Endometriosis is a common disease affecting women in reproductive age. There are several hypotheses on the pathogenesis of this disease. Often, its lesions and symptoms overlap with those of many other medical and surgical conditions, causing a delay in diagnosis. Metabolomics represents a useful diagnostic tool for the study of metabolic changes during a different physiological or pathological status. We used 1H-NMR to explore metabolic alteration in a cohort of patients with endometriosis in order to contribute to a better understanding of the pathophysiology of the disease and to suggest new useful biomarkers. Thirty-seven patients were recruited for the metabolomic analysis: 22 patients affected by symptomatic endometriosis and 15 not affected by it. Their serum samples were collected and analyzed with 1H-NMR. Multivariate statistical analysis was conducted, followed by univariate and pathway analyses. Partial Least Square Discriminant Analysis (PLS-DA) was performed to determine the presence of any differences between the non-endometriosis and endometriosis samples (R2X = 0.596, R2Y = 0.713, Q2 = 0.635, and p < 0.0001). β-hydroxybutyric acid and glutamine were significantly increased, whereas tryptophan was significantly decreased in the endometriosis patients. ROC curves were built to test the diagnostic power of the metabolites (β-hydroxybutyric acid: AUC = 0.85 CI = 0.71–0.99; glutamine: AUC = 0.83 CI = 0.68–0.98; tryptophan: AUC = 0.75 CI = 0.54–0.95; β-hydroxybutyric acid + glutamine + tryptophan AUC = 0.92 CI = 0.81–1). The metabolomic approach enabled the identification of several metabolic alterations occurring in women with endometriosis. These findings may provide new bases for a better understanding of the pathophysiological mechanisms of the disease and for the discovery of new biomarkers. Trial registration number NCT02337816

Metabolic profile of patients with severe endometriosis: a prospective experimental study

Federica Murgia
Primo
;
Stefano Angioni
Secondo
;
Maurizio Nicola D’Alterio;Antonio Noto;Maria Laura Santoru;Laura Tronci;Vassilios Fanos;Luigi Atzori
Penultimo
;
2021-01-01

Abstract

Endometriosis is a common disease affecting women in reproductive age. There are several hypotheses on the pathogenesis of this disease. Often, its lesions and symptoms overlap with those of many other medical and surgical conditions, causing a delay in diagnosis. Metabolomics represents a useful diagnostic tool for the study of metabolic changes during a different physiological or pathological status. We used 1H-NMR to explore metabolic alteration in a cohort of patients with endometriosis in order to contribute to a better understanding of the pathophysiology of the disease and to suggest new useful biomarkers. Thirty-seven patients were recruited for the metabolomic analysis: 22 patients affected by symptomatic endometriosis and 15 not affected by it. Their serum samples were collected and analyzed with 1H-NMR. Multivariate statistical analysis was conducted, followed by univariate and pathway analyses. Partial Least Square Discriminant Analysis (PLS-DA) was performed to determine the presence of any differences between the non-endometriosis and endometriosis samples (R2X = 0.596, R2Y = 0.713, Q2 = 0.635, and p < 0.0001). β-hydroxybutyric acid and glutamine were significantly increased, whereas tryptophan was significantly decreased in the endometriosis patients. ROC curves were built to test the diagnostic power of the metabolites (β-hydroxybutyric acid: AUC = 0.85 CI = 0.71–0.99; glutamine: AUC = 0.83 CI = 0.68–0.98; tryptophan: AUC = 0.75 CI = 0.54–0.95; β-hydroxybutyric acid + glutamine + tryptophan AUC = 0.92 CI = 0.81–1). The metabolomic approach enabled the identification of several metabolic alterations occurring in women with endometriosis. These findings may provide new bases for a better understanding of the pathophysiological mechanisms of the disease and for the discovery of new biomarkers. Trial registration number NCT02337816
2021
endometriosis; metabolomics; 1h-nmr; multivariate analysis; biomarkers
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/299612
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