Urinary steroid profiles: comparison of spot and 24-hour collections.


Journal

The Journal of steroid biochemistry and molecular biology
ISSN: 1879-1220
Titre abrégé: J Steroid Biochem Mol Biol
Pays: England
ID NLM: 9015483

Informations de publication

Date de publication:
06 2020
Historique:
received: 07 11 2019
revised: 18 02 2020
accepted: 13 03 2020
pubmed: 27 3 2020
medline: 5 11 2020
entrez: 27 3 2020
Statut: ppublish

Résumé

Urinary steroid profiling is commonly used in clinical routine for the diagnosis of steroid-related diseases through the analysis of absolute steroid excretion values as well as apparent enzyme activities based on catalysed product-to-precursor ratios. To compensate for diurnal fluctuations in steroid concentrations, 24 hour collections are preferred yet impractical and sometimes not feasible. We therefore measured 40 steroid metabolites by GC-MS in 24 hour and spot urine samples of healthy volunteers and systematically evaluated to which extent 24 hour urine collections can be replaced by spot urine collections for diagnostic purposes. Whereas most steroid concentrations show poor correlation between 24 hour and spot urine collection, apparent enzyme activities show better correlation and defects in steroidogenic enzymes such as SRD5A2, CYP17A1, CYP21A2 and CYP11B1. We confirmed our findings in patient samples from our clinic.

Identifiants

pubmed: 32209387
pii: S0960-0760(19)30670-3
doi: 10.1016/j.jsbmb.2020.105662
pii:
doi:

Substances chimiques

Steroids 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

105662

Informations de copyright

Copyright © 2020 Elsevier Ltd. All rights reserved.

Auteurs

Andrea Bileck (A)

Department of Nephrology and Hypertension and Department of BioMedical Research, Inselspital, Bern University Hospital, University of Bern, Switzerland.

Stefanie Frei (S)

Department of Nephrology and Hypertension and Department of BioMedical Research, Inselspital, Bern University Hospital, University of Bern, Switzerland.

Bruno Vogt (B)

Department of Nephrology and Hypertension and Department of BioMedical Research, Inselspital, Bern University Hospital, University of Bern, Switzerland.

Michael Groessl (M)

Department of Nephrology and Hypertension and Department of BioMedical Research, Inselspital, Bern University Hospital, University of Bern, Switzerland. Electronic address: michael.groessl@dbmr.unibe.ch.

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Classifications MeSH