Objectives
The MAMELI (MApping the Methylation of repetitive elements to track the Exposome effects on health: the city of Legnano as a LIving lab) project will enrol 6200 participants from Legnano (Milan), Italy, within a multi-tiered study design comprising four distinct investigative phases:

First level – Discovery Phase: This initial phase will include 200 healthy blood donors, each providing biological samples at two time points: baseline (T0) and six months later (T1). These two time points are expected to reflect changes in the exposome experienced by participants in their daily lives. Using Nanopore direct genomic DNA sequencing on peripheral blood leukocytes, this phase will generate an unbiased screening of RE methylation status. By identifying a subset of REs whose methylation patterns can vary without compromising genome stability, the Discovery Phase will establish the foundation for subsequent analyses and classification of RE methylation profiles.
Second level – Tuning Phase: In the second phase, a subset comprising the first 2,500 participants enrolled in the cohort will be analysed to develop a predictive model, referred to as the “MAMELI algorithm.” This algorithm will examine the relationship between RE methylation status and specific exposome profiles, generating predictive models of RE methylation based on observed exposomic patterns.
Third level – Validation Phase: In this phase, the MAMELI algorithm will be applied to an additional set of 3,500 participants to compare the observed RE methylation signatures with algorithm-based predictions. In addition, an embedded intervention study in a subset of participants will assess the reversibility of RE methylation changes in response to lifestyle modifications, thereby exploring their potential health-promoting and disease-preventive effects.
Fourth level – Long-term Phase: Finally, the project will investigate the long-term association between RE methylation adaptability and future health outcomes, with a particular focus on chronic disease risk, hospitalizations, and mortality.