Type 2 Diabetes Clinical Trial
— DIABESTOfficial title:
Exploring Individual Determinants of postpranDIAl Glucose Response in Type 2 diaBEteS to opTimize Therapeutic Strategies With a Personalized Approach (DIABEST)
NCT number | NCT06057246 |
Other study ID # | 31/2023 |
Secondary ID | |
Status | Recruiting |
Phase | N/A |
First received | |
Last updated | |
Start date | May 15, 2023 |
Est. completion date | May 2025 |
Postprandial glycemia (PPG) is a relevant determinant of glucose control in people with type 2 diabetes (T2D). Epidemiological and pathophysiological studies indicate that PPG is a better risk predictor for cardiovascular disease and all-cause mortality than fasting plasma glucose. Therefore, both fasting and postprandial glycemia should be targeted to achieve optimal glycemic control and, thus, prevent or reduce the risk of diabetes complications. Post-prandial glucose response (PGR) cannot be predicted based solely on the meals' carbohydrate content. Recent research using continuous glucose monitoring (CGM) systems has identified different patterns of PGR to a standard meal among both healthy people and individuals with type 1 diabetes. Different contributors to the PGR have emerged, including genotype, hormonal and metabolic factors, phenotype, gut microbiota composition, background diet, sleep habits, physical activity levels. The present project aims at exploring the PGR in a real-life setting in a cohort of people with T2D, and identifying person-specific factors associated with different postprandial glucose patterns. To this purpose, 144 individuals with T2D on treatment with diet alone or diet plus metformin will be characterized for their anthropometric, metabolic, and gut-microbiome features and will undergo a one-week observational period through CGM system, while properly recording their food intake, physical activity, and sleep habits. A mixed-nutrient standardized meal will be consumed at home in two occasions by each participant to investigate the intra-individual variability of the PGR. Moreover, in a subgroup of participants (n=60), divided according to anthropometric and metabolic features, hormonal and metabolic response to the standardized meal will be evaluated at the hospital, to explore the contribution of different T2D phenotypes to the PGR. A further step will be developing a prediction algorithm of PGR based on the intra- and inter-individual factors shown to influence postprandial glucose, able to further optimize the management of T2D with precision therapeutic strategies.
Status | Recruiting |
Enrollment | 144 |
Est. completion date | May 2025 |
Est. primary completion date | September 2024 |
Accepts healthy volunteers | No |
Gender | All |
Age group | 30 Years to 70 Years |
Eligibility | Inclusion Criteria: - Men and post-menopausal women - HbA1c = 7.5% - Body Mass Index (BMI) 20-39.9 kg/m2 - Ability to comply with the study protocol activities. Exclusion Criteria: - Any acute or chronic condition possibly influencing the interpretation of the results or possibly worsened because of study participation - Pregnancy or breast-feeding - Use of antibiotics, probiotics, or prebiotics during the last three months. |
Country | Name | City | State |
---|---|---|---|
Italy | Department of Clinical Medicine and Surgery Federico II University | Naples |
Lead Sponsor | Collaborator |
---|---|
Federico II University |
Italy,
Berry SE, Valdes AM, Drew DA, Asnicar F, Mazidi M, Wolf J, Capdevila J, Hadjigeorgiou G, Davies R, Al Khatib H, Bonnett C, Ganesh S, Bakker E, Hart D, Mangino M, Merino J, Linenberg I, Wyatt P, Ordovas JM, Gardner CD, Delahanty LM, Chan AT, Segata N, Fran — View Citation
Bozzetto L, Pacella D, Cavagnuolo L, Capuano M, Corrado A, Scida G, Costabile G, Rivellese AA, Annuzzi G. Postprandial glucose variability in type 1 diabetes: The individual matters beyond the meal. Diabetes Res Clin Pract. 2022 Oct;192:110089. doi: 10.10 — View Citation
Hall H, Perelman D, Breschi A, Limcaoco P, Kellogg R, McLaughlin T, Snyder M. Glucotypes reveal new patterns of glucose dysregulation. PLoS Biol. 2018 Jul 24;16(7):e2005143. doi: 10.1371/journal.pbio.2005143. eCollection 2018 Jul. — View Citation
Shilo S, Godneva A, Rachmiel M, Korem T, Kolobkov D, Karady T, Bar N, Wolf BC, Glantz-Gashai Y, Cohen M, Zuckerman Levin N, Shehadeh N, Gruber N, Levran N, Koren S, Weinberger A, Pinhas-Hamiel O, Segal E. Prediction of Personal Glycemic Responses to Food — View 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, Elina — View Citation
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Post-prandial glucose response | Post-prandial glucose response will be calculated by the trapezoidal method as the area under the curve above the baseline value (iAUC). | 7 days (related to the 7-day continuous glucose monitoring) | |
Secondary | Energy intake | The energy intake expressed in kilocalories and derived by the analysis of the 7-day food record plus the European Prospective Investigation into Cancer and Nutrition (EPIC) questionnaire will be evaluated in relation to the post-prandial glucose response (iAUC). | 7 days (related to the 7-day continuous glucose monitoring and food record) | |
Secondary | Dietary components | The dietary components, namely available carbohydrates, total proteins, animal proteins, plant proteins, total fats, saturated fats, mono- and polyunsaturated fats, fibre and sugars (all expressed in grams), will be derived by the analysis of the 7-day food record and the (European Prospective Investigation into Cancer and Nutrition (EPIC) questionnaire, and evaluated in relation to the to the post-prandial glucose response (iAUC). | 7 days (related to the 7-day continuous glucose monitoring and food record) | |
Secondary | Gut-microbiota composition | Gut microbiota composition will be assessed using relative bacterial taxonomic abundances and measures of community diversity and richness (derived from 16 S ribosomal ribonucleic acid (rRNA) high-throughput sequencing of baseline stool specimens), and will be evaluated in relation to the post-prandial glucose response (iAUC). | 7 days (related to the 7-day continuous glucose monitoring) | |
Secondary | Physical activity levels | Physical activity levels as detected by the ActiGraph device (GT3X+ActiGraph LLC, Pensacola, Florida; sampling frequency: 30 Hz) worn for 7 days on the non-dominant wrist, and expressed as % of time spent in sedentary-light-moderate activity will be evaluated in relation to the post-prandial glucose response (iAUC). | 7 days (related to the 7-day continuous glucose and physical activity monitoring) | |
Secondary | Sleep duration | Sleep metrics, namely total sleep time, sleep onset latency, wake after sleep onset (all measured in minutes), as detected by ActiGraph device worn for 7 days and nights and calculated by the software (ActiGraph LLC, Pensacola, Florida; version 6.13.4), will be evaluated in relation to the post-prandial glucose response (iAUC). | 7 days (related to the 7-day continuous glucose and sleep monitoring) |
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