The concept of the exposome encompasses all the factors influencing human health throughout the life course. The exposome induces epigenetic changes, such as DNA methylation, which influence gene expression and impact overall health. Several recent studies have explored how repetitive elements (REs) in the genome can be activated in response to environmental stimuli. However, most of these investigations have assumed that altered RE methylation is always detrimental to individual health. The MAMELI project proposes an alternative hypothesis: that some REs are plastic entities capable of responding physiologically to environmental stimuli without compromising genome stability. This hypothesis suggests that the ability of DNA to adapt to environmental triggers could be monitored and used as an indicator of health resilience. To test this hypothesis, the MAMELI project will enroll 6,200 participants from the city of Legnano (Italy) and will be conducted in three main phases: i) A total of 200 healthy participants will undergo DNA methylation analysis through third-generation sequencing at two time points: T0 (baseline) and T1 (6 months after T0). This phase aims to identify a set of REs (“differential REs”) whose methylation changes in response to the exposome without affecting genome stability; ii) This phase will include 2,700 subjects (the original 200 participants from the discovery phase plus 2,500 additional subjects). The goal will be to develop a predictive algorithm (the MAMELI algorithm) that links the exposome to RE methylation status, creating a “RE methylation signature” reflecting the environmental impact on DNA methylation; iii) In this phase, the MAMELI algorithm will be applied to a separate cohort of 3,500 participants to compare the measured RE methylation signature with values predicted by the algorithm. Additionally, an intervention study will be embedded within the cohort to assess the reversibility of RE methylation following lifestyle changes. The MAMELI project offers a novel perspective in the field of epigenetics and environmental health, demonstrating how the epigenome can act as a sensor for environmental changes and how this interaction can be harnessed for disease prevention. If validated, the MAMELI algorithm could become a powerful tool for identifying individuals at risk and developing personalized interventions to improve global health outcomes.

Major Depressive Disorder (MDD) is a multifactorial disease which could be influenced by exposure to air pollution through disruption of sleep-wake cycles and other circadian-related behaviors. Our study aimed to investigate the interplay between air pollution exposure, DNA methylation of core clock genes involved in circadian rhythms, and MDD severity. Four hundred sixteen MDD patients (64 % females) agreed to participate and donated a blood sample to measure DNA methylation of the core clock genes CRY1, PER1, PER2, CLOCK, BMAL1. MDD severity and functioning was assessed using five rating scales. Daily mean estimates of particulate matter with diameter ≤ 2.5 μm (PM2.5) and nitrogen dioxide (NO₂) were assigned to study participants based on their residential address, and averaged to estimate different cumulative exposure windows. Multivariate regression models were applied to assess associations between air pollutants and core clock genes methylation and between DNA methylation of those same genes and MDD severity. PM2.5 exposure in the six months preceding recruitment was associated with CLOCK hypomethylation (β=-0.11, 95 % confidence interval [CI]:0.20; -0.02) and CRY1 hypermethylation (β=0.32, 95 %CI: 0.06; 0.58). All NO₂ exposure windows were associated with CRY1 hypermethylation. Increasing methylation of CLOCK was associated with lower MDD severity considering several scales (e.g., Hamilton Depression Rating Scale: β=-7.21, 95 %CI:3.97; -0.44). Taken together our findings shed some light on the complex mechanism underlying the pathogenesis of MDD, with a potentially relevant role of the environment and of its impact on epigenetic mechanisms altering the expression of core clock genes.

MicroRNAs (miRNAs) are small non-coding RNAs that negatively regulate gene expression at the post-transcriptional level. In plants, miRNAs are involved in environmental responses and can be transferred to other species to mediate cross-kingdom regulation of gene expression. This mechanism has recently been proposed in mammals, yet evidence remains scarce and inconsistent. Multiple studies have shown that a fraction of plant-derived miRNAs (pmiRNAs) present in food resist processing, cooking, and digestion. Evidence suggests that dietary-derived pmiRNAs might be absorbed in the gastrointestinal tract and enter circulation, predominantly packaged in extracellular vesicles, and reach different tissues, where they might exert cross-kingdom gene expression regulation. Nonetheless, several attempts to reproduce or confirm the above results have failed, raising questions about the reliability of studies supporting the hypothesis of cross-kingdom gene regulation by pmiRNAs. In this review, we recapitulate the state-of-the-art knowledge in the field, addressing both supporting and opposing evidence, as well as the main analytical challenges that need to be taken into consideration, in an effort to provide a comprehensive framework on the controversial evidence collected so far and support the use of best practices for future research.

Major Depressive Disorder (MDD) is a psychiatric condition whose onset and progression may be influenced by environmental factors. Our study investigates the association between greenness exposure and MDD severity, while also exploring the role of air pollutants and temperature. Three hundred ninety-six MDD patients were included. MDD severity was assessed using five rating scales. Two- and three-dimensional indicators of urban space were estimated around participants' houses: Normalized Difference Vegetation Index (NDVI), Green Volume, Grey Volume, and Normalized Difference Green-Grey Volume Index (NDGG). Annual exposure estimates of air pollutants and temperature were assigned to the participants' residential addresses. Multivariate linear and ordinal regression models were applied to assess associations between exposure variables and MDD severity, adjusting for and stratifying by air pollutants and temperature. Increasing levels of all urban space indicators (within a 100 m radius), except for Grey Volume, were associated with decreased MDD severity. The strongest effect was observed for Green Volume (e.g., Hamilton Depression Rating Scale [HAMD]: β = -2.67, 95 % confidence interval [CI]: -4.57; -0.76, for an interquartile range [IQR] increase in the exposure variable). The inverse associations between greenness and MDD severity were confirmed only when values of particulate matter ≤2.5 μm (PM2.5) were below the median (e.g. β = -5.32, 95 %CI: -8.28; -2.36 for an IQR increase in Green Volume). The same occurred with temperature levels below the median. Green spaces are associated with lower severity of depression, especially when PM2.5 and temperature levels are low.