Fine-mapping genotype-phenotype associations

We propose to apply statistical fine-mapping methods to the UK Biobank genotype-phenotype data. We study how our recently published summary-data based fine-mapping method works with large sample sizes by fine-mapping anthropometric traits (e.g. body-mass-index), biomarker levels (e.g. cholesterol levels) and disease outcomes (e.g. cardiovascular events and cancer) in the UK Biobank. This project is expected to (1) refine information about the molecular mechanisms behind the genotype-phenotype associations in the UK Biobank data and to (2) provide guidelines how fine-mapping could be carried out in other large-scale cohorts. Our research is `health-related and in the public interest` since it generates tools to identify molecular mechanisms behind statistical genotype-phenotype associations, which is a key step in developing therapies against common complex diseases, including cardiovascular disease and cancers, that form a major burden for public health. We will first use the UK Biobank genotype data on hundreds of thousands of samples to generate synthetic phenotype data sets with which we can verify how our recently published fine-mapping method works on data of this scale. Then we will apply the method on the UK Biobank genotype-phenotype data to fine-map those genetic regions that show strong statistical signals of association with phenotypes considered. We will focus on self-reported and baseline measured traits as well as cancer and cardiovascular disease from the medical record data. We are applying for the full UK Biobank cohort.