The additional effects of a probiotic mix on abdominal adiposity and antioxidant Status: A double-blind, randomized trial

Authors


  • Funding agencies: The study was supported by the Fundação de Amparo à Pesquisa do Estado de Goiás (FAPEG), Brazil (grant no. 201200544230609).

  • Disclosure: The authors declared no conflict of interest.

  • Author contributions: ACG: conception and design of the study, acquisition of data, analysis and interpretation of data, drafting the manuscript; RGMS: conception and design of the study, acquisition of data; PBB and TLNG: conception and design of the study, acquisition of data, revising critically for important intellectual content; POP: analysis and interpretation of data; and JFM: revising critically for important intellectual content, final approval of the version to be submitted. All authors read and approved the final manuscript.

  • Clinical trial registration: www.ensaiosclinicos.gov.br, U1111-1137-4566.

Abstract

Objective

To investigate whether a probiotic mix has additional effects when compared with an isolated dietary intervention on the body composition, lipid profile, endotoxemia, inflammation, and antioxidant profile.

Methods

Women who had excess weight or obesity were recruited to a randomized, double-blind trial and received a probiotic mix (Lactobacillus acidophilus and casei; Lactococcus lactis; Bifidobacterium bifidum and lactis; 2 × 1010 colony-forming units/day) (n = 21) or placebo (n = 22) for 8 weeks. Both groups received a dietary prescription. Body composition was assessed by anthropometry and dual-energy X-ray absorptiometry. The lipid profile, lipid accumulation product, plasma fatty acids, lipopolysaccharide, interleukin-6, interleukin-10, tumor necrosis factor-α, adiponectin, and the antioxidant enzymes activities were analyzed.

Results

In comparison with the dietary intervention group, the dietary intervention + probiotic mix group showed a greater reduction in the waist circumference (−3.40% vs. −5.48%, P = 0.03), waist-height ratio (−3.27% vs. −5.00%, P = 0.02), conicity index (−2.43% vs. −4.09% P = 0.03), and plasma polyunsaturated fatty acids (5.65% vs. −18.63%, P = 0.04) and an increase in the activity of glutathione peroxidase (−16.67% vs. 15.62%, P < 0.01).

Conclusions

Supplementation of a probiotic mix reduced abdominal adiposity and increased antioxidant enzyme activity in a more effective way than an isolated dietary intervention.

Introduction

Obesity is considered a low-grade chronic and systemic inflammatory disease [1] and results from complex interactions between genes and environmental factors, such as diet, food components, and lifestyle. It is characterized by increased visceral white adipose tissue mass and associated with a greater propensity to develop type 2 diabetes, hypertension, dyslipidemia, cardiovascular disease, and cancer [2].

Due to the comorbidities associated with obesity, great efforts have been made to develop treatment strategies for weight reduction. Dietary manipulation remains the first-line treatment for people with obesity [3]. However, evidence suggests that the gut microbiota are involved in the development of obesity and that their modulation may aid in the treatment of this disease.

Manipulating the gut microbiota with probiotics affects the host metabolism [4]. Probiotics are defined as “live microorganisms which when administered in adequate amounts confer a health benefit to the host” [5]. Certain strains of Lactobacillus and Bifidobacterium seem to have beneficial effects on metabolism, improving glucose homeostasis and inflammation, reducing body weight and fat mass (FM) [4], and protecting against oxidative stress [6]. These effects may be related to a reduction in lipopolysaccharide (LPS) translocation accompanied by a decrease in inflammatory cytokines, but these mechanisms have yet to be elucidated. Furthermore, it has been hypothesized that different microbial species might modulate the fatty acid composition in tissues crucial for host metabolism, increasing the concentrations of eicosapentaenoic acid and docosahexaenoic acid, two omega-3 (ω-3) polyunsaturated fatty acids with important anti-inflammatory and lipid-lowering properties [7]. This study assessed whether a probiotic mix has additional effects when compared with an isolated dietary intervention (DI) on (1) body composition and lipid profile, (2) metabolic endotoxemia and chronic inflammation, and (3) the antioxidant profile.

Methods

Participants

The participants were identified through advertisement flyers and enrolled at the Clinics Hospital and Nutrition College at the Federal University of Goiás in May 2012. Eligible participants were women with excess weight or obesity and were 20 to 59 years old with a BMI (in kg/m2) from 24.9 to 40. The exclusion criteria were BMI (in kg/m2) values less than 24.9 and higher than 40, participation in a food restriction program or in a diet, the presence of an acute disease requiring treatment, chronic immunologic diseases, thyroid diseases, pregnancy or plans to become pregnant, gastrointestinal surgery, hormone replacement therapy, antibiotic treatment or treatment with any drug known to affect the immune response, and regular consumption of probiotic products and fermented food. We also excluded chronic alcoholics and subjects who used insulin or nutritional supplements. Participants were instructed to refrain from eating fermented dairy products as well as products containing probiotics from the screening until the conclusion of the study.

Ethical approval was obtained from the Ethics Committee of the Federal University of Goiás (reference number 044/2012). The study was registered at http://www.ensaiosclinicos.gov.br/as U1111-1137-4566. All participants were informed about the study orally and in writing and gave their written informed consent to participate.

Study design

The study was a randomized, double-blind, placebo-controlled, two-arm, parallel-group study in women with excess weight or obesity. The intervention lasted 8 weeks, and the evaluations were performed at two time points, at the baseline and at the conclusion of the study. The intervention period was selected based on clinical trials that evaluated the effect of administration of probiotics on other comorbidities associated with obesity. These studies showed that 4 weeks of probiotic intervention is sufficient to cause benefits, as evidenced by the meta-analyzes of Shimizu et al. [8] and Ruan et al. [9].

Random assignment and blinding

Potential female subjects were screened for eligibility and randomly allocated 1:1 into two groups: DI or DI plus probiotic mix (DI + P). The study staff allocated randomization numbers consecutively to the subjects in the order that they attended the randomization visit. The randomization list was provided by an independent research group not involved in the study using the Excel program 1997 to 2003 (Microsoft, Redmond, WA, EUA). The blinding code was provided to the investigators after the statistical analyses were completed.

Viability of strains

The resistance to acidic pH and bile salts was evaluated to test the viability of bacteria in the gastrointestinal tract. The acid tolerance of probiotic strains was studied according to Mishra and Prasad [10] with minor modifications. The acid solutions were prepared with potassium chloride (2 g/L) and pepsin (3 g/L), adjusting the pH, if necessary, using 1N solutions of HCl and NaOH. Active cultures of bacteria were transferred to 9 mL of each pH solution and subsequently subjected to shaking (150 rpm at 37°C) in a thermoshaker (Tecnal TE-420) for 120 min.

The resistance of the strains to bile was studied according to Mishra and Prasad [10], with slight modifications. Active cells were added to 0.3% bile salt solutions (Oxoid) and shaken (150 rpm at 37°C) in a thermoshaker (Tecnal TE-420) for 6 h. After both 3 and 6 h, an aliquot (1 mL) of the culture solution with bile salts was removed and inoculated into MRS broth for a 24-h growth at 37°C, under anaerobic conditions, and then the colony-forming units (CFU) were measured. Analyses were performed in duplicate.

The aforementioned methods were repeated twice at 12-month intervals and applied to the same batch of product stored at room temperature (25 ± 2°C). The mix exhibited satisfactory growth and stability during the 12 and 24 months of analysis, maintaining an average population of all strains above 7 × 1010 CFU/g of product and above 2.3 × 1010 CFU/g after exposure to acid and bile salts.

Intervention/procedures

The sachet with probiotic mix contained maltodextrin (48.3%), modified starch (24.21%), xylitol (24.21%), silicium dioxide (0.97%), and 1 × 109 CFU of each of the probiotic strains: Lactobacillus acidophilus LA-14, Lactobacillus casei LC-11, Lactococcus lactis LL-23, Bifidobacterium bifidum BB-06, and Bifidobacterium lactis BL-4 (Danisco®). The women consumed four sachets daily before breakfast for 8 weeks, totaling 2 × 1010 CFU/day. The placebo product was similar to the active product in appearance, smell, and taste. Participants were instructed to ingest four sachets dissolved in liquid at room temperature each day after waking up. Adherence to treatment was assessed by weekly phone calls, monthly during regularly scheduled appointments, and by counting empty sachets.

In the beginning of the study, participants received the prescription of a normocaloric diet (25 to 30 kcal/kg) calculated by AVANUTRI, version 3.1.5, as well as guidelines for healthy eating. The prescription consisted of six meals, containing ingredients amounts, way of cooking, and a food substitutes list. The diet was isocaloric and contained the same quantity of protein, lipids, and carbohydrates between groups. Participants were also instructed to maintain their usual exercise program for the entire study. Physical activity was assessed at both the beginning and the end of the study using the International Physical Activity Questionnaire (short form, last 7 days, self-administered format) [11]. The metabolic equivalent tasks (METs) were calculated by International Physical Activity Questionnaire evaluation as follows:

  1. Walking MET-minutes per week = 3.3 × walking minutes × walking days
  2. Moderate MET-minutes per week = 4.0 × moderate-intensity activity minutes × moderate-intensity days
  3. Vigorous MET-minutes per week = 8.0 × vigorous-intensity activity minutes × vigorous-intensity days
  4. Total physical activity MET-minutes per week = sum of walking + moderate + vigorous MET-minutes per week scores

To transform the MET values in kilocalories (kcal), the following equation was used: (MET × weight)/60 min.

Follow-up

Each follow-up visit consisted of data collected through a standardized medical history, 3-day food records, anthropometry, body composition, and blood collection.

Assessment of food intake

At the beginning and at the end of the study, dietary intake was assessed using the 24-h dietary recall method, and participants were instructed to record their daily dietary intake for 3 days, including a weekend day. Dietary caloric intakes and macronutrient values were analyzed using AVANUTRI software.

Anthropometry and body composition

The height of the subjects was measured during the selection phase to the nearest 0.5 cm with a stadiometer (Model Standard, Sanny). Weight was measured, after voiding, with participants wearing light clothing to the nearest 0.1 kg on a digital scale (Filizola, Brazil). Waist circumference was measured on undressed subjects at the midpoint between the lower margin of the last palpable rib and the top of the iliac crest.

Dual-energy X-ray absorptiometry (DXA) assessments of FM, fat-free mass, and body fat percentage as well as android and gynoid fat were conducted using a GE Lunar densitometer (DPX NT®, GE) with enCORE 2011 software (version 13.60, GE Healthcare). The coefficient of variation (CV) for the DXA tests of muscle and FM were 0.75% and 1.03%, respectively. Based on anthropometric data, the body adiposity markers of interest were estimated using the formulas described below:

  1. BMI = weight (kg)/height2 (m)
  2. Waist–height ratio = waist circumference (cm)/height (cm)
  3. Conicity index = waist circumference (cm)/0.109 x √weight(kg)/height(m)

Blood sampling and laboratory methods

Blood samples were drawn for each participant from the antecubital vein in the arm after a 12-h fast. The serum samples were separated from the whole blood by centrifugation at 3,500 rpm for 10 min at 4°C (Combate, C.E.L.M) and frozen at −80°C until analysis. Uric acid, γ-glutamyl transferase, alanine aminotransferase, aspartate aminotransferase, urea, creatinine, serum total cholesterol (TC), high-density lipoprotein (HDL) cholesterol, and triglycerides were determined by automated enzymatic methods on a VITROS® 950 Chemistry System (Johnson and Johnson). Glycated hemoglobin was measured in the whole blood by turbidimetric methods with automatic equipment (Analyzer A25, Biosystems), low-density lipoprotein (LDL) cholesterol concentrations were calculated by the Friedewald equation, and Castelli's Risk Indexes were calculated as described below [12]:

  1. Castelli's Risk Index I (CRI I) = TC/HDL
  2. Castelli's Risk Index II (CRI II) = LDL/HDL

The lipid accumulation product (LAP) was obtained by the formula: LAP = (waist circumference [cm] – 58) × triglyceride concentration [mmol/L]) [13].

To determine the plasma fatty acid composition, the samples were derivatized using direct esterification, as described by Shirai et al. [14], and their composition was determined by gas chromatography (Agilent 7890A gas chromatograph, Agilent Technologies Inc., Santa Clara). A fused silica capillary column (J&W DB-23 Agilent 122-236; 60 m × 250 mm inner diameter) was used for injection. High-purity helium was used as the carrier gas at a flow rate of 1 mL/min with a 50:1 split injection. The program for column temperature ran as follows: started at 80°C, heated at a rate of 5°C/min up to 175°C, followed by another gradient of 3°C/min to 230°C, and this temperature maintained for 5 min. The injector and detector temperatures were 250°C and 280°C, respectively. The fatty acids were identified by comparing the retention times with those of a purified standard mixture of four fatty acid methyl esters (Sigma Chemical Co.: 4-7801; 47085-U; 49453-U; and 47885-U). The results were expressed as percentage of total fatty acids.

Inflammatory cytokines were determined in duplicate in 25 μL of plasma using immunoassays multiplex kit (Milliplex® MAP) and Luminex® technology (Millipore), according to the manufacturer's instructions. The Human Cytokine/Chemokine Magnetic Bead Panel kit allowed the simultaneous quantification of the following biomarkers: interleukin (IL)−6, IL-10, and tumor necrosis factor (TNF)-α, and the Human Adipokine Magnetic Bead Panel 1 kit allowed quantification of adiponectin. The CV% of the assay corresponded to the following: IL-6 (intra-assay CV% = 2.0; inter-assay CV%=18.3); IL-10 (intra-assay CV% = 1.6; inter-assay CV% = 16.8); TNF-α (intra-assay CV% = 2.6; inter-assay CV% = 13.0); and adiponectin (intra-assay CV% = 4.0; inter-assay CV% = 10.0).

The superoxide dismutase (SOD), catalase, and glutathione peroxidase (GPx) activities of erythrocyte lysates was determined using a microassay [15] by a multiwavelength detection microplate reader (BioTek, Synergy HT, Winooski, VT). The serum malondialdehyde concentration was determined using the thiobarbituric acid method described by Bilici et al. [16] with modifications.

The LPS levels were determined in duplicate by the limulus amebocyte lysateassay according to the manufacturer's protocol (LAL QCL-1000™, Basal, Switzerland) in plasma samples diluted 1/5 with endotoxin-free water and heated to 70°C for 10 min to inactivate plasma proteins.

Statistical analysis

The power calculation was based on the results of a related study [17] with the assistance of the G-Power software (version 3.0.10). The difference in waist circumference between groups was the primary outcome. The power calculation indicated that 17 subjects per were required (95% power; 5% type I error) to detect a difference of −1.2 (−1.5 to −0.9) cm in waist circumference. Assuming a 40% dropout rate, target enrollment was set at 30 per group.

To ensure a normal distribution of variables, histogram and Kolmogrov-Smirnov tests were applied. The results are expressed as the mean ± standard deviation or median. We used paired-samples t-tests to identify within-group differences (before and after intervention). Student's t-test was used to detect differences between the two groups (DI and DI + P). Wilcoxon's rank test was used for skewed variables. Potential confounders (covariates) that could affect biochemical measures and body composition were examined in the entire group. Significant covariates were identified using multiple linear regression models with backward elimination of those that were nonsignificant. Covariates remained in the model at P < 0.05. Macronutrient intakes were adjusted for energy intake, and total cholesterol and HDL were adjusted for age (P < 0.05; data not shown). The effect of the dietary intervention plus probiotic mix on the variables measured was examined using ANCOVA with adjustment for the screening/baseline observation. The changes in the relationships between the different fatty acid intakes and their plasma concentrations were examined using Pearson's or Spearman's correlation coefficient. P < 0.05 was considered statistically significant. All statistical analyses were performed using STATA, version 12 (StataCorp, College Station, TX). Outcome analyses were carried on intention-to-treat (adjusted by last-observation-carried-forward analysis).

Results

Patient screening, enrollment, and retention by treatment group are shown in Figure 1. The baseline body composition (Table 1) and food intake (Table 2) of the two groups were similar. No adverse events were reported by groups. Blood test results for uric acid, γ-glutamyl transferase, alanine aminotransferase, aspartate aminotransferase, urea, and creatinine did not show physiological differences throughout the study (data not shown). The participants showed no change in the level of physical activity (DI: M0, 5,181.54 kcal/wk; M2, 4,448.99 kcal/wk, and DI + P: M0, 5,386.51 kcal/wk; M2, 5,155.00 kcal/wk). Moreover, no differences between groups were observed (P > 0.05).

Figure 1.

Participant flow through the study. Values are expressed as the number of participants.

Table 1. Body composition before and after treatment with dietary intervention or a dietary intervention plus probiotic mix in women with overweight and obesity
 Dietary intervention (n = 22)Dietary intervention + probiotic mix (n = 21)Intervention effect
BaselineWeek 8Mean changePaBaselineWeek 8Mean changePaPbEffect (95% CI)Pc
  1. Values are presented as mean ± standard deviation.

  2. a

    Difference between baseline and end point. P value obtained from paired t-test/Wilcoxon matched-pairs signed-rank test for the within-group comparisons.

  3. b

    Homoscedasticity test between groups on baseline.

  4. c

    Obtained from unpaired Student's t-test or Mann–Whitney test, as statistical difference between changes (DI vs. DI + P). The effect of the probiotic mix associated with dietary intervention on the variables measured was examined using ANCOVA with adjustment for the screening/baseline observation.

  5. FFM, free-fat mass; FM, fat mass; WC, waist circumference; WHR, waist-to-height ratio.

BMI (kg/m2)33.34 ± 4.6932.61 ± 4.53−0.720.0031.70 ± 3.9031.24 ± 3.96−0.450.010.41−0.49 (−3.24 to 2.25)0.71
Weight (kg)83.55 ± 13.4482.59 ± 13.00−0.950.0276.58 ± 9.9475.60 ± 10.24−0.980.020.18−3.64 (−11.24 to 3.95)0.33
WC (cm)97.50 ± 10.4094.18 ± 10.24−3.320.0093.95 ± 8.3788.80 ± 7.26−5.140.000.331.81 (0.13 to 3.50)0.03
Body fat (%)48.82 ± 4.3948.03 ± 4.18−0.790.0248.56 ± 4.2847.37 ± 5.00−1.190.000.91−1.09 (−3.91 to 1.72)0.43
FM (kg)39.73 ± 8.2339.05 ± 7.35−0.680.2936.30 ± 7.3234.96 ± 7.52−1.330.000.60−1.93 (−7.02 to 3.15)0.44
FFM (%)49.68 ± 4.3350.36 ± 4.090.680.0449.79 ± 4.0950.92 ± 4.761.130.000.79−0.94 (−1.79 to 3.69)0.48
FFM (kg)41.37 ± 6.7441.46 ± 6.530.090.7737.86 ± 3.6538.20 ± 4.200.330.260.00−1.13 (−4.68 to 2.41)0.52
Android (%)54.36 ± 3.3553.05 ± 3.23−1.310.0054.80 ± 3.3653.50 ± 4.14−1.300.020.980.03 (−2.32 to 2.39)0.97
Gynoid (%)53.98 ± 5.3152.75 ± 5.42−1.220.0053.95 ± 4.6653.13 ± 4.70−0.810.000.56−1.92 (5.12 to 1.26)0.23
WHR0.61 ± 0.060.59 ± 0.06−0.020.000.60 ± 0.060.57 ± 0.05−0.030.000.870.01 (0.00 to 0.02)0.02
Conicity index1.23 ± 0.071.19 ± 0.07−0.030.001.22 ± 0.071.16 ± 0.06−0.050.920.910.02 (0.00,0.04)0.03
Table 2. Dietary intake before and after treatment with dietary intervention or a dietary intervention plus probiotic mix in women with overweight and obesity
 Dietary intervention (n = 22)Dietary intervention + probiotic mix (n = 21)Intervention effect
BaselineWeek 8Mean changePaBaselineWeek 8Mean changePaPbEffect (95% CI)Pc
  1. Values are presented as mean ± standard deviation. Macronutrients were adjusted for energy intake.

  2. a

    Difference between baseline and end point. P value obtained from paired t-test/Wilcoxon matched-pairs signed-rank test for the within-group comparisons.

  3. b

    Homoscedasticity test between groups on baseline.

  4. c

    Obtained from unpaired Student's t-test or Mann–Whitney test, as statistical difference between changes (DI vs. DI + P).

  5. CHO, carbohydrates; SFAs, saturated fatty acids; MUFAs, monounsaturated fatty acids; PUFAs, polyunsaturated fatty acids.

Energy (kcal)1,451.86 ± 327.511,417.86 ± 228.09−34.000.651,420.94 ± 215.171,265.52 ± 50.05−155.420.010.07121.42 (−74.43 to 317.27)0.21
Protein (%)20.94 ± 5.4920.97 ± 5.670.020.9820.18 ± 8.5120.21 ± 6.670.030.980.0518.00 (13.05 to 22.94)0.69
CHO (%)57.25 ± 13.8355.18 ± 12.61−2.070.6157.11 ± 9.8352.21 ± 17.24−4.900.280.162.83 (−9.34 to 15.00)0.63
Total fat (%)26.38 ± 8.2625.22 ± 6.26−1.160.5331.79 ± 8.4128.44 ± 8.92−3.340.150.932.18 (−3.67 to 8.04)0.45
SFAs (%)34.68 ± 7.1233.00 ± 11.18−1.670.5331.85 ± 7.1427.66 ± 6.68−4.190.030.912.52 (−3.91 to 8.96)0.43
MUFAs (%)25.66 ± 6.8924.28 ± 8.58−1.380.5626.36 ± 6.0824.58 ± 6.50−1.770.280.610.38 (5.43 to 6.20)0.89
PUFAs (%)12.60 ± 5.2218.39 ± 9.005.790.0018.78 ± 9.5825.65 ± 12.486.870.010.00−1.07 (−7.40 to 5.25)0.73
Fiber (g)16.77 ± 5.1816.04 ± 5.92−0.730.5314.70 ± 5.0512.43 ± 4.57−2.260.180.911.53 (−2.52 to 5.60)0.44

Food intake and body composition

No difference was noted in FM (DI + P: −3.66%; DI: −1.71%, 95% CI: −7.02 to 3.15, P = 0.44) between groups, but in intragroup analysis, only DI + P reduced FM (P = 0.00). Participants taking the probiotic mix had a greater decrease in waist circumference (−3.40% vs. −5.47%, P = 0.03), waist-height ratio (−3.27% vs. −5.00%, P = 0.02), and conicity index (−2.43% vs. −4.09% P = 0.03) than the DI group (Table 1).

There was no difference between groups for energy or the percentages of fat, protein, carbohydrate, and fiber intake (Table 2).

Lipid profile, fatty acid composition, and glycated hemoglobin

No difference was noted in LDL (DI + P: −7.95%; DI: −3.76%, 95% CI: −0.20 to 0.51, P = 0.37), LAP (DI + P: −19.69%; DI: −10.61%, 95% CI: −11.41 to 22.53, P = 0.51), and Castelli's Risk Index I (DI + P: −6.30%; DI: 1.34%, 95% CI: −0.21 to 1.56, P = 0.13) and Index II (DI + P: −11.38%; DI: 3.97%, 95% CI: −0.58 to 0.9, P = 0.62) between groups (Table 3). Regarding fatty acid profile, no difference was noted in monounsaturated fatty acids (MUFAs) (DI + P: 31.11%; DI: 4.11, 95% CI: −9.72 to 3.55, P = 0.35), ω-3 fatty acids (DI + P: 95.86%; DI: −2.91%, 95% CI: −32.58 to 2.87, P = 0.09), and ω-6 fatty acids (DI + P: −13.53%; DI: 3.42%, 95% CI: −2.75 to 39.93, P = 0.08) between groups. Compared with the DI group, the DI + P group had decreased polyunsaturated fatty acids (PUFAs) (5.65% vs. −18.63%, P = 0.04) (Table 4). The saturated fat (r = −0.24, P = 0.12), monounsaturated fat (r = −0.08, P = 0.61), and polyunsaturated fat intake (r = −0.00, P = 0.99) after 8 weeks did not correlate with their respective plasma concentrations. There was no difference in glycated hemoglobin between groups.

Table 3. Blood lipid parameters and glycated hemoglobin before and after treatment with dietary intervention or a dietary intervention plus probiotic mix in women with overweight and obesity
 Dietary intervention (n = 22)Dietary intervention + probiotic mix (n = 21)Intervention effect
 BaselineWeek 8Mean changePaBaselineWeek 8Mean changePaPbEffect (95% CI)Pc
  1. Values are presented as mean ± standard deviation. Total cholesterol and HDL were adjusted for age.

  2. a

    Difference between baseline and end point. P value obtained from paired t-test/Wilcoxon matched-pairs signed-rank test for the within-group comparisons.

  3. b

    Homoscedasticity test between groups on baseline.

  4. c

    Obtained from unpaired Student's t-test or Mann–Whitney test, as statistical difference between changes (DI vs. DI + P). The effect of the probiotic mix associated with dietary intervention on the variables measured was examined using ANCOVA with adjustment for the screening/baseline observation.

  5. CRI, Castelli's Risk Index I; CRII, Castelli's Risk Index II; HbA1c, glycated hemoglobin; HDL, high-density lipoprotein; LDL, low-density lipoprotein; VLDL, very-low-density lipoprotein; LAP, lipid accumulation product; TC, total cholesterol; TG, triglyceride.

HbA1c (%)6.46 ± 0.855.40 ± 0.66−1.060.006.07 ± 0.425.00 ± 0.36−1.070.000.000.26 (−0.72 to 0.20)0.25
TC (mmol/L)5.09 ± 1.254.88 ± 1.17−0.200.235.30 ± 0.905.16 ± 0.82−0.130.320.09−0.07 (−0.51 to 0.36)0.64
HDL (mmol/L)3.06 ± 2.853.03 ± 2.90−0.030.682.08 ± 2.132.03 ± 2.15−0.050.340.350.02 (−0.16 to 0.20)0.82
LDL (mmol/L)3.19 ± 1.023.07 ± 0.91−0.120.443.52 ± 0.703.24 ± 0.68−0.280.000.100.15 (−0.20 to 0.51)0.37
VLDL (mmol/L)0.72 ± 0.400.67 ± 0.35−0.050.470.68 ± 0.260.73 ± 0.300.050.310.05−0.10 (−0.28 to 0.07)0.25
TG (mmol/L)1.60 ± 0.901.48 ± 0.77−0.110.481.50 ± 0.581.62 ± 0.660.110.310.05−0.22 (−0.62 to 0.16)0.24
CRI4.45 ± 0.934.51 ± 1.370.060.824.92 ± 1.104.60 ± 1.03−0.310.040.460.67 (−0.21 to 1.56)0.13
CRII2.77 ± 0.722.88 ± 1.280.100.693.25 ± 0.862.88 ± 0.86−0.370.000.410.18 (−0.58 to 0.95)0.62
LAP60.27 ± 37.2353.87 ± 30.40−6.390.2460.67 ± 35.7948.72 ± 18.12−11.950.040.885.55 (−11.41 to 22.53)0.51
Table 4. Distribution of plasma fatty acids (%) before and after treatment with dietary intervention or a dietary intervention plus probiotic mix in women with overweight and obesity
 Dietary intervention (n = 22)Dietary intervention + probiotic mix (n = 21)Intervention effect
BaselineWeek 8Mean changePaBaselineWeek 8Mean changePaPbEffect (95% CI)Pc
  1. Values are presented as mean ± standard deviation.

  2. a

    Difference between baseline and end point. P value obtained from paired t-test/Wilcoxon matched-pairs signed-rank test for the within-group comparisons.

  3. b

    Homoscedasticity test between groups on baseline.

  4. c

    Obtained from unpaired Student's t-test or Mann–Whitney test, as statistical difference between changes (DI vs. DI + P). The effect of the probiotic mix associated with dietary intervention on the variables measured was examined using ANCOVA with adjustment for the screening/baseline observation.

  5. SFAs, saturated fatty acids; MUFAs, monounsaturated fatty acids; PUFAs, polyunsaturated fatty acids; ω-3, omega-3; ω-6, omega-6.

SFAs43.20 ± 10.0537.97 ± 12.09−5.230.1835.41 ± 13.7336.90 ±14.971.490.650.05−3.93 (−13.80 to 5.92)0.42
MUFAs22.86 ± 7.4523.80 ± 8.720.940.7116.10 ± 32.9721.12 ± 9.285.010.040.96−3.08 (−9.72 to 3.55)0.35
PUFAs32.51 ± 11.4734.35 ± 16.351.840.6446.69 ± 18.4737.98 ±19.38−8.700.010.9713.85 (−2.53 to 30.24)0.04
ω-330.19 ± 22.9929.31 ± 22.250.880.6411.84 ± 8.2423.20 ± 23.7511.350.040.00−14.85 (−32.58 to 2.87)0.09
ω-671.98 ± 25.1274.44 ± 24.452.450.5590.29 ± 8.9978.07 ± 28.33−12.220.030.0318.58 (−2.75 to 39.93)0.08

Antioxidant enzymes and inflammatory markers

At the conclusion of treatment, no difference was noted in the activity of antioxidant enzyme SOD (DI + P: 36.44%; DI: 6.80%, 95% CI: −2.79 to 1.54, P = 0.56) between groups. Compared with the DI group, the DI + P group had increased GPx activity (−16.67% vs. 15.62%, P < 0.01) (Table 5). Compared with the DI group, the DI + P group had increased TNF-α (9.30% vs. −16.86%, P = 0.01) (Table 4). No changes were observed in cytokines and LPS concentrations (Table 5).

Table 5. Oxidative and inflammatory parameters before and after treatment with dietary intervention or a dietary intervention plus probiotic mix in women with overweight and obesity
 Dietary intervention (n = 22)Dietary intervention + probiotic mix (n = 21)Intervention effect
 BaselineWeek 8Mean changePaBaselineWeek 8Mean changePaPbEffect (95% CI)Pc
  1. Values are presented as mean ± standard deviation.

  2. a

    Difference between baseline and end point. P value obtained from paired t-test/Wilcoxon matched-pairs signed-rank test for the within-group comparisons.

  3. b

    Homoscedasticity test between groups on baseline.

  4. c

    Obtained from unpaired Student's t-test or Mann–Whitney test, as statistical difference between changes (DI vs. DI + P). The effect of the probiotic mix associated with dietary intervention on the variables measured was examined using ANCOVA with adjustment for the screening/baseline observation.

  5. ADIPO, adiponectin; CAT, catalase; SOD, superoxide dismutase; GPx, glutathione peroxidase; IL, interleukin; LPS, lipopolysaccharide; MDA, malondialdehyde, TNF-α, tumor necrosis factor-α.

CAT (U/mg)8.10 ± 2.017.17 ± 2.05−0.920.158.20 ± 1.267.71 ± 1.15−0.490.650.060.30 (−0.50 to 0.11)0.44
SOD (U/mg)5.88 ± 1.946.28 ± 1.900.400.555.35 ± 2.507.31 ± 6.291.950.000.10−0.62 (−2.79 to 1.54)0.56
GPx (U/mg)0.42 ± 0.120.34 ± 0.10−0.070.000.32 ± 0.130.37 ± 0.110.050.040.31−0.12 (−0.22 to 0.02)0.01
MDA (nmol/mL)0.16 ± 0.040.16 ± 0.040.000.830.18 ± 0.250.21 ± 0.280.020.390.00−0.01 (−0.13 to 0.10)0.81
LPS (EU/mL)0.85 ± 0.440.95 ± 0.600.090.490.67 ± 0.110.65 ± 0.110.020.340.000.08 (−0.26 to 0.44)0.62
IL-10 (pg/mL)4.65 ± 4.344.53 ± 3.14−0.120.883.57 ± 1.663.96 ± 1.840.390.150.00−1.29 (−3.34 to 0.74)0.20
IL-6 (pg/mL)1.35 ± 1.810.80 ± 1.81−0.540.070.58 ± 0.270.58 ± 0.310.000.940.00−1.98 (−4.15 to 0.18)0.07
TNF-α (pg/mL)2.49 ± 0.892.07 ± 0.78−0.420.071.72 ± 0.441.88 ± 0.370.160.240.00−0.84 (−1.47 to −0.20)0.01
ADIPO (ug/mL)35.59 ± 20.7638.44 ± 29.932.840.6533.72 ± 29.7836.33 ± 27.462.610.630.113.92 (−15.27 to 23.11)0.68

Discussion

To our knowledge, this was the first randomized, double-blind clinical trial to evaluate the effects of a probiotic mix containing Lactobacillus acidophilus LA-14, Lactobacillus casei LC-11, Lactococcus lactis LL-23, Bifidobacterium bifidum BB-06, and Bifidobacterium lactis BL-4 on the body composition, lipid and fatty acid profiles, metabolic endotoxemia, inflammatory cytokines, antioxidant enzymes, and malondialdehyde. Our results show that this treatment improves body composition and antioxidant enzyme activity more effectively than dietary intervention alone, but these results were not accompanied by a decrease in inflammatory markers.

The gut microbiota produce active signaling molecules that interact with the metabolism of the host [18]. The short-chain fatty acids (SCFAs) are produced by fermentation of dietary fibers by gut bacteria. SCFAs interact with G protein-coupled receptors and affect insulin sensitivity in adipocytes and peripheral organs, thus regulating energy metabolism [19]. In this study, we observed that the DI + P group, compared with the DI group, had decreased waist circumference, waist-height ratio, and conicity index, which are all variables related to fat storage. The improvement in body composition due to the administration of probiotics may be a consequence of fasting-induced adipose factor suppression in the gut, which would modulate the production of SCFAs [19]. Kadooka et al. [17] examined the antiobesity effects of the probiotic Lactobacillus gasseri LG2055 in healthy adults and also observed a reduction in waist circumference and body FM, but the participants were instructed to maintain their diet and no dietary intervention was made.

In this study, inflammatory and anti-inflammatory cytokine concentrations did not change, nor did LPS concentrations. However, our study did not induce the inflammatory processes that accompany the consumption of a high-fat diet as in the experimental studies that showed the reduction of inflammatory cytokines after supplementation with probiotics [20]. Thus, we believe that the improvement in inflammatory profile achieved by probiotics occurs when there are more inflammatory processes, such as high-fat diet consumption, and there is no additional effect when compared with dietary intervention.

Bifidobacteria species have been linked to alterations in the fatty acid profile of tissues. At the conclusion of this study, the DI + P group showed lower PUFA concentrations compared with the DI group due to a reduction in the proportion of ω-6. However, no studies evaluating the effect of probiotic supplementation on the proportion of fatty acids in human plasma were performed. A previous study using feces, colon, and cecal contents from germ-free, gnotobiotic, and conventional rodents indicated that gut microbes were capable of transforming linoleic acid (LA) into conjugated linoleic acids (CLAs) during in vitro incubations [21], suggesting the influence of gut microbiota on the profile of fatty acids in various tissues. Bioactive isomers of CLA can exert antidiabetogenic, antiobesogenic, antiatherogenic, hypocholesterolemic, hypotriglyceridemic, and immunomodulatory actions [22]. The mechanisms by which certain bacteria induce changes in ω-3 fatty acid composition has yet to be elucidated, but it may be associated with the use or assimilation of certain polyunsaturated fatty acids, such as α-linolenic acid, or the modulation of dietary fatty acid uptake in the intestine [23]. The modulation of gut microbiota can regulate desaturase activity involved in the metabolism of fatty acids to their longer chain derivatives. Indeed, it has been shown that a variety of commensals increased the activity of rat liver δ-6-desaturase, which resulted in increased amounts of arachidonic acid derived from linoleic acid [24].

Special strains of lactic acid bacteria also have antioxidant properties. The antioxidative mechanisms of probiotics could be ascribed to reactive oxygen species scavenging, metal ion chelation, enzyme inhibition, and activity reduction and inhibition of ascorbate autoxidation [25]. In our study, the antioxidant enzyme activities of SOD and GPx were increased in the DI + P group. This effect was observed by Naruszewicz et al. [26] and Songisepp et al. [27] in humans supplemented with Lactobacillus plantarum 299v and L. fermentum ME-3, respectively. The increased antioxidant enzyme activity from probiotic supplementation can be derived from the restoration of gut microbiota [28] and the induction of genes involved in the biosynthesis of glutathione in the intestinal mucosa [29] and in pancreatic cells [30]. Furthermore, probiotics may also enhance the absorption of micro- and macronutrients, including antioxidants, or finally reduce postprandial lipids, which are connected with oxidative damage and are often responsible for some food-related pathologies [31].

Conclusion

This study was sufficiently powered and adequately blinded. The intervention was noninvasive and short in duration, yielded no adverse effects on the participants, and had good compliance and acceptability in this population. The intervention protocol also enabled an assessment of the importance of probiotics in enhancing the benefits resulting from dietary intervention. Furthermore, the wide scope of data collection allowed numerous outcomes to be examined. One limitation of this study was that we did not evaluate the gut microbiome, which may have indicated the effects of probiotic mix consumption on the gut microflora and confirmed our suggested mechanism of action.

In conclusion, in the present study, supplementation with a probiotic mix reduced abdominal fat and increased antioxidant enzyme activity in a more effective way than an isolated dietary intervention.

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