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The human gut microbiome plays a regulatory role in host health, and is involved in metabolic, immune, and neurological processes. Diet shapes the gut microbiome; by providing essential nutrients, which sustain the existing microorganisms and by introducing foodborne microbes that modulate its composition. Notably, the impact of microbes from fruit and vegetables on the gut microbiome is relatively unexplored. Differences in agricultural practices, organic vs conventional strategies, can lead to variations in nutritional content and associated microbial communities in and on crops, underscoring the potential for variations in cultivated crops to influence the human gut microbiome's composition and function. This study aims to explore how crop cultivation practices affect the composition and function of the human gut microbiome, ultimately influencing overall health.
Objective:
The primary objective of this study is to investigate the effect of differentially cultivated crops (organic versus conventional) on cardiometabolic health outcomes, as reflected by measurements of glucose metabolism and its relation to the gut microbiome composition and function.
The secondary objectives are to assess the effect of differently grown crops on gut microbiome composition and function, plasma and fecal short-chain fatty acid levels, including quantification of pesticide residues and other contaminants in blood and faeces. Additionally, changes will be evaluated in metabolomics of the blood and breath volatile organic compounds (QuinTron), as well as alterations in weight, body composition.
Double-blind randomized dietary intervention study, parallel design. A total of 40 male and female volunteers will be recruited for this study, aged 18-45 years.
20 will have a normal BMI of 19-25 with no current medical conditions, while the remaining 20 will have a BMI of 28-40 with three components of Metabolic Syndrome, drug-naïve.
Participants will be assigned to one of two groups for 4 weeks of dietary intervention. One group will receive produce from conventional agriculture, while the other receives produce from organic agriculture, with a specific focus on differently grown fruits and vegetables.
Both groups will receive:
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| A) 11 MetSyn participants | Active Comparator | Organic Fruits and Vegetables |
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| B) 11 MetSyn participants | Active Comparator | Conventional Fruits and Vegetables |
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| C) 11 Healthy participants | Active Comparator | Organic Fruits and Vegetables |
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| D) Healthy participants | Active Comparator | Conventional Fruits and Vegetables |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Organic Fruits and Vegetables | Dietary Supplement | Dietary Intervention |
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| Measure | Description | Time Frame |
|---|---|---|
| Time in Range | The primary objective of this study is to investigate the effect of deferentially cultivated crops (organic versus conventional) on glucose levels. Measured by the difference in time in range between the groups between baseline, end-of-diet intervention | At Baseline, week 4 (End-of-intervention) |
| Measure | Description | Time Frame |
|---|---|---|
| Continuous glucose monitoring | Changes in glycemic variability, time above range, time below range and hypoglycemic episodes | Between Baseline (week-1) and End-of-intervention (week4) |
| Gut microbiome |
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Inclusion Criteria:
22 Healthy Volunteers : healthy Caucasian adults with a BMI < 25 kg/m^2 will be recruited with no medical conditions.
22 Metabolically Impaired Participants: Caucasian adults with a BMI ranging from 28 kg/m^2 to 40 kg/m^2 with three components of Metabolic Syndrome, drug-naïve:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Max Nieuwdorp, Dr. Prof. | Dept of Vascular Medicine, Amsterdam UMC - AMC | Principal Investigator |
| Hilde H.J. Herrema, PhD | Dept of Vascular Medicine, Amsterdam UMC - AMC | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Amsterdam UMC, locatie AMC | Amsterdam | Amsterdam | 1105 AZ | Netherlands |
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| ID | Term |
|---|---|
| D014675 | Vegetables |
| ID | Term |
|---|---|
| D005502 | Food |
| D000066888 | Diet, Food, and Nutrition |
| D010829 | Physiological Phenomena |
| D019602 | Food and Beverages |
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Study design:
Double-blind randomized dietary intervention study, parallel design.
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| Conventional Fruits and Vegetables | Dietary Supplement | Dietary Intervention |
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Gut microbiome analysis will include qualitative and quantitative assessment via 16S and whole-genome sequencing, differential abundance testing with DESeq2, strain-level tracking using InStrain, and PERMANOVA to evaluate temporal effects
| Every week from baseline (week -1) to follow-up (week 6) |
| Body Composition | Body Impedance Analysis: Free fat mass (kg; %). Fat mass (kg; %). Rest Metabolic Rate (kcal/day). | Baseline, End-of-intervention (week 4), Follow-up (week 6) |
| Anthropometric measurements | Weight will be measured in kilograms (kg). Height will be measured in meters (m). These two measurements will also be combined to calculate Body Mass Index (BMI), defined as weight in kilograms divided by height in meters squared (kg/m²) | Baseline, week 4 and follow-up (week 6) |
| Dietary Intake | Recorded of 3 days with "Eetmeter" | Baseline (week -1), End-of-Intervention (week 4), follow-up (week 6) |
| HbA1c | Millimoles of HbA1c per mole of hemoglobin (mmol/mol) | Baseline, End-of-Intervention (week 4), follow-up (week 6) |
| HOMA-IR | (Fasting Insulin * Fasting Glucose) / Constant | Baseline, End-of-Intervention (week 4), follow-up (week 6) |
| Leukocyte (differentation) | ×10 9 /L | Between Baseline and End-of-intervention (week4), follow-up (week 6) |
| CRP | C-reactive protein (mg/L) | Between Baseline and End-of-intervention (week4), follow-up (week 6) |
| Physical Activity Questionnaire | Physical Activity Questionnaire (SQUASH - Short Questionnaire to Assess Health-enhancing Physical Activity): Assesses weekly physical activity levels across commuting, household, leisure, and work/school activities. Scores are reported in MET-hours per week, with higher scores indicating greater physical activity. Range of activity levels: Low: <10 MET-hours/week, Moderate: 10-29 MET-hours/week, High: ≥30 MET-hours/week. | Between Baseline (week-1), End-of-intervention (week4) and Follow-up (week 6) |
| Breath Gas H₂ | Breath test performed with the QuinTron analyzer, measuring hydrogen (H₂) concentration in parts per million (ppm) as an indicator of fermentation. | Baseline, End-of-Intervention (week 4), follow-up (week 6) |
| Breath Gas CH₄ | Breath test conducted with the QuinTron analyzer to measure methane (CH₄) concentration, expressed in parts per million (ppm), as an indicator of fermentation. | Baseline, End-of-Intervention (week 4), follow-up (week 6) |
| Breath Gas CO₂ | Breath test conducted with the QuinTron analyzer to measure carbon dioxide (CO₂) concentration, expressed as a percentage (%) as control marker | Baseline, End-of-Intervention (week 4), follow-up (week 6) |