Effects of Pulses Through the Gut Microbiome and Bioavailability of Bioactive Compounds

Lifestyle-related Condition Clinical Trial

— LEGUMINIBUS  

Official title:

Discovering the Effects of Pulses Through the Gut Microbiome and Bioavailability of Bioactive Compounds

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05999136
• Other study ID #: DE LEGUMINIBUS
• Status: Recruiting
• Phase: N/A
• Start date: January 10, 2024
• Est. completion date: October 16, 2024

Study information

• Verified date: January 2024
• Source: Federico II University
• Contact: Paola Vitaglione, Professor
• Phone: +390812539357
• Email: paola.vitaglione[@]unina.it
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

The goal of this clinical trial is to investigate the effects of replacing red meat with pulses, on cardiometabolic health and gut microbiome in individuals with unhealthy habits and sedentary lifestyles at high risk for cardiovascular diseases. The main questions it aims to answer are:

1. How does the substitution of red meat with pulses affect some markers of cardiovascular risk?

2. How does this dietary intervention influence the composition and function of the gut microbiome, nutritional status, well-being indices, and biomarkers related to metabolic, oxidative, inflammatory, immune, and intestinal permeability status?

Participants will:

• be assigned to either the Pulses Diet (PulD) group or the Plant Proteins Diet (PPD) group or the Habitual diet (HabD) group;

• follow their habitual diet (HabD) or the prescribed dietary plan designed on individual habitual diet to be isocaloric and isoprotein but replacing red meat with pulses (PulD group) or a combination of pulses and plant-based meat substitutes (PPD group);

• keep their physical activity levels unchanged during the entire intervention period;

• be required to complete 7-day food diaries and associated questionnaires on appetite, along with additional questionnaires related to physical activity levels, overall well-being, mood, sleep quality, stool frequency and consistency at each nutritional intervention time-point.

Researchers will compare PulD, PPD, and HabD to assess if the dietary interventions have an impact on cardiometabolic health and gut microbiome.

Description:

Legumes are recognized for their distinctive nutritional profile, rich in plant-based proteins, low-glycemic-index carbohydrates, fiber, B vitamins, minerals, and polyphenols. Due to their protein content and amino acid composition, legumes in combination with grains can effectively replace meat and its derivatives. Despite worldwide nutritional guidelines recommending legumes as the predominant source of dietary protein, the consumption of red meat and meat products remains high and may have negative consequences for public health. Indeed, epidemiological evidence indicates that long-term consumption of increasing amounts of red and processed meats is associated with a higher risk of mortality, cardiovascular diseases, colon cancer, and type 2 diabetes. Furthermore, a recent study has shown that higher intake of red meat and choline is associated with higher concentrations of trimethylamine-N-oxide (TMAO), a gut microbiota byproduct that has been associated with a higher incidence of adverse cardiovascular events. Numerous research studies indicate that the consumption of plant-based foods brings health benefits for humans and supports the recommendation of international guidelines to modify dietary habits towards a diet richer in plant-based products. In addition, epidemiological studies show a possible association between high legume consumption and a decrease in coronary heart disease and colorectal adenoma, while the evidence for a protective role of legumes against cardiovascular diseases is less strong due to heterogeneity in results and/or potential confounding factors. The ability of legumes to reduce cardiometabolic risk factors is also supported by various scientific evidence from clinical trials. These studies demonstrate that legume consumption has a positive effect on lipid profile, glucose metabolism, blood pressure, body weight, oxidative stress, and inflammatory status.

Despite the recognized health benefits of consuming legumes regularly, there is still a limited understanding of the underlying physiological mechanisms that drive these positive effects. An observational study conducted in Italy shed some light on this issue by demonstrating that individuals who closely adhere to the Mediterranean diet, which emphasizes reducing red meat consumption and increasing the intake of fruits, vegetables, and legumes, have gut microbiota characterized by a higher abundance of fiber-degrading bacteria. These individuals also exhibit higher levels of short-chain fatty acids in their feces and lower concentrations of TMAO in their urine. Furthermore, a randomized controlled trial conducted on individuals at risk of cardiovascular diseases due to an unhealthy lifestyle revealed that shifting from a typical Western diet to a more Mediterranean-like pattern led to an increase in the presence of fiber-degrading bacterial species in the gut microbiota. This dietary change also resulted in elevated circulating microbial metabolites associated with improved inflammatory status. While there is still a lack of comprehensive in vivo studies assessing the bioavailability of nutrients from legumes, a few clinical trials have investigated the influence of legumes on the intestinal microbiome. Nevertheless, the available literature indicates that legumes have the ability to influence the human microbiota. However, it is important to note that the specific effects of legumes on the microbiota can vary significantly across different studies, making it difficult to generalize these findings to all types of legumes.

In this framework, the present project will focus on the evaluation of the effect of replacing red meat with pulses (PulD) or a combination of pulses and plant-based meat substitutes (PPD) on the cardiometabolic health of individuals with unhealthy habits and sedentary lifestyles via the modification of intestinal microbial communities. Additionally, it seeks to investigate the effects on health outcomes, with a primary focus on evaluating changes in inflammatory, oxidative, immune, and hormonal status. The study will include the establishment of a 2-month dietary intervention with an isocaloric and isoprotein pulses diet (PulD) and a plant proteins diet (PPD). Coupled with detailed host phenotyping and gut microbiota profiling during and after the intervention, this will allow assessment of the causal effects of a diet rich in plant-based proteins (mainly from pulses) and the gut microbiome in populations at high risk for cardiovascular disease (CVD).

The potential eligibility of subjects to participate in this study will be assessed through pre-recruitment questionnaires. These questionnaires will collect personal and socio-demographic data of volunteers, general health information (including anthropometry, health status, medical history, smoking and alcohol consumption habits), details about individual dietary habits using the Food Frequency Questionnaire (FFQ), information about eating behavior through the Three Factor Eating Questionnaire (TFEQ), and levels of physical activity using the International Physical Activity Questionnaire (IPAQ). Subjects in the PulD group and PPD group will be assigned a personalized diet prepared on the basis of own eating habits as established by 7-day food diary recalls. Energy values and whole macronutrient composition of habitual diets will be kept unchanged during PulD and PPD intervention. However, changes in carbohydrate (dietary fibre vs. starch), dietary fat (saturated vs. mono/polyunsaturated fatty acids), and protein (vegetable vs. animal) composition will be applied as a consequence of replacing meat with pulses (PulD group) or with a mix of pulses and plant-based meat substitutes (PPD group). Control subjects will not change their habitual diet (HabD) during intervention. All subjects will be requested not to change physical activity levels during the 8 weeks intervention period. Compliance will be assessed every 2 weeks with a phone interview in order to evaluate the dietary intake and physical activity during the previous week. At each intervention time-point (baseline, 4 weeks, 8 weeks), for the nutritional check, subjects will complete 7-day food diaries and associated questionnaires on appetite (Visual Analog Scale, VAS) related to the previous week before the nutritional analysis. Additionally, measurements of blood pressure, weight, circumferences (waist and hips), and body composition through bioimpedance testing will be conducted. During the intervention period, subjects will be asked to fill out the International Physical Activity Questionnaire (IPAQ), questionnaires on quality of life (QoL), on depression, anxiety and stress (DASS), the King's Stool Chart (KSC) to evaluate frequency, weight, and consistency of feces, along with the Pittsburgh Sleep Quality Index (PSQI) to evaluate the quality of sleep.

Further analysis of compliance will be conducted based on metabolomics, allowing discrimination of animal/vegetable protein intake. Metabolomes (well known to reflect both diet and microbial metabolism) will also be compared between categories in order to identify protective or risk profiles using both bioinformatics and chemometrics approaches. Metagenomes will be analyzed following Standard Operating Procedures (SOPs) utilized in landmark studies already published. Comparison of predefined groups of individuals will allow identification of microbial genes that have different abundance in the groups. Furthermore, genes will be associated with continuous variables of clinical and nutritional interest (e.g., intake of specific dietary components, insulin sensitivity) by covariance analysis. Concatenated datasets of physiological output data, metagenomic and metabolome profiles from the intervention studies will be used to predict subsets of features by multivariate analysis (PLS-DA) that can classify subjects according to their relative adherence to a PulD or PPD. The profile will be used to probe the microbiome for specific alterations as a function of the interventions.

The sample size needed to detect an effect of PulD and/or PPD on individual TMAO levels is defined based on previous study from Crimarco and colleagues. It was calculated that a sample of 28 participants per group would allow detecting a minimum difference of approximately -1.3 μM (-38%) in TMAO and approximately -0.9 mM (-18%) in cholesterol between each of the 2 test treatments vs. control and between the two test treatments, with a power of 80% and an α-error 0.017 to account for multiple comparisons (T-test).

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 84
• Est. completion date: October 16, 2024
• Est. primary completion date: October 16, 2024
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 18 Years to 65 Years

Eligibility

Inclusion Criteria:

• men and women aged 18-65;

• 20 = BMI = 35 kg/m2;

• habitual diet characterized by = 3 medium servings of fresh red meat or processed meat (equivalent to a portion weight of 100g of fresh meat and 50g of cured meats);

• habitual diet without probiotics, functional foods, and/or any type of food supplements;

• low level of physical activity (sedentary lifestyle);

• signing the informed consent form and expressing consent for the processing of personal data.

Exclusion Criteria:

• Food allergies and intolerances, such as celiac disease, lactose intolerance, and others;

• Gastrointestinal disorders of any kind;

• Significant medical conditions;

• Pregnancy or breastfeeding;

• Hypertriglyceridemia (Triglycerides > 200 mg/dL);

• Hypercholesterolemia (Cholesterol > 200 mg/dL);

• Diabetes (Blood glucose = 126 mg/dL);

• Hypertension (Blood pressure > 140/90 mm Hg);

• Weight loss = 3 kg in the past 2 months prior to the study;

• Use of any medication at enrollment and in the 2 months prior to the study;

• Regular diet rich in fruits and vegetables;

• Consumption of alcohol equivalent to or exceeding 3 glasses of wine per day;

• Concurrent participation in other clinical trials.

Related Conditions & MeSH terms

• Lifestyle-related Condition

Intervention

Other:
• Pulses diet
Subjects in the PulD group will be assigned a personalized diet prepared based on their own eating habits as established by 7-day food diary recalls. Energy values of habitual diets will be kept unchanged during the PulD intervention. The diet will be characterized by isocaloric and isoprotein substitutions, replacing habitual servings of red meat or processed meat with servings of pulses.
• Plant proteins diet
Subjects in the PPD group will be assigned a personalized diet prepared based on their own eating habits as established by 7-day food diary recalls. Energy values of habitual diets will be kept unchanged during the PPD intervention. The diet will be characterized by isocaloric and isoprotein substitutions, replacing habitual servings of red meat or processed meat with a mixture of pulses and plant-based meat substitutes.
• Habitual diet
Control subjects will not change their habitual diet during intervention. All subjects will be requested not to change physical activity levels during the 8 week intervention period.

Locations

Country	Name	City	State
Italy	Department of Agricultural Sciences, Federico II University	Portici

Sponsors (1)

Lead Sponsor	Collaborator
Paola Vitaglione

Country where clinical trial is conducted

Italy, 

References & Publications (2)

Crimarco A, Springfield S, Petlura C, Streaty T, Cunanan K, Lee J, Fielding-Singh P, Carter MM, Topf MA, Wastyk HC, Sonnenburg ED, Sonnenburg JL, Gardner CD. A randomized crossover trial on the effect of plant-based compared with animal-based meat on trim — View Citation

Meslier V, Laiola M, Roager HM, De Filippis F, Roume H, Quinquis B, Giacco R, Mennella I, Ferracane R, Pons N, Pasolli E, Rivellese A, Dragsted LO, Vitaglione P, Ehrlich SD, Ercolini D. Mediterranean diet intervention in overweight and obese subjects lowe — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Changes in fasting total cholesterol concentration	Measure of serum total cholesterol concentration (mg/dL serum)	2 months
Primary	Changes in plasma TMAO concentration	Measure of plasma TMAO concentration (µmol/L plasma)	2 months
Secondary	Changes in faecal microbiome	Measure of faecal microbiome	2 months
Secondary	Changes in urinary TMAO concentration	Measure of urinary TMAO concentration (mmol/mol creatinine)	2 months
Secondary	Changes in urinary polyphenols concentration	Measure of urinary polyphenols concentration (ng/mg creatinine)	2 months
Secondary	Changes in urinary urolithin concentration	Measure of urinary urolithin concentration (ng/mg creatinine)	2 months
Secondary	Changes in urinary betaine concentration	Measure of urinary betaine concentration (mmol/mol creatinine)	2 months
Secondary	Changes in urinary carnitine concentration	Measure of urinary carnitine concentration (mmol/mol creatinine)	2 months
Secondary	Changes in urinary choline concentration	Measure of urinary choline concentration (mmol/mol creatinine)	2 months
Secondary	Changes in urinary tryptophan betaine concentration	Measure of urinary tryptophan betaine concentration (mmol/mol creatinine)	2 months
Secondary	Changes in urinary indican concentration	Measure of urinary indican concentration (mg/g creatinine)	2 months
Secondary	Changes in urinary creatinine concentration	Measure of urinary concentration (mg/dL)	2 months
Secondary	Variation of complete blood count	Measure of Red blood cell (RBC) count (number of cells/mm3); Hemoglobin (Hb) concentration (g/dL); Hematocrit (HCT) percentage (%); White blood cell (WBC) count (number of cells/mm3); Platelet (PLT) count (number of cells/mm3).	2 months
Secondary	Variation of blood iron status biomarkers	Measure of blood concentrations (mg/dL) of iron, ferritin, total transferrin	2 months
Secondary	Variation of vitamin B status	Measure of blood folic acid and vitamin B12 concentrations (ng/mL)	2 months
Secondary	Variation of individual hormonal status	Measure of plasma glucagon-like peptide 1 (GLP-1), Glucose-dependent Insulinotropic Peptide (GIP), Glucagon, Leptin, Ghrelin, C-peptide concentrations (pg/mL plasma)	2 months
Secondary	Variation of plasma endocannabinoids concentration	Measure of plasma endocannabinoids concentration (ng/mL)	2 months
Secondary	Variation of plasma N-acylethanolamines concentration	Measure of plasma N-acylethanolamines concentration (ng/mL)	2 months
Secondary	Changes in plasma betaine concentration	Measure of plasma betaine concentration (µmol/L plasma)	2 months
Secondary	Changes in plasma carnitine concentration	Measure of plasma carnitine concentration (µmol/L plasma)	2 months
Secondary	Changes in plasma choline concentration	Measure of plasma choline concentration (µmol/L plasma)	2 months
Secondary	Changes in plasma bioactive peptides concentration	Measure of plasma bioactive peptides concentration (ng/mL plasma)	2 months
Secondary	Changes in plasma bile acids concentration	Measure of plasma bile acids concentration (ng/mL plasma)	2 months
Secondary	Variation of plasma oxidative stress biomarkers	Measure in plasma of: TBARS concentration (µM); nitrotyrosine (N-Tyr) concentration (OD/mL); 8-hydroxy-2-deoxyguanosine (8-OHdG) concentration (ng/mL)	2 months
Secondary	Variation of plasma antioxidant enzyme activities	Measure of plasma superoxide dismutase (SOD) activity (U/mL); catalase activity (nmol/min/mL); glutathione peroxidase (GPx) activity (nmol/min/mL)	2 months
Secondary	Variation of serum dipeptidyl peptidase-IV (DPP-IV) concentration and activity	Measure of serum dipeptidyl peptidase-IV (DPP-IV) concentration (ng/mL) and activity (IU/L)	2 months
Secondary	Variation of serum Triglycerides concentration	Measure of serum triglycerides concentration (mg/dL serum)	2 months
Secondary	Variation of serum LDL- and HDL-cholesterol concentrations	Measure of serum LDL-, HDL-cholesterol concentrations (mg/dL serum)	2 months
Secondary	Variation of serum glucose concentration	Measure of serum glucose concentration (mg/dL)	2 months
Secondary	Variation of serum insulin concentration	Measure of serum insulin concentration (µU/mL serum)	2 months
Secondary	Variation of serum Insulin-like Growth Factor-1 (IGF-1) concentration	Measure of serum IGF-1 concentration (ng/mL)	2 months
Secondary	Variation of serum C-reactive protein (CRP) concentration	Measure of serum CRP concentration (mg/L)	2 months
Secondary	Variation of serum zonulin concentration	Measure of serum zonulin concentration (ng/mL)	2 months
Secondary	Changes in immune state blood markers	Measure of monocyte polarization (Arbitrary Units) of Cluster of Differentiation (CD) 86, Tumor Necrosis Factor alpha (TNFa), inducible Nitric Oxide Synthase (iNOS), CD36, CD11c, CD169, CD206, CD163, CD68, CD11b, CD16, e CD14	2 months
Secondary	Variation of erythrocytes antioxidant enzymes activity	Measure in erythrocytes of: superoxide dismutase (SOD) activity (U/mL); catalase activity (nmol/min/mL); glutathione peroxidase (GPx) activity (nmol/min/mL); glutathione reductase (GR) activity (U/mL)	2 months
Secondary	Changes in body weight	Measure of body weight (kg) in fasting subjects	2 months
Secondary	Changes in body mass index	Calculation of body mass index (kg/m2) by using the formula weight in kilograms divided by height in meters squared.	2 months
Secondary	Changes in waist and hip circumferences	Measure of waist circumference (cm) at the midpoint between the lower margin of the least palpable rib and the top of the iliac crest.; Measure of hip circumference (cm) around the widest portion of the buttocks.	2 months
Secondary	Changes in blood pressure	Measure of systolic pressure and diastolic pressure in millimetres of mercury (mmHg) by using a digital sphygmomanometer	2 months
Secondary	Changes in body composition	Body composition (kg body fat mass, body fat-free mass and total body water) is determined by conventional bioelectrical impedance analysis with a single-frequency 50 kilohertz (kHz) bioelectrical impedance analyzer in the postabsorptive state (fasting subjects) and after being in the supine position for 20 min. Body composition data will be calculated from bioelectrical measurements and anthropometric data by using validated predictive equations.	2 months
Secondary	Variation of hunger, fullness and satiety sensation scores	Measures of hunger, fullness and satiety sensations over the day reported by subjects by using hunger Visual Analogue Scales (VAS) 0-10 centimeters. Changes in these scores may reflect potential effects of dietary intervention in modulating hunger, fullness and satiety.	2 months
Secondary	Changes in stool weight, consistency and frequency	Measure of stool weight, frequency and consistency by mean of King's Stool Chart (KSC) filled out by subjects. The chart comprises three categories of stool weight : <100 g, 100-200 g, >200 g. The chart comprises four categories of stool consistency: hard and formed, soft and formed, loose and unformed, liquid. Fecal frequency is incorporated by recording the code of each feces passed over a 24 hour period.	2 months
Secondary	Assessment of diet composition	Measure of individual's usual food consumption through Food Frequency Questionnaires (FFQ) by querying the frequency (times/week) and amount (g) at which the respondent consumed food items based on a predefined food list.	2 months
Secondary	Changes in physical activity level	Measurement of an individual's physical activity level (MET min/week) through the International Physical Activity Questionnaire (IPAQ), which assesses the frequency (times/week) and duration (min) of different activities such as walking, moderate-intensity exercises, vigorous-intensity exercises, and sitting time.	2 months
Secondary	Variation of wellbeing status	Estimate of wellbeing status by mean of quality of life (QoL) questionnaire, which is based on Short Form-12 Health Survey (SF-12), a self-report form of subjective health. Physical and Mental Health Composite Scores (PCS & MCS, arbitrary units) are computed using the scores of twelve questions and range from 0 to 100, where a zero score indicates the lowest level of health measured by the scales and 100 indicates the highest level of health.	2 months