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Urinary steroid profiling in women hints at a diagnostic signature of the polycystic ovary syndrome: A pilot study considering neglected steroid metabolites

BACKGROUND: Although the polycystic ovary syndrome (PCOS) is the most common endocrine disorder in women with vast metabolic consequences, its etiology remains unknown and its diagnosis is still made by exclusion. This study aimed at characterizing a large number of urinary steroid hormone metabolit...

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Autores principales: Dhayat, Nasser A., Marti, Nesa, Kollmann, Zahraa, Troendle, Amineh, Bally, Lia, Escher, Geneviève, Grössl, Michael, Ackermann, Daniel, Ponte, Belen, Pruijm, Menno, Müller, Michael, Vogt, Bruno, Birkhäuser, Martin H., Bochud, Murielle, Flück, Christa E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6181287/
https://www.ncbi.nlm.nih.gov/pubmed/30308019
http://dx.doi.org/10.1371/journal.pone.0203903
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author Dhayat, Nasser A.
Marti, Nesa
Kollmann, Zahraa
Troendle, Amineh
Bally, Lia
Escher, Geneviève
Grössl, Michael
Ackermann, Daniel
Ponte, Belen
Pruijm, Menno
Müller, Michael
Vogt, Bruno
Birkhäuser, Martin H.
Bochud, Murielle
Flück, Christa E.
author_facet Dhayat, Nasser A.
Marti, Nesa
Kollmann, Zahraa
Troendle, Amineh
Bally, Lia
Escher, Geneviève
Grössl, Michael
Ackermann, Daniel
Ponte, Belen
Pruijm, Menno
Müller, Michael
Vogt, Bruno
Birkhäuser, Martin H.
Bochud, Murielle
Flück, Christa E.
author_sort Dhayat, Nasser A.
collection PubMed
description BACKGROUND: Although the polycystic ovary syndrome (PCOS) is the most common endocrine disorder in women with vast metabolic consequences, its etiology remains unknown and its diagnosis is still made by exclusion. This study aimed at characterizing a large number of urinary steroid hormone metabolites and enzyme activities in women with and without PCOS in order to test their value for diagnosing PCOS. METHODS: Comparative steroid profiling of 24h urine collections using an established in-house gas-chromatography mass spectrometry method. Data were collected mostly prospectively. Patients were recruited in university hospitals in Switzerland. Participants were 41 women diagnosed with PCOS according to the current criteria of the Androgen Excess and PCOS Society Task Force and 66 healthy controls. Steroid profiles of women with PCOS were compared to healthy controls for absolute metabolite excretion and for substrate to product conversion ratios. The AUC for over 1.5 million combinations of metabolites was calculated in order to maximize the diagnostic accuracy in patients with PCOS. Sensitivity, specificity, PPV, and NPV were indicated for the best combinations containing 2, 3 or 4 steroid metabolites. RESULTS: The best single discriminating steroid was androstanediol. The best combination to diagnose PCOS contained four of the forty measured metabolites, namely androstanediol, estriol, cortisol and 20βDHcortisone with AUC 0.961 (95% CI 0.926 to 0.995), sensitivity 90.2% (95% CI 76.9 to 97.3), specificity 90.8% (95% CI 81.0 to 96.5), PPV 86.0% (95% CI 72.1 to 94.7), and NPV 93.7% (95% CI 84.5 to 98.2). CONCLUSION: PCOS shows a specific 24h urinary steroid profile, if neglected metabolites are included in the analysis and non-conventional data analysis applied. PCOS does not share a profile with hyperandrogenic forms of congenital adrenal hyperplasias due to single steroid enzyme deficiencies. Thus PCOS diagnosis by exclusion may no longer be warranted. Whether these findings also apply to spot urine and serum, remains to be tested as a next step towards routine clinical applicability.
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spelling pubmed-61812872018-10-26 Urinary steroid profiling in women hints at a diagnostic signature of the polycystic ovary syndrome: A pilot study considering neglected steroid metabolites Dhayat, Nasser A. Marti, Nesa Kollmann, Zahraa Troendle, Amineh Bally, Lia Escher, Geneviève Grössl, Michael Ackermann, Daniel Ponte, Belen Pruijm, Menno Müller, Michael Vogt, Bruno Birkhäuser, Martin H. Bochud, Murielle Flück, Christa E. PLoS One Research Article BACKGROUND: Although the polycystic ovary syndrome (PCOS) is the most common endocrine disorder in women with vast metabolic consequences, its etiology remains unknown and its diagnosis is still made by exclusion. This study aimed at characterizing a large number of urinary steroid hormone metabolites and enzyme activities in women with and without PCOS in order to test their value for diagnosing PCOS. METHODS: Comparative steroid profiling of 24h urine collections using an established in-house gas-chromatography mass spectrometry method. Data were collected mostly prospectively. Patients were recruited in university hospitals in Switzerland. Participants were 41 women diagnosed with PCOS according to the current criteria of the Androgen Excess and PCOS Society Task Force and 66 healthy controls. Steroid profiles of women with PCOS were compared to healthy controls for absolute metabolite excretion and for substrate to product conversion ratios. The AUC for over 1.5 million combinations of metabolites was calculated in order to maximize the diagnostic accuracy in patients with PCOS. Sensitivity, specificity, PPV, and NPV were indicated for the best combinations containing 2, 3 or 4 steroid metabolites. RESULTS: The best single discriminating steroid was androstanediol. The best combination to diagnose PCOS contained four of the forty measured metabolites, namely androstanediol, estriol, cortisol and 20βDHcortisone with AUC 0.961 (95% CI 0.926 to 0.995), sensitivity 90.2% (95% CI 76.9 to 97.3), specificity 90.8% (95% CI 81.0 to 96.5), PPV 86.0% (95% CI 72.1 to 94.7), and NPV 93.7% (95% CI 84.5 to 98.2). CONCLUSION: PCOS shows a specific 24h urinary steroid profile, if neglected metabolites are included in the analysis and non-conventional data analysis applied. PCOS does not share a profile with hyperandrogenic forms of congenital adrenal hyperplasias due to single steroid enzyme deficiencies. Thus PCOS diagnosis by exclusion may no longer be warranted. Whether these findings also apply to spot urine and serum, remains to be tested as a next step towards routine clinical applicability. Public Library of Science 2018-10-11 /pmc/articles/PMC6181287/ /pubmed/30308019 http://dx.doi.org/10.1371/journal.pone.0203903 Text en © 2018 Dhayat et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Dhayat, Nasser A.
Marti, Nesa
Kollmann, Zahraa
Troendle, Amineh
Bally, Lia
Escher, Geneviève
Grössl, Michael
Ackermann, Daniel
Ponte, Belen
Pruijm, Menno
Müller, Michael
Vogt, Bruno
Birkhäuser, Martin H.
Bochud, Murielle
Flück, Christa E.
Urinary steroid profiling in women hints at a diagnostic signature of the polycystic ovary syndrome: A pilot study considering neglected steroid metabolites
title Urinary steroid profiling in women hints at a diagnostic signature of the polycystic ovary syndrome: A pilot study considering neglected steroid metabolites
title_full Urinary steroid profiling in women hints at a diagnostic signature of the polycystic ovary syndrome: A pilot study considering neglected steroid metabolites
title_fullStr Urinary steroid profiling in women hints at a diagnostic signature of the polycystic ovary syndrome: A pilot study considering neglected steroid metabolites
title_full_unstemmed Urinary steroid profiling in women hints at a diagnostic signature of the polycystic ovary syndrome: A pilot study considering neglected steroid metabolites
title_short Urinary steroid profiling in women hints at a diagnostic signature of the polycystic ovary syndrome: A pilot study considering neglected steroid metabolites
title_sort urinary steroid profiling in women hints at a diagnostic signature of the polycystic ovary syndrome: a pilot study considering neglected steroid metabolites
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6181287/
https://www.ncbi.nlm.nih.gov/pubmed/30308019
http://dx.doi.org/10.1371/journal.pone.0203903
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