| Title: | Genetic epidemiological studies of endometriosis and associated symptomatology |
| Lead Institution: | University of Oxford |
| Principal investigator: | Professor Krina Zondervan |
Application 9637
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About
Endometriosis is a chronic inflammatory disease, causing pelvic pain and infertility in pre-menopausal women, with a genetic causative component (heritability) of ~50%. Our previous genome-wide association/replication studies including 5,586 cases identified 7/9 known associated common DNA variants. We are currently conducting analysis of rare protein-coding variants in ~7,000 cases/>17,000 controls from the UK, Australia, Belgium, Estonia, and USA. Variants identified to date explain <4% of heritability. We propose to investigate epidemiological aspects of endometriosis and associated symptoms in UK Biobank, and increase the power of our studies of common/rare genetic variants by conducting (meta-)analyses using UK Biobank genotype data. Endometriosis is associated with severe pelvic pain and subfertility, and a major area of unmet clinical need. Diagnosis requires surgery under general anaesthesia. Population prevalence is unknown, but estimates vary from 5?10% (176M women world-wide; 1.5M in the UK). The current average delay in diagnosis from onset of symptoms is 7 years. Current treatments involve surgical removal of lesions, with high recurrence rates, and/or hormonal drugs with many side-effects. The central aim of UK Biobank ? to improve the prevention, diagnosis and treatment of a wide range of serious illnesses ? is therefore highly applicable to endometriosis. We will conduct epidemiological data analyses to identify endometriosis cases and controls for subsequent genotype analysis. Most women will have been post-menopausal at time of recruitment, and any endometriosis diagnosis will have been made years ago. We will explore diagnostic, surgical, symptomatic,therapeutic, and demographic information available to allow the identification of women most likely to have had a reliable, surgically confirmed diagnosis of endometriosis, contrasting self-reported diagnoses with hospital discharge data. Case groups based on likely diagnostic reliability given the parameters will be compared against controls in subsequent analyses of DNA-genotyping data, to identify genetic variants involved in endometriosis aetiology. For the epidemiological case classification/ sensitivity analyses, we request access to data from all women included in UK Biobank, irrespective of age. One of the analysis aims will be to compare diagnostic, surgical, and therapeutic data between women of different age categories, particularly as laparoscopy as a diagnostic tool has only been common practice in the last 20-30 years. In addition, we are requesting access to available genotyping data for all women in the cohort, to allow identification of the most appropriate control sets based on demographic and clinical data.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 11195 | The genetic basis of endometriosis and comorbidity with other pain and inflammatory conditions | Nilufer Rahmioglu (+132) | 2023 | Nature Genetics |
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