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Descriptive comparative study of immunosenescence markers and their association with nutritional, metabolic, metabolomic and genetic characteristics in young (control), senior (age-associated immunosenescence), and populations susceptible to premature immunosenescence such as obese patients, cancer patients and patients who developed severe forms of COVID19 or persistent COVID19.
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.
The study consists of data capturing to evaluate the differential pattern of molecular markers of immunosenescence in different population groups, and applying a hypocaloric diet in the obesity subgroup together with recommendations for improving lifestyle habits. The data capture of this group during the intervention will be carried out with different sensors and questionnaires for a month. To do this, they will have to follow the explanations of the researchers.
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Group 1 (Traditional → Digital) | Experimental | 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. |
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| Group 2 (Digital → Traditional) | Experimental | 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) |
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| Group 3 - Young healthy population | No Intervention | n=100) Descriptive part: Data capture (clinical, anthropometric, lifestyle, genetic, biochemical, metabolomic and lipidomic data, among others) and comparison with the other groups. | |
| Group 4 - Senior population | No Intervention | n=100) Descriptive part: Data capture (clinical, anthropometric, lifestyle, genetic, biochemical, metabolomic and lipidomic data, among others) and comparison with the other groups. | |
| Group 5 - Oncological population |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Dietary intervention for healthy weight loss | Other | 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. |
| Measure | Description | Time Frame |
|---|---|---|
| BMI | Only in the obese/overweight population. Change in body mass index (Kg/m2) | 1 month |
| Blood Glucose | Change in blood glucose (mg/dl). Blood samples are going to be collected in visit 1 and visit 3 in the obese population, and in the visit 1 in the other populations. | 1 month |
| Concentration of interstitial glucose | Only in the obese/overweight population. Change in Interstitial Glucose (mgl/dl) measured continuously with the Freestyle glucometer (Abbott Laboratories) | 15 days |
| Blood lymphocytes | Variation in the percentage of blood lymphocytes analysed by flow cytometry in five different population groups (young healthy population, elderly, overweight-obese, cancer patients, and patients who developed severe forms of COVID-19 or persistent COVID-19). Other variables (described in the Secondary Outcomes), such as biochemical parameters, genetical data, microbiota, etc., will also be analyzed in order to identify specific molecular markers of immunosenescence. | 12 months |
| Measure | Description | Time Frame |
|---|---|---|
| Weight | Weight change (Kg) | 1 month |
| WC | Change in waist circumference (cm) | 1 month |
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Inclusion Criteria (commun for all groups):
Population-specific inclusion criteria:
Overweight/obese population:
Healthy young population:
Senior population
Oncology patients
Patients who developed severe or persistent COVID-19:
Exclusion Criteria:
Population-specific exclusion criteria:
Overweight/obese population:
Healthy young population:
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| Name | Affiliation | Role |
|---|---|---|
| Ana Ramírez de Molina, PhD | Fundación IMDEA Alimentación | Principal Investigator |
| Enrique Carrillo de Santa Pau, PhD | Fundación IMDEA Alimentación | Principal Investigator |
| María Isabel Espinosa Salinas, PhD | Fundación IMDEA Alimentación | Principal Investigator |
| Cristina María Fernández Díaz, PhD | Fundación IMDEA Alimentación | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| IMDEA Food | Madrid | 28049 | Spain |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 25815989 | Background | 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. | |
| 30954305 | Background | 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. |
| Label | URL |
|---|---|
| Research team profile | View source |
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| ID | Term |
|---|---|
| D002908 | Chronic Disease |
| ID | Term |
|---|---|
| D020969 | Disease Attributes |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
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| ID | Term |
|---|---|
| D004035 | Diet Therapy |
| ID | Term |
|---|---|
| D044623 | Nutrition Therapy |
| D013812 | Therapeutics |
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(n=100) Descriptive part: Data capture (clinical, anthropometric, lifestyle, genetic, biochemical, metabolomic and lipidomic data, among others) and comparison with the other groups. |
| Group 6 - COVID-19 population | No Intervention | (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. |
|
| Body composition | Change in % of fat mass | 1 month |
| Blood pressure | During the 2 weeks in which the participant gathers the information via Traditional data-collection method, it will be measured in the study visits with an automatic Digital Blood Pressure Monitor Model M3 (OMRON HEALTHCARE UK, Kyoto, Japan). And during the 2 weeks in which the participant gathers the information via the Digital data-collection method, it will be measured with the Smartwatch Fitbit Sense. | 1 month |
| Heart Rate | During the 2 weeks in which the participant gathers the information via Traditional data-collection method, it will be measured in the study visits with an automatic Digital Blood Pressure Monitor Model M3 (OMRON HEALTHCARE UK, Kyoto, Japan). And during the 2 weeks in which the participant gathers the information via the Digital data-collection method, it will be measured with the Smartwatch Fitbit Sense. | 1 month |
| Dietary intake | Traditional data-collection method: Two 3-day dietary records (for two working days and a holiday); Digital data-collection method: Pictures of food taken with a smartphone. | 1 month |
| Physical activity | One same outcome measured during 2 weeks with one method and during the other 2 weeks with another method: During the 2 weeks in which the participant gathers the information via Traditional data-collection method, it will be measured via the validated International Physical Activity Questionnaire (USA Spanish version translated 3/2003 - Short last 7 DAYS self-administered version of the IPAQ - Revised August 2002). And during the 2 weeks in which the participant gathers the information via the Digital data-collection method, it will be measured with the Smartwatch Fitbit Sense. | 1 month |
| Sleep | One same outcome measured during 2 weeks with one method and during the other 2 weeks with another method: During the 2 weeks in which the participant gathers the information via Traditional data-collection method, it will be measured via the validated Oviedo Sleep Questionnaire. In the Oviedo Sleep Questionnaire, the higher the score, the greater insomnia's severity. And during the 2 weeks in which the participant gathers the information via the Digital data-collection method, it will be measured with the Smartwatch Fitbit Sense. | 1 month |
| Mental health state | One same outcome measured during 2 weeks with one method and during the other 2 weeks with another method: During the 2 weeks in which the participant gathers the information via Traditional data-collection method, it will be measured via the validated Depression Anxiety and Stress Scale - 21 (DASS-21). In the Depression Anxiety and Stress Scale, the higher the score, the greater the stress, anxiety and depression levels. And during the 2 weeks in which the participant gathers the information via the Digital data-collection method, it will be measured with the Smartwatch Fitbit Sense. | 1 month |
| Cognition | Measured via the validated Mini-mental state examination (MMSE). In the Mini-mental state examination, the higher the score, the better the cognitive status. | 1 month |
| Health status and quality of life | Measured via the validated Short Form-36 Health Survey (SF-36). In the Short Form-36 Health Survey, the higher the score, the better the quality of life and health status. | 1 month |
| Percentage of glycated haemoglobin | During the 2 weeks in which the participant gathers the information via Traditional data-collection method, it will be only measured in the study visits with the blood tests. And during the 2 weeks in which the participant gathers the information via the Digital data-collection method, it will be measured continuously with the Freestyle glucometer (Abbott Laboratories), and in the study visits with the blood tests. | 1 month |
| Total cholesterol | Blood samples are going to be collected in visit 1 and visit 3 in the obese population, and in the visit 1 in the other populations. | 1 month |
| Low density lipoprotein (LDL) | Blood samples are going to be collected in visit 1 and visit 3 in the obese population, and in the visit 1 in the other populations. | 1 month |
| High density lipoprotein (HDL) | Blood samples are going to be collected in visit 1 and visit 3 in the obese population, and in the visit 1 in the other populations. | 1 month |
| Triglycerides | Blood samples are going to be collected in visit 1 and visit 3 in the obese population, and in the visit 1 in the other populations. | 1 month |
| Apo A1 | Blood samples are going to be collected in visit 1 and visit 3 in the obese population, and in the visit 1 in the other populations. | 1 month |
| Apo B | Blood samples are going to be collected in visit 1 and visit 3 in the obese population, and in the visit 1 in the other populations. | 1 month |
| Insulin | Blood samples are going to be collected in visit 1 and visit 3 in the obese population, and in the visit 1 in the other populations. | 1 month |
| Glycated hemoglobin (HbA1c) | Blood samples are going to be collected in visit 1 and visit 3 in the obese population, and in the visit 1 in the other populations. | 1 month |
| Homeostatic model assessment (HOMA) | Blood samples are going to be collected in visit 1 and visit 3 in the obese population, and in the visit 1 in the other populations. | 1 month |
| Albumin | Blood samples are going to be collected in visit 1 and visit 3 in the obese population, and in the visit 1 in the other populations. | 1 month |
| Prealbumin | Blood samples are going to be collected in visit 1 and visit 3 in the obese population, and in the visit 1 in the other populations. | 1 month |
| C-reactive protein (CRP) | Blood samples are going to be collected in visit 1 and visit 3 in the obese population, and in the visit 1 in the other populations. | 1 month |
| Leptin | Blood samples are going to be collected in visit 1 and visit 3 in the obese population, and in the visit 1 in the other populations. | 1 month |
| Adinopectin | Blood samples are going to be collected in visit 1 and visit 3 in the obese population, and in the visit 1 in the other populations. | 1 month |
| Faecal microbiota | Faecal microbiota taxonomic profiling through shotgun sequencing. | 1 month |
| Gut dysbiosis | Lipopolysaccharide-binding protein (LBP) levels as an indirect measure of intestinal dysbiosis. | 1 month |
| Genotype | Genotyping of single nucleotide genetic variants (SNPs) and specific mutations associated with metabolism, nutrition and immunodegenerative processes. | 1 month |
| Gene expression | Expression panels in genes related to the regulation of metabolism, inflammation, immunity, oxidation, nutrition and immunodegenerative processes. | 1 month |
| 32468984 | Background | 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. |
| 40168934 | Derived | 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. |
| Research team profile | View source |
| Research team profile | View source |