Currently, obesity becomes a major global health challenge(Reference Morris, Beilharz and Maniam1). In 2016, 39 % of men and 39 % of women aged 18 years and over were overweight (BMI ≥ 25 kg/m2) and 11 % of men and 15 % of women were obese (BMI ≥ 30 kg/m2)(2). Both obesity and overweight lead to adverse metabolic effects on blood pressure, cholesterol, TAG and insulin resistance, all intermediated factors for several chronic diseases, most notably CVD, type 2 diabetes and certain types of cancer(2). Recently, oxidative stress and inflammation have been postulated as the new risk factors linking obesity to chronic diseases(Reference Bondia-Pons, Ryan and Martinez3).
Inflammation and oxidative stress are interrelated mechanisms which play a central role in the obesity pathogenesis(Reference Fernández-Sánchez, Madrigal-Santillán and Bautista4). The excessive adiposity is associated with antioxidant defence reduction and consequently higher oxidative product formation(Reference Vincent and Taylor5,Reference Savini, Catani and Evangelista6) , while the subclinical inflammation in obesity is characterised by higher concentration of proinflammatory cytokines, such as C-reactive protein, IL-6, IFN-γ, TNF-α, all predictors of co-morbidities(Reference Apostolopoulos, de Courten and Stojanovska7,Reference Ouchi, Parker and Lugus8) . Furthermore, increases in oxidative stress induced by inflammation are the main factor responsible for the development and progression of obesity co-morbidities(Reference Bondia-Pons, Ryan and Martinez3).
Recently, it has been demonstrated that the consumption of food with anti-inflammatory and antioxidant nutrients might bring benefits for overweight subjects(Reference Connaughton, McMorrow and McGillicuddy9,Reference Hermsdorff, Zulet and Abete10) . Several studies show that oleaginous are sources of polyphenols, antioxidant vitamins and minerals and MUFA, which improve insulin resistance, lipid profile, inflammation and oxidative stress(Reference López-Uriarte, Bullo and Casas-Agustench11–Reference Kris-Etherton, Hu and Ros13). Although peanut is a legume, it shares similar nutritional properties to nuts or oilseeds and has anti-inflammatory and antioxidant components(Reference Kris-Etherton, Hu and Ros13–Reference Barbour, Howe and Buckley15). The high-oleic peanut cultivar contains about 83·0 % of MUFA from which approximately 80·0 % are oleic fatty acid(Reference Barbour, Howe and Buckley15,Reference Moreira Alves, Boroni Moreira and Macedo16) . This fatty acid has shown antioxidant and anti-inflammatory activities, reducing the expression of NF-κB by the activation of the AMP-activated kinase signalling pathway(Reference Salvadó, Coll and Gómez-Foix17). Scientific evidence indicates that the inclusion of moderate amounts of high-oleic peanuts in a diet can improve lipid profile, insulin sensitivity and body composition(Reference Barbour, Howe and Buckley15,Reference Moreira Alves, Boroni Moreira and Macedo16,Reference O’Byrne, Knauft and Shireman18) .
However, despite the health benefits attributed to peanuts, few clinical studies available in the literature have evaluated the direct effect of daily intake of high-oleic peanuts on inflammatory markers and oxidative status. Thus, the objective of this nutrition intervention study was to evaluate the impact of the daily intake of conventional and high-oleic peanuts, associated with a hypoenergetic diet on the inflammatory and oxidative status in overweight men.
Methodology
Subjects
All participants were recruited in the local community by advertisements, flyers and posters. Afterwards, they were submitted to nutritional screening and completed self-administered questionnaires about medical history, food intake and physical activity practice. The participants eligibility was assessed according to the following inclusion criteria: men; adults (age 18–50 years); overweight (BMI 26–35 kg/m2); non-smokers; without clinically diagnosed disorders, eating disorders or allergies, including to peanuts; do not taking lipid-lowering or anti-inflammatory medication and do not have a regular consumption of peanuts.
The present study has been approved by the ethics committee on human research of the Universidade Federal de Viçosa (protocol: 185/2011) and carried out in accordance with the Declaration of Helsinki. All participants provided written informed consent prior to inclusion in the study.
Study design
The present study is part of a randomised controlled three-arm parallel group study, designed to investigate the health effects of the high-oleic peanut intake within a hypoenergetic diet(Reference Moreira Alves, Boroni Moreira and Macedo16,Reference Alves, Moreira and MacEdo19,Reference Duarte Moreira Alves, Boroni Moreira and Silva Macedo20) . Briefly, the subjects participated in a 4-week randomised clinical trial, assigned in three parallel arm: control (CT; hypoenergetic diet), conventional peanut group (CVP, hypoenergetic diet plus 56 g/d conventional peanut) and high-oleic peanut group (HOP; hypoenergetic diet plus 56 g/d high-oleic peanuts). The allocation to treatment groups was conducted by a simple randomisation method. At baseline and after the 4-week intervention, the participants were submitted for an experimental day, during which anthropometric and postprandial measurements were taken.
On each experimental day (final and initial), the participants consumed a test meal at fasting state (within 15 min), according to the allocation group, and stayed at the laboratory for 4 h without intake of any other food. Peripheral blood samples were collected at fasting (10–12 h) and 60, 120 and 180 min after the test meal consumption. Subjects were required not to consume caffeine and alcohol and to maintain their physical activity levels and regular sleep–wake schedule (8 h/night) during 72-h before experimental days. During the intervention period, all participants followed a hypoenergetic diet (−250 kcal; −1045 kJ) with similar macronutrient distribution among the groups. Also, the participants received face-to-face nutrition counselling weekly. In this occasion, the peanut packages were distributed to the participants allocated in peanut groups (CVP and HOP). The study compliance was monitored by the return of not consumed peanut packets and evaluation of food records (applied at the beginning and end of the study). The blood samples were used to measure the changes in inflammatory and oxidative status markers.
Nutritional intervention
For the dietary prescription, the energy requirement of subjects was estimated using indirect calorimetry as previously described by Alves et al. (Reference Duarte Moreira Alves, Boroni Moreira and Silva Macedo20) and 250 kcal/d (1045 kJ/d) was restricted. All experimental diets provided 15 % of energy from protein, 30 % from fat and 55 % from carbohydrate. The CT diet did not include any peanuts, while the CVP and HOP diet included a daily portion of 56 g of conventional or high-oleic peanuts, respectively. The energy content provided by the daily peanuts portion was considered in the total energy of experimental diets. For the CT, the energy and macronutrient intake were adjusted with the food of the habitual diet. The peanut portion of 56 g was determined to meet the FDA recommendation about saturated fat disqualifying levels (up to 4 g saturated fat per food portion customarily consumed)(21). Participants were free to eat the peanut portion any time of the day. Also, they were asked to consume the whole portion at once. The portions of the conventional and high-oleic peanuts contained, respectively, 13·6 and 12·8 g of carbohydrates, 16·8 and 16·3 g of proteins, 24·0 and 24·7 g of fat and 5·0 and 5·5 g of dietary fibre. Oleic fatty acid represents 51·0 and 81·5 % of the total fat present in the conventional and high-oleic peanuts, respectively. The peanuts’ preparation was previously shown by Moreira Alves et al. (Reference Moreira Alves, Boroni Moreira and Macedo16).
Moreover, being an intervention study under free-living conditions, all the participants were instructed to use a self-selected exchange food list and do not intake any other oilseed/nuts during the intervention period. Before the baseline assessments and during the fourth-week intervention, the participants were also instructed to keep a 3-d dietary record (two nonconsecutive weekdays and one weekend day) for the compliance evaluation. Dietary data were analysed using Dietpro software (version 5.2i).
Test meal
In the initial and final experimental day, the participants consumed a test meal according to the allocation group. Each test meal consisted of a strawberry-flavoured milkshake with 56 g of high-oleic or conventional peanuts for the experimental groups and biscuit to the CT group. The test meals were prepared to provide 25 % of daily energy requirements and contained similar volume and macronutrient distribution (35 % carbohydrate, 16 % protein and 49 % fat relative to the total energetic value). The test meal preparation was previously described by Moreira Alves et al. (Reference Moreira Alves, Boroni Moreira and Macedo16).
Anthropometry and physical activity level
Anthropometrics measurements (height, weight, waist circumference, BMI) were collected at baseline and post-intervention. Height and weight were assessed in the standing position with the participants wearing light clothing. BMI was calculated as weight/height2 (kg/m2). Waist circumference was measured using an inelastic flexible tape positioned midway between the lower rib margin and the iliac crest. The physical activity level of each subject was evaluated by the International Physical activity Questionnaire and classified according to FAO/WHO/UNU(Reference Ainsworth, Haskell and Whitt22–24).
Blood sampling
Fasting and postprandial (60, 120 and 180 min) blood samples were collected into tubes precoated with EDTA. For this, a catheter was introduced into an antecubital vein by a trained phlebotomist at baseline and post-intervention. The blood samples were centrifuged (2200 g, 15 min, 4°C), aliquoted and stored at −80°C for further analysis.
Inflammatory and oxidative status markers analyses
The inflammatory and oxidative status markers were assessed on fasting and postprandial state. As previously described(Reference Moreira Alves, Boroni Moreira and Macedo16), an automated analytical method was used to measure C-reactive protein concentration. For the determination of IL-2, IL-4, IL-6, IL-10, IL-17A, IFN-γ and TNF-α cytokines plasma concentrations, the Human cytokine kit Th1/Th2/Th17 CBA (BD Biosciences) was used, according to instructions of the manufacturer by flow cytometry technique (BD FACSort™ cytometer; BD Immunocytometry Systems). The data were analysed using matrix FCAP Array Software version 3.0 (BD Biosciences), and the values were expressed in pg/ml.
Oxidative status markers were measured in plasma samples by colorimetric methods. Malondialdehyde was determined in duplicate, by the measurement of thiobarbituric acid reactive substances, described by Buege & Aust(Reference Buege and Aust25). Nitric oxide concentration was determined in duplicate using the Griess reagent according to Grisham et al. (Reference Grisham, Johnson and Lancaster26). The total activity of superoxide dismutase enzyme was determined in triplicate following the method described by Marklund & Marklund, and your activity was expressed as U of superoxide dismutase enzyme/l(Reference Marklund and Marklund27). The enzymatic activity of glutathione S-transferase was determined as described by Habig et al. (Reference Habig, Pabst and Jakoby28). The glutathione S-transferase activity was expressed as µmol/min per g.
Statistical analysis
Statistical analysis was conducted using SPSS 22.0 for Windows (SPSS, Inc.). Data are expressed as mean values with their standard errors. The Shapiro–Wilk test was performed to check the normality of variables. Power analyses were calculated by the analyst procedures of the statistical analysis system considering IL-10 and TNF-α as the primary outcomes. It was indicated that a sample of twenty-one per group would permit detection of a 5 % change of IL-10 and TNF-α with 99 % of power at the 5 % level of probability. For all data analyses, the differences were considered statistically significant for P < 0·05. To evaluate the postprandial cytokine responses, the AUC was calculated through the trapezoidal method by the Excel program (Microsoft ® Excel 2013). Among the groups, variable changes (final fasting measurements – baseline fasting measurements) were compared by one-way ANOVA followed by Tukey’s post hoc test or using the non-parametric Kruskal–Wallis test followed by Dunn’s post hoc test. To compare differences between baseline and post-intervention within the groups, pairwise tests were performed (paired t test or Wilcoxon).
Results
From seventy-six randomised subjects, sixty-four completed the study (Fig. 1), all in compliance to study protocol. The mean of age and BMI was 27 (sem 0·9) years and 29·76 (sem 0·3) kg/m2, respectively. Of the subjects, 61 % (n 39) were overweight, and the rest were obese. At baseline, anthropometric characteristics, energy intake, inflammatory markers and oxidative stress did not differ among the groups (Table 1).
Fig. 1. Flow diagram of enrolment, randomisation, withdrawals and follow-ups of the study subjects.
Table 1. Clinical and biochemical characteristics of the participants according to the experimental group at baseline
(Mean values with their standard errors)
CT, control group; CVP, conventional peanut group; HOP, high-oleic peanut group; NO, nitric oxide; MDA, malondialdehyde; GST, glutathione S-transferase; hs-CRP, high-sensitivity C-reactive protein.
* P value column refers to differences among groups (ANOVA or Kruskal–Wallis test followed by Tukey or Dunn’s test, respectively).
After intervention, body weight reduction (CT −2·2 (sem 0·3) kg, P < 0·001; CVP −1·57 (sem 0·23), P < 0·001, HOP −1·58 (sem 0·31), P < 0·001) was not different among the groups (P = 0·860). A similar result was verified for waist circumference (CT −2·0 (sem 0·3), P < 0·001; CVP −2·1 (sem 0·4), P < 0·001; HOP −1·2 (sem 0·2), P < 0·001). The energy intake did not differ among the experimental groups at 4-week intervention (CT −291·0 (sem 195·8) kcal (−1217·5 (se 819·2) kJ); CVP −275·7 (sem 258·0) kcal (−1077·1 (se 1078·4) kJ); HOP −212·0 (sem 163·7) kcal (−886·1 (se 684·2) kJ), P = 0·542). As expected, the HOP group had a higher MUFA intake (CT −6·6 (sem 2·1) g; CVP 5·0 (sem 3·4) g; HOP 17·8 (sem 5·5) g, P < 0·001). On the other hand, total lipid intake was lower in CT group (CT −17·9 (sem 9·6) g; CVP −0·3 (sem 11·2) g; HOP 8·2 (sem 12·6) g, P < 0·001), which also show lower PUFA intake (CT −4·8 (sem 2·2) g; CVP 0·9 (sem 3·4) g, HOP −1·9 (sem 1·5) g, P < 0·021). The other nutrients carbohydrate, protein, SFA and fibre were similar among groups after the intervention (data not shown). Furthermore, there was no difference between groups for physical activity levels (P = 0·876). Subjects did not change their physical activity level in comparison with baseline (CT, P = 1·0; CVP, P = 0·73; HOP, P = 0·84), and no difference among groups was observed (P = 0·97).
The fasting concentrations and postprandial responses of IL-17A, IL-10, IL-6, IL-4, TNF and C-reactive protein did not show significant differences among the experimental groups at the end of the intervention (Table 2) (Fig. 2). In the baseline assessments, for most of the volunteers (IFN-γ: 93·4 %, n 59 and IL-2: 95·3 %, n 61), IFN-γ and IL-2 cytokines concentrations were below the level of detection of used kit and were excluded from the statistical analysis. Similarly, the peanut consumption was not able to modulate the glutathione S-transferase and superoxide dismutase enzyme activity, as well as nitric oxide concentrations, within or among the group’s comparison (P > 0·05) in the 4th week. However, malondialdehyde fasting concentration reduced significantly in the CT group compared with the baseline (P = 0·020) and among groups (P = 0·002) (Fig. 3).
Table 2. Change (fasting values at week 4 – fasting baseline values) in inflammatory markers after intervention according to the experimental group
(Mean values with their standard errors)
CT, control group; CVP, conventional peanut group; HOP, high-oleic peanut group; hs-CRP, high-sensitivity C-reactive protein.
* P value column refers to differences between groups (Kruskal–Wallis test followed by Dunn’s test).
† Significant difference between final and baseline assessment within groups (P < 0·05; Wilcoxon test).
Fig. 2. Postprandial response of cytokines according to the experimental group. (A) IL-17A; (B) TNF; (C) IL-10; (D) IL-6; (E) IL-4. Empty bars indicate initial AUC, and striped bars indicate final AUC. Values are means, with their standard errors represented by vertical bars. The cytokines did not show difference between experimental groups. * Significant difference between final and baseline assessment within groups (P < 0·05; Wilcoxon test). CT, control group; CVP, conventional peanut group; HOP, high-oleic peanut group.
Fig. 3. Fasting oxidative stress markers. (A) Nitric oxide (NO); (B) malondialdehyde (MDA); (C) superoxide dismutase (SOD); (D) glutathione S-transferase (GST). Empty bars indicate initial mean, and striped bars indicate final mean. Values are means, with their standard errors represented by vertical bars. a,b Mean values with unlike letters were significantly different (P<0·05; ANOVA or Kruskal–Wallis test followed by Tukey or Dunn’s test, respectively). * Significant difference between final and baseline assessment within groups (P < 0·05; paired t test or Wilcoxon test). CT, control group; CVP, conventional peanut group; HOP, high-oleic peanut group.
Discussion
To our knowledge, this is the first randomised clinical trial to verify the effects of high-oleic peanut consumption on inflammatory and oxidative status markers in overweight men. The dietary records assessment and the count of returned peanut bags consumed by the participants revealed that they had good adherence to the dietary intervention. The results of the present study demonstrate that daily consumption of high-oleic or conventional peanut within a hypoenergetic diet did not modify the inflammatory or oxidative status in overweight men.
Unhealthy changes in lifestyle and diet have resulted in the obesity increase, which is associated with inflammation and oxidative stress(Reference Marseglia, Manti and D’Angelo29,Reference Ellulu, Patimah and Khaza’ai30) . Previous studies have supported that excessive body fat induces TH17 proinflammatory cell proliferation and increase in the IL-17A blood concentration(Reference Ahmed and Gaffen31,Reference Chehimi, Vidal and Eljaafari32) . This cytokine has been associated with the induction of tissue inflammation and possibly with chronic low-grade inflammation in obese individuals(Reference Zapata-Gonzalez, Auguet and Aragonès33). The role of IL-4 is not fully understood in the inflammatory process(Reference Ratthé, Ennaciri and Garcês Gonçalves34). Some evidence showed that IL-4 might be involved in lipid and glucose metabolism, proinflammatory chemokines regulation and inflammatory cell recruitment(Reference Ratthé, Ennaciri and Garcês Gonçalves34–Reference de Vries, Carballido and Aversa37). Both cytokines were not modified by peanut consumption after the intervention. Contrary to our results, Rocha et al. demonstrate that MUFA high-fat meal consumption leads to a significant reduction in IL-17A postprandial response in healthy women with a high percentage of body fat(Reference Rocha, Lopes and da Silva38). Similarly, an in vitro study demonstrated an increase in IL-4 concentration after incubation with oleic acid, but not with palmitoleic acid(Reference Passos, Alves and Momesso39). Monocytes extracted from healthy men exhibit a higher concentration of IL-4 after acute consumption of a fat-enriched meal with MUFA and PUFA in comparison with the meal rich in SFA(Reference Naranjo, Garcia and Bermudez40). The explanation for these results is unclear; IL-17A and IL-4 response in overweight patients is largely unexplored, especially after the nutritional intervention. Besides, kinetic mechanisms and the behaviour of IL-17A and IL-4 after a lipid stimulus are not known yet.
For IL-10, TNF, IL-6 and C-reactive protein, no changes were observed in fasting concentration or postprandial response after peanuts consumption. However, some studies have shown that acute or chronic consumption of oilseeds increases IL-10 concentration(Reference Jiang, Jacobs and Mayer-Davis41,Reference Salas-Salvadó, Casas-Agustench and Murphy42) . Also, contrary to our results, Richard et al. (Reference Richard, Couture and Desroches43) verified that men with the metabolic syndrome who followed the Mediterranean Diet, with high amounts of MUFA, PUFA and polyphenols, showed lower TNF fasting concentration in plasma. Similar results have been observed by other studies that evaluated the MUFA effect on TNF-α concentration(Reference Serrano–Martinez, Palacios and Martinez–Losa44,Reference Arpón, Riezu-Boj and Milagro45) .
Nevertheless, studies evaluating the effect of nut consumption on inflammatory markers have observed conflicting results(Reference Tey, Gray and Chisholm46). Although observational studies have shown anti-inflammatory effect associated with nuts consumption(Reference Yu, Malik and Keum47), clinical trials have failed to verify this result consistently. Barbour et al. showed that intake of 56–84 g of high-oleic peanut for 12 weeks by healthy subjects did not modify C-reactive protein concentrations. Other studies with walnut(Reference Ros48–Reference Aronis, Vamvini and Chamberland51), almond(Reference Damasceno, Pérez-Heras and Serra49,Reference Kurlandsky and Stote52) , pistachio(Reference Sari, Baltaci and Bagci53), hazelnut(Reference Balaban Yucesan, Orem and Vanizor Kural54) and mixed nuts(Reference Casas-Agustench, López-Uriarte and Bullo55) have also not observed improvement in inflammatory markers. MUFA – especially oleic fatty acid – acts as an anti-inflammatory by acting on AMP-activated kinase phosphorylation, which inhibits NF-κB activation inhibiting the inflammatory process(Reference Salvadó, Coll and Gómez-Foix17,Reference Harvey, Walker and Xu56) . Taken together, this evidence highlights the complexity involved in the relationship between inflammation, overweight and diet. Only add MUFA-rich food to the habitual diet without other interventions in lifestyle seems not enough to improve inflammatory status in overweight and obese individuals under free-living conditions.
Besides low-grade chronic systemic inflammation, the oxidative stress is also a disturbance frequently observed in obesity(Reference Marseglia, Manti and D’Angelo29,Reference Huang, McAllister and Slusher57) . This condition is influenced by the activation of the innate immune system in adipose tissue, which promotes the pro-inflammatory status and oxidative stress and triggers a systemic acute-phase response(Reference Marseglia, Manti and D’Angelo29). Also, the oxidative stress is associated with an irregular production of adipokines, which contributes to the development of obesity-associated co-morbidities(Reference Huang, McAllister and Slusher57).
The lipid peroxidation is involved in a variety of chronic diseases and has malondialdehyde – a product of the peroxidation of PUFA – as one of its final products(Reference Frijhoff, Winyard and Zarkovic58). Unexpectedly, the malondialdehyde showed significant reduction in the CT group. One possible explanation includes the significant reduction in the PUFA consumption observed in this group, which are known to be more susceptible to lipid peroxidation(Reference Halvorsen and Blomhoff59,Reference Albert, Cameron-Smith and Hofman60) . Despite peanut being the largest l-arginine source(Reference Arya, Salve and Chauhan61), after the 4-week intervention, the peanut consumption did not modify nitric oxide concentration. Studies that evaluate the enzymatic activity of superoxide dismutase enzyme and glutathione S-transferase after oilseeds intervention are still scarce. We believe that the constant supply of non-enzymatic antioxidants by the daily peanuts intake may have contributed to the antioxidant status equilibrium and prevented the free radicals increase. Thus, there was neither oxidative products formation nor stimulus for the increase in activity of antioxidant enzymes. Also, most volunteers of the present study had no obesity-associated co-morbidities, which may be associated with an antioxidant status balance. In this way, the impact of peanut consumption on oxidative status may have been attenuated, since other studies with nuts consumption seem to improve the oxidative stress mainly in subjects with higher imbalance in oxidative status(Reference Li, Jia and Chen62).
There are some limitations to the present study that should be mentioned. The non-evaluation of phenolic compounds present in peanuts stands out as a limiting factor since they might interfere in inflammatory and oxidative stress markers(Reference Pandey and Rizvi63,Reference Umeno, Horie and Murotomi64) . Although food consumption, peanut intake and physical activity have been well controlled, any biomarkers of peanut intake were assessed. Future studies with this evaluation may be of greater utility. The short time of intervention may be another reason for the limited beneficial effect of peanut consumption. In addition, these results may not be generalisable to women because the sample consisted of men. Furthermore, the influence of the dietary intervention on IFN-γ and IL-2 was not possible to be measured.
In conclusion, the daily high-oleic peanut consumption within a hypoenergetic diet did not modify the plasma inflammatory markers in overweight men. Furthermore, the oxidative status markers remained unchanged after peanut consumption. Thus, more studies are needed to evaluate whether peanuts intake associated with habitual diet or specific dietary patterns might improve the antioxidant and anti-inflammatory status in overweight subjects.
Ethical statement
The authors declare that all protocols in the present study were performed in accordance with the ethical standards of the institutional research committee and Helsinki declaration.
Acknowledgements
The authors are grateful to all those who participated in the laboratory carrying out the work and who cooperated in data collection and analysis, especially to Ana Paula Boroni Moreira, Neuza Maria Brunoro Costa and Rita de Cássia Gonçalves Alfenas. They also thank the Instituto Agronômico de Campinas and CAP agroindustrial who donated the peanuts for the study.
The CAPES Foundation provided research grant to APSC. H. H. M. H. and J. B. are CNPq fellows. The present project was supported by Brazilian Government Organization FAPEMIG (CDS – APQ-00771-15).
R. D. M. A. designed the research; A. P. S. C. and L. L. d. O. conducted the analyses; A. P. S. C. wrote the manuscript; J. B., H. H. M. H., R. D. M. A. and L. L. d. O. critically revised the manuscript. All authors read and approved the final manuscript.
There are no conflicts of interest.
