Correlation between serum Urocortin-1 and α-Enolase in endometriosis: insights into a potential stress–metabolism signalling axis
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Abstract
Abstract Background Endometriosis affects approximately 10% of women globally, with diagnostic delays often exceeding 8 years. Urocortin-1 (UCN-1) and alpha-enolase (ENO1) have each been independently implicated in its pathobiology, but their co-regulatory relationship in circulation remains poorly understood. This study aimed to quantify serum UCN-1, ENO1, and MMP-9 in patients versus controls, characterise the ENO1–UCN-1 correlation, and evaluate the independent diagnostic contribution of these biomarkers. Results Principal biomarkers were significantly elevated in patients (MMP-9: p = 0.015; ENO1: p = 0.040; UCN-1: p = 0.021). A pivotal finding was the very strong positive correlation between serum ENO1 and UCN-1 ( r = 0.91, 95% CI 0.853–0.945; p < 0.001), suggesting strong co-regulation. Both markers exhibited significant stage-dependent escalation ( p < 0.001). In multivariate logistic regression adjusted for age and BMI, UCN-1 emerged as a strong independent predictor (aOR = 4.564; 95% CI: 1.083–19.227; p = 0.039), while ENO1 was not independently predictive (aOR = 0.868; p = 0.451) due to high collinearity with UCN-1 (VIF = 5.82). The combined panel (UCN-1 + ENO1 + MMP-9) achieved AUC = 0.717 (bootstrap-corrected 0.701; 95% CI 0.611–0.789). Conclusions The r = 0.91 correlation provides preliminary serum-level evidence consistent with a hypothesised stress–metabolism axis, in which UCN-1-mediated signalling may be associated with glycolytic reprogramming (ENO1), putatively via PI3K–Akt and HIF-1α, although the intracellular steps were not measured in this study and the cascade remains hypothesis-generating only. ENO1 is not an independent biomarker of endometriosis in this dataset; its apparent contribution is fully captured by UCN-1 due to strong co-regulation. The combined UCN-1/ENO1/MMP-9 panel is NOT ready for clinical use: the AUC of 0.717 falls well below clinically deployable thresholds (typically AUC ≥ 0.85–0.90), and prospective external validation in larger, multi-centre cohorts — together with direct mechanistic confirmation — is mandatory before any clinical adoption can be considered.
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