Clinical trial NCT05230342: Personalized Nutrition Based on the Glycemic Response: Effect of Diet and Intestinal Microbiota
Official title: Personalized Nutrition Based on the Glycemic Response: Effect of Diet and Intestinal
Study type: INTERVENTIONAL
Overall status: ACTIVE_NOT_RECRUITING
Phase: NA
Conditions: Obesity
Pre Diabetes
Keywords: Postprandial Blood Glucose
Functional Food
Lead sponsor: Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran
Sponsor class: OTHER
First posted: 2022-02-08
Enrollment: 100
Sex: ALL
Minimum age (years): 18
Maximum age (years): 60
Standard ages: ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Intervention model description: The groups will receive the treatment simultaneously
Primary purpose: TREATMENT

Brief summary: 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.

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.

Eligibility criteria: 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.

Primary outcomes:
measure: Area under the curve of postprandial glucose response
timeFrame: 2 weeks
measure: Evaluation of the total daily interstitial glucose over 140 mg/dl
timeFrame: 2 weeks
Secondary outcomes:
measure: 16s ribosomal gene analysis
timeFrame: 2 weeks
Other outcomes:
Locations:
city: México
country: Mexico
facility: Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán
state: Mexico City
city: Mexico City
country: Mexico
facility: Armando Roberto Tovar Palacio
Study officials:
affiliation: Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubiran
name: Armando R Tovar, PhD
role: PRINCIPAL_INVESTIGATOR
References:
citation: 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.
citation: 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.
citation: 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.
citation: 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.
citation: 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.
citation: 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.
citation: 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.
citation: 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.
citation: 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.
citation: 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.
citation: 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.
citation: 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.