Bookmarks
application of co-occurrence networks to the discovery of preeclampsia risk
Safe People
University of Toronto
Academic Institute
Brian J CoxAbigail FraserAndreea Obersterescu
Safe Projects
B3786
Typical analysis of genetic data to find a gene with a risk for a disease is designed to look for single gene/allele relationships. While multiple relationships can be found they assume independence. We have developed novel methods that assess allele-allele interactions. Normally in biology genes interact and abnormal changes in gene expression or functions in two or more members of an interacting set of genes may lead to disease. OUr novel methods can build netwoks of allels that combine to increase risk of preeclampsia and potentially other diseases of pregnancy.
Our analysis of an unrelated cohort of preeclampsia cases and controls suggest that our methods can identify networks of co-occurring polymorphic variant enriched to specific pathways linked to the pathophysiology of preeclampsia. Our method is more statistically robust than typical GWAS and can use a smaller sample size. The identification of associated co-occurring alleles with the risk of preeclampsia will establish new genetic-based diagnostic tests.
17/05/2021