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Endometriosis phenotypes are associated with specific serum metabolic profiles determined by proton-nuclear magnetic resonance
What is the correlation between serum metabolic profile and endometriosis phenotype? A pilot study nestled in a prospective cohort study at a university hospital, including 46 patients with painful endometriosis who underwent surgery and 21 controls who did not have macroscopic endometriotic lesions...
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Published in: | Reproductive biomedicine online 2020-10, Vol.41 (4), p.640-652 |
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Main Authors: | , , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | What is the correlation between serum metabolic profile and endometriosis phenotype?
A pilot study nestled in a prospective cohort study at a university hospital, including 46 patients with painful endometriosis who underwent surgery and 21 controls who did not have macroscopic endometriotic lesions. Endometriosis was strictly classified into two groups of 23 patients each: endometrioma (OMA) and deep infiltrating endometriosis (DIE). Serum samples were collected before surgery for metabolomic profiling based on proton-nuclear magnetic resonance spectroscopy in combination with statistical approaches. Comparative identification of the metabolites in the serum from endometriosis patients and from controls was carried out, including an analysis according to endometriosis phenotype.
The serum metabolic profiles of the endometriosis patients revealed significantly lower concentrations of several amino acids compared with the controls, whereas the concentrations of free fatty acids and ketone bodies were significantly higher. The OMA and the DIE phenotypes each had a specific metabolic profile, with higher concentrations of two ketone bodies in the OMA group, and higher concentrations of free fatty acids and lipids in the DIE group.
Proton-nuclear magnetic resonance-based metabolomics of serum samples were found to have ample potential for identifying metabolic changes associated with endometriosis phenotypes. This information may improve our understanding of the pathogenesis of endometriosis. |
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ISSN: | 1472-6483 1472-6491 |
DOI: | 10.1016/j.rbmo.2020.06.019 |