Disentangling the genetic mechanisms of endometriosis severity with single-cell multi-omics - ABSTRACT Around 10% of reproductive-age women have endometriosis, but the molecular drivers of this common chronic gynecologic condition are poorly understood. Endometriosis is a major cause of pain and infertility in women, is associated with significant financial burden, and multiple comorbidities including pain syndromes, inflammatory and immune conditions, anxiety, and depression. Staging is commonly used to describe endometriosis in research and in the clinic, but the biologic underpinnings of each stage are poorly understood. We have recently performed key studies to map gene expression in endometriosis and endometrioma, uncovering changes in cell type distribution, gene expression and predicted transcription factor network activities associated with high or low stage disease. This project will focus on characterizing the epigenome of high and low stage endometriosis, combining single cell epigenomics and multiome methods with state-of-the-art analytic methods for dimensionality reduction, allelic imbalance detection and polygenic risk scores. In Aim 1 we will perform large-scale single cell epigenomic profiling to characterize landscapes of disrupted gene regulation in low and high stage endometriosis; Aim 2 will dissect the allele-specific mechanisms of gene regulation across endometriosis stages and Aim 3 will develop genetic predictors of outcome in endometriosis. This project makes use of a large and unique endometriosis cohort study with deep clinical annotation, longitudinal follow-up and >8000 biospecimens. The collaborative and multidisciplinary team have a track record in successful collaboration resulting in high-impact research, and are focused on translating the insights gained to improve diagnostics/screening and/or tools for predicting post-surgical outcomes to help personalize treatment for endometriosis patients.
