Abstract
Background
The European Prospective Investigation into Cancer and Nutrition (EPIC) enrolled volunteers aged 30–65 years in the 1990s, collecting questionnaire data and blood samples. In 2024, the Turin (Italy) center initiated a recall of surviving participants, inviting them to complete an interviewer-administered questionnaire and provide a new blood sample. The aim of this study is to investigate healthy ageing in EPIC participants by comparing baseline and recall data, leveraging the availability of paired blood samples collected approximately 30 years apart to assess longitudinal biological changes.
Methods
A questionnaire concerning lifestyle and dietary habits, physical and psychological well-being, and health status is administrated to volunteers. Historical and recent samples were analysed using multiple approaches, including ELISA-based assessment of senescence-associated secretory phenotype (SASP) factors and metabolomic analysis of blood metabolites (untargeted approach). Preliminary analyses were conducted stratifying by age (70 years as threshold) and by comorbidity status (0, 1, and ≥2 diseases), using correlation analysis for SASP factors and k-means clstering for metabolomic field.
Results
Exploratory analyses included 722 participants. Higher levels of GDF15, TNFR1, and PARC were observed in individuals aged ≥70 years, consistent with existing literature. These biomarkers also increased with the number of comorbidities. Metabolomic analyses identified differences in mean metabolite levels between baseline and recall samples for a subset of metabolites. K-means clustering identified three participant groups characterized by distinct metabolomic profiles.
Conclusions
These preliminary findings support the involvement of selected biomarkers in ageing processes. Ongoing analyses integrating questionnaire data will further elucidate determinants of healthy ageing, with the aim of supporting health promotion strategies.
Key messages
• The availability of paired blood samples over 30 years offers a unique opportunity to track biological ageing and identify early markers of increased risk of multimorbidity in the population.
• Combining biomarker data with lifestyle and health information can support the development of targeted public health strategies to promote healthy ageing and reduce disease burden.