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| Name | Class |
|---|---|
| American Heart Association | OTHER |
| Weizmann Institute of Science | OTHER |
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The aim of this 2-phase, randomized clinical trial will be to examine the effects of two behavioral weight loss interventions on weight loss. This study will be conducted in 200 overweight or obese prediabetic individuals recruited from community-based settings.. Phase 1 will include 6-months of active intervention. Phase 2 will consist of 6-months of maintenance and observation. Measurements will occur at screening, baseline, 3, 6, and 12 months. Participants will be randomized with equal allocation to 2 groups: (1) a standardized behavioral weight loss intervention with a one-size-fits-all regimen that includes counseling about restriction of calories and calories from fat, and physical activity, delivered using mHealth technology, or (2) all of the elements of mHealth, plus personalized dietary recommendations to minimize glycemic response to meals. Participants will be required to attend 6 separate visits over both phases of the study.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| mHealth | Active Comparator |
| |
| Personalized mHealth | Experimental |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| mHealth | Behavioral | Behavioral weight loss intervention using behavioral counseling focusing on physical activity and a one-size-fits-all, calorie-restricted, diet. |
|
| Measure | Description | Time Frame |
|---|---|---|
| Body weight, percent change | the primary outcome will be relative weight change as a percentage of body weight at baseline and 6-months using calibrated scale. | 6 months |
| Measure | Description | Time Frame |
|---|---|---|
| Body Composition | the secondary outcome will be absolute and relative changes in fat and lean body mass based on bioelectrical impedance analysis (BIA) from baseline to 6-months, 6-months to 12-months and baseline to 12-months | 6 & 12 months |
| Metabolic Adaptation |
| Measure | Description | Time Frame |
|---|---|---|
| Glycemic variability (GV ) | GV will be obtained from continuous glucose monitoring (CGM) tracings collected with the Abbott FreeStyle Libre Pro. | 6 months |
| RAGE/AGE/S100/A8/A9 | In the first 30 participants randomized to the study (15 in each group) having BMI ≥35 kg/m2, at each measurement time point we will examine activation of the RAGE/AGE/S100A8/A9 pathway using measurements of sRAGE, AGE level by ELISA, levels of S100A8/A9 by ELISA, circulating TNF-alpha, IL1-beta, IL4, IL10, and IL-17 |
Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Mary Ann Sevick, ScD | NYU Langone Medical Center, Department of Population Health | Principal Investigator |
| Eran Segal, PhD | Weizmann Institute of Science, Department of Computer Science and Applied Mathematics | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| New York University School of Medicine | New York | New York | 10016 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 41539436 | Derived | Berube LT, Wang C, Curran M, Pompeii ML, Hu L, Barua S, Li H, St-Jules DE, Schoenthaler A, Segal E, Bergman M, Popp CJ. Personalized Dietary Feedback Mediates the Association of Dietary Self-Monitoring Adherence and Weight Loss: A Post Hoc Analysis of the Personal Diet Study. J Nutr. 2026 Mar;156(3):101364. doi: 10.1016/j.tjnut.2026.101364. Epub 2026 Jan 13. | |
| 37236549 |
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| ID | Term |
|---|---|
| D018149 | Glucose Intolerance |
| D050177 | Overweight |
| D009765 | Obesity |
| ID | Term |
|---|---|
| D006943 | Hyperglycemia |
| D044882 | Glucose Metabolism Disorders |
| D008659 | Metabolic Diseases |
| D009750 | Nutritional and Metabolic Diseases |
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| ID | Term |
|---|---|
| D017216 | Telemedicine |
| ID | Term |
|---|---|
| D003695 | Delivery of Health Care |
| D010346 | Patient Care Management |
| D006298 | Health Services Administration |
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| Personalized mHealth | Behavioral | Behavioral weight loss intervention with personalized dietary recommendations based on machine learning algorithm that integrates gut microbiota, dietary intake, physical activity and various blood parameters to predict postprandial glycemic response. |
|
the secondary outcome will be the change in resting metabolic rate overall, and in relation to body weight and lean body mass from baseline to 6-months, 6- to 12-months, and baseline to 12-months. Resting metabolic rate will be estimated using indirect calorimetry with the participant in a fasting state (12 hours) |
| 6 & 12 months |
| Weight regain | 12 months |
| 6 & 12 MONTHS |
| Adipokines | Leptin and high molecular weight adiponectin each measurement time point in the subsample of participants having BMI ≥35 kg/m2 | 6 & 12 months |
| Self-efficacy | Self-efficacy for weight loss will be assessed using the well-validated Weight Efficacy Lifestyle Questionnaire (WEL) | 3,6, 12-months |
| Kharmats AY, Popp C, Hu L, Berube L, Curran M, Wang C, Pompeii ML, Li H, Bergman M, St-Jules DE, Segal E, Schoenthaler A, Williams N, Schmidt AM, Barua S, Sevick MA. A randomized clinical trial comparing low-fat with precision nutrition-based diets for weight loss: impact on glycemic variability and HbA1c. Am J Clin Nutr. 2023 Aug;118(2):443-451. doi: 10.1016/j.ajcnut.2023.05.026. Epub 2023 May 24. |
| 36169954 | Derived | Popp CJ, Hu L, Kharmats AY, Curran M, Berube L, Wang C, Pompeii ML, Illiano P, St-Jules DE, Mottern M, Li H, Williams N, Schoenthaler A, Segal E, Godneva A, Thomas D, Bergman M, Schmidt AM, Sevick MA. Effect of a Personalized Diet to Reduce Postprandial Glycemic Response vs a Low-fat Diet on Weight Loss in Adults With Abnormal Glucose Metabolism and Obesity: A Randomized Clinical Trial. JAMA Netw Open. 2022 Sep 1;5(9):e2233760. doi: 10.1001/jamanetworkopen.2022.33760. |
| 35542387 | Derived | Popp CJ, Zhou B, Manigrasso MB, Li H, Curran M, Hu L, St-Jules DE, Aleman JO, Vanegas SM, Jay M, Bergman M, Segal E, Sevick MA, Schmidt AM. Soluble Receptor for Advanced Glycation End Products (sRAGE) Isoforms Predict Changes in Resting Energy Expenditure in Adults with Obesity during Weight Loss. Curr Dev Nutr. 2022 Mar 29;6(5):nzac046. doi: 10.1093/cdn/nzac046. eCollection 2022 May. |
| 31669004 | Derived | Popp CJ, Butler M, Curran M, Illiano P, Sevick MA, St-Jules DE. Evaluating steady-state resting energy expenditure using indirect calorimetry in adults with overweight and obesity. Clin Nutr. 2020 Jul;39(7):2220-2226. doi: 10.1016/j.clnu.2019.10.002. Epub 2019 Oct 14. |
| 30844471 | Derived | Popp CJ, St-Jules DE, Hu L, Ganguzza L, Illiano P, Curran M, Li H, Schoenthaler A, Bergman M, Schmidt AM, Segal E, Godneva A, Sevick MA. The rationale and design of the personal diet study, a randomized clinical trial evaluating a personalized approach to weight loss in individuals with pre-diabetes and early-stage type 2 diabetes. Contemp Clin Trials. 2019 Apr;79:80-88. doi: 10.1016/j.cct.2019.03.001. Epub 2019 Mar 4. |
| D044343 | Overnutrition |
| D009748 | Nutrition Disorders |
| D001835 | Body Weight |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |