This project aims to investigate genetic regulation and molecular mechanisms underlying thoracic diseases, particularly lung cancer, esophageal cancer, thymoma, thymic carcinoma, and COPD. These conditions impose a major health burden, yet their genetic determinants and regulatory networks remain incompletely understood.
We will use OTTERS, a TWAS framework that integrates GWAS data with eQTL reference weights to identify genes whose genetically regulated expression influences disease risk. Stage I eQTL weights will be obtained from public single-cell datasets, while Stage II will use UK Biobank GWAS data. OTTERS is already installed locally; no UKB data will be uploaded, ensuring data security.
The scientific rationale is that GWAS identifies loci but often lacks biological interpretation. TWAS links these loci to functional gene expression changes, and single-cell eQTL weights further localise signals to specific cell types, enabling more precise insights into thoracic disease mechanisms.
Objectives are: (1) perform GWAS and TWAS for thoracic cancers and respiratory diseases; (2) integrate single-cell eQTL with UKB GWAS to detect cell-type-specific associations; (3) extend analyses by incorporating proteomics, metabolomics, imaging, biomarkers, and lifestyle/environmental exposures; (4) identify candidate biomarkers and pathways for prevention or treatment.
Data requested: genetic data (genotyping, WES, WGS, telomere length); proteomics (Olink panels); metabolomics (NMR biomarkers); clinical biomarkers; imaging (thoracic/body MRI, CT, DEXA, ultrasound); cancer registry, HES, mortality; lifestyle/environmental variables.
This is a student project under the student rate. The work will form the basis of the MD thesis of my student at Peking Union Medical College.
