Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

© 2019 Elsevier Inc. All rights reserved. Endometriosis is an estrogen-dependent, progesterone-resistant, inflammatory disease with symptoms that include pelvic pain, infertility, and compromised quality of life in millions of women worldwide. Approximately 50% of the risk of developing endometriosis is due to genetic factors with the remaining 50% due to environmental (i.e., exposome) causes. Treatments are hormonal, surgical, or both, with limited efficacy in the long term. Diagnosis of pelvic endometriosis is through visual identification and confirmatory histopathology of lesions. Recent innovations in genomics, genetics and epigenetics, molecular and cell biology, imaging, and a worldwide effort to standardize patient phenotyping and biospecimen collection have contributed to understanding mechanisms underlying the pathogenesis and pathophysiology of endometriosis. Furthermore, integration of “big data” obtained through these technologies holds great promise for novel targeted therapies, noninvasive diagnostics, and prognostic indicators. This chapter reviews current advances in genomics, genetics, and epigenetics of endometriosis that are providing translational approaches for preventing, diagnosing, and effectively treating this enigmatic disease.

Original publication





Book title

Human Reproductive and Prenatal Genetics

Publication Date



399 - 426