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Record W4407833096 · doi:10.1186/s13148-025-01828-w

Systematic review on the DNA methylation role in endometriosis: current evidence and perspectives

2025· review· en· W4407833096 on OpenAlexaboutno aff
Bastien Ducreux, Catherine Patrat, Julie Firmin, Lucile Ferreux, Charles Chapron, Louis Marcellin, Guillaume Parpex, Mathilde Bourdon, Daniel Vaiman, Piétro Santulli, Patricia Fauque

Bibliographic record

VenueClinical Epigenetics · 2025
Typereview
Languageen
FieldMedicine
TopicEndometriosis Research and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsDNA methylationHuman geneticsEndometriosisReproductive medicineMedicineBioinformaticsBiologyComputational biologyGeneticsGynecologyPregnancyGene

Abstract

fetched live from OpenAlex

BACKGROUND: Endometriosis appears to have a multilayered etiology, with genetic and epigenetic factors each contributing half of the pathogenesis. The molecular processes that underlie the onset of endometriosis are yet unclear, but it is assumed that an important contributor in the etiopathology of the disease is DNA methylation. METHODS: We conducted a systematic review of the literature regarding DNA methylation in endometriosis following PRISMA guidelines. Records were obtained from PubMed and Web of Science on May 31, 2024. Original research articles analyzing regional or genome-wide DNA methylation in patients with confirmed endometriosis (by surgery and/or histological examination) were given consideration for inclusion. Only human studies were included, and there were no restrictions on the types of tissue that was analyzed (i.e., endometrium, blood, or fetal tissue). The study selection process was run by two manual reviewers. In parallel, an adapted virtual artificial intelligence-powered reviewer operated study selection and results were compared with the manual reviewers' selection. Studies were divided into targeted (e.g., single gene or region level) and epigenome-wide association studies. For each, we extracted a list of genes studied with precise location of CpGs analyzed and the DNA methylation status according to the groups compared. Quality assessment of studies was performed following the Newcastle-Ottawa scale. Quality of evidence was graded following the Grading of Recommendations Assessment, Development and Evaluation. RESULTS: A total of 955 studies were screened, and 70 were identified as relevant for systematic review. Our analyses displayed that endometriosis could be polyepigenetic and with alterations in specific genes implicated in major signaling pathways contributing to the disease etiopathology (cell proliferation, differentiation, and division [PI3K-Akt and Wnt-signaling pathway], cell division [MAPK pathway], cell adhesion, cell communication, developmental processes, response to hormone, apoptosis, immunity, neurogenesis, and cancer). CONCLUSION: Our systematic review indicates that endometriosis is associated with DNA methylation modifications at specific genes involved in key endometrial biological processes, particularly in the ectopic endometrium. As DNA methylation appears to be an integral component of the pathogenesis of endometriosis, the identification of DNA methylation biomarkers would likely help better understand its causes and aggravating factors as well as potentially facilitate its diagnosis and support the development of new therapeutic approaches.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.026
metaresearch head score (Gemma)0.110
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.989
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.110
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0110.008
Bibliometrics0.0190.017
Science and technology studies0.0010.002
Scholarly communication0.0040.004
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0070.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.246
GPT teacher head0.512
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations24
Published2025
Admission routes1
Has abstractyes

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