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- W2034353246 abstract "Endometriosis affects 10-32% of women at reproductive age and may cause alterations in the follicular microenvironment resulting in infertility. Metabolites reflect these alterations more quickly than the upstream gene-to-protein cascade, and thus lipid fingerprinting may provide sensitive data for understanding and diagnosing this disease. Thus, we aimed to characterize the lipid profile in follicular fluid (FF) from women with endometriosis compared to controls without endometriosis who achieved pregnancy. Prospective case-control study. FF was obtained from 75 woman submitted to in vitro fertilization (IVF), 18 with endometriosis who subsequently did not achieve pregnancy and 57 controls without endometriosis who did. Lipids were identified using MALDI-TOF MS and the online databases Lipid Maps and KEGG. Post-genomic pathways were generated and functional enrichment of Gene Ontology (GO) terms was analyzed (P<0.01). Finally, a logistic regression model was built to test the lipids in detecting endometriosis, using data filtered for multicollinearity. Of the 767 detected MS peaks, 130 were significantly different between groups, participating in 8 metabolic pathways, related to hormone metabolism, lipid oxidation, and retinoic acid. The logistic model produced a test with a total predictive value of 88.0% and an area under the curve in a ROC graph of 86.5%. Specific lipids were mapped to endometriosis, and these will be further identified by MS/MS analysis. Metabolomics is an important tool in understanding the post-genomic of disease. Moreover, downstream molecule networks in the genomics-to-post-genomics cascade may reflect specific biologic conditions. In our study we observed that specific mechanisms were observed in endometriosis, and lipid fingerprinting initially allowed diagnosis of endometriosis in 88% of cases. Our goal is to transfer this knowledge to blood plasma, and to search for these markers using more specific MS techniques." @default.
- W2034353246 created "2016-06-24" @default.
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- W2034353246 date "2011-09-01" @default.
- W2034353246 modified "2023-10-01" @default.
- W2034353246 title "Post-genomic medicine and its application to understanding and diagnosing endometriosis" @default.
- W2034353246 doi "https://doi.org/10.1016/j.fertnstert.2011.07.288" @default.
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