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 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.

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Publication Details

Journal
Life
Published
2025-05-22
DOI
https://doi.org/10.3390/life15060829
Citations
1
Primary Topic
Metabolism and Genetic Disorders
Type
article
Field-Weighted Citation Impact
1.32
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article

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

Sarah Allegra, Giulio Mengozzi, Maria Paola Puccinelli, Silvia De Francia et al.
1 citations
Life
Metabolism and Genetic Disorders
1.32
article

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

Sarah Allegra, Giulio Mengozzi, Maria Paola Puccinelli, Silvia De Francia, Francesco Chiara, Simona Liuzzi
article en
1 citations

Abstract

<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.

LifeVol. 15(6)
University of Trento (IT), University of Turin (IT)
Openalex Percentile: Top 19%
Metabolism and Genetic Disorders
1.32
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