Biomarker discovery in endometriosis using a transcriptomic/proteomic approach
From 01-10-2009 to 30-09-2013
Description
Biomarker discovery in endometriosis using a transcriptomic/proteomic approach Endometriosis is defined as the presence of endometrial-like tissue outside the uterus and is associated with chronic intrapelvic inflammation. Its symptoms can impact on general well-being (Kennedy et al., 2005) and include: severe dysmenorrhoea; deep dyspareunia; chronic pelvic pain; ovulation pain; cyclical or perimenstrual symptoms (e.g. bowel or bladder associated) with or without abnormal bleeding; infertility and chronic fatigue. The annual cost for endometriosis has been estimated to be higher than for Crohn’s disease (Simoens et.al, 2007). The gold standard for diagnosis of endometriosis is laparoscopic surgery with histological confirmation. So far non-invasive diagnostic approaches such as ultrasound, MRI or blood tests for CA-125 do not have sufficient diagnostic power. The delay between the onset of symptoms and a diagnosis can be as long as 8-11 years. The aim of our study is biomarker discovery in order to develop a noninvasive or semi-invasive diagnostic test for early stage endometriosis, using peripheral blood and eutopic endometrium samples from women with and without endometriosis that are available in the biobank of the Leuven University Fertility Center. In order to identify women with increased risk for endometriosis, a genetic study will be performed to evaluate the association between endometriosis and polymorphisms for genes involved in angiogenic and inflammatory pathways . The baboon model with induced endometriosis will be used for the discovery of new endometriosis-associated biomarkers, based on the hypothesis that the induction of endometriosis causes pain and immunobiological changes in eutopic endometrium and peripheral blood , and that surgical excision of endometriosis and anti-inflammatory medication will reduce pain and biomarker expression. The following techniques will be used: Multiplex Cytokine Assays, single Immunoassay (ELISA), Proteomic (SELDI-TOF), Microarray, and Sequenom approaches.
Team
- Thomas D'Hooghe, Promoter (External)
- Etienne Waelkens, Team member (External)
- Bart De Moor, Team member
- Christel Meuleman, Team member (External)
Financing
Funding: KU Leuven - Internal Funding KU Leuven
Program/Grant Type: BOF-Research - BOF Research Programmes
Events
2/09/2024:
PhD defense - Martijn Oldenhof
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3/09/2024:
Meet the Jury Igor Tetko on Advanced Machine Learning in Drug Discovery
12/09/2024:
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Seminar by Antoine Passemiers
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