Overview of miRNAs for the non-invasive diagnosis of endometriosis: Evidence, challenges and strategies. A systematic review
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OBJECTIVE: The aim of the study was to assess the evidence on miRNAs as biomarkers for the diagnosis of endometriosis, as well as to provide insights into the challenges and strategies associated with the use of these molecules as accessible tools in clinical practice. METHODS: Systematic review conducted on PubMed®, Latin American and Caribbean Health Sciences Literature (LILACS), MEDLINE® and Web of Science databases using the search terms endometriosis (all fields) AND miRNA (all fields), evaluating all publication up to May 2019. RESULTS: Most miRNAs found to be dysregulated in this study were harvested from tissue samples, which precludes their use as a non-invasive diagnostic test. However, differential expression of 62 miRNAs was reported in samples that may be used for non-invasive diagnosis of endometriosis, such as blood, serum and plasma. CONCLUSION: Despite the identification of several candidates, studies are investigatory in nature and have been conducted with small number of samples. Also, no particular miRNA has been validated for diagnostic purposes so far. Studies based primarily on biological samples and applicable to translational research are warranted. Large databases comprising information on sample type and the use of saliva and vaginal fluid for miRNAs identification may prove essential to overcome current barriers to diagnosis of endometriosis.
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No specific miRNA has been validated for diagnostic purposes.
“To date, no specific miRNA has been validated for diagnostic purposes (systematic review conducted on PubMed®, Latin American and Caribbean Health Sciences Literature (LILACS), MEDLINE® and Web of Science databases using the search terms endometriosis (all fields) AND miRNA (all fields), evaluating all publications up to May 2019) [168].”
From Endometriosis: Epidemiology, Classification, Pathogenesis, Treatment and Genetics (Review of Literature) (2021) · cites this paper as [168]
Upregulation of miRNA-199a and miRNA-16 promotes inflammation and cell proliferation in endometrial lesions.
“Upregulation of miRNA-199a and miRNA-16 promotes inflammation and cell proliferation in endometrial lesions [168].”
From Endometriosis: Epidemiology, Classification, Pathogenesis, Treatment and Genetics (Review of Literature) (2021) · cites this paper as [168]
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- Authors
- Monnaka, V. U., Hernandes, C., Heller, D., & Podgaec, S.
- Affiliations
- Hospital Israelita Albert Einstein (BR)
- Corresponding author
- Hernandes, Camila
- Venue
- Einstein (São Paulo)
- Published
- 2021
- Volume
- 19
- Pages
- eRW5704-eRW5704
- ISSN
- 1679-4508 (ISSN-L)
- 2317-6385
- PMC
- PMC8054530
- OpenAlex
- W3156012110
- Cited by
- 33
- References
- 101
- Citations by year
- 2026: 4 · 2025: 4 · 2024: 10 · 2023: 5 · 2022: 9 · 2021: 1
- FWCI
- 1.03
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by
- Locations
- Einstein (São Paulo) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (publishedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Medicine › Reproductive Medicine › Endometriosis Research and Treatment
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › MicroRNA in disease regulation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Extracellular vesicles in disease
- Keywords
- endometriosis, microRNA, non-invasive diagnosis, biomarkers, serum microRNA, plasma microRNA, saliva, vaginal secretions, microRNA dysregulation, translational research
- MeSH terms
- Endometriosis, Female, Humans, Biomarkers, Caribbean Region, MicroRNAs
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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