Pre DiabetesNCT03222791
Personalized Nutrition for Pre-Diabetes
A study testing Algorithm-based diet and Mediterranean-style low-fat diet in people with Pre Diabetes, run by Weizmann Institute of Science at 1 site in Israel.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 to 55 yearsHealthy volunteers can take part
- Conditions the study is for
- Pre Diabetes
- What is being tested?
- Algorithm-based diet and Mediterranean-style low-fat diet
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 244 participants
- Where
- 1 siteIsrael
- Study dates
- 1 Feb 2017to 1 Mar 2020
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 55 years
- All sexes
- Healthy volunteers accepted
- Adult
Who may be able to join
- HbA1C 5.7 - 6.4
- Fasting Glucose 100 - 125 mg/dl
- Age - 18-55
- Capable of working with smartphone application
Who cannot join
- 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
Show all 11Show fewer
- Psychiatric disorders
- Coagulation disorders
- IBD (inflammatory bowel diseases)
- Bariatric surgery
- Alcohol or substance abuse
Trial locations and contacts
1 site in 1 country.
About this study
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.
Read the 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.
- Conditions
- Pre Diabetes
- Being tested
- Algorithm-based diet, Mediterranean-style low-fat diet
- Keywords
- Diabetes
- Medical subject headings
- Glucose Intolerance, Diabetes Mellitus
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Algorithm-based dietOther
Personalized nutrition plan based on an algorithm for predicting the personalized glucose response to food. The algorithm's predictions are based on many personal measurements, including blood tests, personal lifestyle and gut bacteria.
Mediterranean-style low-fat dietOther
The Israeli standard of care dietary guidelines for prediabetes.
| Study group | Role | What they receive |
|---|---|---|
| Algorithm-based diet | Experimental | Subjects randomized to this arm will receive personally tailored dietary recommendations based on their predicted glycemic responses according to the study algorithm. Receives: Other: Algorithm-based diet |
| Mediterranean-style low-fat diet | Other | Subjects randomized to this arm will receive nutritional recommendations according to the standard Israeli dietary approach for treating pre-diabetes: Mediterranean-style low-fat diet. Receives: Other: Mediterranean-style low-fat diet |
What is being measured
The primary outcome is the main question the study is designed to answer.
Evaluation of the total daily time of plasma glucose levels below 140 mg/dl
Total daily plasma glucose levels will be evaluated by using a Continuous glucose monitoring (CGM)
Measured: 6 months
Mean change in HbA1C from the baseline level
Difference of at least 0.1% in the reduction of HbA1C between control group and experimental group
Measured: 6 months
Mean change in Glucose Tolerance Test from the baseline level
GTT glucose values (mg/dl)
Measured: 6 months
Secondary outcomes (2)
Change is Fasting plasma glucose from baseline
Fasting glucose values (mg/dl)
Measured: 6 months
Change in HOMA-IR from baseline
Change in insulin sensitivity from baseline to 6 months will be measured via HOMA-IR
Measured: 6 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted19 Jul 2017
- Study start1 Feb 2017
- Primary completion10 Sep 2019
- Study completion1 Mar 2020
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (2)Papers the sponsor has linked to this study.
- Other trials for Pre DiabetesStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Prevention
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind
- Who is masked
- Participant
- Enrolment
- 244 participants (actual)
Sponsor and investigators
- Lead sponsor
- Weizmann Institute of Science
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Eran Segal, Prof., Principal investigator, Weizmann Institute of ScienceEran Elinav, MD, Principal investigator, Weizmann Institute of Science
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03222791
- Sponsor's protocol ID
- 20170117
- Status last verified
- Apr 2020
- First submitted
- 13 Jul 2017
- Last updated
- 22 Apr 2020
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
Ben-Yacov O, Godneva A, Rein M, Shilo S, Lotan-Pompan M, Weinberger A, Segal E. Gut microbiome modulates the effects of a personalised postprandial-targeting (PPT) diet on cardiometabolic markers: a diet intervention in pre-diabetes. Gut. 2023 Aug;72(8):1486-1496. doi: 10.1136/gutjnl-2022-329201. Epub 2023 May 3.
PubMed 37137684Ben-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.
PubMed 34301736
Study at a glance
From the registry record, last updated by the sponsor on 22 Apr 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Personalized Nutrition for Pre-Diabetes
- ClinicalTrials.gov ID
- NCT03222791
- Acronym / sponsor ID
- 20170117
- Conditions
- Pre Diabetes
- Keywords
- Diabetes
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 244 participants (actual)
- Lead sponsor
- Weizmann Institute of ScienceUniversity, hospital or other
- Study start
- 1 Feb 2017 (actual)
- Primary completion
- 10 Sep 2019 (actual)
- Study completion
- 1 Mar 2020 (actual)
- First posted
- 19 Jul 2017 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Primary purpose
- Prevention
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (participant)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Algorithm-based diet | Experimental | Other: Algorithm-based dietSubjects randomized to this arm will receive personally tailored dietary recommendations based on their predicted glycemic responses according to the study algorithm. |
| Mediterranean-style low-fat diet | Other | Other: Mediterranean-style low-fat dietSubjects randomized to this arm will receive nutritional recommendations according to the standard Israeli dietary approach for treating pre-diabetes: Mediterranean-style low-fat diet. |
Who may qualify
- Ages
- 18 to 55 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult
Key inclusion criteria (4 listed)
- HbA1C 5.7 - 6.4
- Fasting Glucose 100 - 125 mg/dl
- Age - 18-55
- Capable of working with smartphone application
Key exclusion criteria (11 listed)
- 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.)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Algorithm-based dietPersonalized nutrition plan based on an algorithm for predicting the personalized glucose response to food. The algorithm's predictions are based on many personal measurements, including blood tests, personal lifestyle and gut bacteria. | Other | Algorithm-based diet |
| Mediterranean-style low-fat dietThe Israeli standard of care dietary guidelines for prediabetes. | Other | Mediterranean-style low-fat diet |
Primary outcome
Evaluation of the total daily time of plasma glucose levels below 140 mg/dl
Time frame: 6 months
Total daily plasma glucose levels will be evaluated by using a Continuous glucose monitoring (CGM)
Mean change in HbA1C from the baseline level
Time frame: 6 months
Difference of at least 0.1% in the reduction of HbA1C between control group and experimental group
Mean change in Glucose Tolerance Test from the baseline level
Time frame: 6 months
GTT glucose values (mg/dl)
2 secondary outcomes
Change is Fasting plasma glucose from baseline
Time frame: 6 months
Change in HOMA-IR from baseline
Time frame: 6 months
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 22 Apr 2020.
- Derived from this study: PubMed 37137684Ben-Yacov O, Godneva A, Rein M, Shilo S, Lotan-Pompan M, Weinberger A, Segal E. Gut microbiome modulates the effects of a personalised postprandial-targeting (PPT) diet on cardiometabolic markers: a diet intervention in pre-diabetes. Gut. 2023 Aug;72(8):1486-1496. doi: 10.1136/gutjnl-2022-329201. Epub 2023 May 3.
- Derived from this study: PubMed 34301736Ben-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.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Eran Segal, Prof. principal investigator
Weizmann Institute of Science
Eran Elinav, MD principal investigator
Weizmann Institute of Science
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Algorithm-based diet and Mediterranean-style low-fat diet in people with Pre Diabetes, run by Weizmann Institute of Science at 1 site in Israel.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 11 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 22 Apr 2020. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Israel. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Evaluation of the total daily time of plasma glucose levels below 140 mg/dl (time frame: 6 months). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT03222791, which also lists 2 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 22 Apr 2020.