Description of Immunosenescence Biomarkers and Nutritional Intervention to Evaluate the Implementation of Digital Tools
NCT ID: NCT05807243
Last Updated: 2023-04-11
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
NA
500 participants
INTERVENTIONAL
2022-05-09
2022-11-18
Brief Summary
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In one of these populations of premature immunosenescence, the population group with overweight or obesity, a prospective and cross-sectional nutritional intervention study is proposed, with data capture and monitoring using digital tools, to evaluate the evolution of immunosenescence markers and assess more objectively and effectively the nutritional status and help in making personalised decisions thanks to the application of these tools. This nutritional intervention will be focused on controlled and safe weight loss that will allow the capture of a large number of variables on lifestyle and dietary habits, nutritional assessment, biochemical, metabolic, genetic, metagenomic, lipidomic and metabolomic markers measured statically and also continuously.
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Detailed Description
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The data capture during the nutritional intervention (only for the overweight and obese population group) will be done as follows:
Group 1 (Traditional → Digital): will start with traditional data-collection methods, i.e. filling in nutritional and lifestyle questionnaires (Visit 1 to Visit 2). After two weeks, they will start capturing data digitally through the application of sensors (Visit 2 to Visit 3).
Group 2 (Digital → Traditional): will start with digital data-collection methods, using sensors and taking pictures of what they eat with a smartphone (Visit 1 to Visit 2). After two weeks, they will start capturing data traditionally, by filling in nutritional and lifestyle questionnaires (Visit 2 to Visit 3).
The nutritional intervention participant group will follow the tailored nutritional weight loss diet and lifestyle guidelines, which will be provided to them at the start of the study by the researchers. In addition, they should follow instructions for proper continuous data collection using sensors. This will avoid biases in the data collection process.
Conditions
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Study Design
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RANDOMIZED
CROSSOVER
PREVENTION
NONE
Study Groups
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Group 1 (Traditional → Digital)
Participants in both groups will be monitored for a month while following an hypocaloric diet for healthy weight-loss.
The first group (n=50) will start collecting data via questionnaires (traditional method) for the first two weeks, and switch to the digital data-collection method for the last two weeks.
Dietary intervention for healthy weight loss
Balanced and varied dietary plan adjusted to each participant's needs, with an approximate reduction of 500 Kcal from their total metabolic expenditure. The diet will be followed by the subjects during the 4 weeks of the study.
Group 2 (Digital → Traditional)
Participants in both groups will be monitored for a month while following an hypocaloric diet for healthy weight-loss.
The second group (n=50) will start with the digital data-collection method for the first two weeks and switch to the data collection via questionnaires (traditional method) for the last two weeks.
n=100)
Dietary intervention for healthy weight loss
Balanced and varied dietary plan adjusted to each participant's needs, with an approximate reduction of 500 Kcal from their total metabolic expenditure. The diet will be followed by the subjects during the 4 weeks of the study.
Group 3 - Young healthy population
n=100) Descriptive part: Data capture (clinical, anthropometric, lifestyle, genetic, biochemical, metabolomic and lipidomic data, among others) and comparison with the other groups.
No interventions assigned to this group
Group 4 - Senior population
n=100) Descriptive part: Data capture (clinical, anthropometric, lifestyle, genetic, biochemical, metabolomic and lipidomic data, among others) and comparison with the other groups.
No interventions assigned to this group
Group 5 - Oncological population
(n=100) Descriptive part: Data capture (clinical, anthropometric, lifestyle, genetic, biochemical, metabolomic and lipidomic data, among others) and comparison with the other groups.
No interventions assigned to this group
Group 6 - COVID-19 population
(n=100) patients who developed severe forms of COVID-19 or persistent COVID-19. Descriptive part: Data capture (clinical, anthropometric, lifestyle, genetic, biochemical, metabolomic and lipidomic data, among others) and comparison with the other groups.
No interventions assigned to this group
Interventions
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Dietary intervention for healthy weight loss
Balanced and varied dietary plan adjusted to each participant's needs, with an approximate reduction of 500 Kcal from their total metabolic expenditure. The diet will be followed by the subjects during the 4 weeks of the study.
Eligibility Criteria
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Inclusion Criteria
* Minimum 18 years old
* Adequate cultural level and understanding of the clinical study.
* Agree to participate voluntarily in the study and give written informed consent.
* Overweight/obese population:
* BMI 25-35 Kg/m2
* Ability to handle electronic devices for data capture.
* Healthy young population:
* Between 18 and 25 years old (both inclusive).
* Senior population
* Over 55 years of age.
* Oncology patients
* Over 18 years of age.
* With a clinical diagnosis of an active tumour process.
* Patients who developed severe or persistent COVID-19:
* Severe COVID-19: Patients who have suffered from COVID-19 disease and whose symptomatology is considered within the clinical pictures of severity of this disease, which may include: severe pneumonia, acute respiratory distress syndrome (ARDS), presence of respiratory failure (SaO2 \<90% room air) or respiratory rate ≥ 30 breaths per minute, sepsis, septic shock, thromboembolism and multi-organ dysfunction (including acute cardiac and renal injuries).
* COVID-19 persistence: Patients who have had COVID-19 disease and who remain with active symptomatology after what is considered the acute phase of the disease, after 4 or even 12 weeks, with symptoms persisting over time.
Exclusion Criteria
* Severe diseases (liver disease, kidney disease, etc.)
* BMI \> 35 Kg/m2
* Pregnancy or breastfeeding.
* Overweight/obese population:
* BMI \<25 Kg/m2 or \> 35 Kg/m2
* Pharmacological treatment for weight loss.
* Refusal to be monitored for one month by means of sensors and nutritional visits.
* Refusal to follow healthy eating guidelines for weight loss.
* Healthy young population:
* Chronic or acute pathologies.
18 Years
ALL
Yes
Sponsors
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IMDEA Food
OTHER
Responsible Party
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Principal Investigators
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Ana Ramírez de Molina, PhD
Role: PRINCIPAL_INVESTIGATOR
Fundación IMDEA Alimentación
Enrique Carrillo de Santa Pau, PhD
Role: PRINCIPAL_INVESTIGATOR
Fundación IMDEA Alimentación
María Isabel Espinosa Salinas, PhD
Role: PRINCIPAL_INVESTIGATOR
Fundación IMDEA Alimentación
Cristina María Fernández Díaz, PhD
Role: PRINCIPAL_INVESTIGATOR
Fundación IMDEA Alimentación
Locations
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IMDEA Food
Madrid, , Spain
Countries
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References
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Fontana L, Partridge L. Promoting health and longevity through diet: from model organisms to humans. Cell. 2015 Mar 26;161(1):106-118. doi: 10.1016/j.cell.2015.02.020.
GBD 2017 Diet Collaborators. Health effects of dietary risks in 195 countries, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2019 May 11;393(10184):1958-1972. doi: 10.1016/S0140-6736(19)30041-8. Epub 2019 Apr 4.
Moore JB. From personalised nutrition to precision medicine: the rise of consumer genomics and digital health. Proc Nutr Soc. 2020 Aug;79(3):300-310. doi: 10.1017/S0029665120006977. Epub 2020 May 29.
Lacruz-Pleguezuelos B, Bazan GX, Romero-Tapiador S, Freixer G, Tolosana R, Daza R, Fernandez-Diaz CM, Molina S, Crespo MC, Laguna T, Marcos-Zambrano LJ, Aguilar-Aguilar E, Fernandez-Cabezas J, Cruz-Gil S, Fernandez LP, Vera-Rodriguez R, Fierrez J, Ramirez de Molina A, Ortega-Garcia J, Morales A, Carrillo de Santa Pau E, Espinosa-Salinas I. AI4Food, a feasibility study for the implementation of automated devices in the nutritional advice and follow up within a weight loss intervention. Clin Nutr. 2025 May;48:80-89. doi: 10.1016/j.clnu.2025.03.003. Epub 2025 Mar 11.
Related Links
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Research team profile
Research team profile
Research team profile
Other Identifiers
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IMD: PI-052
Identifier Type: -
Identifier Source: org_study_id
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