Endometriosis is a chronic, often debilitating condition affecting approximately 10% of women of reproductive age. Its underlying causes remain poorly understood, though both genomic variants and mitochondrial dysfunction have been implicated.
This project aims to explore how variation in mitochondrial and genomic DNA may contribute to endometriosis risk, using the large-scale genotype and health data available through the UK Biobank. Specifically, we will access data on endometriosis diagnoses using ICD codes, reproductive health history (e.g. menstrual and fertility data), and relevant lifestyle and anthropometric factors such as BMI, smoking status, and age. If needed, a small number of locally collected whole-genome sequenced (WGS) endometriosis patient samples may be used for comparison to our local patient population, but the study is designed to stand alone using Biobank data.
We will identify a cohort of women diagnosed with endometriosis from the UK Biobank using relevant ICD-coded hospital records and self-reported health data. Appropriately age-matched female controls without an endometriosis diagnosis will also be selected for comparison. Our analysis will draw on genes identified in an ongoing systematic review, including VEGF, FCRL3, HSD17B1, and intergenic regions near NFE2L3 and HOXA10. The UK Biobank’s well-characterised cohort and comprehensive genotype data offer a unique opportunity to explore these associations at scale.
This project will form part of a postgraduate MSc by Research (Biomedical Sciences) thesis in Genetics and Endometriosis. By validating findings from previous, often small-scale studies using GWAS data from the UK Biobank, I aim to provide new insights into the role of genomic and mitochondrial variations in the pathogenesis of endometriosis. I hope these findings will assist future researchers in identifying novel diagnostic markers or therapeutic targets to improve outcomes for patients with endometriosis.