Clinical trial NCT03732690: The Interaction Between Protein Intake, Gut Microbiota and Type 2 Diabetes in Subjects With Different Ethnic Backgrounds
Official title: Modulation of Protein Intake to Target Gut-microbiota Derived Metabolites of Amino Acids in Individuals With Type 2 Diabetes From Varying Ethnic Backgrounds
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Type 2 Diabetes
Keywords: Type 2 diabetes
Diet
Protein
Gut microbiota
Metabolites
Lead sponsor: Assistance Publique - Hôpitaux de Paris
Sponsor class: OTHER
Collaborators: name: ICAN Nutrition Education and Research
First posted: 2018-11-07
Enrollment: 65
Sex: ALL
Minimum age (years): 40
Maximum age (years): 70
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: TREATMENT

Brief summary: Context and justification:

There is growing evidence that the gut microbiota is a key element in the pathophysiology of cardio-metabolic diseases (CMD) such as Type 2 Diabetes (T2D). One hypothesis is that gut-derived metabolites (from diet) have an important role in the host metabolism. Preliminary results show that imidazole propionate (ImP), a degradation product of the essential amino acid histidine, is produced by the gut microbiota of T2D patients, but not healthy subjects. The gut microbiota itself is strongly influenced by diet and ethnicity. However, most dietary intervention studies have focused on the role of fiber intake and the effect of dietary protein on the gut microbiota composition and metabolite production is not well known. Our hypothesis is that, depending on the baseline gut microbiome composition, a diminution in protein intake could decrease the microbial production of metabolites such as ImP and improve the metabolism of the host. We also hypothesize that the effects of such an intervention could depend the ethnic background.

Objective:

To study the effects of a high protein (HP) vs a low protein (LP) diet on gut microbiota composition and production of pro-diabetic metabolites in type 2 diabetes (T2D) patients from Caucasian and Caribbean ethnicity depending on baseline metagenomics richness.

Study design:

Randomized controlled three months dietary intervention study

Study Population:

T2D patients from Caucasian (N=80) and Caribbean (N=40) background who are on a stable dose of metformin and do not use insulin or proton-pump inhibitors.

Intervention:

Subjects will be randomized to either a high protein (HP) or low protein (LP) diet for three months. Individuals of Caucasian ethnicity, will also be stratified according to either a high or low gut microbiota gene richness. All subjects will receive pre-cooked meals 6 days per week and daily food packages. Subjects are required to keep food diaries three days a week and will also have weekly contact with an Pitié-Salpêtrière dietician.

Outcome measures:

Primary endpoint is the change in glycemic excursion (area under the curve) after a mixed meal test between baseline and 12 weeks after the beginning of the intervention. Furthermore, we will study oral and fecal microbiota composition changes as well as serum levels of intestinal metabolites, such as ImP, body weight and body composition at baseline and after 12 weeks.

Sample Size:

It is calculated that a total of 20 patients per arm are needed so 120 patients in total.

Detailed description: Context and justification:

There is growing evidence that the gut microbiota is a key element in the pathophysiology of cardio-metabolic diseases (CMD) such as Type 2 Diabetes (T2D). One hypothesis is that gut-derived metabolites (from diet) have an important role in the host metabolism. Preliminary results show that imidazole propionate (ImP), a degradation product of the essential amino acid histidine, is produced by the gut microbiota of T2D patients, but not healthy subjects. The gut microbiota itself is strongly influenced by diet and ethnicity. However, most dietary intervention studies have focused on the role of fiber intake and the effect of dietary protein on the gut microbiota composition and metabolite production is not well known. Moreover, it has been shown that the response to a dietary intervention may depend on the baseline gut microbiome richness.

Main hypothesis: Depending on the baseline gut microbiome composition, a diminution in protein intake could decrease the microbial production of metabolites such as ImP and improve the metabolism of the host. We also hypothesize that the effects of such an intervention could depend the ethnic background.

Study population:

Individuals with type 2 diabetes (T2D), of Caucasian or Caribbean origin, 120 patients will be included in total

Intervention:

Assignment after randomization to one of the following 2 diets:

* HP diet: high protein (High Protein, HP) diet with 30% protein, 40% carbohydrate and 30% fat (as% of total energy intake)
* LP diet: low protein diet (Low Protein, LP) with 10% protein, 55% carbohydrate and 35% fat (as% of total energy intake) Food boxes adapted to each diet (HP or LP pre-cooked meals, HP or LP breads and snacks) will be provided to the participants throughout the study reaching 40-50% of their prescribed daily energy intake for 6 days per week.

Subjects are required to keep food diaries three days a week and will also have weekly contact with a dietician.

Visits:

- Inclusion visit V0 (maximum 1 month before V1): Participants will first be recruited from the diabetic population of the French cohort of the European project METACARDIS. Individuals eligible for the study are screened for inclusion.

Baseline phenotyping is performed (metabolic, inflammatory blood markers, stool and oral microbiota sampling, body composition by DXA, questionnaires)

- Randomization visit V1 (T0 - start of the intervention): Randomization into 2 parallel groups (High Protein or Low protein diet) will be stratified based on metagenomics richness (obtained from Metacardis results), age (\< or ≥ 60), gender, ethnic background (Caribbean or Caucasian).

Meal tolerance test, anthropometric measures, resting energy expenditure measure, one week CGMS, 24h urinary urea measure are performed.

- Follow-up visit V2 (T42 +/- 7 days): Mid protocol visit with anthropometric measures, one week CGMS, 24h urinary urea measures, stool sampling.

- End of study visit V3 (T84 +/- 7 days): Phenotyping is performed (metabolic, inflammatory blood markers, stool and oral microbiota sampling, body composition by DXA, questionnaires, meal tolerance test, anthropometric measures, resting energy expenditure measure, one week CGMS, 24h urinary urea measure)

Statistical analysis:

There are no multiple hypotheses since our study has only one primary objective (AUC delta of the glycemic excursion after a mixed meal tolerance test (MMT) between the beginning of study and 3 months post intervention). Thus, the problem of the type 1 error will not arise.

The primary endpoint will be analyzed to compare changes in AUC for glycemic excursion versus diet (rich vs. low protein), based on initial metagenomic richness (high vs. low) and ethnicity (Caucasian vs. Caribbean). AUC changes after dietary intervention between the different groups will be tested using linear regression models for repeated measurements with adjustment for initial levels. The effect of diet composition within the groups will be tested using Bonferroni's post-hoc covariance analysis (ANCOVA) analyzes. For secondary endpoints, the same approaches will be used for analysis of postprandial metabolites (AUC, AUC, post-MMT variation). Differences in relative abundance of bacterial species and functional modules (generated by metagenomic sequencing) and quality of life questionnaires will also be analyzed by subgroups using uni / multivariate analyzes. Correlations will be sought between changes in bio-clinical variables and changes in measurements of different metabolites.

Funding:

* European Program (Join Program Initiative, JPI HDHL / ERA-NET cofund HDHL-INTIMIC, -Edition 2017) through the National Agency for Research (ANR)
* Leducq Foundation (Research Grant 17CVD01 titled "Gut Microbiome as a Target for the Treatment of Cardiometabolic Diseases").
* K Santé Society providing meals for the study.
* Nutrisens Society providing snacks for the study.

Eligibility criteria: Inclusion Criteria:

1. Age ≥ 40 years and \<70 years 2.
2. Type 2 Diabetic Subjects (T2D)
3. Treated with stable dose of metformin (no dose change in the last 3 months)
4. BMI ≥ 25 kg / m2
5. Caucasian or Caribbean origin
6. Written and oral comprehension of the French language
7. Patient affiliated to health care.
8. Patient having been informed of the study and having given written consent to participation

Exclusion Criteria:

1. Pregnancy or breastfeeding
2. Insulin treatment
3. HbA1c ≥ 9% (\<3 months)
4. Recent antibiotic treatment (\<3 months)
5. Recent treatment with proton pump inhibitor (\<3 months)
6. Food allergies or documented intolerances
7. Patient not willing to eat the foods provided in the protocol
8. Neuromuscular or neurological disease
9. History of digestive cancer and / or abdominal radiotherapy
10. History of gastrointestinal surgery with gastrointestinal resection
11. Acute or chronic inflammatory or infectious disease (including HIV, HCV, HBV)
12. Organ Transplantation, Immunosuppressive drugs
13. Severe chronic renal insufficiency (creatinine\> 150 μmol / l or eDFG \<50 ml / min per 1.73 m2 body surface area)
14. Patient currently included in an interventional clinical study (patients included in an observational study may be included)
15. Patient who received an experimental treatment in a research involving the human person in the last 2 months
16. Subject taking a dietary supplement (\> 100kcal / d)
17. Subject with severe eating disorders (anorexia, bulimia, binge eating disorders, etc.)
18. History of bariatric surgery
19. Subject practicing an intense sport activity (more than 10 hours of sport per week)
20. Subject unwilling to maintain an alcohol consumption of less than 50g per week (eg 5 glasses of wine) and less than 10g per day (eg 1 glass of wine)
21. Patient under tutorship or curatorship

Primary outcomes:
measure: Post meal tolerance test glycemic excursion (area under the curve)
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
Secondary outcomes:
measure: Post meal tolerance test insulin excursion (area under the curve)
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Matsuda index (from post meal tolerance test glucose and insulin levels)
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Insulinogenic index (from post meal tolerance test glucose and insulin levels)
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Disposition index (kahn) (from post meal tolerance test glucose and insulin levels)
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Serum concentration of glycated hemoglobin (HbA1c)
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Fasting concentration of glucose
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Insulin resistance index : HOMA 2 IR (based on fasting glucose and insulin concentration)
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Insulin secretion index: HOMA 2 B (based on fasting glucose and insulin concentration)
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: One week postprandial glucose excursions measured by continuous glucose monitoring sensors (CGMS)
timeFrame: Evolution between T0 (baseline) T6 weeks and T12 weeks of intervention
measure: Weight (kg)
timeFrame: Evolution between T0 (baseline) T6 weeks and T12 weeks of intervention
measure: Waist circumference (cm)
timeFrame: Evolution between T0 (baseline) T6 weeks and T12 weeks of intervention
measure: Sagittal diameter (cm)
timeFrame: Evolution between T0 (baseline) T6 weeks and T12 weeks of intervention
measure: Fat mass (DXA)
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Fat free mass (DXA)
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Visceral fat mass (DXA)
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Fat mass (BIA)
timeFrame: Evolution between T0 (baseline) T6 weeks and T12 weeks of intervention
measure: Fat free mass (BIA)
timeFrame: Evolution between T0 (baseline) T6 weeks and T12 weeks of intervention
measure: Fasting concentration of Alanine transaminase (ALT)
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Fasting concentration of Aspartate transaminase (AST)
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Concentration of total cholesterol
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Concentration of LDL cholesterol
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Concentration of HDL cholesterol
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Concentration of triglycerides
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Gut microbiota changes
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Oral microbiota changes
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Concentration of Imidazole propionate
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Concentration of Trimethyl amine oxide (TMAO)
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Concentration of p cresol
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Concentration of indoxyl sulfate
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Concentration of C reactive protein (CRP)
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Urinary urea excretion
timeFrame: Evolution between T0 (baseline) T6 weeks and T12 weeks of intervention
measure: SF 36 score (short form 36 quality of life questionnaire)
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: General self efficacy scale score (GSES questionnaire)
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Patient health questionnaire 9 score (PHQ-9 questionnaire)
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Gastro-intestinal discomfort changes
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Resting energy expenditure changes
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Epigenetic modifications
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
measure: Adipose tissue gene expression modifications
timeFrame: Change between baseline (T0) and the end of the intervention (T12 weeks)
Other outcomes:
Locations:
city: Paris
country: France
facility: Hôpital PITIE SALPETRIERE - APHP
Study officials:
affiliation: Hôpital PITIE SALPETRIERE - APHP
name: Karine CLEMENT
role: PRINCIPAL_INVESTIGATOR
References: