Obesity Clinical Trial
— METHYL-UPOfficial title:
Targeting DNA-methylation Fingerprints Linked to Ultra-Processed Foods Consumption to Prevent Non-communicable Diseases: the METHYL-UP Study
Verified date | February 2023 |
Source | IMDEA Food |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Interventional |
Non-communicable diseases (NCD) are the main health challenge in industrialized countries. However, these diseases are preventable if an intervention based on lifestyle is implemented at the population level. Diet has a great impact on the onset and progression of NCD. In this regard, ultra-processed food (UPF) consumption has been related to higher morbidity and mortality. UPF are defined as "formulations made mostly or entirely from substances derived from foods and additives, with little if any intact unprocessed or minimally processed foods" (NOVA definition). UPF are rich in saturated fats and additives and poor in fiber other nutrients. UPF consumption has raised in the last decades in the industrialized countries and this increase has been associated with higher prevalence of metabolic disorders such as diabetes, obesity, metabolic syndrome, cardiovascular disease, and cancer. However, mechanisms that link UPF consumption with NCD are poorly understood and clinical trials are needed to unravel these mechanisms and how to impact on them through lifestyle interventions. The investigators have previously identified DNA methylation marks associated with UPF consumption. DNA methylation marks are modifiable. The aim of the study is to assay if DNA methylation marks related to UPF consumption are reversible by reducing UPF consumption in a population of adults with overweight or obesity and with a high basal UPF consumption (>35% of total food consumption in g/day).
Status | Completed |
Enrollment | 33 |
Est. completion date | December 31, 2022 |
Est. primary completion date | December 31, 2022 |
Accepts healthy volunteers | No |
Gender | All |
Age group | 18 Years to 50 Years |
Eligibility | Inclusion Criteria: - Men/women - 18-50 years old - BMI 25-40 Kg/m2 - UPF consumption > 35% of total intake in g/day Exclusion Criteria: - Pregnancy - Menopause - IMC <25 Kg/m2 or > 40 Kg/m2 - Excessive alcohol consumption - Prevalent cardiovascular, renal, lung, pancreatic or liver disease - Type 1 diabetes - Type 2 diabetes with poor glucose control or unstable medication during last 3 months - Prevalent endocrine disease - Changes in anti-hypertensive medication during last 3 months - Insulin, systemic anti-inflammatory, or glucocorticoid medication during last 3 months - Food allergies or intolerances - Psychosocial or cultural factors that prevent from following the intervention |
Country | Name | City | State |
---|---|---|---|
Spain | IMDEA Food | Madrid |
Lead Sponsor | Collaborator |
---|---|
IMDEA Food |
Spain,
Konieczna J, Morey M, Abete I, Bes-Rastrollo M, Ruiz-Canela M, Vioque J, Gonzalez-Palacios S, Daimiel L, Salas-Salvado J, Fiol M, Martin V, Estruch R, Vidal J, Martinez-Gonzalez MA, Canudas S, Jover AJ, Fernandez-Villa T, Casas R, Olbeyra R, Buil-Cosiales P, Babio N, Schroder H, Martinez JA, Romaguera D; PREDIMED-Plus investigators. Contribution of ultra-processed foods in visceral fat deposition and other adiposity indicators: Prospective analysis nested in the PREDIMED-Plus trial. Clin Nutr. 2021 Jun;40(6):4290-4300. doi: 10.1016/j.clnu.2021.01.019. Epub 2021 Jan 28. — View Citation
Martinez-Perez C, Daimiel L, Climent-Mainar C, Martinez-Gonzalez MA, Salas-Salvado J, Corella D, Schroder H, Martinez JA, Alonso-Gomez AM, Warnberg J, Vioque J, Romaguera D, Lopez-Miranda J, Estruch R, Tinahones FJ, Lapetra J, Serra-Majem L, Bueno-Cavanillas A, Tur JA, Sanchez VM, Pinto X, Delgado-Rodriguez M, Matia-Martin P, Vidal J, Vazquez C, Ros E, Basterra J, Babio N, Guillem-Saiz P, Zomeno MD, Abete I, Vaquero-Luna J, Baron-Lopez FJ, Gonzalez-Palacios S, Konieczna J, Garcia-Rios A, Bernal-Lopez MR, Santos-Lozano JM, Bes-Rastrollo M, Khoury N, Saiz C, Perez-Vega KA, Zulet MA, Tojal-Sierra L, Ruiz ZV, Martinez MA, Malcampo M, Ordovas JM, San-Cristobal R. Integrative development of a short screening questionnaire of highly processed food consumption (sQ-HPF). Int J Behav Nutr Phys Act. 2022 Jan 24;19(1):6. doi: 10.1186/s12966-021-01240-6. — View Citation
Martinez-Perez C, San-Cristobal R, Guallar-Castillon P, Martinez-Gonzalez MA, Salas-Salvado J, Corella D, Castaner O, Martinez JA, Alonso-Gomez AM, Warnberg J, Vioque J, Romaguera D, Lopez-Miranda J, Estruch R, Tinahones FJ, Lapetra J, Serra-Majem L, Bueno-Cavanillas A, Tur JA, Sanchez VM, Pinto X, Gaforio JJ, Matia-Martin P, Vidal J, Vazquez C, Ros E, Bes-Rastrollo M, Babio N, Sorli JV, Lassale C, Perez-Sanz B, Vaquero-Luna J, Bazan MJA, Barcelo-Iglesias MC, Konieczna J, Rios AG, Bernal-Lopez MR, Santos-Lozano JM, Toledo E, Becerra-Tomas N, Portoles O, Zomeno MD, Abete I, Moreno-Rodriguez A, Lecea-Juarez O, Nishi SK, Munoz-Martinez J, Ordovas JM, Daimiel L. Use of Different Food Classification Systems to Assess the Association between Ultra-Processed Food Consumption and Cardiometabolic Health in an Elderly Population with Metabolic Syndrome (PREDIMED-Plus Cohort). Nutrients. 2021 Jul 20;13(7):2471. doi: 10.3390/nu13072471. — View Citation
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Other | DNA methylation | Reversibility of DNA methylation marks | 12 months | |
Other | Glucose | Change in fastin glucose levels (mg/dL) | 9 months | |
Other | Glycated haemoglobin | Change in fastin glycated haemoglobin levels (%) | 9 months | |
Other | Triglycerides | Change in fasting triglycerides levels (mg/dL) | 9 months | |
Other | LDL-cholesterol | Change in fasting LDL-cholesterol levels (mg/dL) | 9 months | |
Other | HDL-cholesterol | Change in fasting HDL-cholesterol levels (mg/dL) | 9 months | |
Other | Liver profile | Change in HSI liver function index | 9 months | |
Other | Microbiota | Changein microbiota diversity | 24 months | |
Primary | UPF | Ultra-processed food consumption | 6 months | |
Secondary | Weight | Weight change (Kg) | 6 months | |
Secondary | BMI | Change in body mass index (Kg/m2) | 6 months | |
Secondary | Obesity | Percentage of participants who reverse obesity condition (BMI < 30 Kg/m2) | 6 months | |
Secondary | Body composition | Change in % of fat mass | 6 months |
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