Systematic interpretation of large-scale GWAS analyses of 5,035 phenotypes

Abstract

This thesis presents the systematic interpretation of 5,035 genome-wide association studies (GWAS) conducted within the Estonian Biobank, aiming to elucidate the genetic determinants influencing a diverse array of phenotypic traits. Through a review of existing literature and the application of advanced bioinformatic tools, the work done in this thesis outlined the results of main post-GWAS methods, such as the identification of novel variants, SNP heritability estimation, fine-mapping of causal variants, and prioritization of genes associated with complex traits. Around 26% of the variants identified as lead ones in this work are novel and had not been implicated by GWASs before. Fine mapping prioritized single genetic variants for 10.3% of investigated loci, providing hypotheses for further functional studies, and the gene prioritization approach identified the 2,402 lead variants to be related to 804 genes, several of those biologically interpretable. Heritability was reliably inferred for 25% of studied phenotypes, the most heritable traits being “Other specified hypothyroidism” (ICD-10 code E03.8), “Obesity due to excess calories” (E66.0), “Obesity” (E66), “Myopia” (H52.1), and “Hypertension” (I10). These findings are a good starting point for a more in-depth interpretation of loci associated with complex diseases in the Estonian Biobank.