Aging is an inevitable physiological process that shows signs of functional decline at the tissue and cellular levels over time. Chronic diseases such as neurodegenerative diseases, cardiovascular diseases, metabolic disorders, and immune system dysfunction have become the main threat to the decline of quality of life and the end of life of the elderly. Therefore, it is particularly urgent to seek strategies and biomarkers to delay aging, and to develop early personalized interventions. We will focus on the following aspects:
1. Construction of aging prediction model
Integrating the biological datasets-genomics, proteomics, metabolomics, imaging, and behavioral data-to build a comprehensive aging prediction model. The model is instrumental in forecasting individual biological age and pinpointing biomarkers with the potential to retard the aging process.
2. Study of the causal relationship between lifestyle and aging, and to propose personalized regulation strategies
To harness genomic data to perform a genome-wide association study (GWAS) coupled with Mendelian randomization analysis, thereby dissecting the intricate causal interplay between lifestyle, like physical activity, dietary habits, sleep patterns, and psychological well-being, with the biological age. The objective is to uncover the factors that may expedite the aging process, offering insights for crafting personalized, multifaceted intervention strategies, such as augmenting physical exercise, refining dietary intake, and fostering psychological resilience.
3. Mediation analysis of behaviour – biological age – chronic diseases
Using mediation analysis, where behavioral and psychological attributes are treated as independent variables, biological age as the mediator, and chronic diseases as the dependent variable, to elucidate the mechanisms through which biological age influences the onset and progression of chronic conditions linked to unhealthy lifestyle.
