Personalized Nutrition Based on the Glycemic Response: Effect of Diet and Intestinal Microbiota

Personalized Nutrition Based on the Glycemic Response: Effect of Diet and Intestinal

This study will investigate whether changes in the intestinal microbiota generated through a nutritional strategy based on functional foods, modifies postprandial glycemic responses in subjects with prediabetes and obesity, which in turn will generate a personalized dietary intervention through a prediction of postprandial blood glucose levels.

Study Overview

• Status: Active, not recruiting
• Conditions: Obesity; Pre Diabetes
• Intervention / Treatment: Dietary supplement: A package containing a mix of functional foods; Other: Placebo ingredient group

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). Prediabetes is characterized by alterations in blood glucose concentrations and is considered an important risk factor for the development of T2D, considering that 70% of subjects with prediabetes will eventually develop the disease. Therefore, maintaining normal blood glucose concentrations is considered a critical point to prevent and control the development of T2D, mainly through lifestyle changes. 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.

Dietary intake is a central determinant of blood glucose concentrations therefore to maintain these concentrations within normal values, it is important to make adequate decisions regarding food, to induce a normal PPGRs. There are several methods to control the PPGRs such as the carbohydrate count which depends on the phenotypic characteristics of the patient. Other methods aimed at estimating the PPGRs like the glycemic index, which quantifies the PPGR derived from the consumption of a single type of food already tested, having limited applicability in the evaluation of the PPGR in real life where food is a set of different types and amounts of food, which are consumed at different times of the day under different conditions of sleep, physical activity and other activities of daily life that alter 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 evaluate whether the changes in the intestinal microbiota generated through a nutritional strategy based on functional foods, modifies postprandial glycemic responses in subjects with prediabetes and obesity, which in turn may generate a personalized dietary intervention through a prediction of postprandial blood glucose levels by an algorithm based-diet. This nutritional strategy consists of providing a set of functional foods such as nopal, chia, soy, inulin and the isoflavone genistein, since there is evidence that these foods lower blood glucose concentrations and modify the intestinal microbiota. A clinical trial will be conducted with 100 adults with prediabetes and obesity who meet the inclusion criteria. These patients will be divided into two groups of 50 each and their glucose will be continuously monitored with a continuous glucose monitor which will be taking glucose concentrations every 15 min. The patients will have one of two treatments; placebo or nutritional strategy with functional foods. They will be determined before and after monitoring: anthropometric and biochemical parameters, food consumption, physical activity, lifestyle, metabolites in urine as well as determination of the composition of the intestinal microbiota.

• Study Type: Interventional
• Enrollment (Actual): 100
• Phase: Not Applicable

Contacts and Locations

Study Locations

• Mexico
  • Mexico City, Mexico, 14080
    • Armando Roberto Tovar Palacio
  • Mexico City
    • México, Mexico City, Mexico, 14080
      • Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 60 years (Adult)
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

• Male and female.
• Adults between 18 and 60 years of age.
• BMI ≥ 30 and ≤ 50 kg/m2.
• Basal blood glucose 100 - 125 mg/dl
• 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.
• Positive smoking.

• Drug treatment:

  • Antihypertensive drugs or treatment (thiacycline, loop or potassium-sparing diuretics, angiotensin-converting enzyme inhibitor, angiotensin II receptor blockers, alpha blockers, calcium antagonists, beta blockers).
  • Treatment with hypoglycemic agents (sulfonylureas, methylalanines , 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 orlistat.
  • Supplements with any of the functional foods used in the study.
  • Probiotic, prebiotic or symbiotic supplements.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Treatment
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Double

Number of Arms

2

Arms and Interventions

Participant Group / 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 and genistein.	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 and genistein.
Placebo Comparator: Placebo Ingredient Group; The placebo group will receive a comparable set of food items that contain an equivalent number of calories per portion but without the added functional ingredients	Other: Placebo ingredient group; The control group will receive a comparable set of food items that contain an equivalent number of calories per portion but without the added functional ingredients

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Area under the curve of postprandial glucose response	Compare the effect between a nutritional strategy based on functional foods and the placebo group on postprandial glycemic response in subjects with obesity	2 weeks
Evaluation of the total daily interstitial glucose over 140 mg/dl	Total daily interstitial glucose levels will be evaluated by using Continuous glucose monitoring (CGM).	2 weeks

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
16s ribosomal gene analysis	Determine if changes in the composition of intestinal microbiota after the consumption of a nutritional strategy based on functional foods modify the postprandial glycemic response in subjects with obesity.	2 weeks

Collaborators and Investigators

• Sponsor: Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran
• Investigators: Principal Investigator: Armando R Tovar, PhD, Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran

Publications and helpful links

General Publications

• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• Kolodziejczyk AA, Zheng D, Elinav E. Diet-microbiota interactions and personalized nutrition. Nat Rev Microbiol. 2019 Dec;17(12):742-753. doi: 10.1038/s41579-019-0256-8. Epub 2019 Sep 20.
• 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. doi: 10.1093/ajcn/nqz142.

Study record dates

Study Major Dates

• Study Start (Actual): August 2, 2022
• Primary Completion (Estimated): May 31, 2025
• Study Completion (Estimated): August 30, 2025

Study Registration Dates

• First Submitted: January 7, 2022
• First Submitted That Met QC Criteria: January 28, 2022
• First Posted (Actual): February 8, 2022

Study Record Updates

• Last Update Posted (Actual): April 24, 2025
• Last Update Submitted That Met QC Criteria: April 19, 2025
• Last Verified: April 1, 2025

More Information

Terms related to this study

• Keywords: Functional Food; Postprandial Blood Glucose
• Additional Relevant MeSH Terms: Endocrine System Diseases; Metabolic Diseases; Glucose Metabolism Disorders; Diabetes Mellitus; Prediabetic State
• Other Study ID Numbers: 3312

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No