Grant: Project Grant

Genome-wide association studies (GWASs) test all the genetic variants in our DNA, one at a time, for association with a disease or disease-related trait. These results allow researchers to generate and test hypotheses about the underlying molecular mechanisms of diseases. To date, GWASs have revealed hundreds of thousands of genetic variants across the DNA sequence, each associated with at least one human trait. The web-based analytical PheWeb tool was developed and applied to the largest GWASs in thousands of individuals to allow researchers to navigate and query this massive amount of information for hidden links and use it to test their disease-specific hypothesis. A key limitation is the inability to identify whether specific associations differ by sex. This gap prevents crucial hypothesis generation for sex-specific molecular mechanisms of complex diseases that is required to ultimately move towards personalized medicine. In this project, we will extend our interactive webtool, PheWeb, to allow for intuitive visualization and sharing of sex-stratified results as well as a quantitative metric to identify whether sex influences the association at each variant. Through this extension, PheWeb 2.0 will make sex-stratified association results from large GWASs available to researchers at their fingertips. The goal of this resource is to facilitate data sharing and collaboration among the community to advance research in computational genetic and genetic epidemiological analyses that allow for the discovery of sex-biased effects. We will use the Canadian Longitudinal Study of Aging (CLSA) and CARTaGENE (CaG) as the first genetic datasets to be used with the enhanced version of our tool. CLSA and CaG have collected information on hundreds of traits/diseases and millions of DNA genetic variants in close to thirty-thousand Canadians each, of which approximately half are female.