Our research project aims to investigate how phenotypes (e.g., lifestyle choices, environmental factors, genes, and pre-existing diseases) influence the risk of developing disease, mortality from disease, and alterations in disease-related biomarkers, particularly in relation to aging, mental health, cancer, heart health, infections, and autoimmune diseases, as well as to explore potential mediating factors. The UK Biobank Cohort offers a vast database of genetic and phenotypic information from a diverse group of individuals, making it an invaluable resource for our study. By analyzing this data, we hope to gain insights into the complex interplay between observable traits, which could ultimately lead to better strategies for preventing, diagnosing, and treating diseases. We’ll be using advanced statistical methods like generalized regression analysis and Cox proportional hazards models to examine the relationships between phenotypes, genes, and disease outcomes. These analyses will be adjusted for various factors like age, gender, race, income, BMI, smoking, alcohol consumption, and physical activity to ensure accurate results. Furthermore, we’ll explore both linear and nonlinear associations between traits and diseases, as well as conducting subgroup analyses to see if these associations differ across different population groups. Additionally, we’ll conduct mediation analyses to better understand the underlying mechanisms linking phenotypic traits to disease outcomes. Ultimately, our research aims to provide valuable insights into the complex relationships between observable traits, shedding light on the underlying mechanisms of disease development and progression. By doing so, we hope to contribute to the field of genetic epidemiology and population health research, ultimately leading to improved strategies for disease prevention and management.
