Identification and function of genes that increase risk for endometriosis

2019 update:

This project has made some very good progress in 2019, with Jessica Chung providing the expertise from our team to enable

•  development of a method to normalise cycle stage effects in endometrium expression data
•  developed an interactive R Shiny application where the research group can explore microarray and RNA-seq data with their own parameters
•  analysis of endometriosis severity and BMI, lipidomics data, uterine receptivity, and clinical factors that influence repeat surgery.

Project description

Endometriosis is a disorder that affects 5 – 10% of reproductive age women in Australia, causing severe pain and infertility. This project aims to use genomic data to identify candidate genes that increase the risk of endometriosis. We are also investigating mechanisms that cause reduced endometrial receptivity, the association between BMI and endometriosis, and clinical indicators that can predict repeat surgery for endometriosis.

Project collaborators

Grant