Clinical trial NCT03222791: Personalized Nutrition for Pre-Diabetes
Official title: Personalized Nutrition for Pre-Diabetes
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Pre Diabetes
Keywords: Diabetes
Lead sponsor: Weizmann Institute of Science
Sponsor class: OTHER
First posted: 2017-07-19
Enrollment: 244
Sex: ALL
Minimum age (years): 18
Maximum age (years): 55
Standard ages: ADULT
Accepts healthy volunteers: yes
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: PREVENTION

Brief summary: The Personalized Nutrition Project for Prediabetes (PNP3) study will investigate whether personalized diet intervention will improve postprandial blood glucose levels and other metabolic health factors in individuals with prediabetes as compared with the standard low-fat diet.

Detailed description: Blood glucose levels are rapidly increasing in the population, as evident by the sharp incline in the prevalence of prediabetes and impaired glucose tolerance estimated to affect, in the U.S. alone, 37% of the adult population. Chronic hyperglycaemia is a significant risk factor for type II diabetes mellitus (TIIDM), with up to 70% of prediabetics eventually developing the disease. It is also linked to other manifestations, collectively termed the metabolic syndrome, including obesity, hypertension, non-alcoholic fatty liver disease, hypertriglyceridemia and cardiovascular disease.

As blood glucose levels are mainly affected by food consumption, the growing number of blood glucose abnormalities is likely attributable to nutrition. Indeed, dietary and lifestyle changes normalize blood glucose levels in 55% -80% of the cases. Therefore, maintaining normal blood glucose levels is critical for preventing diabetes and its metabolic complications.

Currently, there are no effective methods for predicting the post prandial glycemic response (PPGR) of people to food. The current practice of using the meal carbohydrate content is a poor predictor of the PPGR and has limited efficacy.The glycemic index (GI), which quantifies PPGR to consumption of a single tested food type, and the derived glycemic load have limited applicability in assessing the PPGR to real-life meals consisting of arbitrary food combinations and varying quantities, consumed at different times of the day, and at different proximity to physical activity and other meals. Indeed, studies examining the effect of diets with a low glycemic index on TIIDM risk, weight loss, and cardiovascular risk factors yielded mixed results. The limited success of GI measure is probably due to the fact that it is a general index, which does not take into consideration the large variation between individuals in their glycemic response to food. It can be concluded, therefore, that in order to control glycemic response of an individual, a personalized tailored diet which takes into account various factors is required. Although genetic factors influence the levels of fasting blood glucose and glycemic response to food, these factors only explain approximately 10% of the variance in the population. Supporting this claim is the fact that the number of people with diabetes is increasing in recent years regardless of patients' genetic background. In contrast, environmental factors such as the composition of the intestinal bacteria and their metabolic activity may affect the glycemic response. The entire bacteria population in the digestive tract (microbiome) consist of \~1,000 species with a genetic repertoire of \~3 million different genes. The microbiome is directly affected by our diet and directly affect the body's response to food. This special relationship between the host and the intestinal flora is reflected by the composition of bacteria unique to type 2 diabetes and in the significant changes in the bacteria composition upon transition from a diet rich in fiber to a "Western" diet rich in simple sugars.

The study is conducted to evaluate a highly accurate algorithm developed at the Weizmann Institute of Science for predicting the personalized glucose response to food for each person. The algorithm"s predictions are based on many personal measurements, including blood tests, personal lifestyle and gut bacteria. In a small-scale pilot study that was conducted using this algorithm, the investigators personally tailored dietary interventions to healthy and prediabetic people, which resulted in significantly improved PPGRs accompanied by consistent alterations to the gut microbiota. These findings led the investigators to hypothesize that tailoring personalized diets based on PPGRs predictions may achieve better outcomes in terms of controlling blood glucose levels and its metabolic consequences relative to the current standard nutritional therapy for prediabetes.

Eligibility criteria: Inclusion Criteria:

* HbA1C 5.7 - 6.4
* Fasting Glucose 100 - 125 mg/dl
* Age - 18-55
* Capable of working with smartphone application

Exclusion Criteria:

* Antibiotics/antifungal in the last 3 month
* Use of anti-diabetic and/or weight-loss medication
* People under another diet regime and/or a dietitian consultation/another study
* Pregnancy, fertility treatments
* Chronic disease (e.g. HIV, Cushing syndrome, CKD, acromegaly, hyperthyroidism etc.)
* Cancer and recent anticancer treatment
* Psychiatric disorders
* Coagulation disorders
* IBD (inflammatory bowel diseases)
* Bariatric surgery
* Alcohol or substance abuse

Primary outcomes:
measure: Evaluation of the total daily time of plasma glucose levels below 140 mg/dl
timeFrame: 6 months
measure: Mean change in HbA1C from the baseline level
timeFrame: 6 months
measure: Mean change in Glucose Tolerance Test from the baseline level
timeFrame: 6 months
Secondary outcomes:
measure: Change is Fasting plasma glucose from baseline
timeFrame: 6 months
measure: Change in HOMA-IR from baseline
timeFrame: 6 months
Other outcomes:
measure: Patients compliance evaluation using a compliance questionnaire
timeFrame: 6 months, 12 months
Locations:
city: Rehovot
country: Israel
facility: The Weizmann Institute of Science
Study officials:
affiliation: Weizmann Institute of Science
name: Eran Segal, Prof.
role: PRINCIPAL_INVESTIGATOR
affiliation: Weizmann Institute of Science
name: Eran Elinav, MD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Ben-Yacov O, Godneva A, Rein M, Shilo S, Kolobkov D, Koren N, Cohen Dolev N, Travinsky Shmul T, Wolf BC, Kosower N, Sagiv K, Lotan-Pompan M, Zmora N, Weinberger A, Elinav E, Segal E. Personalized Postprandial Glucose Response-Targeting Diet Versus Mediterranean Diet for Glycemic Control in Prediabetes. Diabetes Care. 2021 Sep;44(9):1980-1991. doi: 10.2337/dc21-0162. Epub 2021 Jul 23.