Extended abstract:

Background:
Cognitive decline represents one of the most impactful aspects of pathological aging, influencing autonomy and quality of life in older adults. Multiple biological, psychological, and environmental factors contribute to cognitive resilience or vulnerability. Among these, personality traits and circulating biochemical markers may modulate risk trajectories. This preliminary study explores their interrelation using data from the Novara Cohort Study (NCS), a longitudinal aging study in Northern Italy.

Materials and Methods:
We analyzed a subsample of 100 individuals (mean age: 60 years; 46.15% female), selected from the NCS based on the availability of cognitive, personality, and biochemical data. Cognitive performance was assessed using the Montreal Cognitive Assessment (MoCA), corrected for age and education (Aiello, 2023). Personality traits were evaluated through the Italian version of the Big Five Inventory-10 (BFI-10). Eight serum biomarkers associated with cognitive aging were measured: IGF-1, insulin, HbA1c, CRP, LDL, HDL, cortisol, and homocysteine. Statistical analyses included normality testing, group comparisons (MoCA ≤ or > 20.69), and Spearman correlations.

Results:
Subjects with preserved cognitive function showed higher median scores in openness, emotional stability, agreeableness, and conscientiousness, though differences were not statistically significant. HbA1c levels tended to be higher in cognitively impaired subjects. Significant inverse correlations were observed between HbA1c and MoCA (ρ = -0.244, p = 0.042), and between HbA1c and emotional stability (ρ = -0.240, p = 0.017), suggesting a possible mediating role of metabolic dysregulation. Additionally, homocysteine was negatively correlated with conscientiousness (ρ = -0.284, p = 0.040), and CRP with emotional stability (ρ = -0.107, p = 0.032).

Conclusion:
This study highlights potential associations between personality traits, metabolic biomarkers, and cognitive health. Although limited by sample size, the findings suggest that personality may influence cognitive aging indirectly via biological pathways. Larger cohorts and longitudinal analyses are needed to validate these trends and inform early prevention strategies targeting multidimensional determinants of cognitive decline.

Short abstract:

Cognitive decline is a key hallmark of pathological aging and results from complex interactions between biological and psychological factors. This study explores the relationship between cognitive performance, personality traits, and biochemical markers in older adults enrolled in the Novara Cohort Study (NCS). A subset of 65 participants (mean age: 70.8 years; 46.15% female) underwent cognitive screening with the Montreal Cognitive Assessment (MoCA), personality assessment using the Big Five Inventory-10 (BFI-10), and blood sampling for eight biomarkers: IGF-1, insulin, HbA1c, CRP, LDL, HDL, cortisol, and homocysteine. Participants were stratified into cognitively impaired (MoCA ≤ 20.69) and preserved (MoCA > 20.69) groups. Results revealed non-significant trends toward higher openness, emotional stability, agreeableness, and conscientiousness in the cognitively preserved group. Statistically significant negative correlations were observed between HbA1c and MoCA (ρ = -0.244; p = 0.042), as well as between HbA1c and emotional stability (ρ = -0.240; p = 0.017), suggesting that glucose metabolism dysregulation may impact both cognitive and personality domains. Homocysteine levels inversely correlated with conscientiousness (ρ = -0.284; p = 0.040), while CRP was negatively associated with emotional stability (ρ = -0.107; p = 0.032). These preliminary results suggest that personality traits may interact with metabolic and inflammatory pathways to influence cognitive aging. Future research on larger samples and with longitudinal follow-up is needed to confirm these findings and to investigate the potential for personality-informed preventive strategies.

Background:

Aging is a key factor influencing cancer onset, progression, therapeutic response, and tissue regenerative capacity. To develop preclinical models that integrate tumor biology with aging-related alterations, we established the GREAT Project: a growing biobank collection of patient-derived organoids (PDOs) alongside mesenchymal stem cells (MSCs) isolated from subcutaneous and visceral adipose tissues. The collection is continuously expanding to increase the diversity and number of cases.

Methods:

PDOs were generated from surgical specimens of primary colorectal and endometrial tumors through mechanical and enzymatic dissociation, followed by 3D culture in defined matrix conditions. These organoids retain the histological and molecular characteristics of the original tumors. Concurrently, MSCs were isolated from adipose tissue of patients with cancer or undergoing bariatric surgery, expanded in vitro, and characterized for stemness and differentiation potential.

Results:

PDOs faithfully replicate their tumors of origin, proving suitable for drug screening and biomarker discovery. MSCs provide a versatile platform to investigate aging’s impact on the tumor microenvironment, stromal support, and tissue regeneration. Together, these systems facilitate functional analysis of aging-related mechanisms driving cancer progression, therapy resistance, and regenerative processes.

Conclusions:

The GREAT biobank offers a translational bridge between cancer modeling and stem cell biology, advancing research by integrating aging, tumor development, and personalized therapy. Its ongoing expansion aims to further enhance the understanding and treatment of age-associated cancers.

Short version:

Aging is intricately associated with cancer onset, progression, and therapeutic response. To explore this connection, we have established an expanding biobank of patient-derived organoids (PDOs) from both healthy and tumor tissues, including colorectal and endometrial cancers, linked to detailed clinical data. The collection also includes mesenchymal stem cells (MSCs) isolated from subcutaneous and visceral adipose tissues. This integrated and continuously expanding biobank provides a robust preclinical platform for investigating personalized cancer therapies and the complex interplay between aging and tumor biology. PDOs preserve the histological, molecular, and functional features of the original tumors, enabling ex vivo drug testing and detailed molecular profiling. In parallel, MSCs serve as a model to study aging-related changes in the tumor microenvironment. The combined use of organoid and MSC models facilitates a comprehensive exploration of how aging influences cancer development, therapeutic resistance, and tissue remodeling.

Beyond oncology, MSCs are a key component of regenerative medicine due to their multipotency, immunomodulatory properties, and capacity to promote tissue repair. Their inclusion in the biobank enables investigations into how aging affects MSC function, with implications for the development of age-adjusted cell-based therapies in degenerative and inflammatory diseases.

Overall, this expanding biobank serves as a valuable translational platform to support precision oncology and to advance our understanding of the molecular and cellular mechanisms underlying age-related cancer and regenerative processes.

Background

Frailty is a complex medical condition characterized by a decline in physiological functions and global health and is a strong risk factor for disability, hospitalization and mortality. The identification of biomarkers associated with frailty could provide more information on the health status of older subjects. To this end, in this study, we investigated whether biomarkers such as GDF15, FGF21, sRAGE and NfL, alone or in combination, are associated with frailty in community-dwelling subjects of different ages.

Methods

We analyzed a cohort of 463 subjects (50-113 years) divided into four age groups (adults, elderly, nonagenarians and centenarians) and classified as frail and non-frail on the basis of a 45-items deficit accumulation model (frailty index, FI). Plasma levels of these biomarkers were analyzed by ELISA and studied for their possible association with FI. A Random Forest decision model (RFD) was used to evaluate the discriminatory power of the biomarkers with respect to FI.

Results

FI was associated with plasma levels of GDF15, NfL and FGF21, and the first two were also associated with survival. The RFD model based on the combination of four biomarkers estimated frailty with an accuracy of 82%. Furthermore, frailty estimation with this model led to a more accurate survival prediction over a 3-year follow-up period compared to FI.

Discussion

Our data suggest that GDF15, NfL, FGF21 and sRAGE could be valid parameters to provide additional information on frailty status and survival compared to FI alone in community-dwelling older subjects.

Background: Population-based cohorts enhanced with long-term air pollution (lt-AP) exposure data can elucidate the pathways linking lt-AP to cardiovascular (CV) risk. We report here on lt-AP data quality and cross-sectional analyses with CV health in the RoCAV cohort.

Methods: RoCAV is a population-based cohort of n=3777 50+ years old residents in Varese. At baseline (2013-2016), participants underwent lifestyles, clinical and laboratory assessments; we calculated the AHA-LS7 metric of CV health. Monthly and yearly concentrations of PM_2.5, PM₁₀, NO₂ and O₃ (8-hrs peak) in 2000-2019 were retrieved from the EXPANSE models (spatial resolution: 25mt), we compared these vs. measured concentrations at urban monitoring stations in the study region. Individuals’ concentrations were attributed from linkage at the residential address at baseline, geo-referenced; different lt-AP metrics were computed. We report Spearman correlation coefficients, and the associations between CV health and lt-AP in initially CV disease-free individuals (n=3,313).

Results: EXPANSE slightly overestimated the measured concentrations in the region, Variation Coefficients being +4.8% (PM_2.5) and +5.5% (NO₂). Among study participants, the 2013 mean±SD concentrations were 18.4±1.4 (PM_2.5) and 30.6±3.8 (NO₂) µg/m³; over 2010-2019, yearly concentrations slightly decreased for PM_2.5 and NO₂, increased for O₃. PM_2.5 was positively correlated with PM₁₀, NO₂ and with O₃; NO₂ was negatively correlated with O₃. Lower PM_2.5 and NO₂ values were associated with higher CV health, irrespective of the lt-AP metric used.

Conclusion: Lt-AP data in the RoCAV cohort are representative of contemporary concentrations in northern Italian urban areas, and well-suited to investigate the associations with CV risk.