About
This project aims to develop and validate multi-omics risk prediction models for otolaryngological diseases, including hearing loss, tinnitus, chronic rhinosinusitis, Ménière's disease, obstructive sleep apnea, and head-neck cancers. The primary research questions focus on identifying proteomic, metabolomic, and lipidomic biomarkers associated with these conditions, integrating them with polygenic risk scores (PRS) derived from genomic data to improve predictive accuracy. Objectives include constructing disease-specific PRS using UK Biobank's genetic data, performing cross-omics correlation analyses to identify synergistic biomarker networks, and validating models through prospective risk stratification. The scientific rationale lies in addressing the heterogeneity and multifactorial etiology of otolaryngological diseases, where single-omics approaches have limited discriminative power. By leveraging UK Biobank's large-scale multi-omics datasets, this study will elucidate molecular pathways (e.g., inflammatory, oxidative stress) contributing to disease onset and progression, enabling early-risk identification and personalized prevention strategies.