ArticleJournal of assisted reproduction and genetics2020
External validation of putative biomarkers in eutopic endometrium of women with endometriosis using NanoString technology.
Article in Journal of assisted reproduction and genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.
- An integrated multi-tissue approach for endometriosis candidate biomarkers: a systematic review.Reproductive biology and endocrinology : RB&E · 2024Pooled it
- Bioinformatic analysis and validation of candidate genes in the eutopic endometrium reveal differential expressions in diffuse adenomyosis, endometrioma, and their co-existence.European journal of medical research · 2025Article
- The Role of Matrix Metalloproteinases in Endometriosis: A Potential Target.Biomolecules · 2021Review
Corrections and comments
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Authors and funding
9 authors at 4 institutions in 2 countries.
Funding
Abstract
purposeTo combine different independent endometrial markers to classify the presence of endometriosis.
methodsEndometrial biopsies were obtained from 109 women with endometriosis as well as 110 control women. Nine candidate biomarkers independent of cycle phase were selected from the literature and NanoString was performed. We compared differentially expressed genes between groups and generated generalized linear models to find a classifier for the disease.
resultsGeneralized linear models correctly detected 68% of women with endometriosis (combining deep infiltrating and ovarian endometriosis). However, we were not able to distinguish between individual types of endometriosis compared to controls. From the 9 tested genes, FOS, MMP7, and MMP11 seem to be important for disease classification, and FOS was the most over-expressed gene in endometriosis. CONCLUSION(S): Although generalized linear models may allow identification of endometriosis, we did not obtain perfect classification with the selected gene candidates.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.