which, at 3 d of age, large litters were reduced to eight pups, ensuring a standard litter size per mother.
Sample collection and analyses
At the end of the experimental period (day 14 of lactation), the rats were killed. Blood samples were collected, serum was obtained by centrifugation, and aliquots were used to measure serum glucose level by the oxidase–peroxidase method (Trinder, Reference Trinder1969), total serum protein by the biuret modified method (Wolfson et al. Reference Wolfson, Chon, Calvary and Ichiba1948) and serum albumin by the bromocresol green method (Doumas et al. Reference Doumas, Watson and Biggs1971).
Serum insulin concentration were determined by RIA using rat insulin as standard, 125I-labelled bovine insulin as the radioactive tracer and guinea-pig anti-porcine insulin serum as the antibody (Scott et al. Reference Scott, Atwater and Rojas1981). The intra-assay and interassay variations of this method are 8 % and 14 %, respectively. The processed detect rat serum insulin between 0·039 to 5·0 ng/ml.
Serum leptin concentrations were analysed by ELISA assay (Kits Cristal Chem. Inc., Chicago, IL, USA). The intra-assay and interassay precisions of the rat leptin ELISA kit were 5·4 % and 6·9 %, respectively. The ELISA kit has a minimum rat leptin detection level of 200 pg/ml and a measurable range of concentration of 200–12 800 pg/ml.
The physiological index of insulin resistance used was homeostasis model assessment of insulin resistance (HOMA-IR), assessed from fasting glucose and fasting insulin concentrations using the following formula:
![HOMA-IR = \,\,(fasting\,insulin\,[ng/ml])\,\%\,\,\,(fasting\,glucose\,[mg/dl])/22\cdot 5.](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20160321074942166-0144:S0007114507106863_eqnu1.gif?pub-status=live)
The retroperitoneal and gonadal white adipose tissue, and brown adipose tissue, was quickly removed to determine the fresh weight.
Measurements of carcass composition and energy intake
The carcasses were eviscerated, weighed and stored at − 20°C for posterior composition analysis. Carcass water was measured by oven-drying at 80°C until a constant weight was reached. By subtracting the dry from the wet carcass weight, body water was determined. Fat carcass was measured by extraction in petroleum ether using a Soxlet continuous fat extractor (Fanen, São Paulo, Brazil). Fat content was then calculated by subtracting the fat-free dry mass from the dry carcass weight. Ash content was estimated, following combustion at 550°C until constant weight. Protein content was determined by subtracting the water, fat and ash content from the wet carcass weight.
To calculate carcass energy and energy intake, we assumed the energy content of protein and carbohydrate to be 16·74 kJ/g and that of fat to be 37·7 kJ/g (Du et al. Reference Du, Higginbotham and White2000). To calculate the carcass composition at the beginning of lactation (initial carcass energy), we used data from female rats under similar dietary treatments and the same physiological status at day 1 of lactation. From the difference between the final carcass composition and the calculated initial carcass composition, we calculated the residual lipid balance, protein balance, energy balance, energy efficiency (ratio of energy gain to energy balance) and energy expenditure (difference between energy intake and energy balance).
Statistical analyses
The results are expressed as the means and their standard errors for the number of rats indicated. Initially, Levene's test for homogeneity of variance was used to check the fit of the data to the assumptions for parametric analysis of variance. When necessary, a Box–Cox transformation was used to correct variance heterogeneity or non-normality (Sokal & Rohlf, Reference Sokal and Rohlf1995). All data were subsequently analysed by two-way ANOVA (nutritional status and physiological status) followed by the Tukey–HSD test for individual differences between groups when necessary. The correlation coefficient was used to examine the relationship between serum leptin or insulin levels and some predictory variables of obesity.
In all comparisons, statistical significance was accepted at P ≤ 0·05. Statistical analysis was performed using the Statistic Software package (StatSoft, Inc., Tulsa, OK, USA).
Results
Biochemical and hormonal factors
At day 14 of lactation, serum total protein and glucose concentration did not differ between the groups. In both nutritional statuses, lactating rats had a lower albumin level than non-lactating rats (F 1,27 = 15·71, P < 0·001). Serum insulin was influenced by nutritional status (F 1,27 = 15·00, P < 0·001), but not by physiological status (F 1,27 = 3·27, P = 0·083) and had interaction between both statuses (F 1,27 = 26·55, P < 0·001). No difference was observed between the LPL and LPNL groups, and the serum insulin of CL rats was significantly higher than that of the LPL, LPNL and CNL groups (P < 0·01). The serum leptin concentration was influenced only by nutritional status (F 1,27 = 33·52, P < 0·001). An interaction was observed between the two effects (F 1,27 = 13·71, P < 0·001) in that results in the LPL and LPNL groups were similar, and values were lower in the CL group than in the CNL, LPL and LPNL groups (P < 0·01; Table 2). HOMA-IR was calculated and had a lower value in the LPL (1·57) than the CL (3·96; P = 0·02) rats.
Serum concentration of glucose, albumin, total protein, insulin and leptin of non-lactating and lactating groups of rats maintained with control (CNL, CL, respectively) or low-protein (LPNL, LPL, respectively) diets (Values are means and their standard errors for the number of rats indicated)
a,b,c Mean values within a row with unlike superscript letters were significantly different (Tukey HSD test; P ≤ 0·05).
Mean values were significantly different in relation to non-lactating rats; *** P < 0·001 (two-way ANOVA).
Body weight and food intake
Lactation significantly increased total food intake and consequently the total energy and protein intakes in both nutritional statuses. These values were, however, lower in LPL than CL rats (P < 0·001). When expressed per gram body weight, food intake did not differ between the LPL and LPNL rats but was greater in the CL group than the CNL group (P < 0·001; Table 3).
Absolute and relative food intake, total energy food intake and total protein intake, of non-lactating and lactating groups of rats maintained with control (CNL, CL, respectively) or low-protein (LPNL, LPL, respectively) diets (Values are means with their standard errors for the number of rats indicated)
a,b,c Means with unlike superscript letters were significantly different (Tukey HSD test; P ≤ 0·05).
The relationship between energy intake and serum insulin concentration, energy intake and leptin levels are shown in Fig. 1A and 1B, respectively. In lactating rats, there was a significant positive correlation between serum insulin level and energy intake (r = 0·82, P < 0·001) and a negative relationship between serum leptin concentration and energy intake (r = − 0·83, P < 0·001). These correlations were absent in non-lactating animals for serum insulin (r = –0·15, P = 0·606) and leptin (r = 0·04, P = 0·879) levels. When data for non-lactating and lactating rats were pooled, energy intake was directly correlated with serum insulin concentration (r = 0·44, P < 0·02) but not with serum leptin concentration (r = − 0·32, P < 0·09). Significant correlations were not observed when the groups were separated in the low-protein and control diet groups.
Correlation between energy intake and serum insulin levels (A), energy intake and serum leptin levels (B), energy expenditure and serum insulin concentration (C) and energy expenditure and serum leptin concentration (D) of lactating (○) and non-lactating (●) rats. (A) Lactating, r = 0·82, P < 0·001; non-lactating, r = − 0·15, P = 0·606. (B) Lactating, r = − 0·83, P < 0·001; non-lactating, r = 0·04, P = 0·879. (C) Lactating, r = 0·89, P < 0·001; non-lactating, r = − 0·33, P = 0·248. (D) Lactating, r = − 0·87, P < 0·001; non-lactating, r = − 0·54, P = 0·066.
Carcass composition and energy balance
Independently of nutritional status, lactating rats had a body weight higher at the beginning of the experimental period (F 1,27 = 19·58, P < 0·001) and a lower weight at day 14 of lactation compared with non-lactating rats (F 1,27 = 4·91, P < 0·03). No effects were observed in nutritional status (initial weight, F 1,27 = 1·23, P = 0·276; final weight, F 1,27 = 1·58, P = 0·219), and there was no interaction between nutritional status and physiological status (initial weight, F 1,27 = 0·00, P = 0·981; final weight, F 1,27 = 0·01, P = 0·907).
Carcass fresh weight and carcass protein content were also lower in the lactating rats than in the non-lactating rats for both nutritional statuses (F 1,27 = 8·79, P < 0·006 and F 1,27 = 5·70, P < 0·024, respectively). No effect occurred in nutritional status (carcass fresh weight, F 1,27 = 1·13, P = 0·295; carcass protein content, F 1,27 = 0·00, P = 0·946), and there was no interaction between these factors (carcass fresh weight, F 1,27 = 0·11, P = 0·740; carcass protein content, F 1,27 = 0·22, P = 0·642).
The fat content of the carcass in absolute and relative values was significantly affected by lactation (F 1,27 = 18·81, P < 0·001 and F 1,27 = 13·06, P < 0·001, respectively) and by dietary protein content (F 1,27 = 24·39, P < 0·001 and F 1,27 = 27·41, P < 0·001, respectively), but there was no interaction between these factors (F 1,27 = 1·97, P = 0·172 and F 1,27 = 2·778, P = 0·107, respectively). Thus, the carcass fat content of lactating rats was lower than that of non-lactating rats and higher in the protein-deprived groups than in the control group.
The carcass water and ash contents were not influenced by nutritional status (F 1,27 = 2·20, P = 0·150 and F 1,27 = 0·25, P = 0·621, respectively) or by physiological status (F 1,27 = 0·65, P = 0·423 and F 1,27 = 3·02, P = 0·093, respectively), nor was there any interaction between the groups (F 1,27 = 0·04, P = 0·834 and F 1,27 = 0·01, P = 0·89, respectively). There was also no difference between groups when the carcass protein and ash contents were expressed relative to body weight. The proportion of water in the carcass was affected by the physiological (F 1,27 = 16·46, P < 0·001, respectively) and nutritional (F 1,27 = 29·56, P < 0·001) status, but there was no interaction between these factors (F 1,27 = 2·024, P = 0·166); hence, lactating rats exhibited a lower proportion of fat and a higher proportion of water in their carcass than did non-lactating rats. In contrast, protein-deprived rats had a higher percentage of fat and a lower proportion of water in their carcass than control rats (Table 4).
Carcass composition of non-lactating and lactating groups of rats maintained with control (CNL, CL, respectively) or low-protein (LPNL, LPL, respectively) diets (Values are means with their standard errors for the number of rats indicated)
Mean values were significantly different in relation to non-lactating rats: *P < 0·05, **P < 0·01, ***P < 0·001 (two-way ANOVA).
Mean values were significantly different in relation to rats fed with the control diet: †P < 0·05, ††P < 0·01, †††P < 0·001 (two-way ANOVA).
The retroperitoneal and gonadal fat pad weights were significantly affected by lactation (F 1,27 = 8·90, P < 0·005 and F 1,27 = 33·16, P < 0·001, respectively) and by protein deprivation (F 1,27 = 4·90, P < 0·03 and F 1,27 = 15·33, P < 0·001) in absolute values but not in terms of the two-way interaction nutritional status % physiological status (F 1,27 = 0·003, P = 0·953 and F 1,27 = 0·28, P = 0·603, respectively). Similar results were observed in relative values for lactation (F 1,27 = 6·24, P < 0·019 and F 1,27 = 42·24, P < 0·001, respectively) and protein deprivation (F 1,27 = 4·84, P < 0·03 and F 1,27 = 20·68, P < 0·001, respectively) and in the two-way interaction nutritional status % physiological status (F 1,27 = 0·30, P = 0·582 and F 1,27 = 0·04, P = 0·831, respectively). Thus, the fat pad weights of lactating rats were lower than those of non-lactating rats, and higher in the protein-deprived groups than in the control groups.
Brown adipose tissue weight was modified only by nutritional status in absolute values (F 1,26 = 14·02, P < 0·001) and in relative values (F 1,26 = 10·42, P < 0·001). Protein-deprived rats exhibited an absolute brown adipose tissue weight higher than that of control rats, independent of physiological status. This was confirmed when values were expressed as a percentage of body weight (Table 5).
Absolute and relative weights of retroperitoneal and gonadal white adipose tissue and brown adipose tissue of non-lactating and lactating groups of rats maintained with control (CNL, CL, respectively) or low-protein (LPNL, LPL, respectively) diets (Values are means with their standard errors for the number of rats indicated)
Mean values were significantly different in relation to non-lactating rats: *P < 0·05, ***P < 0·01, ***P < 0·001 (two-way ANOVA).
Mean values were significantly different in relation to rats fed with the control diet: †P < 0·05, ††P < 0·01, †††P < 0·001 (two-way ANOVA).
Serum leptin concentration was directly correlated with lipid carcass content (r = 0·63, P < 0·001) and the weights of the retroperitoneal fat pads (r = 0·55, P < 0·002), gonadal fat pads (r = 0·50, P < 0·007) and brown adipose tissue (r = 0·43, P < 0·022). In contrast, there was an inverse relationship between serum insulin level and fat carcass content (r = − 0·62, P < 0·001), retroperitoneal fat (r = − 0·54, P < 0·001) and weight of gonadal fat (r = − 0·56, P < 0·002). Serum insulin levels were not correlated with weight of brown adipose tissue (r = − 0·35, P = 0·070).
LPL rats had a lower energy intake but a higher carcass energy than CL rats. The energy balance was influenced by nutritional status (F 1,27 = 30·86, P < 0·001) and lactation (F 1,27 = 113·04, P < 0·001), as well as by the interaction between the two factors (F 1,27 = 8·82, P < 0·006). There was thus a negative energy balance in lactating rats, less severe in the LPL than in the CL group. Energy balance correlated negatively with energy intake in lactating rats (r = − 0·81, P < 0·001) and when the data from the two groups were combined (r = − 0·87, P < 0·001). This correlation was weaker only in non-lactating rats (r = 0·44, P = 0·117).
A considerable carcass energy loss as lipid was observed in the LPL and CL groups, but this was less severe in the former group (P < 0·001). Independent of nutritional status, lactating rats showed a reduction in carcass energy as protein in relation to the non-lactating rats (F 1,27 = 28·13, P < 001).
Energy expenditure, calculated by the energy-balance method, was significantly affected by the nutritional (F 1,27 = 31·08, P < 0·001) and physiological (F 1,27 = 443·13, P < 0·001) status, as well as by the interaction between these factors (F 1,27 = 39·16, P < 0·001). Thus, energy expenditure was significantly higher in the lactating rats, but lower in the LPL than the CL group (P < 0·001). Energy efficiency was significantly modified by lactation (F 1,27 = 90·01, P < 0·001) and by nutritional status (F 1,27 = 20·78, P < 0·001), but no effect of the interaction of these factors was verified (F 1,27 = 2·15, P = 0·154). Hence, energy efficiency was reduced by lactation and increased by protein deprivation (Table 6).
Residual energy balance of non-lactating and lactating groups of rats maintained with control (CNL, CL, respectively) or low-protein (LPNL, LPL, respectively) diets (Values are means with their standard errors for the number of rats indicated)
a,b,c Mean values within a row with unlike superscript letters were significantly different (Tukey HSD test; P ≤ 0·05).
* Mean values were significantly different in relation to non-lactating rats: ***P < 0.001 (two-way ANOVA).
† Mean values were significantly different in relation to rats fed with control diet: †††P < 0·001 (two-way ANOVA).
‡ Carcass energy was calculated from the energy content of protein and carbohydrate to be 16·74 kJ/g and that of fat to be 37·7 kJ/g.
§ Energy balance was calculated as the difference between energy intake and energy expenditure.
∥ Energy expenditure was calculated by the balance method (energy expenditure = energy intake – energy balance).
¶ Energy efficiency was calculated as the (energy balance/energy intake) × 100.
The relationship between energy expenditure and serum insulin level was positive (r = 0·89, P < 0·001), and that between energy expenditure and serum leptin level negative (r = − 0·87, P < 0·001) in lactating rats. These correlations were weaker in non-lactating rats (Fig. 1C, 1D). When data from non-lactating and lactating rats were pooled, energy expenditure correlated directly with serum insulin concentration (r = − 0·53, P < 0·004) and inversely with serum leptin concentration (r = − 0·46, P < 0·012).
Discussion
Rats fed with a low-protein diet did not exhibit the typical features of protein malnutrition such as low body weight and hypoalbuminaemia. However, the ‘adiposity signals’ (serum insulin and serum leptin concentrations) were different in response to dietary protein content. In LPL and LPNL rats, the insulinaemia was similar, whereas in CL rats, the serum insulin concentration was higher than in CNL rats.
In addition, serum leptin concentration did not differ between LPL and LPNL rats, and in CL rats the leptinaemia was reduced by 50 % compared with CNL rats. In consequence, the serum leptin concentration was higher in LPL than in CL rats. Although some researchers have found no change in serum leptin in lactating rats (Chien et al. Reference Chien, Hara, Rouard, Yano, Phillippe, Polonsky and Bell1997; Carmen-Garcia et al. Reference Carmen-Garcia, Casanueva, Dieguez and Senaris2000), several studies have shown that there is a 20–75 % decrease in serum leptin in the daytime during lactation (Brogan et al. Reference Brogan, Mitchell, Trayhurn and Smith1999; Herrera et al. Reference Herrera, Lasunción, Huerta and Martín-Hidalgo2000; Woodside et al. Reference Woodside, Abizaid and Walker2000).
There are several possible explanations for the increase in serum leptin concentration verified in lactating rats submitted to protein restriction in the present study. First, lactating rats fed protein-restricted diet have a low rate of milk production, as already described (Grigor et al. Reference Grigor, Allan, Carrington, Carne, Geursen, Young, Thompson, Hayness and Coleman1987) and verified in the present study (data not shown), and in situations in which milk production is decreased, there is an elevation in serum leptin concentration (Cowie et al. Reference Cowie, Forsyth and Hart1980; Denis et al. Reference Denis, Williams and Vernon2003).
The second explanation is the decreased clearance rate of leptin due to a reduced cardiac output and reduced blood flow and/or milk yield (Sakanashi et al. Reference Sakanashi, Brigham and Rasmussen1987). This supposition is reinforced by the fact that the clearance rate of leptin is increased in normal lactating rats, which is compatible with the high cardiac output during lactation (Williamson, Reference Williamson1980), and that leptin is also secreted into the milk (Bonnet et al. Reference Bonnet, Delavaud, Laud, Gourdou, Leroux, Djiane and Chilliard2002).
Finally, the major explanation is the increased synthesis of hormone by white adipose tissue since leptin is synthesised predominantly by this tissue, proportionally to body fat stores (Frühbeck, Reference Frühbeck2001; Harvey & Ashford, Reference Harvey and Ashford2003). In the present study, despite the fact that rats fed with a low-protein diet ate less than control rats, a significant increase in weight of the retroperitoneal and gonadal fat pads, as well as higher carcass fat content, was verified. Moreover, serum leptin concentrations were directly correlated with carcass fat, gonadal and retroperitoneal adipose tissue fresh weight, explaining the increase in the synthesis of leptin in malnourished rats.
The higher adiposity verified in the present study in rats submitted to protein restriction may be the consequence of lower milk production and thus energy expenditure. It could also be the result of a higher sensitivity of adipocytes to insulin, with a consequent increase in the synthesis of lipids and an inhibition of their degradation. This hypothesis is supported by a lower HOMA-IR value and a higher rate constant for the disappearance of serum glucose during insulin tolerance test (data not shown) seen in LPL rats compared with CL rats. In accordance, our results showed an inverse correlation between insulinaemia and fat carcass content and retroperitoneal and gonadal fat pad weights.
A high sensitivity of adipocytes to insulin could also contribute to increase leptin secretion and biosynthesis. Studies in vitro showed that insulin acts directly at the level of the adipocytes, increasing leptin mRNA level and secretion (Hardie et al. Reference Hardie, Guilhot and Trayhurn1996; Barr et al. Reference Barr, Malide, Zarnowski, Taylor and Cushman1997), perhaps due to increased glucose transport and metabolism (Müller et al. Reference Müller, Gregoire, Stanhope, Mobbs, Mizuno, Warden, Stern and Havel1998). On the other hand, the enhanced peripheral sensitivity to insulin might be a consequence of higher leptin levels, since the administration of leptin either centrally or peripherally increased insulin-stimulated glucose use by peripheral tissues in normal rats (Barzilai et al. Reference Barzilai, Wang, Massilon, Vuguin, Hawkins and Rossetti1997; Lin et al. Reference Lin, Higginbotham, Judd and White2002).
Finally, the negative energy balance shown by lactating rats in the present study maintained with a low-protein diet could be involved. The negative energy balance appears to be the major factor responsible for the hypoleptinaemia of lactation (Vernon et al. Reference Vernon, Denis, Sorensen and Williams2002). Confirming this supposition, we observed that leptinaemia was directly related to energy balance only in lactating rats. Moreover, LPL rats that showed higher levels of this hormone also had a negative energy balance, although this was less accentuated.
Hypoleptinaemia during lactation may drive, or at least facilitate, hyperphagia (Vernon et al. Reference Vernon, Denis, Sorensen and Williams2002). In this study, LPL rats, which had higher serum leptin and lower serum insulin levels, consumed less food (in absolute values and also when expressed per gram of body weight) than the CL rats with lower serum leptin and higher serum insulin levels. In lactating rats, there was a significant negative correlation between serum leptin and energy intake, but this correlation was absent in non-lactating rats and when the data for non-lactating and lactating rats were pooled. The relationship between energy intake and serum insulin level was not significant in non-lactating rats alone; there was, however, a positive correlation in lactating rats and in the combined data from the two groups. Furthermore, energy intake was negatively related to energy balance in lactating rats.
These findings suggest the following. First, in normal lactation, peripheral insulin resistance occurs (Vernon et al. Reference Vernon, Faulkner, Hay, Calvert and Flint1990) that contributes to negative energy balance, leading to hypoleptinaemia. Together with hypothalamic insulin resistance, this results in hyperphagia. Second, protein restriction during lactation reduces serum insulin levels, favouring an enhanced peripheral sensitivity to hormones that contributes to greater maternal fat deposition and hyperleptinaemia. The high serum leptin levels associated with the increase in the hypothalamic sensitivity to insulin decreased the food intake.
Studies have showed that the high cost of lactation in energy terms is paid by the increase in food intake associated with use of the stored fat (Naismith et al. Reference Naismith, Richardson and Pritchard1982), and by conserving metabolic fuels owing to a reduction in brown fat thermogenesis (Trayhurn & Richard, Reference Trayhurn and Richard1985). In the reduction of dietary protein level, although hyperphagia occurs, there is an accompanying decrease in food efficiency and an increase in energy expenditure in an apparent attempt to dissipate excess energy (Specter et al. Reference Specter, Hamilton, Stern and Howitz1995). These changes in metabolic efficiency appear to be the result of adaptive diet-induced thermogenesis associated with an increased activity of brown adipose tissue (Rothwell & Stock, Reference Rothwell and Stock1987). In this study, LPL rats had decreased energy expenditure and a lower depletion of the reserves of fat carcass compared with CL rats.
Curiously, the groups maintained with a low-protein diet exhibited better energy efficiency, possibly due to hypophagia that resulted in a decrease of energy expenditure in an attempt to conserve energy. This change in metabolic efficiency did not appear to be the result of adaptive diet-induced thermogenesis, as judged by the higher brown adipose tissue weight in rats maintained with a low-protein diet, an indication of greater metabolic activity in this tissue (Rothwell & Stock, Reference Rothwell and Stock1987). Nor did this result from a decrease in BMR as this change is related, among others factors, to a low thyroid hormone concentration. In our case, hypothyroidism could be discounted, at least in the lactation, once this alteration is associated to hypoleptinaemia (Ahima, Reference Ahima2000).
As well as hypophagia, hypoinsulinaemia is another candidate to explain the reduced energy expenditure as the latter was directly correlated to serum insulin level and negatively correlated to serum leptin. A low serum insulin concentration could determine increased insulin sensitivity in the adipocytes, raising the rate of lipogenesis in the white adipose tissue.
Thus, rats submitted to protein restriction during pregnancy and lactation showed, at peak lactation, a preservation of maternal reserves owing to negative energy balance, although this was less severe when compared with lactating control rats. This metabolic adaptation was obtained, at least in part, by the hypoinsulinaemia that resulted in increased insulin sensitivity favouring enhanced fat deposition, hyperleptinaemia and hypophagia.
Acknowledgements
The authors thank Celso Roberto Afonso for valuable technical assistance. This work was partly supported by the Brazilian foundations FAPEMAT (grant n.175/04), CNPq (grant n. 479138/2003-6) and FINEP/PRONEX (grant n. 134/97). C. L. P. F. was the recipient of a CAPES fellowship.
