Development and validation of polygenic risk score models for human traits and disease
MyOme's mission is to provide actionable insights from genetic information. We will use whole genome sequencing to provide users with information pertaining to disease risk for a variety of common diseases such as coronary heart disease and more rare conditions such as Lynch syndrome. We will also provide information on variants that might impact a customer's reaction to certain medications. MyOme aims to develop a generalizable method of predicting an individual's genetic risk for a range of health conditions based on their whole genome sequence. We intend to use the UK biobank to test the applicability and accuracy of our approach. Methods developed using this dataset could enable more accurate disease prediction and improved approaches to screening that will be useful in the context of personal and family health.
At Myome we intend to use information gleaned from WGS in our customers to provide individuals with a polygenic-risk score-based risk assessments for a number of common disorders. Our first phase will focus on coronary artery disease, breast cancer, inflammatory bowel disease and both type 1 and type 2 diabetes mellitus. Access to the UK Biobank database for these disorders and related phenotypes will allow us to critically evaluate the models we propose to use and/or improve them.
The aims of this project are to (1) evaluate the performance of existing polygenic models within the UK biobank population. (2) apply machine learning techniques to further improve and refine predictive models
This scope is updated to reflect that WGS information has both polygenic and monogenic (single gene) disease information. At MyOme we will develop total-genetic risk assessments that take into account polygenic, monogenic and other clinical/lifestyle information. We plan to apply this to a variety of cancers, cardiometabolic conditions, autoimmune disorders, psychiatric conditions and other diseases that affect well-being. Access to the UK Biobank database for these disorders and related phenotypes will allow us to critically evaluate the models we propose to use, identify new gene-disease associations and/or improve models to better predict an individual's disease risk.