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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

by
Francesco Chiara
1,2,†,
Sarah Allegra
2,*,†,
Simona Liuzzi
3,
Maria Paola Puccinelli
3,
Giulio Mengozzi
3 and
Silvia De Francia
2
1
Department of Physics, University of Trento, 38123 Povo, Italy
2
Department of Clinical and Biological Sciences, University of Turin, 10043 Orbassano, Italy
3
Clinical Biochemistry Laboratory “Baldi e Riberi”, A.O.U. Città della Salute e della Scienza di Torino, 10134 Turin, Italy
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Life 2025, 15(6), 829; https://doi.org/10.3390/life15060829
Submission received: 1 April 2025 / Revised: 5 May 2025 / Accepted: 12 May 2025 / Published: 22 May 2025
(This article belongs to the Section Physiology and Pathology)

Abstract

:
Background: 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. Methods: 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. Results: 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. Conclusions: 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.

1. Introduction

The analysis of steroid metabolites in biological fluids is crucial for understanding endocrine function and diagnosing metabolic disorders. Due to the structural complexity and wide range of concentrations of these compounds, sophisticated analytical techniques are required. While early approaches relied on less specific methods, the advent and coupling of gas chromatography with electron ionization mass spectrometry (GC-EI-MS) in the mid-20th century [1] revolutionized the field, enabling the detailed analysis and “profiling” of complex steroid mixtures in urine following enzymatic hydrolysis and derivatization [2]. This technique rapidly became a cornerstone for steroid metabolomics [3,4], particularly valued for its high chromatographic resolution, essential for separating numerous steroid isomers, and for providing highly characteristic EI mass spectra suitable for confident identification via comparison with extensive mass spectral libraries. Although liquid chromatography–mass spectrometry (LC-MS) techniques, including electrospray ionization (ESI), also developed and became prominent, offering distinct advantages particularly for polar and conjugated metabolites and high-throughput analysis, the application to comprehensive steroid panels evolved over time [5,6]. Nevertheless, GC-MS after appropriate sample preparation remains a powerful and often preferred method for comprehensive profiling of the less polar, unconjugated urinary steroid metabolites where maximizing chromatographic separation and obtaining definitive spectral information for identification are paramount for resolving complex diagnostic profiles relevant to inborn errors of metabolism and other endocrine disorders [4,6,7,8,9].
In parallel with technological advancements, the clinical utility of urinary steroid profiling has expanded significantly. Modern mass spectrometry-based platforms now allow for the simultaneous quantification of dozens of steroid metabolites, enabling not only the diagnosis of enzymatic defects but also the evaluation of functional activity along steroidogenic pathways [3,10]. In contrast to isolated single-analyte testing, the profiling approach captures complex biochemical signatures, making it a valuable tool for both diagnostic and prognostic purposes.
More recently, urinary steroid metabolomics has emerged as a powerful tool not only in rare metabolic syndromes but also in common endocrine conditions, including disorders of the female reproductive system. Alterations in the androgen, estrogen, and corticosteroid pathways are observed in a range of conditions, from polycystic ovary syndrome and endometriosis to adrenal tumors [11,12]. These alterations often manifest as characteristic shifts in the relative abundance of specific urinary metabolites, such as etiocholanolone, androsterone, tetrahydro-cortisol derivatives, and their hydroxylated or keto counterparts.
Despite the growing importance of these profiles in clinical endocrinology, standardized, validated methods for the simultaneous quantification of extended urinary steroid panels remain limited. GC-MS remains a cornerstone and often considered a reference method for comprehensive steroid profiling, particularly for isomeric compounds and low-abundance metabolites [4,6,7,8]. However, most available protocols are either insufficiently validated for clinical translation or restricted to limited subsets of steroids.
In this context, we report the analytical validation of a GC-MS method designed to quantify a comprehensive panel of 32 urinary steroid metabolites, including key androgens, estrogens, pregnanes, and corticosteroids. This method was developed to address current gaps in routine diagnostics, integrating both historical markers of congenital metabolic disorders and emerging indicators of reproductive and adrenal dysfunction. The final profile, detailed in Table 1, Table 2, Table 3, Table 4 and Table 5 was selected to maximize clinical relevance based on both the legacy literature and recent metabolomic evidence [13].

2. Materials and Methods

2.1. Chemicals

Unless otherwise specified, all reagents were purchased from Merck (Darmstad, Germany). In particular n-hexane, ethyl acetate, methanol, isopropanol, and anhydrous pyridine were GC-MS grade; silylating mixture II according to Horning [14] was constituted from N,O-Bis(trimethylsilyl)acetamide, chlorotrimethylsilane, and 1-(trimethylsilyl)imidazole mixture, with volumetric ratio as BSA+TMCS+TMSI 3:2:3. The Sigmatrix Urine Diluent (SUD), non-biological diluent that mimics human urine, was used to prepare simulated sample. The 18 M Ω water was produced with Thermo Scientific™ (Waltham, MA, USA) Barnstead™ GenPure™ Pro; the standard powders of each steroid were purchased from Steraloids Inc., based in Newport, (RI, USA). The Strata C18-E SPE cartridges were obtained from Phenomenex (Torrance, CA, USA). Beta-glucuronidase/sulfatase enzyme from Helix pomatia (Type H-2, aqueous solution, Product Number G0876) was purchased from Sigma-Aldrich (St. Louis, MO, USA). According to the Certificate of Analysis, the lot used had a glucuronidase activity of 85,707 units/mL and a sulfatase activity of 778 units/mL.

2.2. Stock Solutions, Standards (STDs), and Quality Controls (QCs)

  • Individual stock solutions: Each steroid standard was dissolved according to the manufacturer’s certificate of analysis to prepare a stock solution at the recommended concentration.
  • Working solutions: Stock solutions were diluted in isopropanol to obtain individual working solutions for each analyte.
  • Mixed stock solution: Equal volumes of each individual working solution were combined to prepare a mixed stock solution containing all target analytes.
  • Calibration solutions: The mixed stock solution was serially diluted in isopropanol to generate six calibration levels.
  • Spiked samples: Each calibration level was diluted 1:10 in surrogate urine diluent (SUD) to prepare matrix-based spiked samples for calibration.
  • Quality control (QC) samples: Three QC levels (low, medium, high) were prepared in SUD in accordance with ICH M10, Section 3.2.5.1.
  • Blank sample: Prepared by mixing deionized water and SUD in a 1:10 volume ratio without any added analytes.
  • Buffer A (3 M Acetate Buffer, pH 4.6)—A solution (A1) of 3 M acetic acid is prepared by diluting 43.27 mL of glacial acetic acid (d = 1.04) to a final volume of 250 mL with deionized water. A solution (B1) of 3 M sodium acetate is prepared by dissolving 61.5 g of anhydrous salt or 102 g of trihydrate salt in 250 mL of deionized water. Mix 152 mL of A1 with 147 mL of B1. The pH is then measured.
  • Buffer B (0.2 M Acetate, pH 4.6): A solution (A2) of 0.2 M acetic acid is prepared by diluting 5.75 mL of glacial acetic acid (d = 1.04) to a final volume of 500 mL with deionized water. A solution (B2) of 0.2M sodium acetate is prepared by dissolving 8.2 g of anhydrous salt or 13.6 g of trihydrate salt in 500 mL of deionized water. Mix 255 mL of A2 with 245 mL of B2. The pH is then checked.
  • Bicarbonate Buffer (pH 10.5): A solution (A) of 0.1 M sodium carbonate is prepared by dissolving 10.6 g of anhydrous Na2CO3 in 1 L of deionized water. A solution (B) of 0.1M sodium bicarbonate is prepared by dissolving 4.200 g of anhydrous salt (MW = 84.007) in 500 mL of deionized water. Mix 771.5 mL of solution (A) with 228.5 mL of solution (B) and adjust the final volume to 1L with deionized water. The pH is checked and, if necessary, adjusted by adding a few drops of 2N sodium hydroxyde.
  • Internal Standard (IS) Solution: A stock solution of stigmasterol was prepared by dissolving 18 mg of standard powder in 10 mL of isopropanol. The working solution was then prepared by diluting the stock solution 1:100 in methanol.
  • Methoxyamine (MOX) solution: 100 mg of methoxyamine hydrochloride was dissolved in 10 mL of anhydrous pyridine. The prepared solution is stored in an amber tube, protected from light, at −20 °C.
  • 0.05 M Sulfuric acid solution: It was prepared by diluting 250 μ L of fuming H2SO4 in 93 mL of deionized water.
  • Acidified water: It was prepared by diluting 3 mL of glacial acetic acid in 1 L of deionized water.

2.3. Preparation of Urinary Samples for GC-MS Analysis of the Steroids Profile

2.3.1. Total Steroids Extraction

Before proceeding with the extraction, the samples must be vortexed and centrifuged. If they are frozen (stored at −80 °C), they should be properly thawed. Then, a series of new SPE columns, numbered according to the analytical sequence, should be set up on the SPE manifold and conditioned as follows: 3 mL of methanol is dispensed, followed by 3 mL of acidified water; the vacuum is applied, and the eluate is discarded. The flow is stopped by closing the valves when the meniscus is about 3–5 mm from the upper portion of the stationary phase.
At this point, using a series of plastic tubes with caps, numbered in the same way as the SPE columns, 5 mL of urine is dispensed into each tube. Then, 2 mL of buffer A is added, vortexed, and centrifuged. Next, 100 μ L of internal standard (IS) solution (stigmasterol, stored at −20 °C) is dispensed into each column, and the buffered urine solution is transferred from the tubes to the columns. Percolation is carried out through the SPE columns by applying a vacuum to maintain a flow rate not exceeding 3 mL/min, and the eluate is discarded.
At this point, a series of glass tubes, numbered like the SPE columns, is placed under the outlet nozzles. Elution is performed twice using 2 mL of methanol each time, percolating at a moderate flow rate and collecting the eluate in the previously prepared tubes. The eluate is then evaporated under a nitrogen stream in a water bath at 45 °C until the volume is reduced to approximately 500 μ L. This partial evaporation, avoiding complete dryness, to avoid potential degradation or loss of thermolabile derivatized metabolites and facilitates reconstitution in the subsequent enzymatic hydrolysis buffer. The extraction procedure can be interrupted at this stage by freezing the eluate and storing the SPE columns in the refrigerator for up to 24 h. The volume of buffer used in the subsequent step is sufficient to dilute the residual methanol, ensuring optimal activity of the enzyme mixture.

2.3.2. Enzymatic Hydrolysis of Conjugates and Extraction

To the concentrated eluate obtained, 5 mL of buffer B and 200 μ L of glucuronidase/ sulfatase are added. The tubes are then incubated for 3 h at 55 °C in a thermostated water bath. After incubation, the samples are vortexed and centrifuged.
At this point, the previously used columns are reconditioned by dispensing 3 mL of methanol followed by 3 mL of acidified water, ensuring that the eluate is percolated and discarded by applying the necessary vacuum. The solvent flow is stopped under the same conditions described in the previous section.
The supernatant from each tube is then transferred to the corresponding numbered column and percolated under vacuum, ensuring that the elution flow rate does not exceed 3 mL/min. The eluate is discarded, and the SPE columns are eluted twice with 2 mL of ethyl acetate, maintaining a moderate elution flow rate and collecting the eluate in the prenumbered tubes.
At this stage, 2 mL of bicarbonate buffer (pH 10.5) is dispensed into each tube, capped, and vortexed for 30 s, then centrifuged. In a third set of correspondingly numbered tubes, the supernatant (organic phase) is transferred and evaporated to dryness under a nitrogen stream in a water bath at 45 °C.
If necessary, this second preparative phase can be interrupted, resuming the process by reconstituting the dried residue with 50 μ L of methanol and storing it at −20 °C for up to 24 h.

2.3.3. Double Derivatization of Free Steroids

To each tube, 100 μ L of MOX solution in pyridine is added. At this stage, it is important to cap the tubes with clean and dry caps; vortex, invert, and incubate for 1 h at 80 °C. Then, 100 μ L of derivatizing reagent F is added to each tube; vortex, invert, and incubate for 4 h at 100 °C. This phase can be interrupted by freezing the tubes at −20 °C, knowing that the derivatized compound is stable under these conditions for 15 days. The overall derivatization mechanism, including both methoximation and silylation steps with the BSA+TMCS+TMSI mixture, is illustrated in Figure 1.
Next, 3 mL of n-hexane and 2 mL of 0.05 M sulfuric acid are added. Vortex for 30 s until the solution is clear, then proceed to remove the aqueous phase at the bottom of the tube using a Pasteur pipette. Add 2 mL of 0.05 M sulfuric acid again, vortex the tubes for 30 s, and then centrifuge.
Afterward, transfer the upper organic phase obtained into a new glass tube. The solvent is then evaporated to dryness in a water bath at 45 °C under nitrogen. The residue is reconstituted with 120 μ L of n-hexane, vortexed well, and 50 μ L is transferred into a vial for GC-MS injection.

2.4. GC-MS Analysis

The analyses were performed using a Hewlett Packard HP 6890 gas chromatograph (Agilent Technologies Inc., Santa Clara, CA, USA) coupled with an HP 5973 mass selective detector (MSD) (Agilent Technologies Inc., Santa Clara, CA, USA). Chromatographic separation was achieved using a CPS Analitica CC-5 MS capillary column (CPS Analitica, Milano, Italy) (50 m length, 0.25 mm internal diameter, 0.25 μ m film thickness, crossbond), with helium as the carrier gas under constant flow conditions (initial flow: 0.6 mL/min; inlet pressure: 7.65 psi). The maximum column temperature was 350 °C.
The GC oven temperature program was as follows: initial temperature 50 °C (held for 0 min), then ramped at 50 °C/min to 230 °C, 0.4 °C/min to 250 °C (held for 5 min), 20 °C/min to 270 °C, and 50 °C/min to 285 °C (held for 30 min). Total run time was 89.9 min.
This temperature program, including the multiple ramps, was empirically optimized to achieve maximal chromatographic resolution for the complex panel of steroid metabolites, ensuring adequate separation of critical isomers across the entire elution range.
The injector was operated in splitless mode at 285 °C. The injection volume was 2.0 μ L, using a 10 μ L syringe. The purge flow was set to 50.5 mL/min, with a purge activation delay of 2.5 min. A gas saver flow of 15 mL/min was used after 2 min.
The MS detector operated in scan mode with a solvent delay of 20 min, scanning from m/z 75 to 700. The ion source and quadrupole temperatures were set at 230 °C and 150 °C, respectively. Electron ionization was used, and mass calibration was verified before acquisition.
Chromatographic data were automatically integrated. Compounds were identified by comparing their retention times and acquired full mass spectra with those contained in the NIST 05 Mass Spectral Library and a dedicated in-house library (STEROIDI.L) generated using authentic standards of all target analytes under the method’s specific conditions. Quantification was performed by integrating the area of specific ions (target ion (Tgt), and qualifying ions (Q1, Q2, Q3)) extracted from the full scan data for each analyte. Calibration curves were generated using multiple concentration levels (6 points) covering the relevant range, and quality control samples were analyzed at three levels of concentration. Blank samples were also included in each analytical batch. Quantification was performed using linear regression models, applying quality acceptance criteria in accordance with international validation guidelines (ICH M10).

2.5. Method Performance: Selectivity, Specificity, Accuracy, Precision, and Sensitivity Parameters

Selectivity was evaluated using a blank surrogate urine matrix (Sigmatrix Urine Diluent, SUD) processed in the same way as study samples. The absence of interference was confirmed by analyzing at least six blank samples, ensuring that any signal at the retention time of the analytes and internal standards was <20% of the LLOQ response for each analyte and <5% for the internal standard, in accordance with ICH M10 guidelines.
Specificity was assessed by verifying the absence of significant interference from structurally related compounds, endogenous substances, or degradation products. No significant back-conversion or cross-talk between analytes was observed under the analytical conditions applied.
Accuracy and precision were determined by analyzing five replicates of QC samples at three concentration levels (low, medium, and high) across the calibration range, in multiple analytical runs. QCs were prepared by diluting reference mix solutions (10× in solvent) in a 1:10 volume ratio using SUD. Acceptance criteria followed ICH M10: accuracy within ±15% of nominal values (±20% for LLOQ), and precision (%CV) not exceeding 15% (20% for LLOQ), both within- and between-run.
Limits of Detection (LOD) and Limits of Quantification (LLOQ) were estimated according to the statistical model proposed by Hubaux and Vos [15], based on the confidence intervals of the regression line derived from six calibration levels. This method, based on the confidence intervals of the regression line derived from six calibration levels, allows for defining two kinds of lower limits from a statistical point of view: a decision limit (yc = LLOQ), representing the lowest signal that can be statistically distinguished from the background, and a detection limit (yD = LOD), corresponding to the content under which, a priori, any sample may erroneously be taken for a blank. These limits were calculated considering predefined type I and type II error probabilities, and the data are reported in Table 6, Table 7, Table 8, Table 9, Table 10, Table 11, Table 12, Table 13, Table 14 and Table 15.

2.6. Analyte Recovery and Extraction Efficiency Evaluation

Recovery (R) was assessed by comparing the peak areas of analytes spiked into SUD before extraction with those spiked after extraction (post-extraction spike), at low and high QC levels.
Extraction efficiency (EE) was evaluated by comparing the response of extracted samples to that of equivalent neat solutions prepared at the same concentrations. All measurements were performed in triplicate, and acceptable values for R and EE were within 85–115% of the nominal response.

2.7. Evaluation of Method Robustness and Matrix Interference

Robustness of the method was evaluated by intentionally introducing minor variations in analytical conditions, including injector temperature, carrier gas flow rate, and sample preparation timing. Under all tested conditions, the method maintained acceptable levels of accuracy and precision, confirming its robustness. Although the current validation was conducted using a surrogate matrix, the method is considered suitable for future clinical application, provided that equivalent performance is confirmed in real urine samples.
Matrix effects were assessed using Sigmatrix Urine Diluent, a synthetic surrogate matrix with a controlled and reproducible composition. Given its high lot-to-lot consistency, matrix effect evaluation was performed using multiple replicates of low and high QC samples from a single validated lot. The internal standard-normalized matrix factor (MF) showed a %CV below 15%, indicating minimal ion suppression or enhancement and confirming the suitability of the matrix for method validation purposes.

2.8. Stability of Analytes and Samples

Stability of the analytes was evaluated under different conditions:
  • Freeze-thaw stability was tested over three cycles using low and high QCs stored at −20 °C between cycles.
  • Short-term (bench-top) stability was assessed by keeping spiked QCs at room temperature for the duration of sample preparation and analysis.
  • Long-term stability was evaluated for QCs stored at −20 °C for a period exceeding the expected study sample storage time.
  • Post-preparative (autosampler) stability was tested by re-injecting extracted samples after storage at the autosampler temperature for the full runtime.
In all cases, the mean measured concentrations remained within ±15% of the nominal value, confirming stability. Stock and working solutions were also tested and shown to be stable under the applied storage conditions.

3. Results

3.1. Specificity, Selectivity, Accuracy, Precision, and Limits of Quantification and Detection

The total ion chromatogram (TIC) and individual mass spectra acquired for each analyte confirmed high specificity of the method, with full chromatographic separation and no evidence of cross-talk or overlapping peaks. Mass spectra showed the expected fragmentation patterns for all target compounds and were consistent with reference spectra from both commercial and in-house libraries.
Selectivity was verified by the absence of interfering peaks in the blank surrogate matrix (Sigmatrix Urine Diluent) at the retention times of the analytes and internal standard (Stigmasterol). No matrix components exceeded 20% of the analyte response at the LLOQ level.
Accuracy and precision were confirmed across the entire analytical range. All analytes met the acceptance criteria established by ICH M10, with intra-assay and inter-assay coefficients of variation (CV%) below 15% at each QC level (and below 20% at LLOQ). The method demonstrated acceptable performance for all validated analytes in terms of repeatability and reproducibility, as defined by CV% values across three quality control (QC) levels (low, medium, high).
Repeatability (Rep.) and reproducibility (Repr.) data for each steroid class are presented separately in Table 16, Table 17, Table 18 and Table 19. Specifically, Table 16 summarizes the performance of progestins, Table 17 for mineralocorticoids, Table 18 for glucocorticoids, Table 20 for androgens, and Table 19 for estrogens. In each table, Rep. and Repr. are expressed as CV% and refer to intra-assay and inter-assay precision, respectively.
All values obtained were below the acceptance criteria of 15% CV for medium and high QC levels, and 20% for the lower limit of quantification (LLOQ), in accordance with the ICH M10 guidelines. These results confirm the robustness and reproducibility of the method for each metabolite tested.
The internal standard (IS), stigmasterol, was monitored to ensure consistency in sample preparation and instrument performance but was excluded from the QC-based CV calculations. The precision and retention time data demonstrate the reliability and robustness of the method for clinical application.
The Limits of Detection (LOD) and Quantification (LLOQ) were calculated according to the statistical approach proposed by Hubaux and Vos. All analytes displayed sufficient signal-to-noise ratios to meet detection criteria, with LLOQs compatible with expected urinary concentrations under physiological and pathological conditions.
According to ICH M10 guidelines, selectivity is confirmed when the response of blank samples at the analyte retention time is less than 20% of the response at the lower limit of quantification (LLOQ), and less than 5% for internal standards. In our method, at least six blank samples were analyzed and no significant signals were observed. The representative extracted ion chromatograms (EICs) shown in Figure 2 demonstrate the high selectivity and lack of interference in the detection of target analytes.

3.2. Recovery and Extraction Efficiency

Although absolute recovery was not the primary endpoint of this method validation, the consistency of analytical response across QC levels and minimal variability in replicate samples support an efficient extraction protocol. Peak areas of spiked samples showed minimal deviation from expected values, confirming stable analyte behavior through sample handling and derivatization.

3.3. Robustness and Matrix Effect Evaluation

Robustness was tested using a factorial design (Yates matrix) by varying key instrumental parameters, including injector temperature, carrier gas flow rate, and splitless time. The F-test applied to compare the standard deviations of replicate measurements under normal and stressed conditions revealed no statistically significant differences (F < Fcrit = 2.87) for any analyte. The only borderline case was observed for 11ß-OH-androsterone, which nonetheless remained within acceptable precision limits, confirming overall method robustness. Representative results are illustrated in Figure 3 and Figure 4.
Matrix effects were assessed in the surrogate matrix used for method development. Due to the standardized and defined composition of Sigmatrix Urine Diluent, consistent signal responses were observed across replicate preparations. IS-normalized matrix factors showed a coefficient of variation below 15%, fulfilling the requirements for bioanalytical application.

3.4. Stability

Stability was evaluated under multiple storage and processing conditions. All analytes demonstrated stability in the autosampler (post-preparative stability), after three freeze–thaw cycles, and during short-term benchtop exposure. No significant degradation or loss of signal was observed. Analyte responses remained within ±15% of nominal values across all tested conditions, confirming suitability for routine use in a clinical or research setting.

4. Discussion

The method here demonstrates excellent analytical performance in terms of sensitivity, reproducibility, and robustness, aligning with the acceptance criteria of ICH M10. GC-MS has long been recognized as the gold standard for urinary steroid profiling, enabling the detection of complex metabolic signatures in endocrine and metabolic diseases [4].
Our assay quantifies 32 urinary steroids across five major hormonal classes—progestins, mineralocorticoids, glucocorticoids, androgens, and estrogens—with precision values consistently below 15% CV (Table 16, Table 17, Table 18 and Table 19). The performance was maintained even under conditions of analytical stress, as shown by robustness testing (Figure 3 and Figure 4). These findings support the suitability of the method for routine application in clinical laboratories.
Importantly, the method also allows for the calculation of diagnostic ratios between steroid metabolites. These ratios—first proposed by Shackleton and later refined by Rousson et al. and Ackermann et al.—serve as functional biomarkers reflecting enzymatic activities within steroidogenic pathways [2,9,16]. Examples include the ET/AN ratio (5 β /5 α ), 11 β -hydroxylase deficiency indices (e.g., THS/THF), or 21-hydroxylase markers (17HP/PTONE), which are crucial in the differential diagnosis of congenital adrenal hyperplasia (CAH) and other inborn errors of metabolism [17].
The method’s application is not limited to rare diseases. Recent data support its utility in subtyping Cushing’s syndrome [18], as well as in steroid-related nephrotic syndrome and reproductive endocrinology [6]. The inclusion of estrogens and progestins, often neglected in routine workflows, expands its potential utility in assessing disorders such as PCOS, endometriosis, or hormonal therapies.
Finally, the minimal matrix effect and use of a stable surrogate matrix (SUD) confirm the method’s compatibility with high-throughput sample processing and quantitative metabolomics workflows. Its design is well suited to future integration with multi-omics platforms and longitudinal patient stratification approaches [7,19].

5. Conclusions

We developed and validated a GC-MS method for the quantitative profiling of urinary steroid metabolites that meets international analytical standards. The method allows for the simultaneous measurement of 36 key steroids, with high precision and robustness, and enables the calculation of clinically relevant diagnostic ratios.
By integrating classic metabolic profiling with updated diagnostic criteria, this method paves the way for broader implementation of urinary steroid metabolomics in clinical endocrinology. Its application to real clinical samples will further validate its use in the differential diagnosis of endocrine and metabolic disorders, particularly in contexts where steroidogenic enzyme defects are suspected. The results presented support its suitability for routine application and for future integration into personalized medicine workflows.

Author Contributions

Conceptualization, F.C. and S.A.; methodology, F.C.; software, F.C.; validation, F.C., S.A. and M.P.P.; formal analysis, S.L.; investigation, S.L.; resources, M.P.P.; data curation, G.M.; writing—original draft preparation, F.C.; writing—review and editing, S.A.; visualization, S.D.F.; supervision, S.D.F.; project administration, G.M.; funding acquisition, G.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

Analytes

The following Analytes are used in this manuscript:
GC-MSGas Chromatography–Mass Spectrometry
LODLimit of Detection
LLOQLower Limit of Quantification
QCQuality Control
CV%Coefficient of Variation (Percent)
CAHCongenital Adrenal Hyperplasia
ISInternal Standard
SPESolid Phase Extraction
SUDSigmatrix Urine Diluent
MOXMethoxyamine
ICHInternational Council for Harmonisation
Rep.Repeatability
Repr.Reproducibility
TICTotal Ion Chromatogram
RTRetention Time
PregnanediolP2
Pregnentriol5PT
17OH-Pregnanolone17HP
PregnantriolPT
PregnantriolonePTONE
TH-11DesoxicorticosteroneTHDOC
TH-11DehydrocorticosteroneTHA
5 α -Tetrahydrocorticosterone5 α THB
TetrahydrocorticosteroneTHB
TH-11DeoxycortisolTHS
CortisolF
TetrahydrocortisolTHF
5 α -Tetrahydrocortisol5 α -THF
β -Cortol β -Cortolo
α -Cortol α -Cortolo
20 α -Dihydrocortisol20 α -DHF
11 β -Hydroxyetiocholanolone11 β -OHET
TetrahydrocortisoneTHE
α -Cortolone α -Cortolone
β -Cortolone β -Cortolone
11-Ketoetiocholanolone11ketoET
DehydroepiandrosteroneDHEA
16 α -Hydroxy-DHEA16 α -OHDHEA
5-Androstene-3 β ,17 β -diolD5-ADIOL
AndrostenetriolD5-ATRIOL
EtiocholanoloneET
AndrosteroneAN
5 α -Androstanediol5 α -ADIOLO
11 β -Hydroxyandrosterone11 β -OHAN
EstriolE3
17 β -EstradiolE2
EstroneE1

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Figure 1. Reaction scheme of the derivatization process for hydroxysteroids: methoximation (MOX) followed by silylation using a mixture of BSA (N,O-Bis(trimethylsilyl)acetamide), TMCS (chlorotrimethylsilane), and TMSI (trimethylsilylimidazole). The resulting derivatives are trimethylsilyl (TMS)-protected steroids, as shown in the final structure.
Figure 1. Reaction scheme of the derivatization process for hydroxysteroids: methoximation (MOX) followed by silylation using a mixture of BSA (N,O-Bis(trimethylsilyl)acetamide), TMCS (chlorotrimethylsilane), and TMSI (trimethylsilylimidazole). The resulting derivatives are trimethylsilyl (TMS)-protected steroids, as shown in the final structure.
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Figure 2. Extracted ion chromatograms for α -Cortol, β -Cortolone, and the internal standard stigmasterol (IS) are shown in the top row. Each panel displays the ion currents of the monitored transitions: target ion (black), qualifier 1 (magenta), and qualifier 2 (purple), corresponding to m/z values used in the acquisition. Dots represent the raw signal intensity, while the overlaid solid lines reflect the smoothed chromatographic profiles of each individual ion current. The bottom panel shows the unprocessed total ion current (TIC) chromatogram of a representative sample, illustrating the overall complexity and retention time distribution of the steroidal metabolites analyzed.
Figure 2. Extracted ion chromatograms for α -Cortol, β -Cortolone, and the internal standard stigmasterol (IS) are shown in the top row. Each panel displays the ion currents of the monitored transitions: target ion (black), qualifier 1 (magenta), and qualifier 2 (purple), corresponding to m/z values used in the acquisition. Dots represent the raw signal intensity, while the overlaid solid lines reflect the smoothed chromatographic profiles of each individual ion current. The bottom panel shows the unprocessed total ion current (TIC) chromatogram of a representative sample, illustrating the overall complexity and retention time distribution of the steroidal metabolites analyzed.
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Figure 3. Standard deviation profile for P3, THF, and 11OHA across robustness testing conditions (Yates matrix).
Figure 3. Standard deviation profile for P3, THF, and 11OHA across robustness testing conditions (Yates matrix).
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Figure 4. Standard deviation profile for Estrone and TH-Corticosterone across robustness testing conditions (Yates matrix).
Figure 4. Standard deviation profile for Estrone and TH-Corticosterone across robustness testing conditions (Yates matrix).
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Table 1. Steroid metabolites in the progestins group with retention times and associated clinical conditions.
Table 1. Steroid metabolites in the progestins group with retention times and associated clinical conditions.
AnalyteAbbreviationRT (min)Associated Conditions
17OH-Pregnanolone17HP45.72Elevated in CAH due to 21-hydroxylase or 11 β -hydroxylase deficiency.
PregnanediolP250.66Major metabolite of progesterone; increased in 21-hydroxylase deficiency (classic CAH).
Pregnentriol5PT60.29Marker of 3 β -hydroxysteroid dehydrogenase (3 β -HSD) deficiency; increased in non-classic CAH variants.
PregnantriolonePTONE60.67Derived from 17-hydroxyprogesterone (17OHP); elevated in 21-hydroxylase deficiency. Often reported with pregnanetriol.
PregnantriolPT61.92Major urinary metabolite of 17OHP; markedly elevated in 21- and 11 β -hydroxylase deficiency (CAH).
Table 2. Steroid metabolites in the mineralocorticoids group with retention times and associated clinical conditions.
Table 2. Steroid metabolites in the mineralocorticoids group with retention times and associated clinical conditions.
AnalyteAbbreviationRT (min)Associated Conditions
TH-11-DeoxycorticosteroneTHDOC60.38Metabolite of DOC; elevated in 11 β -hydroxylase deficiency, sometimes in AME.
5 α -TH-Corticosterone5 α THB64.04Metabolite in the aldosterone biosynthesis pathway.
TH-CorticosteroneTHB64.80Aldosterone pathway metabolite.
TH-11-DehydrocorticosteroneTHA65.04Derived from 11-dehydrocorticosterone; altered in 11 β -hydroxylase deficiency.
Table 3. Steroid metabolites in the glucocorticoids group with retention times and associated clinical conditions.
Table 3. Steroid metabolites in the glucocorticoids group with retention times and associated clinical conditions.
AnalyteAbbreviationRT (min)Associated Conditions
11-Keto-Etiocholanolone11ketoET42.88Metabolite of cortisone pathway.
11 β -OH-Etiocholanolone11 β OHET45.79Elevated in 11 β -hydroxylase deficiency.
TH-11-DeoxycortisolTHS57.39Highly elevated in 11 β -hydroxylase deficiency.
TH-CortisoneTHE63.03Cortisone metabolite.
TH-CortisolTHF63.80Cortisol metabolite.
5 α -TH-Cortisol5 α THF64.33Cortisol metabolite; used in 5 α /5 β ratio for ACRD.
β β -Cortol β Cortol65.10Cortisol metabolite; altered in ACRD.
α -Cortolone α Cortolone65.40Cortisol metabolite; altered in ACRD.
β -Cortolone β Cortolone66.75Cortisol metabolite; altered in ACRD.
α -Cortol α Cortol66.95Cortisol metabolite; altered in ACRD.
CortisolF77.63Primary glucocorticoid excreted in urine.
20 α -Dihydro-Cortisol20 α DHF81.19Minor cortisol metabolite.
Table 4. Steroid metabolites in the androgens group with retention times and associated clinical conditions.
Table 4. Steroid metabolites in the androgens group with retention times and associated clinical conditions.
AnalyteAbbreviationRT (min)Associated Conditions
5 α -Androstanediol5 α ADIOL30.50Androgen metabolite.
AndrosteroneAN34.24Elevated in CAH and androgen excess. ET/AN ratio is informative.
Δ 5-AndrostenediolD5-ADIOL34.37Altered in 3 β -HSD deficiency.
EtiocholanoloneET35.40Elevated in CAH and androgen excess. ET/AN ratio is informative.
DehydroepiandrosteroneDHEA38.25Precursor/metabolite in adrenal androgen pathway; elevated in CAH and adrenal tumors.
11 β -OH-Androsterone11 β OHAN40.00Derived from cortisol metabolism; elevated in 11 β -hydroxylase deficiency.
16 α -OH-DHEA16 α OHDHEA47.90DHEA pathway metabolite.
AndrostenetriolD5-ATRIOL53.02Altered in 3 β -HSD deficiency.
Table 5. Steroid metabolites in the estrogens group with retention times and associated clinical conditions.
Table 5. Steroid metabolites in the estrogens group with retention times and associated clinical conditions.
AnalyteAbbreviationRT (min)Associated Conditions
EstroneE143.39Estrogen metabolite.
EstriolE359.14Estrogen metabolite; also a pregnancy marker.
17 β -EstradiolE276.06Estrogen metabolite.
Table 6. Slope and intercept parameters with 95% confidence intervals for progestins (GC-MS).
Table 6. Slope and intercept parameters with 95% confidence intervals for progestins (GC-MS).
AnalytesSlope (m)CIlow(m)CIhigh(m)Intercept (q)CIlow(q)CIhigh(q)
P20.03260.03090.03430.09130.05290.1298
5PT0.01110.01070.01150.14590.13680.1550
17HP0.03370.03300.03450.19220.17540.2090
PT0.01530.01500.01560.13790.13110.1447
PTONE0.06860.06560.07170.09700.02820.1658
Table 7. LOD, LOQ, LLOQ, recovery, and R 2 for progestins (GC-MS).
Table 7. LOD, LOQ, LLOQ, recovery, and R 2 for progestins (GC-MS).
AnalytesLOD ( μ g/mL)LOQ ( μ g/mL)LLOQ ( μ g/mL)Recovery (%)R2
P22.1726.5810.01097.71000.9986
5PT1.5074.5670.010109.38000.9993
17HP0.9192.7850.010107.70000.9997
PT0.8182.4780.010102.55000.9998
PTONE1.8485.5990.010110.30000.9990
Table 8. Slope and intercept parameters with 95% confidence intervals for mineralocorticoids (GC-MS).
Table 8. Slope and intercept parameters with 95% confidence intervals for mineralocorticoids (GC-MS).
AnalytesSlope (m)CIlow(m)CIhigh(m)Intercept (q)CIlow(q)CIhigh(q)
THDOC0.04900.04770.05040.0068−0.02340.0369
THA0.07840.07640.08030.13710.09380.1804
5 α THB0.04830.04690.04970.06110.02990.0923
THB0.05680.05480.05890.09670.05020.1431
Table 9. LOD, LOQ, LLOQ, recovery, and R 2 for mineralocorticoids (GC-MS).
Table 9. LOD, LOQ, LLOQ, recovery, and R 2 for mineralocorticoids (GC-MS).
AnalytesLOD ( μ g/mL)LOQ ( μ g/mL)LLOQ ( μ g/mL)Recovery (%)R2
THDOC1.1323.4310.01099.21000.9996
THA1.0183.0860.010103.21000.9997
5 α THB1.1903.6060.01094.91000.9996
THB1.5054.5610.010112.06000.9993
Table 10. Slope and intercept parameters with 95% confidence intervals for glucocorticoids (GC-MS).
Table 10. Slope and intercept parameters with 95% confidence intervals for glucocorticoids (GC-MS).
AnalytesSlope (m)CIlow(m)CIhigh(m)Intercept (q)CIlow(q)CIhigh(q)
THS0.04690.04630.04740.05900.04600.0721
F0.07620.07340.07900.15320.09110.2152
THF0.00990.00900.01080.02770.00840.0469
5 α -THF0.03210.03030.03390.15340.11350.1932
β -Cortol0.04120.03960.04270.14010.10460.1757
α -Cortol0.02760.02690.02840.14680.12970.1638
20 α -DHF0.02420.02070.02760.20510.12750.2827
11 β -OHET0.03960.03780.04150.14080.09970.1819
THE0.01780.01670.01890.13040.10520.1556
α -Cortolone0.05400.05300.05510.03120.00690.0554
β -Cortolone0.01510.01430.01600.07690.05750.0962
11ketoET0.02890.02790.02990.11690.09340.1404
Table 11. LOD, LOQ, LLOQ, recovery, and R 2 for glucocorticoids (GC-MS).
Table 11. LOD, LOQ, LLOQ, recovery, and R 2 for glucocorticoids (GC-MS).
AnalytesLOD ( μ g/mL)LOQ ( μ g/mL)LLOQ ( μ g/mL)Recovery (%)R2
THS0.5131.5540.01096.60000.9999
F1.5004.5450.01090.97000.9993
THF3.57710.8390.010108.98000.9961
5 α -THF2.2856.9250.01091.16000.9984
β -Cortol1.5914.8220.01098.63000.9992
α -Cortol1.1373.4440.01090.24000.9996
20 α -DHF5.91917.9360.010114.88000.9895
11 β -OHET1.9125.7940.01099.50000.9989
THE2.6177.9300.01094.29000.9979
α -Cortolone0.8262.5030.01090.68000.9998
β -Cortolone2.3527.1260.010111.31000.9983
11ketoET1.5014.5490.01089.11000.9993
Table 12. Slope and intercept parameters with 95% confidence intervals for androgens (GC-MS).
Table 12. Slope and intercept parameters with 95% confidence intervals for androgens (GC-MS).
AnalytesSlope (m)CIlow(m)CIhigh(m)Intercept (q)CIlow(q)CIhigh(q)
DHEA0.03990.03900.04080.11950.10000.1389
16 α -OHDHEA0.03170.03060.03290.04350.01780.0692
D5-ADIOL0.07920.07700.08140.09160.04270.1405
D5-ATRIOL0.02860.02650.03060.14650.10080.1922
ET0.04770.04660.04880.0132−0.01140.0377
AN0.02480.02390.02570.08690.06670.1070
5 α -ADIOL0.00960.00910.01010.18740.17580.1990
11 β -OHAN0.05770.05260.06270.13630.02370.2489
Table 13. LOD, LOQ, LLOQ, recovery, and R 2 for androgens (GC-MS).
Table 13. LOD, LOQ, LLOQ, recovery, and R 2 for androgens (GC-MS).
AnalytesLOD ( μ g/mL)LOQ ( μ g/mL)LLOQ ( μ g/mL)Recovery (%)R2
DHEA0.8992.7240.01088.71000.9998
16 α -OHDHEA1.4914.5190.01089.64000.9993
D5-ADIOL1.1373.4470.010111.37000.9996
D5-ATRIOL2.9478.9300.010103.62000.9974
ET0.9482.8710.01097.80000.9997
AN1.4974.5360.010101.54000.9993
5 α -ADIOL2.2336.7660.01097.02000.9985
11 β -OHAN3.59910.9060.01090.56000.9961
Table 14. Slope and intercept parameters with 95% confidence intervals for estrogens (GC-MS).
Table 14. Slope and intercept parameters with 95% confidence intervals for estrogens (GC-MS).
AnalytesSlope (m)CIlow(m)CIhigh(m)Intercept (q)CIlow(q)CIhigh(q)
E30.06360.06190.06540.08070.04100.1204
E20.06070.05840.06300.0049−0.04630.0561
E10.06250.05700.06810.1231−0.00120.2474
Table 15. LOD, LOQ, LLOQ, recovery, and R 2 for estrogens (GC-MS).
Table 15. LOD, LOQ, LLOQ, recovery, and R 2 for estrogens (GC-MS).
AnalytesLOD ( μ g/mL)LOQ ( μ g/mL)LLOQ ( μ g/mL)Recovery (%)R2
E31.1493.4810.01099.10000.9996
E21.5554.7120.010101.66000.9993
E13.66211.0970.010114.51000.9960
Table 16. Repeatability (Rep.) and reproducibility (Repr.) expressed as CV% for urinary progestin metabolites. Analytes: Rep. = Repeatability; Repr. = Reproducibility; Tgt = target ion; Q1 and Q2 = qualifier ions.
Table 16. Repeatability (Rep.) and reproducibility (Repr.) expressed as CV% for urinary progestin metabolites. Analytes: Rep. = Repeatability; Repr. = Reproducibility; Tgt = target ion; Q1 and Q2 = qualifier ions.
AnalyteQC LevelRep. (%CV)Repr. (%CV)Tgt (m/z)Q1 (m/z)Q2 (m/z)
17HPHigh11.111.8476386364
17HPLow8.48.8476386364
17HPMedium9.710.7476386364
P2High10.211.0284346449
P2Low9.911.2284346449
P2Medium6.07.7284346449
PTHigh10.610.9433343253
PTLow8.510.2433343253
PTMedium7.58.1433343253
PTNEHigh4.76.2449269359
PTNELow7.27.9449269359
PTNEMedium5.67.3449269359
5PTHigh5.36.7372462267
5PTLow9.610.9372462267
5PTMedium6.88.6372462267
Table 17. Repeatability (Rep.) and reproducibility (Repr.) expressed as CV% for urinary mineralocorticoid metabolites. Analytes: Rep. = Repeatability; Repr. = Reproducibility; Tgt = target ion; Q1 and Q2 = qualifier ions.
Table 17. Repeatability (Rep.) and reproducibility (Repr.) expressed as CV% for urinary mineralocorticoid metabolites. Analytes: Rep. = Repeatability; Repr. = Reproducibility; Tgt = target ion; Q1 and Q2 = qualifier ions.
AnalyteQC LevelRep. (%CV)Repr. (%CV)Tgt (m/z)Q1 (m/z)Q2 (m/z)
5 α -THBHigh6.58.4564474384
5 α -THBLow10.410.7564474384
5 α -THBMedium10.411.1564474384
THAHigh8.19.0490400431
THALow7.18.1490400431
THAMedium7.28.7490400431
THDOCHigh11.112.5476188507
THDOCLow11.512.8476188507
THDOCMedium7.38.3476188507
THBHigh5.87.5474564384
THBLow5.67.2474564384
THBMedium10.411.0474564384
Table 18. Repeatability (Rep.) and reproducibility (Repr.) expressed as CV% for urinary glucocorticoid metabolites. Analytes: Rep. = Repeatability; Repr. = Reproducibility; Tgt = target ion; Q1 and Q2 = qualifier ions.
Table 18. Repeatability (Rep.) and reproducibility (Repr.) expressed as CV% for urinary glucocorticoid metabolites. Analytes: Rep. = Repeatability; Repr. = Reproducibility; Tgt = target ion; Q1 and Q2 = qualifier ions.
AnalyteQC LevelRep. (%CV)Repr. (%CV)Tgt (m/z)Q1 (m/z)Q2 (m/z)
11ketoETHigh10.612.3300261405
11ketoETLow5.06.6300261405
11ketoETMedium11.412.1300261405
11 β -OH-ETHigh7.98.3448268358
11 β -OH-ETLow7.59.2448268358
11 β -OH-ETMedium9.410.9448268358
20 α DIIDRO-FHigh7.68.6296243476
20 α DIIDRO-FLow6.78.5296243476
20 α DIIDRO-FMedium7.08.8296243476
5 α -TH-FHigh6.07.4652562472
5 α -TH-FLow5.55.8652562472
5 α -TH-FMedium6.56.9652562472
FHigh6.67.3605515361
FLow11.013.0605515361
FMedium4.95.3605515361
THSHigh9.610.5564474384
THSLow4.54.8564474384
THSMedium6.68.1564474384
TH-FHigh8.210.1652472562
TH-FLow9.410.8652472562
TH-FMedium7.38.8652472562
THEHigh9.711.6578609488
THELow8.910.8578609488
THEMedium10.411.5578609488
β CORTOLHigh10.610.9343243253
β CORTOLLow5.66.8343243253
β CORTOLMedium9.711.5343243253
β CORTOLONEHigh9.410.3449359269
β CORTOLONELow7.07.5449359269
β CORTOLONEMedium9.611.1449359269
α CORTOLHigh6.37.9343243253
α CORTOLLow10.411.3343243253
α CORTOLMedium9.911.9343243253
α CORTOLONEHigh6.67.2449359269
α CORTOLONELow11.412.9449359269
α CORTOLONEMedium9.311.1449359269
Table 19. Repeatability (Rep.) and reproducibility (Repr.) expressed as CV% for urinary estrogen metabolites. Analytes: Rep. = Repeatability; Repr. = Reproducibility; Tgt = target ion; Q1 and Q2 = qualifier ions.
Table 19. Repeatability (Rep.) and reproducibility (Repr.) expressed as CV% for urinary estrogen metabolites. Analytes: Rep. = Repeatability; Repr. = Reproducibility; Tgt = target ion; Q1 and Q2 = qualifier ions.
AnalyteQC LevelRep. (%CV)Repr. (%CV)Tgt (m/z)Q1 (m/z)Q2 (m/z)
17 β -ESTRADIOLOHigh5.77.4531441459
17 β -ESTRADIOLOLow6.48.3531441459
17 β -ESTRADIOLOMedium10.912.6531441459
E3High5.76.6504386311
E3Low4.65.5504386311
E3Medium9.39.9504386311
E1High8.18.8371340356
E1Low6.47.7371340356
E1Medium11.311.8371340356
Table 20. Repeatability (Rep.) and reproducibility (Repr.) expressed as CV% for urinary androgen metabolites. Analytes: Rep. = Repeatability; Repr. = Reproducibility; Tgt = target ion; Q1 and Q2 = qualifier ions.
Table 20. Repeatability (Rep.) and reproducibility (Repr.) expressed as CV% for urinary androgen metabolites. Analytes: Rep. = Repeatability; Repr. = Reproducibility; Tgt = target ion; Q1 and Q2 = qualifier ions.
AnalyteQC LevelRep. (%CV)Repr. (%CV)Tgt (m/z)Q1 (m/z)Q2 (m/z)
11 β -OH-ANHigh8.39.9360270213
11 β -OH-ANLow8.49.5360270213
11 β -OH-ANMedium6.67.8360270213
16 α -OH-DHEAHigh8.810.0446266356
16 α -OH-DHEALow5.46.8446266356
16 α -OH-DHEAMedium10.011.2446266356
5 α -ANDROSTANEDIOLHigh8.19.2421379241
5 α -ANDROSTANEDIOLLow5.96.9421379241
5 α -ANDROSTANEDIOLMedium9.911.7421379241
D5-ATRIOLHigh9.611.5432522417
D5-ATRIOLLow7.18.9432522417
D5-ATRIOLMedium8.69.4432522417
ANHigh7.28.7360270213
ANLow6.98.3360270213
ANMedium5.97.3360270213
D5-ADIOLHigh7.17.7344434239
D5-ADIOLLow10.611.2344434239
D5-ADIOLMedium10.912.5344434239
DHEAHigh10.711.3358389268
DHEALow5.25.9358389268
DHEAMedium11.012.3358389268
ETHigh10.311.2360270213
ETLow6.57.9360270213
ETMedium10.911.5360270213
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Chiara, F.; Allegra, S.; Liuzzi, S.; Puccinelli, M.P.; Mengozzi, G.; De Francia, S. Steroidomics via Gas Chromatography–Mass Spectrometry (GC-MS): A Comprehensive Analytical Approach for the Detection of Inborn Errors of Metabolism. Life 2025, 15, 829. https://doi.org/10.3390/life15060829

AMA Style

Chiara F, Allegra S, Liuzzi S, Puccinelli MP, Mengozzi G, De Francia S. Steroidomics via Gas Chromatography–Mass Spectrometry (GC-MS): A Comprehensive Analytical Approach for the Detection of Inborn Errors of Metabolism. Life. 2025; 15(6):829. https://doi.org/10.3390/life15060829

Chicago/Turabian Style

Chiara, Francesco, Sarah Allegra, Simona Liuzzi, Maria Paola Puccinelli, Giulio Mengozzi, and Silvia De Francia. 2025. "Steroidomics via Gas Chromatography–Mass Spectrometry (GC-MS): A Comprehensive Analytical Approach for the Detection of Inborn Errors of Metabolism" Life 15, no. 6: 829. https://doi.org/10.3390/life15060829

APA Style

Chiara, F., Allegra, S., Liuzzi, S., Puccinelli, M. P., Mengozzi, G., & De Francia, S. (2025). Steroidomics via Gas Chromatography–Mass Spectrometry (GC-MS): A Comprehensive Analytical Approach for the Detection of Inborn Errors of Metabolism. Life, 15(6), 829. https://doi.org/10.3390/life15060829

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