Challenges in uncovering non-invasive biomarkers of endometriosis

Quanah J Hudson, Alexandra Perricos, Rene Wenzl, René Wenzl, Iveta Yotova
Experimental biology and medicine (Maywood, N.J.) · 2020 · vol. 245(5) , pp. 437–447 · doi:10.1177/1535370220903270 · PMID:32019326 · PMC7082884 · W3004753616
review OA: green CC0 ⤵ 22 in-corpus citations
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⚙ AI-generated summary by claude@2026-06, 2026-06-07 ⓘ

Despite numerous studies, variability in design and small sample sizes hinder endometriosis biomarker discovery, necessitating standardized, large-scale, multi-center efforts to validate candidates and identify new markers.

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⚙ AI-generated deep summary by claude@2026-06, 2026-06-09 ⓘ

This mini-review discusses the challenges of discovering and validating non-invasive diagnostic biomarkers for endometriosis, comparing hypothesis-driven target selection with high-throughput “omics” approaches (e.g., transcriptomics and proteomics) that aim to detect disease-specific signals in accessible fluids. It argues that symptom non-specificity and the lack of a clinically accepted biomarker contribute to diagnostic delay, and that cross-study validation is hindered by variability in study design, cohort selection, and analytic methods, with many studies being small-scale. A major caveat is that, although it outlines numerous biological pathways and candidate marker categories, it does not present new experimental results and emphasizes the need for standardized, large multi-center studies to validate candidates. Relevance to endometriosis: the entire paper is centrally about endometriosis biomarker discovery challenges and explicitly frames the need for non-invasive diagnostics for endometriosis (with adenomyosis mentioned as a related condition that can co-exist and is sometimes treated as a subtype).

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Abstract

Endometriosis affects up to 10% of women of childbearing age, causing symptoms that can include chronic pelvic pain and reduced fertility. The symptoms are not specific to the disease and can be confused with other gynecological conditions or normal menstruation. Currently, the disease can be only definitively diagnosed by laparoscopy, as no clinically accepted biomarker exists. Biomarker discovery can either follow a hypothesis-driven approach selecting targets to be tested based on current knowledge of the disease, or take an unbiased high-throughput screening “omics” approach, such as transcriptomics or proteomics, to identify markers that are unique or elevated in accessible bodily fluids of patients with the disease. Numerous studies have been conducted using these approaches to try and identify endometriosis biomarkers, but variabilities in study design, cohort selection, and analysis, together with the fact that most studies were small-scale, have made independent validation of biomarker candidates difficult. Therefore, efforts are underway to standardize cohort selection, patient data, and sample collection to allow better cross-study comparisons. Large scale multi-center studies using this standardized approach are necessary to validate existing endometriosis biomarker candidates and uncover potential new markers. Given the complexity and heterogeneity of the disease, it is likely that a panel of biomarkers will be necessary to diagnose and categorize endometriosis. Impact statement Endometriosis is a common disease affecting reproductive age women, which is associated with chronic pain and reduced fertility reducing the quality of life of many women. Definitive diagnosis requires invasive laparoscopic surgery creating a high barrier to diagnosis that can delay the onset of treatment significantly. Clinically approved biomarkers of endometriosis are currently lacking, making the discovery and validation of biomarkers that would lead to earlier diagnosis a priority for improving treatment of the disease.

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Condition tags

endometriosischronic_pelvic_pain

MeSH descriptors

Biomarkers Endometriosis Biomarkers Comorbidity Endometriosis Endometriosis Endometriosis Female Genomics Humans Models, Biological

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Papers in the corpus that this work cites (lower rings, blue) and that cite this one (upper rings, green). Dot size scales with the paper's in-corpus citation count — bigger dot = more influential within the endo/adeno field. Click a dot to open that paper. [ expand to 2 hops ] — adds papers reached through this work's immediate citers/citees. Heavier; up to 60 extra dots.

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Cited by (23)

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