PPGR: Postprandial Glucose Levels, Gut Microbiota and Supplementation With Functional Foods in Adults
Study Details
Study Description
Brief Summary
This is a clinical study with participants over 18 years of age that meet the selection criteria. This will be 42-day study divided into three phases of 14 days each: 14 days without intervention, 14 days with intervention with functional foods and 14 days without intervention again. With the objective of assess the changes in the postprandial glycemic responses through the gut microbiota and urine metabolites.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
|
N/A |
Detailed Description
The increase in postprandial blood glucose constitutes a global epidemic and an important risk factor for the development of prediabetes and type 2 diabetes (T2D). In addition, the elevated postprandial glycemic responses (PPGRs) are an independent risk factor for the development of T2D and are associated with the presence of obesity. Therefore the prediction of PPGRs is a tool that could be used to maintain normal blood glucose concentrations.
Studies have shown inter and intrapersonal differences in PPGRs after consuming the same amount of the same food. Factors that can affect interpersonal differences in PPGRs include genetics, lifestyle, and insulin sensitivity. Another factor that may be involved is the gut microbiota.
The objective of this study is to characterize the postprandial blood glucose levels, gut microbiota and urine metabolites in participants over 18 years of age after a functional foods intervention and observed whether this intervention modifies the postprandial glycemic response through the gut microbiota and urine metabolites.
This will be a 42-day study divided into three phases of 14 days each where the patient will attend four visits: at day 1, 14, 28 and 42. 200 adults who meet the inclusion criteria will be recruited. During the three phases a continuous glucose monitor will be taking intersticial glucose concentrations every 15 min., divided into three phases of 14 days each: 14 days without intervention, 14 days with intervention with functional foods and 14 days without intervention again.In the three phases the following will be determined; anthropometric and biochemical parameters, food consumption, physical activity, lifestyle, metabolites in urine as well as determination of the composition of the intestinal microbiota.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Experimental: Nutritional strategy based on functional foods Participants will be provided with a nutritional strategy based on functional foods to use over the 2 week trial. These will be nopal, chía seeds, inulin, soy protein, agave extract and genistein. |
Dietary Supplement: Dietary Supplement: A package containing a mix of functional foods
Participants will be provided with a nutritional strategy based on functional foods to use over the 2 week trial. These will be nopal, chía seeds, inulin, soy protein, agave extract and genistein.
|
Outcome Measures
Primary Outcome Measures
- Changes in postprandial glucose responses [6 weeks]
Postprandial glucose concentrations (mmol/L). The incremental area under the curve will be calculated and expressed as mmol*minutes/litre.
- Changes in diversity analysis of intestinal microbiota with and without intervention with functional foods [6 weeks]
Based on the gene and species composition of each sample, the Chao1 and Shannon indexes, as well as the observed operational taxonomic units, will be calculated in order to identify the differences in gene and species diversity for each group
Secondary Outcome Measures
- Changes in metabolite profiles of urine with and without intervention with functional foods [6 weeks]
Metabolite profiles will be analyzed using a semi targeted screening approach with multiple Schedule multiple reaction monitoring-independent data acquisition-enhanced product ion (sMRM-IDA-EPI) experiments in an liquid chromatography-mass spectrometer-triple quadrupole with linear trap mass spectrometer (LC-MS-QTRAP) metabolomic platform. The concentration of the identified metabolites in the different urinary fractions will be expressed in relative intensities. From the latter, putative biomarkers may be obtained to determine the fingerprint of the dietary intervention assessed in this clinical trial.
- Feasibility of the functional food treatment decision algorithm. Proportion of patients with presumed improvement in postprandial glucose response who have completed the algorithm. [2 weeks]
The algorithm will be considered completed if a decision to initiate functional food intervention has been taken at any step of the algorithm or if improvement in the prediction of postprandial glucose response has been excluded after systematic evaluation, and all steps planned in the algorithm have been implemented.
Eligibility Criteria
Criteria
Inclusion Criteria:
-
Male and female
-
Adults between 18 and 60 years of age.
-
The signing of the informed consent.
Exclusion Criteria:
-
Patients with any type of diabetes.
-
Patients with high blood pressure.
-
Patients with acquired diseases secondarily producing obesity and diabetes.
-
Patients who have suffered a cardiovascular event.
-
Patients with gastrointestinal diseases.
-
Weight loss > 3 kg in the last 3 months.
-
Catabolic diseases such as cancer and acquired immunodeficiency syndrome.
-
Pregnancy status.
-
Drug treatment:
-
Antihypertensive drugs or treatment (thiacycline, loop or potassium-sparing diuretics, angiotensin-converting enzyme inhibitors, angiotensin II receptor blockers, alpha blockers, calcium antagonists, beta blockers).
-
Treatment with hypoglycemic agents (sulfonylureas, biguanides, incretins) or insulin and antidiabetic drugs.
-
Treatment with statins, fibrates or other drugs to control dyslipidemia.
-
Use of antibiotics in the three months prior to the study.
-
Use of steroid drugs, chemotherapy, immunosuppressants, or radiation therapy.
-
Anorexigenic or that accelerate weight loss such as sibutramine or orlistat.
-
Supplements with any of the functional foods used in the study.
-
Probiotic, prebiotic or symbiotic supplements.
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán | México | Mexico City | Mexico | 14080 |
Sponsors and Collaborators
- Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran
- Fundación Gonzalo Río Arronte
Investigators
- Principal Investigator: Armando R Tovar, Doctor, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubiran
Study Documents (Full-Text)
None provided.More Information
Publications
- Blaak EE, Antoine JM, Benton D, Bjorck I, Bozzetto L, Brouns F, Diamant M, Dye L, Hulshof T, Holst JJ, Lamport DJ, Laville M, Lawton CL, Meheust A, Nilson A, Normand S, Rivellese AA, Theis S, Torekov SS, Vinoy S. Impact of postprandial glycaemia on health and prevention of disease. Obes Rev. 2012 Oct;13(10):923-84. doi: 10.1111/j.1467-789X.2012.01011.x. Epub 2012 Jul 11.
- Ceriello A. Impaired glucose tolerance and cardiovascular disease: the possible role of post-prandial hyperglycemia. Am Heart J. 2004 May;147(5):803-7. doi: 10.1016/j.ahj.2003.11.020.
- Christensen L, Roager HM, Astrup A, Hjorth MF. Microbial enterotypes in personalized nutrition and obesity management. Am J Clin Nutr. 2018 Oct 1;108(4):645-651. doi: 10.1093/ajcn/nqy175.
- Eleazu CO. The concept of low glycemic index and glycemic load foods as panacea for type 2 diabetes mellitus; prospects, challenges and solutions. Afr Health Sci. 2016 Jun;16(2):468-79. doi: 10.4314/ahs.v16i2.15.
- Gallwitz B. Implications of postprandial glucose and weight control in people with type 2 diabetes: understanding and implementing the International Diabetes Federation guidelines. Diabetes Care. 2009 Nov;32 Suppl 2(Suppl 2):S322-5. doi: 10.2337/dc09-S331. No abstract available.
- Guevara-Cruz M, Flores-Lopez AG, Aguilar-Lopez M, Sanchez-Tapia M, Medina-Vera I, Diaz D, Tovar AR, Torres N. Improvement of Lipoprotein Profile and Metabolic Endotoxemia by a Lifestyle Intervention That Modifies the Gut Microbiota in Subjects With Metabolic Syndrome. J Am Heart Assoc. 2019 Sep 3;8(17):e012401. doi: 10.1161/JAHA.119.012401. Epub 2019 Aug 27.
- Mendes-Soares H, Raveh-Sadka T, Azulay S, Ben-Shlomo Y, Cohen Y, Ofek T, Stevens J, Bachrach D, Kashyap P, Segal L, Nelson H. Model of personalized postprandial glycemic response to food developed for an Israeli cohort predicts responses in Midwestern American individuals. Am J Clin Nutr. 2019 Jul 1;110(1):63-75. doi: 10.1093/ajcn/nqz028. Erratum In: Am J Clin Nutr. 2019 Sep 1;110(3):783.
- Sanchez-Tapia M, Tovar AR, Torres N. Diet as Regulator of Gut Microbiota and its Role in Health and Disease. Arch Med Res. 2019 Jul;50(5):259-268. doi: 10.1016/j.arcmed.2019.09.004. Epub 2019 Oct 5.
- Vrolix R, Mensink RP. Variability of the glycemic response to single food products in healthy subjects. Contemp Clin Trials. 2010 Jan;31(1):5-11. doi: 10.1016/j.cct.2009.08.001. Epub 2009 Sep 6.
- Zeevi D, Korem T, Zmora N, Israeli D, Rothschild D, Weinberger A, Ben-Yacov O, Lador D, Avnit-Sagi T, Lotan-Pompan M, Suez J, Mahdi JA, Matot E, Malka G, Kosower N, Rein M, Zilberman-Schapira G, Dohnalova L, Pevsner-Fischer M, Bikovsky R, Halpern Z, Elinav E, Segal E. Personalized Nutrition by Prediction of Glycemic Responses. Cell. 2015 Nov 19;163(5):1079-1094. doi: 10.1016/j.cell.2015.11.001.
- Zhu J, Xing G, Shen T, Xu G, Peng Y, Rao J, Shi R. Postprandial Glucose Levels Are Better Associated with the Risk Factors for Diabetes Compared to Fasting Glucose and Glycosylated Hemoglobin (HbA1c) Levels in Elderly Prediabetics: Beneficial Effects of Polyherbal Supplements-A Randomized, Double-Blind, Placebo Controlled Trial. Evid Based Complement Alternat Med. 2019 Apr 15;2019:7923732. doi: 10.1155/2019/7923732. eCollection 2019.
- 3312B