Jenny Pavlides, UQ : "Integrating genome-wide association study data with gene expression to understand complex traits and common diseases"

Speaker:

Jenny Pavlides (MPhil Exit Seminar)

Queensland Brain Institute, University of Queensland

Title: "Integrating genome-wide association study data with gene expression to understand complex traits and common diseases"

Abstract:

Complex traits and diseases are generally polygenic in nature, meaning they are influenced by many genetic loci, and the effect of each genetic variant is likely to be small. Most complex traits and diseases are moderately to highly heritable, however the proportion of genetic variance attributable to genome-wide significant variants, identified to date, is relatively low. Elucidating the genetic basis of complex traits and disease remains challenging. Although genome-wide association studies (GWAS) have helped to identify hundreds of susceptible loci for many complex traits and diseases, in most cases the actual causal variants are yet to be identified. The central theme of my thesis was to consider ways in which different types of genomic data, such as GWAS summary statistics and gene expression data, can be leveraged and combined to gain a better understanding of the aetiology of complex traits and diseases. My thesis had two key aims centred on the use of newly developed statistical methods for integrating GWAS and gene expression data. My first aim was identification of causal genes for complex traits. My second aim was to gain insight into sex differences in lifetime risk of psychiatric and neurological disorders.