Steroidomics via Gas Chromatography–Mass Spectrometry (GC-MS): A Comprehensive Analytical Approach for the Detection of Inborn Errors of Metabolism

Steroidomics via Gas Chromatography–Mass Spectrometry (GC-MS): A Comprehensive Analytical Approach for the Detection of Inborn Errors of Metabolism

<b>Background:</b> Urinary steroid profiling plays a key role in the diagnosis of inherited and acquired endocrine disorders. Despite the proven diagnostic value of gas chromatography–mass spectrometry (GC-MS), standardized and clinically validated protocols for extended steroid panels r...

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Bibliographic Details
Main Authors: Francesco Chiara, Sarah Allegra, Simona Liuzzi, Maria Paola Puccinelli, Giulio Mengozzi, Silvia De Francia
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Life
Subjects:
GC-MS
steroidomics
urinary steroids
inherited metabolic disorders
Online Access:https://www.mdpi.com/2075-1729/15/6/829
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Summary:<b>Background:</b> Urinary steroid profiling plays a key role in the diagnosis of inherited and acquired endocrine disorders. Despite the proven diagnostic value of gas chromatography–mass spectrometry (GC-MS), standardized and clinically validated protocols for extended steroid panels remain limited. <b>Methods:</b> We developed and validated a GC-MS method for the quantification of 32 urinary steroid metabolites, including androgens, estrogens, progestins, glucocorticoids, and mineralocorticoids. Sample preparation involved solid-phase extraction, enzymatic hydrolysis, and dual derivatization, followed by chromatographic separation and mass detection under full scan mode. Validation followed ICH M10 guidelines. <b>Results:</b> The method demonstrated high selectivity, accuracy (within ±15%), and precision (CV% < 15%) across three QC levels. Limits of Quantification were estimated using the Hubaux–Vos approach and were suitable for detecting both physiological and pathological steroid concentrations. Robustness and matrix effect tests confirmed the method’s reliability and reproducibility. <b>Conclusions:</b> This GC-MS protocol enables comprehensive urinary steroid profiling and calculation of diagnostic ratios for inborn errors of steroid metabolism and endocrine disorders. The method is suitable for clinical application and future integration into personalized medicine workflows.
ISSN:2075-1729

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