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Animal Models

Wheat gluten intake increases weight gain and adiposity associated with reduced thermogenesis and energy expenditure in an animal model of obesity



The association between gluten and body weight is inconsistent. Previously, we showed that a gluten-free diet reduces weight gain without changing food intake in mice fed high-fat diets. In the present study, we investigated the effects of gluten intake on fat metabolism, thermogenesis and energy expenditure in mice fed a standard or high-fat diet.


Mice were fed four different experimental diets during 8 weeks: a control-standard diet (CD), a CD added with 4.5% of wheat gluten (CD-G), a high-fat diet (HFD) and a HFD added with 4.5% of wheat gluten (HFD-G). After 8 weeks, the mice received 99mTc-radiolabeled gluten orally to study gluten absorption and biodistribution or they underwent indirect calorimetry. After killing, subcutaneous and brown adipose tissues (SAT and BAT) were collected to assess thermogenesis-related protein expression. Lipid metabolism was studied in adipocyte cultures from the four groups.


Despite having had the same energy intake, CD-G and HFD-G mice exhibited increased body weight and fat deposits compared with their respective controls. 99mTc-GLU or its peptides were detected in the blood, liver and visceral adipose tissue, suggesting that gluten can even reach extraintestinal organs. Uncoupling protein-1 expression was reduced in the BAT of HFD-G and in the SAT of CD-G and HFD-G mice. Indirect calorimetry showed lower oxygen volume consumption in CD-G and HFD-G groups compared with their controls. In HFD mice, daily energy expenditure was reduced with gluten intake. Gluten also reduced adiponectin, peroxisome proliferator-activated receptor (PPAR)-α and PPARγ and hormone-sensitive lipase in cultures of isolated adipocytes from HFD mice, whereas in the CD-G group, gluten intake increased interleukin-6 expression and tended to increase that of tumor necrosis factor.


Wheat gluten promotes weight gain in animals on both HFD and CD, partly by reducing the thermogenic capacity of adipose tissues.


Gluten is a protein complex founded in cereals such as wheat, rye, barley and oats. Wheat gluten proteins can be divided into two main fractions: gliadin and glutenins.1, 2 Gluten is a main dietary component in several countries and gluten-free diets have been used by individuals as a method of weight control.3 For this reason, understanding the effect of gluten on lipid metabolism and the possible mechanism of this effect could contribute to nutritional strategies to prevent obesity. Despite the huge popularity of gluten-free diets, an association between gluten and obesity is still inconsistent, and there are few controlled studies in the scientific literature.3, 4

In 2013, our group published the first controlled study that verified the effects of wheat gluten in a murine model of diet-induced obesity. Animals that were fed gluten-free diets showed a reduction in weight gain and adiposity associated with an upregulation of peroxisome proliferator-activated receptor-α (PPARα), lipoprotein lipase, hormone-sensitive lipase(HSL) and carnitine palmitoyl-transferase-1 in adipose tissue that are related to lipolysis and fatty acid oxidation. Moreover, we have previously observed that tumor necrosis factor (TNF), interleukin (IL)-6 and IL-10 expression and concentration were increased in adipose tissue, suggesting a higher proinflammatory profile in mice fed a high-fat gluten-enriched diet.5

The mechanisms by which wheat gluten causes weight gain and the expansion of adipose tissue depots are still unknown. In the present study, we investigated the mechanisms by which gluten increases adiposity gain by studying the gluten action on thermogenesis, the browning of white adipose tissue (WAT) and oxygen consumption as well as gluten intestinal absorption and biodistribution.

Materials and methods

Animals and diets

The study was approved by the Animal Ethics Committee at the Federal University of Minas Gerais (protocol no. 5/2013). Eight-week-old male C57BL/6 mice were group-housed (2–5 animals per cage) in a room with a 12 h light cycles and a controlled temperature (26±2 °C). All mice had free access to food and water. Physical activity was similar among all groups during the experiment and the indirect calorimetry test. The animals were fed four different experimental diets during 8 weeks: a control-standard diet (CD group), a CD added with 4.5% of wheat gluten (CD-G group), a high-fat diet (HFD group) to induce obesity and a HFD added with 4.5% of wheat gluten (HFD-G group). Diets with or without wheat gluten (Granotec, Curitiba, Brazil) supplementation were adjusted to be isocaloric and to present the same nutritional composition. The animals were distributed into the experimental groups based on their initial weight to insure that their weight was statistically similar among groups.

The body weight of each animal was measured weekly. Food intake was primarily calculated as the difference between food offered and food recovered from the top and bottom (spillage) of the cages at the end of each experimental week. The food consumption in each cage was divided by the number of mice/cage (average of energy intake). The result was given as the average of the energy intake/animal/day. After 8 weeks, oxygen consumption was measured in the mice by indirect calorimetry or they underwent a radioisotope assay using gluten radiolabeled with technetium (99mTc-GLU) to study energy expenditure and gluten intestinal absorption and biodistribution, respectively. The mice were then killed under anesthesia to collect blood, liver, epididymal visceral adipose tissue (VAT), subcutaneous inguinal adipose tissue (SAT) and interscapular brown adipose tissue (BAT). All analyses were performed using randomly coded samples.

Wheat gluten absorption and biodistribution

Hydrolyzed wheat gluten (H6784, Sigma-Adrich Co., St Louis, MO, USA) was labeled with the radioactive nuclide technetium-99m (99mTc), according to the methods proposed by Faintuch et al.6 and de Barros et al.7 Evaluation of the radiolabeled yield was determined in vitro using thin-layer chromatography, and stability of the radiolabeled complex 99mTc-GLU in vivo was determined using scintigraphic images. For this purpose, C57BL/6 mice images were captured using a gamma-camera (Nuclide TH 22, Mediso, Budapest, Hungary) at 1, 4 and 6 h after gavage of 5.5 MBq of 99mTc-GLU or 5.5 MBq of 99mTcO4-. Intestinal transit time and absorption were performed in C57BL/6 mice without any previous treatment. The animals received 5.5 MBq of 99mTc-GLU by gavage and their intestinal tract was removed. Images of the stomach and small and large intestine were captured using a gamma-camera at 1, 2, 4 and 6 h after 99mTc-GLU administration.

To evaluate the biodistribution of gluten and its peptides in mice after receiving the assigned diet for 8 weeks, C57BL/6 mice from the CD-G and HFD-G underwent 5–6 h of fasting and then received 5.5 MBq of 99mTc-GLU by gavage. Tissues and organs, such as blood, liver and VAT, were removed 30 min, 1 h and 2 h after 99mTc-GLU gavage. The radioactivity was measured using a gamma counter (Wizard, Perkin-Welmer Life Sciences, Turku, Finland). A standard dose containing a known amount of radioactivity was counted simultaneously to correct for radioactive 99mTc decay. The final results were expressed as a percentage of the administered dose per gram of tissue or organ (% dose g−1).

Energy expenditure estimate

The metabolic rate was estimated using continuous recorders of oxygen consumption (VO2) and CO2 released (VCO2) with an open-flow indirect calorimeter (LE405 Gas Analyzer, Panlab Harvard Apparatus, Barcelona, Spain). After week 8 of the diet, mice were weighed and placed individually into the gas chamber, where they remained for 50 min without any external influence. VO2 was recorded for each min using a computerized system (Metabolism, Harvard Apparatus, Spain). The final 20 min were used for the analysis, and the initial 30 min were disregarded to allow the animal to calm and acclimate to the chamber (after the stress of handling), and to avoid the influence of room gases inside the chamber (O2 and CO2). The VO2 and respiratory exchange ratio (RER=VCO2/VO2) values were used to estimate energy expenditure (EE), using the following equation: EE=(3.815+(1.232 × RER)) × VO2 × 1.44.

VO2 was measured under two conditions: after an overnight fast and in the fed state. All experiments were conducted during the same period of time to prevent circadian variations (fasting state: 0800 to 1200 hours and fed state: 1200 to 1600 hours), and the room temperature was controlled at 25±1 °C.

Adipocyte culture

VAT was removed under sterile conditions for adipocyte isolation, according to Rodbell.8 Briefly, 1 g of VAT was digested with collagenase for 40 min at 37 °C under continuous agitation. The cells were then filtered and washed three times with culture medium (complete Dulbecco’s modified Eagle’s medium) to remove collagenase and other debris. The infranatant was discarded after each washing stage and centrifugation (500 r.p.m. for 3 min at 4 °C). Isolated adipocytes were then resuspended in 6 ml of Dulbecco’s modified Eagle’s medium. Cell counting was performed in a Neubauer chamber (1.4 × 106 to 1.0 × 107 cells per ml).

The isolated adipocyte-containing solution was incubated in duplicate at 37 °C and 5% CO2 with 1 ml of Dulbecco’s modified Eagle’s medium for 2 h. After incubation, the infranatant (1.6 ml) was removed and the plate was stored at −70 °C for subsequent RNA extraction and inflammatory and metabolic-related protein analysis by real-time quantitative reverse transcription-PCR.

Real-time quantitative reverse transcription-PCR

BAT, SAT and adipocytes isolated from VAT were collected for the analysis of gene expression using real-time quantitative reverse transcription-PCR. Total RNA from the samples was extracted using TRizol reagent (Invitrogen/Life Technologies, Grand Island, NY, USA) according to the manufacturer’s protocol. Reverse transcription was performed to obtain complementary DNA. Samples were placed in the thermocycler at 72 °C for 5 min for annealing, then 42 °C for 3 h and 72 °C for 15 min for transcription. The mRNA levels were determined using the SYBR Green reagent (Applied Biosystems/Life Technologies, USA) and specific primers in an ABiPrism 7900HT Sequence Detection System (Applied Biosystems/Life Technologies, Foster City, CA, USA). Gene expression was normalized to endogenous glyceraldehyde-3-phosphate dehydrogenase (GAPDH), and the results are expressed as the fold increase over control (2-ΔΔCT). The primers were:


UCP1 (uncoupling protein 1): Fwd: 5′-IndexTermGTGAACCCGACAACTTCCGAA-3′ and Rev: 5′-IndexTermTGCCAGGCAAGCTGAAACTC-3′;

PGC1α (peroxisome proliferator-activated receptor-γ coactivator-1α): Fwd: 5′-IndexTermGTCAACAGCAAAAGCCACAA-3′ and Rev: 5′- IndexTermTCTGGGGTCAGAGGAAGAGA-3′;

BMP7 (bone morphogenetic protein 7): Fwd: 5′-IndexTermCAGCCTGCAAGATAGCCATT-3′ and Rev: 5′-IndexTermAATCGGATCTCTTCCTGCTC-3′;

PRDM16 (PR domain containing 16): Fwd: 5′-IndexTermCAGCACGGTGAAGCCATTC-3′ and Rev: 5′-IndexTermGCGTGCATCCGCTTGTG-3′;




Adiponectin: Fwd: 5′-IndexTermAGGTTGGATGGCAGGC-3′ and Rev: 5′- IndexTermGTCTCACCCTTAGGACCAAGAA-3′;



Lipoprotein lipase: Fwd: 5′-IndexTermAGTCTGGCCTCGAACTAAACTATGTAT-3′ and Rev: 5′-IndexTermTCCCAGGACACAGGAAGCTAA-3′;

Hormone sensitive lipase (HSL): Fwd: 5′-IndexTermACCGAGACAGGCCTCAGTGTG-3′ and Rev: 5′-IndexTermGAATCGGCCACCGGTAAAGAG-3′;

Carnitine palmitoyl-transferase-1b: Fwd: 5′-IndexTermTCCCAGGCAAAGAGACAGACTTGC-3′ and Rev: 5′-IndexTermGCAGGCGCGAGCCCTCATAG-3′.

Statistical analyses

Sample size was based on previous results published by Soares et al.5 Statistical analyses were performed using the software GraphPad Prism 5.0 (GraphPad Software Inc., San Diego, CA, USA). Normality was evaluated using the Kolmogorov–Sminorv test, and outliers were detected using Grubb’s test. The data were analyzed using Student’s t-test or a one-way analysis of variance followed by the Newman–Keuls multiple comparison test (parametric variables). Nonparametric variables were analyzed using either the Mann–Whitney or Kruskal–Wallis test, followed by Dunn’s multiple comparisons test. Variance was similar between groups that were statistically compared. The results are presented as mean±s.e. (parametric variables) or median and interquartile interval (nonparametric variables), with a significance level of 5% (P<0.05).


Effect of gluten supplementation on food intake and body composition

Energy intake of mice fed high-fat diets (HFD and HFD-G) was greater than energy intake of mice fed standard diets (CD and CD-G). As expected, mice from the HFD groups showed a higher weight gain compared with mice fed the standard diets. The addition of wheat gluten (4.5%) did not alter food intake. Despite the same energy intake, animals from the CD-G and HFD-G groups showed an increased body weight, as well as VAT and SAT expansion, compared with their respective controls (Figure 1).

Figure 1

Average energy intake, body weight and adiposity of CD, CD-G, HFD and HFD-G mice. (a) Estimated average of the energy intake per cage in calories/animal/day, n=12/12/20/18 (CD/CD-G/HFD/HFD-G) cages. Kruskal–Wallis test+Dunn’s test. The different letters indicate P<0.05. (b) Weekly body weight (g), n=44/46/43/42. One-way analysis of variance (ANOVA)+Newman–Keuls post-test (P<0.05). Statistical difference between CD and HDF. §Statistical difference among four groups. (c) VAT weight (g), n=44/46/43/42; #Bars present median and line interquartile interval; Mann–Whitney test; P<0.05. (d) SAT weight (g), n=26/25/25/24. Student’s t-test, *P<0.05. Except for Figure 6c (CD and CD-G groups), bars represent the mean and vertical lines represent s.e.

Wheat gluten absorption and biodistribution in peripheral tissues

We studied gluten intestinal absorption and the kinetics of biodistribution 99mTc-GLU.

Initially, we confirmed the purity of 99mTc-GLU using chromatography. The results showed a purity of 92.3±2.1%, an acceptable level of radiochemical impurities (99mTcO4- and 99mTcO2 mainly). Free technetium (99mTcO4-) is mainly retained in the thyroid because of similar characteristics to the iodide ion, and the in vivo stability of 99mTc-GLU was confirmed by the absence of radioactivity in thyroid images from animals that received 99mTc-GLU (Figure 2).

Figure 2

In vivo scintigraphic images obtained using a gamma-camera. (a) Schematic figure representing how the animal was disposed. (b–d) Scintigraphic images of C57Bl/6 mice captured using a gamma-camera at 1 h (b), 4 h (c) and 6 h (d) after gavage of 5.5 MBq of 99mTcO4- (n=3). (e–g) Scintigraphic images captured using a gamma-camera at 1 h (e), 4 h (f) and 6 h (g) after gavage of 5.5 MBq of 99mTc-GLU (n=4).

The transit of 99mTc-GLU was analyzed 1, 2, 4 and 6 h after gavage. After 1 h, gluten was found in the stomach and small intestine. After 2 h, the nonabsorbed fraction reached the ileum and cecum. At 4 and 6 h after gavage, gluten was detected exclusively in the large intestine, representing the fraction that was not digested and absorbed (Figures 3a–e). 99mTc-GLU was mainly detected in the blood and liver, and also in VAT, as soon as 30 min after gavage. Although the kinetics of 99mTc-GLU show a slower initial absorption in the HFD-G (30 min) compared with the CD-G group, it becomes similar 1 and 2 h after gavage. As result, the total 99mTc-GLU detected in all sites was similar between CD-G and HFD-G groups (Figures 3f–h).

Figure 3

Scintigraphic images of the intestinal tract and biodistribution of wheat gluten radiolabeled with Technetium (99mTc-GLU) in the blood, liver and VAT. (a) Schematic representation of how the gastrointestinal tract was disposed. (b–e) Scintigraphic images of the stomach and small and large intestine captured using a gamma-camera at 1 h (b), 2 h (c), 4 h (d) and 6 h (e) after gavage of 5.5 MBq of 99mTc-GLU (n=3 per time). (f–h) The absorption kinetics of 99mTc-GLU and the area under curve for blood, liver and VAT. CD-G and HFD-G, n=6 per group per time. Statistical test: *P<0.05 (Student’s t-test). Results are expressed as mean (dots and bars) and s.e. (vertical lines).

EE and thermogenesis

Because the increase in total weight and adiposity was not associated with changes in food intake, we investigated whether it could be a result of differences in EE in both the fasting and fed states. Indirect calorimetry showed that in the fed state, there were no differences in VO2 consumption in the CD groups (CD 23.7±0.7 ml min−1 kg−1 vs CD-G 25.4±0.9 ml min−1 kg−1) or HFD groups (HFD 28.5±0.6 ml min −1kg−1 vs HFD-G 28.9±1.9 ml min−1 kg−1). EE was not different among groups (CD 180.0±12.7 ml min−1 kg−1 vs CD-G 179.2±5.8 ml min−1 kg−1; HFD 195.3±4.0 ml min−1 kg−1 vs HFD-G 191.4±12.9 ml min−1 kg−1). When the fasting state was analyzed, lower basal oxygen consumption was detected in the CD-G and HFD-G groups over time. Although a modest but statistically reduction in oxygen consumption ratio was seen in CD-G group (P<0.05), total daily EE was not different in comparing CD and CD-G groups. In the HFD groups, EE was reduced by >10% in HFD-G compared with HFD mice (Figure 4).

Figure 4

Oxygen consumption (VO2), mean EE and RER of CD, CD-G, HFD and HFD-G mice in the fasting state. (a, b) The oxygen consumption measurement of CD and HFD groups (ml min−1 kg−1). Statistical test: Paired Student’s t-test. Lines represent the mean of each min. (c, d) EE of CD and HFD groups (kcal day−1 kg−1), respectively. (e, f) RER (RER=VCO2/VO2) of CD and HFD groups, respectively. *P<0.05 (Student’s t-test). Bars represent the mean and vertical lines represent s.e.; n=9/10/15/15 (CD/CD-G/HFD/HFD-G).

To further understand the molecular mechanisms supporting the reduced caloric expenditure associated with gluten intake, we studied the expression of molecules associated with thermogenesis in SAT and BAT. In BAT, wheat gluten intake reduced mitochondrial UCP1 and increased UCP1 regulator protein PGC1α expressions in HFD mice. No significant differences were observed in BMP7 or PRDM16 expression, both of which are related to the development of brown adipocytes and multilocular morphology. No differences were observed in BMP7 and PRDM16 expression in CD groups (Figure 5).

Figure 5

Expression of thermogenesis-related proteins in the BAT and SAT of CD, CD-G, HFD and HFD-G mice. Analyses were performed using real-time quantitative reverse transcription-PCR (qRT-PCR). CD/CD-G/HFD/HFD-G: (a) n=9/10/10/11; (b) n=6/7/7/7; (c) n=8/10/10/11; (d) n=7/7/7/7; (e) n=5/5/5/5; (f) n=6/7/7/7; (g) n=5/5/5/5; (h) n=6/7/7/7. *P<0.05 (Student’s t-test), #P<0.05 (Mann–Whitney test). Bars represent the mean and vertical lines represent the s.e. except for (c) that shows the median and interquartile interval, respectively. Reference value (fold change=1) for mice fed control diet (CD and CD-G) is the mean of values of CD group mice. For mice fed high-fat diet (HFD and HFD-G) fold change=1 is the mean of HFD group mice.

In SAT, no differences were observed in PGC1α and PRDM16 expression; however, we found a decrease in UCP1 and BMP7 expression in both groups fed with gluten-rich diets (CD-G and HFD-G) that was associated with the differentiation of white into brown adipocytes in SAT (Figure 5).

Effect of wheat gluten on adipocyte expression

We studied the expression of molecules related to lipid metabolism and adipokine homeostasis in adipocyte cultures from mice in the four groups. In CD mice, wheat gluten intake increased the expression of the proinflammatory cytokine IL-6 and showed a tendency to increase TNF (P=0.06). No differences were observed in leptin and adiponectin. In HFD mice, only adiponectin expression was reduced in the HFD-G group. No alterations were detected for metabolic-related proteins in the CD groups. In HFD mice, gluten led to a reduction in PPARα, PPARγ and HSL expression (Figure 6).

Figure 6

Effects of wheat gluten on inflammatory and metabolic-related gene expression in culture of adipocytes from CD, CD-G, HFD and HFD-G mice. (a, b) Inflammatory-related gene expression in adipocyte cultures from (a) CD and CD-G or (b) HFD and HFD-G. (c, d) Metabolic-related gene expression in adipocyte culture from (c) CD and CD-G and in (d) HF and HFD-G. CPT1: carnitine palmitoyl-transferase-1; LPL, lipoprotein lipase. Analyses were performed using real-time quantitative reverse transcription-PCR (qRT-PCR); (a) n=5/6; (b) n=8/7, (c) n=5/6; (d) n=8/8. Statistical test: *P<0.05 (Student’s t-test) and #P<0.05 (Mann–Whitney test). Bars represent the mean and vertical lines represent s.e., except for (a) (leptin) and (b) (TNF and adiponectin) that represent median and interquartile interval, respectively. Reference value (fold change=1) for mice fed control diet (CD and CD-G) is the mean of values of CD group mice. For mice fed high-fat diet (HFD and HFD-G), fold change=1 is the mean of HFD group mice.


In the present study, we confirmed the obesogenic effects of wheat gluten that were observed previously by Soares et al.,5 and demonstrated that such an effect can also be detected in animals that received a standard diet. Despite having had the same energy intake, weight gain was 20% higher in mice fed gluten-enriched diets compared with the respective gluten-free groups. Adipose tissue depots were increased by 30% in CD-G and HFD-G groups. No other controlled studies using animal models or clinical trials have evaluated the obesogenic effects of gluten intake. A study with pigs showed a greater weight gain among animals fed a cereal-based diet containing gluten; however, it was a noncontrolled study, and the effects of gluten could not be measured.9

It is not clear whether the effects of dietary gluten on body weight are a result of direct action on adipose tissue or whether it is a consequence of the systemic inflammatory profile caused by its presence in the gastrointestinal tract. In the present study, we investigated whether gluten is detected in adipose tissue, an essential condition for a (possible) direct effect of gluten on that tissue. We hypothesized that mechanisms linked to a direct effect of gluten or its peptides could be involved in promoting weight gain. In support of this, Drago et al.10 showed that the gluten peptide gliadin increases intestinal permeability, permitting it to reach extraintestinal organs and alter the expression of inflammatory cytokines.

In our study we detected the presence of radiolabeled gluten in the circulation and peripheral organs, including VAT, suggesting that this protein and its fractions could also act directly on these tissues. The small presence of gluten peptides in the circulation is in agreement with the low digestibility of this protein related to its glutamine and proline content. Gluten peptides were shown to present >50 toxic epitopes, exerting cytotoxic, immunomodulatory and gut-permeating activities, with the 33-mer gliadin fragment being the most immunogenic.11, 12 It is possible that, after oral intake, such peptides would act on adipose tissue and induce specific changes in cell metabolism.

We investigated the possible mechanisms of gluten’s effect on weight gain, including thermogenesis and the browning process in BAT and SAT. In the fasting state, gluten intake in HFD mice reduced VO2 and EE compared with mice fed HFD without gluten, suggesting that there was reduced thermogenesis. This phenomenon was also observed in CD-G mice, although to a lesser extent. In the fed state, the effect of gluten intake was not observed. We believe that because of the increased EE caused by the thermic effect of food, the smaller but significant effect of gluten on basal metabolism could be masked. To better characterize thermogenesis and browning, we studied important thermogenesis-linked proteins in BAT and SAT. BAT contains multilocular adipocytes, with a large amount of mitochondria and a high expression of UCP1.13 This protein has been negatively related to the development of obesity, because the genetic ablation of BAT leads to obesity14 and induced expression of UCP prevents obesity in mice.15 This protein dissipates proton motive force from oxidative phosphorylation as heat instead of adenosine triphosphate production.16, 17 However, UCP1 is not expressed in classical white adipocytes, but it is present in brite adipocytes (‘brown-in-white’ or ‘beige’ adipocytes). These cells are adipocytes that develop in the subcutaneous adipose tissue in a process referred to as ‘browning’.18 We found a reduced UCP1 expression in all adipose tissue from mice fed gluten diets, except in BAT of the CD-G group. In SAT, gluten also reduced BMP7 expression in CD-G and HFD-G animals. This protein induces extensive ‘browning’ of WAT, regardless of the environmental temperature.19 BMP7 is important for brown adipocyte differentiation and UCP1 expression and it increases in EE.20 Thus, reduction in BMP7 and UCP1 expression is in agreement with the reduction of VO2 consumption observed in CD-G and HFD-G animals. Moreover, we also found increased PGC1α expression in the BAT of the HFD-G group. This protein seems to be the most important regulatory protein in BAT thermogenesis. PGC1α activates key mitochondrial enzymes in the respiratory chain and UCP1 expression, and also induces mitochondrial biogenesis. PGC1α is a well-known UCP1 inducer. Nevertheless, it has been shown that reduction of UCP1 could increase the expression of molecules involved in thermogenesis (including PGC1α), suggesting that this may be a compensatory increase of PGC-1α expression.21

We confirmed our previous results showing that weight gain observed with gluten intake is associated with the reduced PPARα, PPARγ and HSL expression, and we showed that this effect is observed in adipose tissue and also in cultures of isolated adipocytes. PPARs play an important role in lipid metabolism and energy homeostasis. PPARα and PPARγ downregulation reduce fatty acid oxidation-related genes22 and HSL expression,23 respectively. We found that PPARα downregulation in HFD-G could reduce intracellular triglycerides lipolysis and the consequent increase in fat accumulation. Moreover, the reduction of PPARγ observed in HFD-G could be related to the downregulation of adiponectin expression by adipocytes.24 Adiponectin is an anti-inflammatory adipokine and its levels negatively correlate with visceral fat accumulation. Evidence indicates that adiponectin protects against obesity-linked metabolic dysfunction.25 In the CD-G mice, weight and adiposity gains were associated with reduced VO2 consumption that could be related to downregulation of UCP1 and BMP7 in SAT and upregulation of the proinflammatory cytokines IL-6 and TNF in adipocytes from VAT. IL-6 and TNF are proinflammatory cytokines that have a central role in inflammation and their increased secretion contributes to metabolic dysfunction in obesity.25 TNF participates in obesity-related systemic insulin resistance by inhibiting the insulin receptor tyrosine kinase in muscle and fat.26 IL-6 levels are positively correlate with adiposity27 and its increase is predictive of the development of type 2 diabetes.28

In HFD mice fed a gluten diet, the obesogenic effect of wheat gluten was more prominent than in CD mice. The proinflammatory adipokine leptin regulates feeding behavior through the central nervous system. Its levels in the blood positively correlate with adipose mass, indicating the occurrence of leptin resistance in obese individuals.25 It could be expected that leptin expression would be higher in CD-G and HFD-G compared with their respective controls, because body weight was higher in those mice. However, leptin is secreted mainly by subcutaneous adipose tissue that was not used in our adipocyte cultures.29 Results from our adipocyte cultures are in agreement with the results found in adipose tissue by Soares et al.,5 showing the reduction of PPARα and PPARγ are associated with the reduction of HSL in HFD-G mice. These results support our hypothesis that gluten intake affects lipid metabolism in adipocytes of obese mice.

As mentioned above, HFD-G and CD-G presented different profiles of adipokine production in adipocyte cultures. In CD mice, only the proinflammatory cytokines TNF and IL-6 were increased in the CD-G group, whereas in HFD mice, fat metabolism enzyme expression was more affected by gluten. These results suggest that gluten could act on different pathways and is more intense in the presence of metabolic alterations linked to obesity. The causes of such effects were not explored in the present study and deserve future investigations.

Our study supports the hypothesis that gluten intake (4.5% of diet) can contribute to an acceleration of body weight gain that results from a reduction in energetic expenditure. The present results open a field of study that will help us to understand the association between gluten or gluten peptides and fat metabolism.

We conclude that gluten or its peptides could reach extraintestinal organs, such as liver and VAT, supporting a direct effect on these sites. Moreover, the inclusion of wheat gluten in isocaloric diets decreases thermogenesis, browning and EE, and accelerates weight gain and adiposity in CD-G and, mainly, in HFD-G mice.


  1. 1

    Wieser H . Chemistry of gluten proteins. Food Microbiol 2007; 24: 115–119.

    CAS  Article  Google Scholar 

  2. 2

    Shewry PR, Halford NG, Belton PS, Tatham AS . The structure and properties of gluten: an elastic protein from wheat grain. Philos Trans R Soc Lond B Biol Sci 2002; 357: 133–142.

    CAS  Article  Google Scholar 

  3. 3

    Marcason W . Is there evidence to support the claim that a gluten-free diet should be used for weight loss? J Am Diet Assoc 2011; 111: 1786.

    Article  Google Scholar 

  4. 4

    Gaesser GA, Angadi SS . Gluten-free diet: imprudent dietary advice for the general population? J Acad Nutr Diet 2012; 112: 1330–1333.

    Article  Google Scholar 

  5. 5

    Soares FL, de Oliveira Matoso R, Teixeira LG, Menezes Z, Pereira SS, Alves AC et al. Gluten-free diet reduces adiposity, inflammation and insulin resistance associated with the induction of PPAR-alpha and PPAR-gamma expression. J Nutr Biochem 2013; 24: 1105–1111.

    CAS  Article  Google Scholar 

  6. 6

    Faintuch BL, Teodoro R, Duatti A, Muramoto E, Faintuch S, Smith CJ . Radiolabeled bombesin analogs for prostate cancer diagnosis: preclinical studies. Nucl Med Biol 2008; 35: 401–411.

    CAS  Article  Google Scholar 

  7. 7

    de Barros AL, Mota L, Ferreira CeA, Oliveira MC, Góes AM, Cardoso VN . Bombesin derivative radiolabeled with technetium-99m as agent for tumor identification. Bioorg Med Chem Lett 2010; 20: 6182–6184.

    Article  Google Scholar 

  8. 8

    Rodbell M . Metabolism of isolated fat cells. I. effects of hormones on glucose metabolism and lipolysis. J Biol Chem 1964; 239: 375–380.

    CAS  PubMed  Google Scholar 

  9. 9

    Jönsson T, Ahrén B, Pacini G, Sundler F, Wierup N, Steen S et al. A Paleolithic diet confers higher insulin sensitivity, lower C-reactive protein and lower blood pressure than a cereal-based diet in domestic pigs. Nutr Metab (Lond) 2006; 3: 39.

    Article  Google Scholar 

  10. 10

    Drago S, El Asmar R, Di Pierro M, Grazia Clemente M, Tripathi A, Sapone A et al. Gliadin, zonulin and gut permeability: Effects on celiac and non-celiac intestinal mucosa and intestinal cell lines. Scand J Gastroenterol 2006; 41: 408–419.

    CAS  Article  Google Scholar 

  11. 11

    Thomas KE, Sapone A, Fasano A, Vogel SN . Gliadin stimulation of murine macrophage inflammatory gene expression and intestinal permeability are MyD88-dependent: role of the innate immune response in Celiac disease. J Immunol 2006; 176: 2512–2521.

    CAS  Article  Google Scholar 

  12. 12

    Fasano A . Zonulin and its regulation of intestinal barrier function: the biological door to inflammation, autoimmunity, and cancer. Physiol Rev 2011; 91: 151–175.

    CAS  Article  Google Scholar 

  13. 13

    Cannon B, Nedergaard J . Brown adipose tissue: function and physiological significance. Physiol Rev 2004; 84: 277–359.

    CAS  Article  Google Scholar 

  14. 14

    Lowell BB, S-Susulic V, Hamann A, Lawitts JA, Himms-Hagen J, Boyer BB et al. Development of obesity in transgenic mice after genetic ablation of brown adipose tissue. Nature 1993; 366: 740–742.

    CAS  Article  Google Scholar 

  15. 15

    Kopecky J, Clarke G, Enerbäck S, Spiegelman B, Kozak LP . Expression of the mitochondrial uncoupling protein gene from the aP2 gene promoter prevents genetic obesity. J Clin Invest 1995; 96: 2914–2923.

    CAS  Article  Google Scholar 

  16. 16

    Klingenberg M, Huang SG . Structure and function of the uncoupling protein from brown adipose tissue. Biochim Biophys Acta 1999; 1415: 271–296.

    CAS  Article  Google Scholar 

  17. 17

    Bartelt A, Heeren J . Adipose tissue browning and metabolic health. Nat Rev Endocrinol 2014; 10: 24–36.

    CAS  Article  Google Scholar 

  18. 18

    Klingenspor M, Herzig S, Pfeifer A . Brown fat develops a brite future. Obes Facts 2012; 5: 890–896.

    Article  Google Scholar 

  19. 19

    Boon MR, van den Berg SA, Wang Y, van den Bossche J, Karkampouna S, Bauwens M et al. BMP7 activates brown adipose tissue and reduces diet-induced obesity only at subthermoneutrality. PLoS One 2013; 8: e74083.

    CAS  Article  Google Scholar 

  20. 20

    Tseng YH, Kokkotou E, Schulz TJ, Huang TL, Winnay JN, Taniguchi CM et al. New role of bone morphogenetic protein 7 in brown adipogenesis and energy expenditure. Nature 2008; 454: 1000–1004.

    CAS  Article  Google Scholar 

  21. 21

    Kontani Y, Wang Y, Kimura K, Inokuma KI, Saito M, Suzuki-Miura T et al. UCP1 deficiency increases susceptibility to diet-induced obesity with age. Aging Cell 2005; 4: 147–155.

    CAS  Article  Google Scholar 

  22. 22

    Lee JY, Hashizaki H, Goto T, Sakamoto T, Takahashi N, Kawada T . Activation of peroxisome proliferator-activated receptor-α enhances fatty acid oxidation in human adipocytes. Biochem Biophys Res Commun 2011; 407: 818–822.

    CAS  Article  Google Scholar 

  23. 23

    Deng T, Shan S, Li PP, Shen ZF, Lu XP, Cheng J et al. Peroxisome proliferator-activated receptor-gamma transcriptionally up-regulates hormone-sensitive lipase via the involvement of specificity protein-1. Endocrinology 2006; 147: 875–884.

    CAS  Article  Google Scholar 

  24. 24

    Maeda N, Takahashi M, Funahashi T, Kihara S, Nishizawa H, Kishida K et al. PPARgamma ligands increase expression and plasma concentrations of adiponectin, an adipose-derived protein. Diabetes 2001; 50: 2094–2099.

    CAS  Article  Google Scholar 

  25. 25

    Ouchi N, Parker JL, Lugus JJ, Walsh K . Adipokines in inflammation and metabolic disease. Nat Rev Immunol 2011; 11: 85–97.

    CAS  Article  Google Scholar 

  26. 26

    Hotamisligil GS, Budavari A, Murray D, Spiegelman BM . Reduced tyrosine kinase activity of the insulin receptor in obesity-diabetes. Central role of tumor necrosis factor-alpha. J Clin Invest 1994; 94: 1543–1549.

    CAS  Article  Google Scholar 

  27. 27

    Vgontzas AN, Papanicolaou DA, Bixler EO, Kales A, Tyson K, Chrousos GP . Elevation of plasma cytokines in disorders of excessive daytime sleepiness: role of sleep disturbance and obesity. J Clin Endocrinol Metab 1997; 82: 1313–1316.

    CAS  Article  Google Scholar 

  28. 28

    Pradhan AD, Manson JE, Rifai N, Buring JE, Ridker PM . C-reactive protein, interleukin 6, and risk of developing type 2 diabetes mellitus. JAMA 2001; 286: 327–334.

    CAS  Article  Google Scholar 

  29. 29

    Samaras K, Botelho NK, Chisholm DJ, Lord RV . Subcutaneous and visceral adipose tissue gene expression of serum adipokines that predict type 2 diabetes. Obesity (Silver Spring) 2010; 18: 884–889.

    CAS  Article  Google Scholar 

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This study was supported by CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico), PRPq (Pro-reitoria de Pesquisa of UFMG), FAPEMIG (Fundação de Amparo a Pesquisa de Minas Gerais) and CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior). We thank Maria Helena Alves for animal care and all LABiN (Laboratório de Aterosclerose e Bioquímica Nutricional) members for their contributions and assistance.

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Correspondence to J I Alvarez-Leite.

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Freire, R., Fernandes, L., Silva, R. et al. Wheat gluten intake increases weight gain and adiposity associated with reduced thermogenesis and energy expenditure in an animal model of obesity. Int J Obes 40, 479–486 (2016).

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