Anti-doping authorities have high expectations of the athlete steroidal passport (ASP) for anabolic-androgenic steroids misuse detection. However, it is still limited to the monitoring of known well-established compounds and might greatly benefit from the discovery of new relevant biomarkers candidates. In this context, steroidomics opens the way to the untargeted simultaneous evaluation of a high number of compounds. Analytical platforms associating the performance of ultra-high pressure liquid chromatography (UHPLC) and the high mass-resolving power of quadrupole time-of-flight (QTOF) mass spectrometers are particularly adapted for such purpose. An untargeted steroidomic approach was proposed to analyse urine samples from a clinical trial for the discovery of relevant biomarkers of testosterone undecanoate oral intake. Automatic peak detection was performed and a filter of reference steroid metabolites mass-to-charge ratio (m/z) values was applied to the raw data to ensure the selection of a subset of steroid-related features. Chemometric tools were applied for the filtering and the analysis of UHPLC-QTOF-MS(E) data. Time kinetics could be assessed with N-way projections to latent structures discriminant analysis (N-PLS-DA) and a detection window was confirmed. Orthogonal projections to latent structures discriminant analysis (O-PLS-DA) classification models were evaluated in a second step to assess the predictive power of both known metabolites and unknown compounds. A shared and unique structure plot (SUS-plot) analysis was performed to select the most promising unknown candidates and receiver operating characteristic (ROC) curves were computed to assess specificity criteria applied in routine doping control. This approach underlined the pertinence to monitor both glucuronide and sulphate steroid conjugates and include them in the athletes passport, while promising biomarkers were also highlighted.
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http://dx.doi.org/10.1016/j.forsciint.2011.07.023 | DOI Listing |
Hypertension
October 2024
Department of Medicine III, University Hospital Carl Gustav Carus (G.C., S.F., C.P., G.F.E.).
Background: Diagnosis of primary aldosteronism (PA) is complicated by the need to withdraw antihypertensive medications that interfere with test results, particularly renin. This study examined whether machine learning-based steroid-probability scores offer a renin measurement-independent approach for testing less prone to interference than the aldosterone-to-renin ratio (ARR).
Methods: This prospective multicenter cohort study involved the use of plasma steroidomics and the ARR in 839 patients tested for PA, including 190 with and 578 without PA (71 indeterminate).
J Steroid Biochem Mol Biol
October 2024
Institute of Biochemistry and Molecular Genetics, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia. Electronic address:
Mass spectrometric-based steroidomics is a valuable analytical approach that gives a comprehensive understanding of the interlinked steroid biosynthetic pathways. Here, we describe a rapid and versatile liquid chromatography-tandem mass spectrometry (LC-MS/MS) method designed to accurately quantify endogenous steroids in human serum. Sample preparation involved liquid-liquid extraction with methyl tert-butyl ether (MTBE) from 180 µL serum.
View Article and Find Full Text PDFSci Rep
March 2024
CIRAD, AGAP Institut, Avenue Agropolis, F-34398, Montpellier, France.
Humans have a long history of transporting and trading plants, contributing to the evolution of domesticated plants. Theobroma cacao originated in the Neotropics from South America. However, little is known about its domestication and use in these regions.
View Article and Find Full Text PDFSci Rep
January 2024
Laboratory of Pharmacokinetics and Metabolomic Analysis, Institute of Translational Medicine and Biotechnology, I.M. Sechenov First Moscow Medical University, Moscow, Russia.
The steroid submetabolome, or steroidome, is of particular interest in prostate cancer (PCa) as the dependence of PCa growth on androgens is well known and has been routinely exploited in treatment for decades. Nevertheless, the community is still far from a comprehensive understanding of steroid involvement in PCa both at the tissue and at systemic level. In this study we used liquid chromatography/high resolution mass spectrometry (LC/HRMS) backed by a dynamic retention time database DynaSTI to obtain a readout on circulating steroids in a cohort reflecting a progression of the PCa.
View Article and Find Full Text PDFClin Chem Lab Med
November 2022
Department of Internal Medicine III, University Hospital "Carl Gustav Carus", Technische Universität Dresden, Dresden, Germany.
Objectives: Mass spectrometry-based steroidomics combined with machine learning (ML) provides a potentially powerful approach in endocrine diagnostics, but is hampered by limitations in the conveyance of results and interpretations to clinicians. We address this shortcoming by integration of the two technologies with a laboratory information management systems (LIMS) model.
Methods: The approach involves integration of ML algorithm-derived models with commercially available mathematical programming software and a web-based LIMS prototype.
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