Research Questions:
1. Develop and apply aging clock model based on multi-omics, functional performance, cognitive function, and imaging data environmental exposures, and health outcomes to quantify the impact of environmental pollution on biological aging.
2. To identify biomarkers and phenotypic characteristics that could predict accelerated aging due to environmental pollutants.
3. To assess the individual variability in resistance to pollution-induced aging using genomic data and identify potential genetic factors linked to this resistance.
4. COPD is an age-related disease, and both genetics and environment are risk factors for COPD. How do environmental exposures interact with these genetic variants to influence COPD susceptibility?
5. Through a comprehensive GWAS approach, we aim to elucidate the genetic underpinnings of age-related disease and provide insights into the interplay between genetics and environment in disease pathogenesis.
objectives and scientific rationale:
Aging is a complex biological process influenced by genetic, environmental, and lifestyle factors. Environmental pollutants, particularly air pollution, have been implicated in the acceleration of aging, contributing to various age-related diseases.
Aging clocks, which utilize biological markers such as blood biochemistry, gene expression, and omics data to estimate biological age, have become an essential tool for investigating the impact of environmental exposures on aging. By integrating multiple aging clocks with data on environmental exposures, phenotypic age, cognitive function, and functional performance, we can gain insights into how pollutants influence aging across different organs and systems. Moreover, genetic factors likely contribute to individual variability in the response to environmental stressors, making genetic susceptibility a crucial consideration in understanding the mechanisms behind accelerated aging.
