Identifying and understanding the molecular mechanisms of migraine via functional interpretation of genome-wide association study (GWAS) data
Abstract
Migraine is the most common brain disorder, affecting almost 14% of the adult population, yet its molecular mechanisms and pathogenic tissue(s) remain unclear. In this thesis, I have developed a novel approach that uses genome-wide association study (GWAS) summary statistics and expression quantitative trait loci (eQTL) data to impute genetically regulated tissue-specific gene expression and prioritise disease-relevant pathogenic tissues. In subsequent studies, I compared three transcriptome imputation models to characterise genome-wide significant migraine GWAS risk loci and identified 14 novel migraine risk loci that were confirmed to be true risk loci in a recent larger migraine GWAS.
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