Menstrual Effluent in the Pathogenesis and Diagnosis of Endometriosis-A Systematic Review

This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines ( Supplementary Materials ) [ 47 ]. All methodological steps—including search strategy, eligibility criteria, screening procedure, data extraction, and synthesis framework—were defined a priori and consistently applied throughout the review. A systematic literature search was conducted in PubMed/MEDLINE, Semantic Scholar, and via the EBSCOhost platform (including Academic Search Premier, APA PsycArticles, APA PsycInfo, CINAHL, and MEDLINE) from database inception to 30 November 2025. The PubMed search combined Medical Subject Headings (MeSH) with free-text terms and was structured as follows: (“Endometriosis”[MeSH] OR “Endometriosis”) AND (“menstrual effluent” OR “menstrual blood” OR “menstrual discharge” OR “menstrual endometrium” OR “dried menstrual spots”). Semantic Scholar was searched using the search string “Endometriosis” AND (“menstrual effluent” OR “menstrual blood” OR “menstrual discharge” OR “menstrual endometrium” OR “dried menstrual spots”) , whereas EBSCOhost was searched using the combination of terms: “Endometriosis” AND (“menstrual effluent” OR “menstrual blood”) . This query retrieved: • 230 records in PubMed • 347 records via EBSCOhost • 167 records in Semantic Scholar 230 records in PubMed 347 records via EBSCOhost 167 records in Semantic Scholar No filters were applied regarding language, publication year, study size, or methodology. In addition, Google Scholar was searched on 30 November 2025 using the query (“Endometriosis” AND “menstrual effluent”), sorted by relevance; all retrieved records ( n = 963) were screened by title. Search results from PubMed/MEDLINE, EBSCOhost, and Semantic Scholar were exported to Zotero (Corporation for Digital Scholarship, Vienna, VA, USA), and duplicates were removed prior to screening. A total of 744 records were identified from databases. After removal of duplicates ( n = 506), 238 unique records underwent title and abstract screening by two independent reviewers (R.W., S.K.). After exclusion of clearly irrelevant studies ( n = 191), 47 full-text articles were assessed for eligibility. Of these: • 35 studies met all inclusion criteria and were included in the final synthesis. • 12 were excluded due to (i) insufficient use of ME or menstrual blood, (ii) absence of comparative data between endometriosis and control groups, (iii) use of unrelated cellular models, or (iv) insufficient reporting for reproducible data extraction. 35 studies met all inclusion criteria and were included in the final synthesis. 12 were excluded due to (i) insufficient use of ME or menstrual blood, (ii) absence of comparative data between endometriosis and control groups, (iii) use of unrelated cellular models, or (iv) insufficient reporting for reproducible data extraction. Disagreements during screening were resolved through discussion with third evaluators (R.S., E.T., and S.G.V.). The selection process has been summarized in the PRISMA 2020 flow diagram ( Figure 1 ). Studies were eligible if they: (a) used human ME or ME-derived cellular fractions (e.g., stromal cells, immune cells, extracellular vesicles) as the primary biospecimen; (b) included human participants of reproductive age with endometriosis confirmed by laparoscopy and/or histopathology, and compared them to an appropriate control group (asymptomatic, laparoscopically confirmed disease-free, or self-reported healthy controls); (c) reported original data on molecular, cellular, functional, or multi-omics analyses relevant to endometriosis pathophysiology or diagnosis; (d) presented comparative results between endometriosis and control groups based on the human ME-derived material; and (e) provided sufficient methodological detail to allow reproducible data extraction (including the analytical method and reporting units for quantified biomarkers). Eligible study types included diagnostic accuracy investigations, reporting area-under-the-curve (AUC), sensitivity, specificity or cut-off values, and mechanistic research focused on the role of ME in the pathogenesis of endometriosis (e.g., decidualization capacity, immune dysfunction, scRNA-seq-based profiling), but often holding potential diagnostic relevance. Studies were excluded if they: (a) used endometrial biopsies, peritoneal fluid, or serum without concurrent analysis of ME; (b) relied exclusively on non-human biospecimens (e.g., rodent ME, primate models); (c) used non-human cell lines or xenografts without originating from human ME; (d) were case reports, reviews, conference abstracts, or methodological papers without a human endometriosis/control cohort; or (e) lacked sufficient reporting of biomarker quantification methods and/or measurement units to enable reproducible extraction and comparison. Studies combining human ME collection with secondary experimental models (e.g., in vitro functional assays, murine xenografts, or mechanistic validation in animal models) were retained, provided the primary biospecimen and comparative human data originated from ME of endometriosis patients and controls. Data were independently extracted by two reviewers (R.W. and S.K.) using a pre-defined template covering: (a) study design and population characteristics; (b) sample size (cases vs. controls), diagnosis confirmation method, and control type; (c) timing and method of ME collection and processing; (d) analytical methods (e.g., qPCR, scRNA-seq, ELISA, proteomics, functional assays); (e) diagnostic performance metrics (AUC, sensitivity, specificity, and thresholds where provided); (f) mechanistic insights (e.g., hormone signaling, decidualization defects, immune alteration, ECM remodeling); and (g) reported clinical implications and authors’ recommendations. Any discrepancies were resolved through discussion and cross-checking against the full texts. Risk of bias was assessed separately for diagnostic-accuracy studies and for mechanistic or exploratory observational studies. For diagnostic-accuracy studies (i.e., studies reporting sensitivity, specificity, AUC and/or predefined cut-offs for ME-based markers), we used the domains of the QUADAS-2 framework: (a) patient selection, (b) index test, (c) reference standard, and (d) flow and timing. Each domain was judged as low, high, or unclear risk of bias. Given the predominance of case–control designs and surgically selected populations, special attention was paid to spectrum bias and applicability. For mechanistic and non-diagnostic observational studies, we used a simplified, NIH-inspired approach based on the NIH Quality Assessment Tools for observational cohort/cross-sectional and case–control studies. We evaluated: (a) study population and selection, (b) exposure/biomarker measurement, (c) outcome ascertainment, (d) control of confounding (where applicable), and (e) reporting/analysis clarity. These domains were also graded as low, moderate, high, or unclear risk of bias. Given the diversity of analytical techniques and outcome measures, meta-analysis was not appropriate. Instead, we applied structured qualitative synthesis, grouping findings according to predefined categories: • Diagnostic markers were synthesized narratively and tabulated including reported sensitivity, specificity, AUC, and cut-offs where available. AUC 95% confidence intervals were extracted from the original publications where reported; otherwise, they were approximated from the AUC and case/control sample sizes using the Hanley–McNeil method, implemented in R via the JASP R-syntax module (JASP statistical software version 0.95.4; JASP Team, 2025) • Mechanistic studies were grouped according to biological domains: stromal decidualization/progesterone resistance, immune dysregulation, extracellular remodeling and angiogenesis, metabolic elements (lipidomics), and multi-omic integration. • When findings overlapped across platform types (e.g., reduced IGFBP1 + stromal cells seen both in ME culture and scRNA-seq), this was highlighted to enhance trans-method validation. Diagnostic markers were synthesized narratively and tabulated including reported sensitivity, specificity, AUC, and cut-offs where available. AUC 95% confidence intervals were extracted from the original publications where reported; otherwise, they were approximated from the AUC and case/control sample sizes using the Hanley–McNeil method, implemented in R via the JASP R-syntax module (JASP statistical software version 0.95.4; JASP Team, 2025) Mechanistic studies were grouped according to biological domains: stromal decidualization/progesterone resistance, immune dysregulation, extracellular remodeling and angiogenesis, metabolic elements (lipidomics), and multi-omic integration. When findings overlapped across platform types (e.g., reduced IGFBP1 + stromal cells seen both in ME culture and scRNA-seq), this was highlighted to enhance trans-method validation. Tables were constructed to summarize general study characteristics ( Table 1 ), diagnostic accuracy ( Table 2 ), and mechanistic insights ( Table 3 ). Narrative synthesis aligned with the review objectives.

Endometriosis is a chronic, estrogen-dependent inflammatory disease defined by the presence of endometrium-like tissue outside the uterine cavity [ 1 ]. It affects approximately 10% of women of reproductive age [ 1 ]. Despite global incidence variation due to biological and diagnostic factors, a rising burden has been observed over the past three decades [ 2 ]. Although retrograde menstruation remains the most established etiological model, current concepts increasingly recognize that the eutopic endometrium itself may be altered even before lesion formation (“endometrium as the first culprit of endometriosis”). These changes include deregulated gene expression, enhanced proliferative, adhesive, and angiogenic potential, aberrant cytokine release, impaired apoptotic regulation, and altered immune interactions [ 3 , 4 , 5 ]. Consequently, the pathogenesis of endometriosis can be viewed as a cascade where the nature of the transported tissue is as critical as the transport mechanism itself [ 6 ]. This sequence is likely initiated by uterine hyperperistalsis and tissue injury and repair (TIAR) mechanisms, which generate a “super-charged” menstrual effluent (ME) characterized by progesterone resistance, stem cell abundance, and invasive potential (the altered seed ) [ 7 ]. Following retrograde menstruation (the transport ), specific factors carried within this effluent—such as TGF-β1, VEGF, and immune-suppressive cytokines—actively condition the peritoneal microenvironment (the soil ) [ 8 , 9 ]. By inducing macrophage reprogramming and mesothelial conditioning, the ME creates its own hospitable niche, allowing the “altered” tissue to evade immune clearance and establish ectopic lesions [ 6 , 10 , 11 , 12 ]. Recent evidence further characterizes endometriosis as a systemic disease with multiple comorbidities, involving neuroendocrine, immunological, metabolic, and inflammatory disturbances that extend beyond the local pelvic environment [ 13 , 14 ]. The disease presents with a broad spectrum of symptoms including nociceptive, neuropathic, and nociplastic pelvic pain, dysmenorrhea, dyspareunia, subfertility, gastrointestinal symptoms (“endobelly”), chronic fatigue, and psychological comorbidity such as anxiety and depression [ 15 , 16 , 17 ]. These manifestations significantly impair health-related quality of life and are often under-addressed in routine clinical care [ 18 , 19 , 20 ]. The coexistence of endometriosis with adenomyosis is up to 80%, and the pathogenetic mechanisms and clinical presentations are shared [ 21 , 22 , 23 ]. The socioeconomic burden is substantial, with high healthcare utilization, work absenteeism, and annual costs estimated at >10,000 EUR per patient [ 24 ]. Laparoscopy remains the reference standard, particularly in “see-and-treat” clinical contexts [ 1 , 25 ]. However, current diagnostic strategies increasingly prioritize non-invasive assessment, favoring transvaginal sonography (TVS) and magnetic resonance imaging (MRI) [ 26 , 27 , 28 , 29 ]. Despite this recommendation shift, imaging-based diagnosis is primarily limited to detecting deep infiltrating endometriosis, whereas superficial, lateral pelvic or extrapelvic lesions remain largely undetectable. Diagnostic accuracy is dependent on lesion location and examiner expertise [ 30 , 31 , 32 ], with considerable interobserver variability [ 33 ]. In one study, TVS demonstrated a sensitivity of only 61% (95% CI 49–72%), and a specificity of 94% (95% CI 71–100%), but a negative predictive value as low as 36% [ 34 ]. A Cochrane review concluded that no current imaging modality fulfills the criteria for a replacement or triage test compared with laparoscopy [ 25 ]. Thus, although current guidelines increasingly promote non-invasive diagnostic strategies, mainly via imaging-based approaches, these remain confined to structural visualization and fail to capture underlying biological disease activity. Given the substantial diagnostic delay and the invasive nature of surgical confirmation, there is an urgent clinical need for reliable, biologically based, non-invasive biomarkers. As in other diseases, biomarkers of endometriosis should be reliable and reproducible, but also acceptable for patients, easily obtainable, and cost-effective [ 35 , 36 ]. Unfortunately, only few circulating biomarkers, including serum CA-125, inflammatory proteins (S100-A12), and proteomic patterns, have demonstrated moderate diagnostic utility but with limited reproducibility and specificity [ 37 , 38 ]. In peritoneal fluid, nitric oxide [ 39 ], phenylalanyl-isoleucine [ 40 ], fibronectin, or collagen IV [ 41 ] are significantly elevated in endometriosis, but peritoneal-fluid sampling is inherently invasive or, if performed during laparoscopy, of questionable utility. Alternative biofluids such as urine, saliva, and ME have therefore gained attention [ 29 , 38 , 42 ]. Molecular approaches—such as the salivary miRNA signature validated by Bendifallah et al. [ 43 ], with a sensitivity of 97.3% and a specificity of 94.1%—provide a proof of concept that biologically informed diagnostics may outperform purely imaging-based assessment. In this context, ME represents a uniquely informative biospecimen reflecting cellular and molecular features at the moment of retrograde dissemination [ 44 ]. Unlike peripheral blood, ME contains intact stromal and local immune cells, epithelial elements, extracellular vesicles, and tissue fragments mirroring intrauterine biology [ 45 ]. Importantly, ME may capture pre-lesional aberrations at the moment they enter the pelvic cavity via retrograde menstruation, potentially reflecting early pathogenic characteristics including inflammatory activation, immune evasion, cellular resilience, or defective decidualization. This aligns with the emerging hypothesis that endometrial dysfunction precedes lesion formation and therefore may be detectable using ME-based testing [ 44 , 45 , 46 ]. Therefore, systematic evaluation of ME may enable simultaneous insight into both disease mechanisms and diagnostic performance, providing a biologically grounded approach that complements and potentially enhances current imaging-based strategies. The aim of this systematic review was to examine the available evidence on the role of ME in diagnosing and understanding endometriosis, with specific focus on (i) evaluating diagnostic biomarker performance, (ii) identifying mechanistic alterations reflected in ME, and (iii) assessing methodological considerations relevant for future translation into clinical practice.

A total of 35 studies met the inclusion criteria ( Table 1 ). Publication years ranged from 1990 to 2025, with a clear increase in studies published after 2020 [ 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 ]. Study designs were predominantly case–control, with all included studies analyzing ME or ME-derived cells. Sample sizes varied widely, from small exploratory cohorts (e.g., 7 vs. 7 in [ 74 ]) to moderate-sized case–control studies with a total of 40–70 participants (e.g., [ 55 , 56 , 57 , 75 ]) or more [ 71 , 73 ]. Endometriosis was confirmed surgically in 34 studies, while one study relied on symptom profile [ 69 ]. Control groups consisted mainly of healthy individuals without pelvic pain [ 55 , 56 , 58 , 60 , 61 , 68 , 69 , 70 , 75 ], with several studies including symptomatic but endometriosis-negative controls [ 52 , 59 , 81 ]. ME was predominantly collected using menstrual cups, typically during the first 24–48 h of menstruation, although a minority of studies used pads [ 55 , 58 ], a Cusco speculum [ 56 ], aspiration by syringe [ 61 , 67 , 68 , 77 , 81 , 82 ] or a pipelle [ 62 , 65 , 79 ]. As shown in Table 1 , analytical approaches varied widely and included ELISA-based protein quantification, RT-qPCR-based assays, immunocytochemistry, lipidomics, single-cell RNA sequencing, proteomics, and functional decidualization assays. No study included a prospective validation cohort, and all diagnostic analyses were conducted in case–control designs [ 55 , 56 , 60 , 68 , 69 , 70 , 75 , 81 , 82 ]. Mechanistic investigations focused on stromal-cell function [ 48 , 50 , 65 ], immune signatures [ 53 , 64 , 66 ], progenitor cell profiles [ 67 ], senescence [ 48 , 50 ], angiogenesis-related factors [ 69 , 71 , 72 ], extracellular vesicles [ 52 , 62 ], or multi-omic regulation [ 61 ]. The risk-of-bias rating for each included study is presented in Table A1 ( Appendix A ). Overall, most diagnostic studies were at high risk of bias in patient selection (case–control designs, surgical populations) and unclear risk regarding the blinding of index-test interpretation. Mechanistic studies were predominantly moderate-risk, driven by small sample sizes and limited control of confounding, but with generally robust laboratory methods and clearly reported outcomes. Diagnostic performance related to ME analysis was reported in nine studies [ 55 , 56 , 60 , 68 , 69 , 70 , 75 , 81 , 82 ], all of which provided numerical diagnostic metrics such as sensitivity, specificity, AUC, or defined cut-offs ( Table 2 ). These studies predominantly evaluated molecular markers, protein concentrations, functional stromal-cell assays, or lipidomic signatures in case–control settings with laparoscopically confirmed endometriosis and healthy controls. Several additional studies investigated ME-based biomarkers in a diagnostic context but did not report ROC values, sensitivity/specificity, or diagnostic thresholds. These exploratory diagnostic studies are summarized in Appendix A ( Table A2 ) [ 51 , 57 , 58 , 59 , 61 , 66 , 67 , 71 , 72 , 73 , 74 , 76 , 77 , 80 ]. Two early studies evaluated the diagnostic performance of CA-125 in ME. In women with chronic pelvic pain, ME-CA-125 at the threshold of ≥72,000 U/mL identified endometriosis with a sensitivity of 89.3% and a specificity of 96.3% [ 81 ]. At the threshold of 100,000 U/mL, ME-derived CA-125 differentiated women from those without endometriosis with a sensitivity of 65.7% and a specificity of 89.3%, showing elevated ME-CA-125 levels across all endometriosis stages (sensitivity ranging from 60% for Stages I/II to 72.2% for Stages III/IV) and substantially outperforming serum CA-125 in the same population (sensitivity 32.5%, specificity 80.3%) [ 82 ]. These findings established an early proof-of-concept for ME-based biomarkers. Across the nine studies with formal diagnostic metrics, discriminatory performance was highest for molecular markers related to steroidogenesis and inflammatory growth factors, as well as for functional stromal-cell assays and one lipidomic model. Aromatase mRNA expression in ME achieved the strongest individual performance, with an AUC of 0.977, sensitivity of 95%, and specificity of 90% at a defined expression ratio >1.63 [ 55 ]. SF-1 (AUC 0.862) and HSD17B2 (AUC 0.807) also demonstrated clinically relevant discriminatory ability, supporting the concept that aberrant hormonal gene expression and local hyperestrogenism are detectable in ME [ 55 ]. Protein biomarkers quantified via ELISA showed variable but generally moderate-to-high diagnostic potential. TGF-β1 concentration reached an AUC of 0.973 (95% CI 0.928–1.000), with sensitivity of 80% and specificity of 90% at a predefined threshold of 515 ng/mL [ 60 ]. VEGF-A levels distinguished cases from controls with sensitivity and specificity of 84.2% and 85.7%, respectively, and an AUC of 0.853; however, the small control group (38/7) increases uncertainty, especially for specificity [ 69 ]. Another study, analyzing VEGF staining intensity in endometrial cells from ME using immunocytochemistry, reported an AUC of 0.672 with low sensitivity (40%) but high specificity (93.33%) at a histoscore cut-off > 6 [ 68 ]. Functional assays based on ME-derived stromal cells also performed well. A decidualization-based test quantifying IGFBP1 secretion reached an AUC of 0.92 (95% CI 0.82–1.00), differentiating endometriosis from controls with 87.5% sensitivity and 91.7% specificity [ 70 ]. PR-B mRNA expression analyzed by qRT-PCR demonstrated 90.5% sensitivity and 81.0% specificity at a defined optical-density threshold of ≤1.1355 μg/dL [ 75 ]. However, the original publication contains inconsistent labeling between PR-B receptor expression and progesterone hormone concentration, and the reported unit (μg/dL) is unconventional for qRT-PCR data; the diagnostic metrics should therefore be interpreted with caution [ 75 ]. In addition, a lipidomic two-lipid model based on cardiolipin CL 16:0_18:0_22:5_22:6 and plasmenylphosphatidylethanolamine PE P-16:0/18:1 in dried menstrual blood spots achieved an AUC of 0.87 in cross-validated ROC analysis, with 81% sensitivity and 85% specificity at an optimal threshold of 0.59 [ 56 ]. This model was derived from 23 women with histologically verified endometriosis and 16 controls and indicates that lipid signatures in ME can carry independent diagnostic information. To summarize, high diagnostic accuracy was most consistently achieved in: (a) Molecular markers of hormonal regulation • Aromatase (AUC 0.977) [ 55 ]; • TGF-Β1 (Auc 0.973) [ 60 ]; • SF-1 (Auc 0.862) [ 55 ]; • HSD17B2 (Auc 0.807) [ 55 ]; • Marker combinations: aromatase and SF-1 0.92 (AUC 0.92), aromatase and HSD17B2 (AUC 0.89), SF-1 and HSD17B2 (0.83), and AUC 0.88 for all three markers [ 55 ]. (b) Functional stromal-cell assays • Decidualization response via IGFBP1 secretion (AUC 0.92) [ 70 ]; • PR-B expression (sens 90.5%, spec 81.0%) [ 75 ]. (c) Protein-based markers • CA-125 (sens 65.7%, spec 89.3% at >100,000 U/mL [ 82 ]; sens 89.3%, spec 96.3% at ≥72,000 U/mL [ 81 ]); • VEGF-A (sens 84.2%, spec 85.7%; Auc 0.853) [ 69 ]. (d) Lipidomic signatures • Two-lipid model (CL 16:0_18:0_22:5_22:6 + PE P-16:0/18:1) from dried menstrual blood spots (AUC 0.87, sens 81%, spec 85%, threshold 0.59) [ 56 ]. Molecular markers of hormonal regulation • Aromatase (AUC 0.977) [ 55 ]; • TGF-Β1 (Auc 0.973) [ 60 ]; • SF-1 (Auc 0.862) [ 55 ]; • HSD17B2 (Auc 0.807) [ 55 ]; • Marker combinations: aromatase and SF-1 0.92 (AUC 0.92), aromatase and HSD17B2 (AUC 0.89), SF-1 and HSD17B2 (0.83), and AUC 0.88 for all three markers [ 55 ]. Aromatase (AUC 0.977) [ 55 ]; TGF-Β1 (Auc 0.973) [ 60 ]; SF-1 (Auc 0.862) [ 55 ]; HSD17B2 (Auc 0.807) [ 55 ]; Marker combinations: aromatase and SF-1 0.92 (AUC 0.92), aromatase and HSD17B2 (AUC 0.89), SF-1 and HSD17B2 (0.83), and AUC 0.88 for all three markers [ 55 ]. Functional stromal-cell assays • Decidualization response via IGFBP1 secretion (AUC 0.92) [ 70 ]; • PR-B expression (sens 90.5%, spec 81.0%) [ 75 ]. Decidualization response via IGFBP1 secretion (AUC 0.92) [ 70 ]; PR-B expression (sens 90.5%, spec 81.0%) [ 75 ]. Protein-based markers • CA-125 (sens 65.7%, spec 89.3% at >100,000 U/mL [ 82 ]; sens 89.3%, spec 96.3% at ≥72,000 U/mL [ 81 ]); • VEGF-A (sens 84.2%, spec 85.7%; Auc 0.853) [ 69 ]. CA-125 (sens 65.7%, spec 89.3% at >100,000 U/mL [ 82 ]; sens 89.3%, spec 96.3% at ≥72,000 U/mL [ 81 ]); VEGF-A (sens 84.2%, spec 85.7%; Auc 0.853) [ 69 ]. Lipidomic signatures • Two-lipid model (CL 16:0_18:0_22:5_22:6 + PE P-16:0/18:1) from dried menstrual blood spots (AUC 0.87, sens 81%, spec 85%, threshold 0.59) [ 56 ]. Two-lipid model (CL 16:0_18:0_22:5_22:6 + PE P-16:0/18:1) from dried menstrual blood spots (AUC 0.87, sens 81%, spec 85%, threshold 0.59) [ 56 ]. In contrast, a large group of mechanistic studies identified statistically significant biomarker differences (e.g., proteomic, transcriptomic, immune, and stromal-cell signatures) without providing ROC-derived diagnostic metrics. These studies ( Appendix A ( Table A2 )) suggest diagnostic potential but cannot be quantitatively assessed (e.g., [ 61 , 64 ]). No study performed prospective validation, head-to-head comparison with imaging modalities, or real-world diagnostic testing. All diagnostic data were generated in small case–control cohorts, and none evaluated multi-marker algorithms in an independent population. Mechanistic alterations detectable in ME or ME-derived cells were examined across molecular, cellular, immunological, proteomic, transcriptomic, and lipidomic approaches ( Table 3 ) [ 48 , 49 , 50 , 52 , 53 , 55 , 56 , 58 , 61 , 63 , 64 , 65 , 66 , 67 ]. Although the heterogeneity of the methods precluded quantitative synthesis, several reproducible mechanistic themes emerged. Multiple studies demonstrated reduced decidualization capacity of ME-derived stromal cells, accompanied by lower IGFBP1 secretion [ 63 , 70 , 74 ], altered expression of progesterone-responsive genes [ 63 ], and diminished PR-B levels [ 75 ]. These findings are consistent with impaired progesterone signaling, a hallmark of endometriosis pathophysiology. Functional decidualization defects were observed both in diagnostic studies (PR-B analysis, decidualization assays) and in mechanistic investigations evaluating cellular responses to hormonal or inflammatory stimuli [ 55 , 58 , 74 ]. Several studies reported altered immune signatures within ME, indicating dysregulated innate and adaptive immune responses in endometriosis. These alterations included increased neutrophil activation and aging phenotypes [ 53 ], expansion or transcriptional reprogramming of Th17-associated immune profiles [ 64 ], reduced frequencies of perforin-positive CD8 + cytotoxic T cells [ 66 ], and disrupted macrophage-related signaling pathways [ 64 ]. These immune alterations were not uniform across studies, reflecting methodological differences (flow cytometry vs. transcriptomics) and heterogeneous immune compartments analyzed. Cytokine and mediator profiling further demonstrated elevations in pro-inflammatory factors alongside relative reductions in anti-inflammatory or regulatory signals in endometriosis samples [ 77 ]. Proteomic, cytokine-based, and immunocytochemical studies identified alterations in angiogenesis-related factors and ECM-remodeling enzymes within ME, involving VEGF, endoglin (CD105), matrix metalloproteinases (mostly MMP-9), and their inhibitors [ 68 , 69 , 71 , 72 , 76 , 77 ]. An imbalance between MMP-9 and TIMP-1 was repeatedly noted [ 71 , 76 ], suggesting enhanced matrix-degrading capacity, although effect sizes and diagnostic discriminability varied across cohorts. The expression of VEGF or VEGF-A was increased in endometriosis-associated menstrual samples [ 69 , 72 ]; however, modest or non-significant differences were also reported [ 77 , 80 ]. Evidence for altered stem/progenitor cell populations in ME includes increased clonogenic endometrial cell subsets—encompassing mesenchymal stromal and epithelial progenitor fractions—in women with endometriosis [ 67 ], supporting the concept that ME contains an expanded pool of regeneration-competent cells with enhanced survival or implantation potential. Beyond abundance, the stromal/stem cell compartment in endometriosis is characterized by a lesion-supportive biological program, with concomitant signals consistent with inflammatory activation, matrix remodeling/invasiveness, pro-angiogenic drive, and relative apoptosis resistance [ 62 , 78 ]. These findings position ME-derived progenitor/stromal cells as plausible “seed” contributors linking uterine-origin dysfunction with downstream establishment and persistence after retrograde dissemination [ 67 ]. Menstrual endometrial stromal cells (ESCs) from women with endometriosis showed higher adherence to LP9 peritoneal mesothelial cells (PMCs) than controls (43% vs. 32%), while epithelial cells (EECs) showed a similar trend that did not reach statistical significance (23% vs. 15%) [ 79 ]. This pro-adhesive phenotype was accompanied by more frequent expression of CD44 variant isoforms involved in hyaluronan binding (CD44v6–v9), particularly in ESCs [ 79 ]. In cultured ME-derived stromal stem cells (MenSCs), endometriosis-derived cells displayed higher expression of CD9, CD10, and CD29 and showed increased proliferation and Matrigel invasion, although adhesion to fibronectin-coated plates was not significantly different [ 78 ]. These findings support the concept that ME in endometriosis exhibits a more invasive and adhesive phenotype, facilitating ectopic implantation after retrograde menstruation. Two studies [ 48 , 50 ] identified markers of premature cellular senescence and compromised genomic stability in ME-derived stromal cells from women with endometriosis. Reported alterations included impaired DNA damage repair responses, accumulation of senescence-associated markers, and dysregulation of p53-dependent stress signaling. Single-cell transcriptomic analyses showed disease-associated immune-stromal interactions, expanded inflammatory and dysfunctional cell states, and altered cellular proportions within ME from affected individuals [ 49 , 59 , 63 ]. In parallel, proteomic and lipidomic investigations identified discriminative metabolic, inflammatory, and structural protein patterns, as well as altered lipid species, distinguishing endometriosis from control samples [ 56 , 61 ]. In addition, analyses of ME-derived extracellular vesicles demonstrated disease-related changes in protein cargo implicated in immune modulation and tissue repair, suggesting that vesicle-mediated intercellular signaling contributes to the pathophysiology captured in ME [ 52 ]. One proof-of-concept study revealed ME not only as a diagnostic specimen but also as a source for cell-free therapeutic interventions. Exosomes derived from healthy menstrual stromal cells (NE-MenSCs) reduced the expression of inflammatory (IL-6, IL-8, IL-1β, COX-2, NF-κB, and TNF-α), proliferative (cyclin D1), migratory (MMP-2 and MMP-9), and angiogenic (VEGF) markers in endometriosis-derived MenSCs, and induced apoptosis of E-MenSC [ 62 ].

This systematic review provides the most comprehensive synthesis to date of 35 studies evaluating ME as a source of diagnostic and pathophysiologic (mechanistic) information in endometriosis. We found consistent evidence that ME acts as a “liquid biopsy” of the eutopic endometrium, reflecting central pathophysiological abnormalities such as progesterone resistance, immune dysregulation, and altered cellular kinetics. Importantly, these biological signals translate into promising diagnostic performance. Several molecular and functional assays demonstrated area-under-the-curve (AUC) values exceeding 0.90 [ 55 , 60 , 70 ], supporting the concept that ME is a biologically meaningful, non-invasive tissue source for discriminating affected individuals from controls. Mechanistically, the most consistently reported abnormality was impaired decidualization associated with progesterone resistance. Reduced IGFBP1 secretion, diminished PR-B expression, and dysregulation of progesterone-responsive genes were identified in both mechanistic [ 54 , 55 ] and diagnostic investigations [ 70 , 74 , 75 ]. These findings indicate that stromal-cell dysfunction is intrinsic to the eutopic endometrium and remains detectable during menstruation. Immune dysregulation was another hallmark feature. Findings included pro-inflammatory shifts such as increased neutrophil activation, Th17 expansion, aberrant macrophage polarization, and reduced cytotoxic CD8 + T-cell frequency [ 49 , 53 , 64 , 66 , 77 ]. These alterations align with the hypothesis that impaired immune clearance and heightened inflammatory tone in shed tissue promote the persistence of refluxed endometrial fragments. Similarly, markers of angiogenic signaling (VEGF and endoglin) and extracellular matrix remodeling (MMP-9 and TIMP-1) were consistently altered [ 69 , 71 , 72 ], reflecting an invasive phenotype. Further biological complexity was revealed by studies identifying stem/progenitor cell abnormalities [ 67 , 73 ], premature cellular senescence with genomic instability [ 48 , 50 ], and distinct extracellular vesicle cargo [ 52 ]. Multi-omic and single-cell analyses confirmed that these disease-associated signatures—including altered immune-stromal interactions—are robustly mapped in ME [ 49 , 59 ]. The enhanced adhesive and invasive properties of menstrual endometrial cells from affected women [ 78 , 79 ] provide cellular-level validation of the “altered seed”. Differential expression of CD44 splice variants and adhesion molecules (CD9, CD10, and CD29) equips these cells with superior capacity to attach to peritoneal mesothelium and invade underlying stroma [ 78 , 79 ]. The observation that exosomes from healthy MenSCs can partially reverse the pathological phenotype of endometriosis-derived cells [ 62 ] further supports the concept that these cellular differences are modifiable and may represent therapeutic targets. These intrinsic cellular differences, combined with progesterone resistance and immune dysregulation, create a multi-level pathophysiological cascade detectable in ME. Assays targeting these core disease mechanisms achieved the highest discriminatory accuracy. Among the nine studies reporting formal test metrics, molecular markers of hormonally regulated pathways performed best. Aromatase mRNA (AUC 0.977), TGF-β1 protein (AUC 0.973), and SF-1 mRNA (AUC 0.862) showed excellent diagnostic potential [ 55 , 60 ]. Functional assays assessing stromal-cell decidualization (IGFBP1; AUC 0.92) and receptor status (PR-B; sensitivity 90.5%) also demonstrated high diagnostic accuracy [ 70 , 75 ]. However, the diagnostic performance reported for PR-B [ 75 ] should be interpreted cautiously, as the original publication contains reporting inconsistencies regarding the measured analyte and its unit. Lipidomic profiling offered promising sensitivity (81%) and specificity (85%) based on a two-lipid model (cardiolipin CL 16:0_18:0_22:5_22:6 plus PE P-16:0/18:1), further supporting the biological plausibility of ME-based diagnostics [ 56 ]. Conversely, simple immunocytochemical staining showed high specificity but lower sensitivity, suggesting that functional and molecular assays provide superior diagnostic value compared to morphology alone [ 68 , 73 ]. Despite these promising results, the risk of bias was rated as high across all diagnostic studies due to case–control designs that recruited surgically confirmed patients and healthy or asymptomatic controls. No study included a prospective validation cohort or assessed performance in an unselected, real-world population. Given the high risk of spectrum bias inherent to case–control designs, reported AUC values should be interpreted as proof-of-concept rather than as direct estimates of clinical diagnostic performance in routine care settings. Moreover, the potential of ME-based testing is not restricted to distinguishing endometriosis from health. A reliable non-invasive assay could also help identify endometriosis in oligosymptomatic or atypical presentations. A particular unmet need concerns patients presenting with gastrointestinal symptoms (often referred to as “endo belly” or misattributed to irritable bowel syndrome) [ 18 , 83 ] or with bladder pain syndrome/interstitial cystitis [ 84 ]. These presentations are often not initially considered gynecological, which can contribute to unnecessary investigations, higher costs, and diagnostic delay. A screening test that helps rule out or support endometriosis in patients with diffuse gastrointestinal symptoms or chronic bladder-associated pain could meaningfully improve diagnostic pathways and quality of life for many affected women. The ability to non-invasively access cellular and molecular signatures of endometriosis offers a significant advantage over current diagnostic pathways. Definitive diagnosis often relies on laparoscopy, contributing to delays of several years. ME-based testing could shorten this interval, reduce the disease burden and save costs. Because markers like IGFBP1 and PR-B reflect intrinsic progesterone resistance—a process believed to precede overt lesion formation—they may offer utility for early detection and risk stratification even in the absence of visible lesions on imaging. Furthermore, inflammatory signatures (TGF-β1, cytokines) or lipidomic profiles might help distinguish endometriosis from other causes of pelvic pain [ 56 , 60 ]. These approaches are complementary to analyses of extracellular-vesicle cargo and non-coding RNA signatures as emerging non-invasive biomarker classes that may reflect inflammatory activity and disease phenotypes in conditions like endometriosis or adenomyosis [ 22 , 85 , 86 ]. The feasibility of home-based sampling using menstrual cups supports the potential for large-scale implementation [ 70 , 74 ]. Unlike biopsy-based methods, this approach allows for repeated longitudinal monitoring, which could be valuable for assessing treatment response or disease recurrence. For instance, persistent progesterone resistance or inflammatory activity in ME after hormonal therapy could guide personalized adjustments in management. The potential cost advantage of ME testing is driven less by the assay price alone (in Germany, a single serum biomarker ELISA- or PCR-based test costs approximately 15–25 EUR) and should not be directly compared with the costs of complex endometriosis surgery. The main economic benefit is more likely to come from reducing avoidable invasive procedures and from shortening diagnostic delay and enabling earlier therapy initiation. An earlier non-invasive diagnosis would reduce not only patients’ symptom burden but also their considerable personal expenses, which, in Germany, average 4234 EUR per year, comprising direct costs (e.g., outpatient care, pain therapy, fertility treatments, hormone therapies) estimated at 2060 EUR and indirect costs (e.g., income loss or costs related to comorbidities) estimated at 2174 EUR annually [ 87 ]. To our knowledge, this is the most comprehensive synthesis of studies specifically evaluating ME as a key specimen in endometriosis research. By integrating diagnostic outcomes with mechanistic evidence, we demonstrate that high-performing assays (e.g., aromatase, IGFBP1) correspond directly to the underlying pathology of progesterone resistance and impaired decidualization. The present systematic synthesis supports the “seed and soil” paradigm of endometriosis pathogenesis, in which Sampson’s concept of retrograde menstruation and Leyendecker’s TIAR hypothesis represent sequential stages rather than competing models. ME differs fundamentally from peripheral blood [ 67 , 77 ], as it constitutes a proinflammatory, proangiogenic, and clonogenic “charged” biofluid, further capable of modifying the peritoneal “soil” through immune modulation and extracellular signaling [ 49 , 52 ]. The limitations of included studies include modest sample sizes and no prospective or longitudinal data. The reported research span over three decades (1990–2025), during which analytical technologies evolved substantially from radioimmunoassay-based protein quantification [ 81 , 82 ] to single-cell transcriptomics [ 49 , 58 , 61 ] and digital droplet ELISA platforms [ 50 ]. This technological heterogeneity limits direct comparability of diagnostic metrics but demonstrates consistent biological signals—particularly elevated inflammatory, adhesive, and hormonal markers—across diverse analytical platforms. Clinical translation is currently limited by methodological heterogeneity and the lack of comparison with current first-line modalities like TVS or MRI. Integration into clinical guidelines will require methodological standardization, including protocols for sample collection, pre-analytical processing, and harmonization of analytical assays (ELISA, RT-qPCR, and ICC). Standardization should address pre-analytical sample stability resulting from collection technique. Across studies, ME was obtained via menstrual cups, pads, aspiration, or catheter-based sampling, yet key parameters (cycle day, dwell time in a collection device, transport temperature, time-to-processing, and anticoagulants/preservatives) were inconsistently reported. Pre-analytical conditions may differentially affect biomarker classes. While RNA-based biomarkers show acceptable stability in peripheral blood/serum [ 22 , 86 , 88 ], data regarding other types of biomarkers in menstrual blood are conflicting [ 89 , 90 , 91 ]. For this reason, further research should address the optimal and standardized time and form of self-collection of ME, maintaining the sampling simplicity, but ensuring that the collection technique, transport, and pre-analytical processing would not influence the sample stability and diagnostic capacity. Second, prospective, multi-center validations in real-world populations are critical for ensuring reliability and reproducibility of ME-based diagnosis. Future studies must move beyond case–control designs to assess diagnostic performance in unselected symptomatic women, adolescents, and those with early-stage disease, ideally in direct comparison with first-line imaging. Third, the dynamic nature of ME offers a unique opportunity for longitudinal monitoring. Studies should evaluate intra-individual stability and biomarker changes in response to hormonal or surgical therapy for tracking treatment success or recurrence. Longitudinal analyses should identify key determinants of within-person biomarker variation (e.g., cycle characteristics, inflammation, medication, and comorbidities). Fourth, diagnostic precision may be enhanced by integrating multi-marker approaches that combine complementary signatures (e.g., immune, lipidomic, and RNA-based markers) [ 22 , 85 , 92 ]. Finally, mechanistic insights—such as progesterone resistance and immune dysregulation—should be applied to develop predictive biomarkers for personalized management, guiding treatment selection and risk stratification. In parallel, targeting upstream uterine drivers and peritoneal conditioning steps may represent future disease-modifying therapeutic approaches. Evaluating the health–economic impact and patient acceptability will further support the integration of ME testing into routine care.

This systematic review demonstrates that ME provides a feasible, patient-acceptable, and pathophysiologically relevant source of diagnostic and mechanistic information in endometriosis. Across 35 studies, ME analysis reveals signatures mirroring intrinsic eutopic endometrial abnormalities, immune dysregulation, angiogenic alterations, progesterone resistance, impaired decidualization, and cellular senescence. These findings confirm that ME reflects core disease biology rather than merely representing shed menstrual debris. Diagnostically, several biomarkers related to hormonal regulation and stromal-cell function (such as aromatase mRNA, TGF-β1, and IGFBP1) demonstrated very good discriminatory accuracy, with AUC values exceeding 0.90 in controlled settings, while additional modalities—including a lipidomic two-marker model—showed promising accuracy in the moderate-to-high range. Clinical translation now requires prospective validation in real-world populations and direct comparison with established imaging modalities. With methodological optimization, ME-based testing can offer a pathway to shift the diagnostic paradigm from late-stage surgical confirmation toward early, non-invasive, and personalized detection strategies.