A proteomic signature of healthspan.

The focus of aging research has shifted from increasing lifespan to enhancing healthspan to reduce the time spent living with disability. Despite significant efforts to develop biomarkers of aging, few studies have focused on biomarkers of healthspan. We developed a proteomics-based signature of healthspan (healthspan proteomic score (HPS)) using data from the UK Biobank Pharma Proteomics Project (53,018 individuals and 2920 proteins). A lower HPS was associated with higher mortality risk and several age-related conditions, such as COPD, diabetes, heart failure, cancer, myocardial infarction, dementia, and stroke. HPS showed superior predictive accuracy for these outcomes compared to chronological age and biological age measures. Proteins associated with HPS were enriched in hallmark pathways such as immune response, inflammation, cellular signaling, and metabolic regulation. Our findings demonstrate the validity of HPS, making it a valuable tool for assessing healthspan and as a potential surrogate marker in geroscience-guided studies.

Proteomic aging clock (PAC) predicts age-related outcomes in middle-aged and older adults.

Beyond mere prognostication, optimal biomarkers of aging provide insights into qualitative and quantitative features of biological aging and might, therefore, offer useful information for the testing and, ultimately, clinical use of gerotherapeutics. We aimed to develop a proteomic aging clock (PAC) for all-cause mortality risk as a proxy of biological age. Data were from the UK Biobank Pharma Proteomics Project, including 53,021 participants aged between 39 and 70 years and 2923 plasma proteins assessed using the Olink Explore 3072 assay®. 10.9% of the participants died during a mean follow-up of 13.3 years, with the mean age at death of 70.1 years. The Spearman correlation between PAC proteomic age and chronological age was 0.77. PAC showed robust age-adjusted associations and predictions for all-cause mortality and the onset of various diseases in general and disease-free participants. The proteins associated with PAC proteomic age deviation were enriched in several processes related to the hallmarks of biological aging. Our results expand previous findings by showing that biological age acceleration, based on PAC, strongly predicts all-cause mortality and several incident disease outcomes. Particularly, it facilitates the evaluation of risk for multiple conditions in a disease-free population, thereby, contributing to the prevention of initial diseases, which vary among individuals and may subsequently lead to additional comorbidities.

Proteomic aging clock (PAC) predicts age-related outcomes in middle-aged and older adults.

Beyond mere prognostication, optimal biomarkers of aging provide insights into qualitative and quantitative features of biological aging and might, therefore, offer useful information for the testing and, ultimately, clinical use of gerotherapeutics. We aimed to develop a proteomic aging clock (PAC) for all-cause mortality risk as a proxy of biological age. Data were from the UK Biobank Pharma Proteomics Project, including 53,021 participants aged between 39 and 70 years and 2,923 plasma proteins assessed using the Olink Explore 3072 assay®. The Spearman correlation between PAC proteomic age and chronological age was 0.77. A total of 10.9% of the participants died during a mean follow-up of 13.3 years, with the mean age at death 70.1 years. We developed a proteomic aging clock (PAC) for all-cause mortality risk as a surrogate of BA using a combination of least absolute shrinkage and selection operator (LASSO) penalized Cox regression and Gompertz proportional hazards models. PAC showed robust age-adjusted associations and predictions for all-cause mortality and the onset of various diseases in general and disease-free participants. The proteins associated with PAC were enriched in several processes related to the hallmarks of biological aging. Our results expand previous findings by showing that age acceleration, based on PAC, strongly predicts all-cause mortality and several incident disease outcomes. Particularly, it facilitates the evaluation of risk for multiple conditions in a disease-free population, thereby, contributing to the prevention of initial diseases, which vary among individuals and may subsequently lead to additional comorbidities.

Personality traits and Chinese college students' satisfaction with physical education classes: the mediating role of trait fluency and the moderating role of physical education class difficulty.

Background: This study aims to investigate the impact mechanism of personality traits on physical education satisfaction among college students, validating the mediating effect of trait flow and the moderating effect of physical education difficulty. By analyzing the influence mechanism of personality traits on college students' satisfaction with physical education classes, it helps to explore more channels to enhance satisfaction with physical education classes. Methods: A questionnaire survey was conducted using the Big Five Personality Scale, the Physical Education Class Satisfaction Scale, the Trait Fluency Scale, and the Physical Education Class Difficulty Scale with 868 public physical education students in 10 universities in Shanghai. Moderated mediation modeling was conducted using Hayes' PROCESS macro. Results: Personality traits are positively correlated with physical education satisfaction, and the predictive effect is significant (ß = 0.786, p < 0.001). This association is mediated by trait fluency (indirect effect: ß = 0.797, p < 0.001), accounting for 62.7% of the total effect. Physical education difficulty significantly moderates the predictive effects of personality traits on physical education satisfaction (ß = -0.183, p < 0.01) and trait fluency (ß = -0.130, p < 0.001). Additionally, physical education difficulty significantly moderates the predictive effect of trait fluency on physical education satisfaction (ß = 0.172, p < 0.001). Conclusion: Personality traits predict physical education satisfaction, with trait fluency playing a mediating role, and physical education difficulty moderates the direct and indirect paths through which personality traits influence physical education satisfaction.