Identification of endogenous carbonyl steroids in human serum by chemical derivatization, hydrogen/deuterium exchange mass spectrometry and the quantitative structure-retention relationship.
Carbonyl steroids
Derivatization
H/D exchange
Quantitative structure-retention relationship
UPLC-Q-exactive-MS/MS
Journal
Journal of chromatography. B, Analytical technologies in the biomedical and life sciences
ISSN: 1873-376X
Titre abrégé: J Chromatogr B Analyt Technol Biomed Life Sci
Pays: Netherlands
ID NLM: 101139554
Informations de publication
Date de publication:
15 Jul 2023
15 Jul 2023
Historique:
received:
06
04
2023
revised:
09
05
2023
accepted:
30
05
2023
medline:
11
7
2023
pubmed:
13
6
2023
entrez:
13
6
2023
Statut:
ppublish
Résumé
Steroids are tetracyclic aliphatic compounds, and most of them contain carbonyl groups. The disordered homeostasis of steroids is closely related to the occurrence and progression of various diseases. Due to high structural similarity, low concentrations in vivo, poor ionization efficiency, and interference from endogenous substances, it is very challenging to comprehensively and unambiguously identify endogenous steroids in biological matrix. Herein, an integrated strategy was developed for the characterization of endogenous steroids in serum based on chemical derivatization, ultra-performance liquid chromatography quadrupole Exactive mass spectrometry (UPLC-Q-Exactive-MS/MS), hydrogen/deuterium (H/D) exchange, and a quantitative structure-retention relationship (QSRR) model. To enhance the mass spectrometry (MS) response of carbonyl steroids, the ketonic carbonyl group was derivatized by Girard T (GT). Firstly, the fragmentation rules of derivatized carbonyl steroid standards by GT were summarized. Then, carbonyl steroids in serum were derivatized by GT and identified based on the fragmentation rules or by comparing retention time and MS/MS spectra with those of standards. H/D exchange MS was utilized to distinguish derivatized steroid isomers for the first time. Finally, a QSRR model was constructed to predict the retention time of the unknown steroid derivatives. With this strategy, 93 carbonyl steroids were identified from human serum, and 30 of them were determined to be dicarbonyl steroids by the charge number of characteristic ions and the number of exchangeable hrdrogen or comparing with standards. The QSRR model built by the machine learning algorithms has an excellent regression correlation, thus the accurate structures of 14 carbonyl steroids were determined, among which three steroids were reported for the first time in human serum. This study provides a new analytical method for the comprehensive and reliable identification of carbonyl steroids in biological matrix.
Identifiants
pubmed: 37311272
pii: S1570-0232(23)00186-1
doi: 10.1016/j.jchromb.2023.123776
pii:
doi:
Substances chimiques
Deuterium
AR09D82C7G
Steroids
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
123776Informations de copyright
Copyright © 2023 Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.