Evaluation of the Effect of Seasonality on Biological Age in Adults
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age40+
SponsorSociété des Produits Nestlé (SPN)
About this trial
This research aims to provide insights on how seasonal variations influence biological age and enhance the design and analysis of long-term lifestyle interventions targeting biological clocks.
Aging is a gradual decline in cellular and organ functions, significantly increasing the risk of non-communicable and infectious diseases. Recent research has focused on identifying aging biomarkers that can better predict functional capability in healthy individuals. Biological age clocks, which can be measured from samples like blood or saliva, are emerging as valuable tools for assessing the pace of aging and calculating age acceleration-the difference between chronological and biological age.
These clocks utilize molecular and clinical data, including DNA methylation and plasma proteomics, to predict future health outcomes, such as disease risk and mortality. Various DNA methylation-based clocks have been developed, with the Dunedin Pace of Aging (PoAm) offering a more precise modeling of physiological changes over time. Lifestyle factors, including diet and physical activity, can influence age acceleration, suggesting that lifestyle interventions may impact biological aging.
Current evidence indicates that three specific epigenetic clocks-PhenoAge, GrimAge, and Dunedin PACE-are particularly effective in detecting beneficial effects on aging trajectories. However, the stability of these clocks during long-term lifestyle interventions remains unclear, as they can exhibit variability over short periods and may be affected by factors influenced by seasonal changes, such as Vitamin D levels, climate, and white blood cells composition.
To investigate these seasonal effects on biological age, a proposed observational study will track changes over a 12-month period in middle-aged and older adults.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
Males and females aged over 40 years, inclusive, at enrolment.
Assessed by the investigator to be in general good health or have stable, well-controlled chronic medical conditions (e.g. hypertension, type 2 diabetes, etc.) that are not expected to interfere with study participation or outcomes. (Note: stable medical condition is defined as controlled medical condition, with no change in medication, worsening of the condition, or hospitalization in the past 3 months prior to enrolment).
Body mass index (BMI) ≥18.5 kg/m².
Able to understand and to sign a written informed consent prior to study enrolment.
Disqualifiers
Any past or on-going significant medical/surgical condition and/or psychiatric condition, which in the opinion of the investigator may risk participant's wellbeing/safety, impede participant compliance with study procedures or ability to complete the study and/or could confound the primary objectives of the study (such as seasonal allergy).
Any acute illness or any recent medical/surgical intervention, including vaccination, within 21 days prior to enrolment.
Female participants who are pregnant or intending to become pregnant, lactating and/or breastfeeding
Currently participating in another interventional research study.
Trial population
In this study we will aim to enroll a total of 60 participants (accounting for a 20% drop out rate), living in Switzerland, that are over 40-year-old. The study aims to enroll male and female with balanced representation of each sex.
Trial design
Design model
Cohort
Time perspective
Prospective
Treatments tested in this trial
Not listed
Trial groups
60 Participants
are grouped into 1 trial groupGroup A: Adults (above or equal 40 y of age)
Trial outcomes
Primary outcomes
1
Effect of seasonality (meaning change between summer and winter observed in western Europe) on biological age calculated through different clocks in adults
Inter seasons (winter vs summer) variation in the difference between epigenetic age and chronological age, named "acceleration", calculated using the Phenoage, GrimAge and DunedinPace clock.
Time frame
From enrollment, 2 times over one year, 1 during summer and one during winterSecondary outcomes
1
Underlying factors explaining the seasonal differences in biological age measurements across various epigenetic clocks
Evaluation of the correlation between sleep (Pittsburgh Sleep Quality Index), diet (Healthy Eating Index) , exercise (number of hours spent doing physical activity per week) with biological age acceleration.and their correlation with inter-season epigenetic clocks variation
Time frame
From enrollment, 4 timepoints, one per season, throughout the whole study duration (1 year).2
Differences and associations in biological age measurements between various epigenetic clocks.
Correlation between Epigenetic age acceleration of GrimAge, PhenoAge and DunedinPace epigenetic clocks. Identify systematic differences between the three epigenetic clocks in age acceleration.
Time frame
From enrollment, 4 timepoints, one per season, throughout the whole study duration (1 year).3
Relationship between biological age and individuals' self-assessment of their overall health.
Evaluation of the correlation between age acceleration (calculated as the difference between epigenetic age and the chronological age) and the General health scale derived from answers to the SF-36 questionnaire
Time frame
From enrollment, 4 timepoints, one per season, throughout the whole study duration (1 year).Sponsors and contacts
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Source ClinicalTrials.gov