Environmental exposure to pollutants is a known risk factor for various diseases, including cardiovascular, cerebrovascular, metabolic, and neurodegenerative conditions. Pollutants such as particulate matter, heavy metals, and endocrine-disrupting chemicals contribute to inflammation, oxidative stress, and vascular dysfunction, accelerating disease progression. However, the underlying molecular mechanisms remain unclear.
This project aims to leverage UK Biobank data to identify key proteins, genes, and metabolites involved in disease progression. Using a multi-omics approach-integrating genomics, proteomics, and metabolomics-we will examine how environmental chemicals interact with or influence these biological molecules. The goal is to uncover molecular signatures linking environmental exposures to disease risk and build predictive models to improve risk assessment and forecasting.
Ultimately, we aim to identify early biomarkers to support targeted prevention and treatment strategies. This research will enhance understanding of how environmental factors contribute to disease and inform better prevention and therapeutic approaches using multi-omics data.
We plan to publish findings in peer-reviewed journals and present them at academic conferences through oral and poster presentations. Throughout, we will follow AI and data governance policies to ensure transparency, fairness, and reproducibility, and proactively address algorithmic bias.