Influence of sex and functional status on the value of serum steroid profiling in discriminating adrenocortical carcinoma from adrenocortical adenoma.

Background: It is challenging for clinicians to distinguish adrenocortical carcinoma (ACC) from benign adrenocortical adenomas (ACA) in their early stages. This study explored the value of serum steroid profiling as a complementary biomarker for malignancy diagnosis of ACC other than diameter and explored the influence of sex and functional status. Methods: In this retrospective study, a matched cohort of patients diagnosed with either ACC or ACA based on histopathology was meticulously paired in a 1:1 ratio according to sex, age, and functional status. Eight serum steroids including 11-deoxycortisol, 11-deoxycorticosterone, progesterone, androstenedione, dehydroepiandrosterone (DHEA), dehydroepiandrosterone sulfate (DHEAS), 17-hydroxyprogesterone, and estradiol, were quantified by liquid chromatography tandem mass spectrometry. We conducted a comparative analysis of the clinical characteristics and serum steroid profiles of patients with ACC and ACA, with further subgroup analysis. Results: The study included 31 patients with ACC and 31 matched patients with ACA. Patients with ACC exhibited significantly larger tumor diameters, lower body mass index (BMI), and higher levels of 11-deoxycortisol, progesterone, and androstenedione than those with ACA. 11-deoxycortisol was the only valuable index for discriminating ACC from ACA, regardless of functional status and sex. Progesterone, DHEA, and DHEAS levels were higher in the functional ACC group than in the non-functional ACC group. Female ACC patients, especially in postmenopausal female exhibited higher levels of androstenedione than male patients. The area under the curve of tumor diameter, 11-deoxycortisol, and BMI was 0.947 (95% CI 0.889-1.000), with a sensitivity of 96.8% and specificity of 90.3%. Conclusion: Serum steroid profiling serves as a helpful discriminative marker for ACC and ACA, with 11-deoxycortisol being the most valuable marker. For other steroid hormones, consideration of sex differences and functional status is crucial.

Gender-specific alteration of steroid metabolism and its impact on viral replication in a mouse model of hepatitis B virus infection.

Hepatitis B virus (HBV) is a sex-specific pathogen that is more severe in males than in females. Sex disparities in HBV infection have been attributed to hormonal differences between males and females. However, whether HBV infection affects the metabolic signatures of steroid hormones and how these influences viral replication remains unclear. In this study, we investigated whether HBV infection alters steroid metabolism and its effects on HBV replication. Serum samples from male and female mice obtained after the hydrodynamic injection of replication-competent HBV plasmids were subjected to quantitative steroid profiling. Serum steroid levels in mice were analyzed using an in vitro metabolism assay with the mouse liver S9 fraction. The alteration of steroids by HBV infection was observed only in male mice, particularly with significant changes in androgens, whereas no significant hormonal changes were observed in female mice. Among the altered steroids, dehydroepiandrosterone (DHEA) levels increased the most in male mice after HBV infection. An in vitro metabolism assay revealed that androgen levels were significantly reduced in HBV-infected male mice. Furthermore, the genes involved in DHEA biosynthesis were significantly upregulated in HBV-infected male mice. Interestingly, reduced dihydrotestosterone in male mice significantly inhibits viral replication by suppressing HBV promoter activity, suggesting a viral strategy to overcome the antiviral effects of steroid hormones in males. Our data demonstrated that HBV infection can cause sex-specific changes in steroid metabolism.

A Very Early Diagnosis of Complete Androgen Insensitivity Syndrome Due to a Novel Variant in the AR Gene: A Neonatal Case Study.

Androgen insensitivity syndrome (AIS) is one of the most common Disorders of Sexual Differentiation (DSDs). AIS is characterized by an X-linked recessive inheritance pattern associated with variants in the androgen receptor (AR) gene that affects the masculinization process in individuals with XY karyotype. Here, we report a neonatal case of a very early diagnosis of complete AIS due to a novel variant in the AR gene. In the present case, after the clinical evaluation, the infant has undergone the following tests: biochemical analyses, including newborn screening workflow, karyotype analysis, and Next-Generation Sequencing (NGS) panel of 50 genes involved in DSDs. The NGS analysis identified a missense variant, c.2108C>A, in the AR gene. According to a cytogenetic analysis, the patient presented a 46, XY karyotype, thus the resulting hemizygote for the AR gene variant. The variant is not currently described in the literature nor in the ClinVar database. However, according to computational models, the variant could have a pathogenetic effect. This clinical case reveals a novel variant of the AR gene with a possible pathogenetic effect associated with AIS and highlights the importance of a multidisciplinary approach for the timely diagnosis and appropriate follow-up of the patient.

A novel ultra-high-performance supercritical fluid chromatography hyphenated to tandem mass spectrometry method for the analysis of urinary endogenous steroids in the anti-doping context.

The first step in the detection of testosterone (T) doping is to measure the urinary steroid profile for the athlete biological passport (ABP). To harmonise the analysis between anti-doping laboratories, urinary steroid profiling is parametrised in deep detail and shall be performed by gas chromatography hyphenated to mass spectrometry (GC-MS). However, due to its requirement for extensive sample preparation, alternatives to GC-MS are being actively pursued. The aim of this study was the evaluation of Ultra-High-Performance Supercritical Fluid Chromatography hyphenated to tandem Mass Spectrometry (UHPSFC-MS/MS) as an alternative for the quantification of endogenous urinary steroids. In this context, we developed a high throughput sample extraction method, followed by a novel UHPSFC-MS/MS method for the analysis of 10 endogenous urinary steroids which are relevant for doping control analysis. Depending on the steroid, the herein presented method is capable of quantification from 0.5 ng/mL up to 10 µg/mL. After validation, the applicability of the method was evaluated by analysing 132 authentic urine samples, which demonstrated results similar to classical GC-MS analysis. Steroid concentrations determined by UHPSFC-MS/MS were slightly overestimated in comparison with GC-MS, but the ratios had <10 % difference between the two methods. As the ABP considers the steroid ratios for passport evaluation, the herein presented method could be used for steroid profiling without reducing the sensitivity of the ABP. Thus, we would propose to consider UHPSFC-MS/MS as an alternative to GC-MS after more tests would have been performed to support our findings. Furthermore, we have also investigated the potential of this technology for sample purification prior to Isotope Ratio Mass Spectrometry (IRMS) for the differentiation between exogenous and endogenous origin of T and its metabolites. While the achieved separation was sufficient to purify urine samples for IRMS analysis in our proof-of-concept study, the instrumental parameters should be further refined for future use.

A practical approach to supported liquid extraction and measurement of 18 steroids in plasma and serum by targeted liquid chromatography tandem mass spectrometry.

Chromatography combined with mass spectrometry is a gold standard technique for steroid measurement, however the type of sample preparation, the dynamic range and reliability of the calibration curve, the chromatographic separation and mass spectrometry settings ultimately determine the success of the method. The steroid biosynthetic pathway is conserved in higher mammals and literature demonstrates that the concentration ranges of different steroid groups are relatively comparable across species. We sought to develop a robust and reliable multi steroid targeted analysis method for blood that would have wide application across higher mammals. The method was developed following bioanalytical method validation guidelines to standards typically applied to human clinical studies, including isotopically labelled internal standards where at all possible. Here we describe the practical approach to a 96-well supported liquid extraction (SLE) method of extraction from plasma (200 µL) using an Extrahera liquid handling robot (Biotage, Sweden), including quality control samples, followed by a comprehensive separation and targeted LC-MS/MS analysis of 18 steroids in plasma (pregnenolone, progesterone, 17α-hydroxyprogesterone, 11-deoxycorticosterone, corticosterone, 11-dehydrocorticosterone, aldosterone, 11-deoxycortisol, 21-deoxycortisol, cortisol, cortisone, androstenedione, testosterone, 5α-dihydrotestosterone, dehydroepiandrosterone, estrone, 17ß-estradiol and estriol). •SLE in a 96-well format of up to 74 biological plasma samples, enriched with multiple isotopically labelled internal standards, a 12-point aqueous calibration curve, and 6 serum quality controls, designed to monitor long-term performance of the method•Chromatographic separation of multiple steroids along the gradient, with ammonium fluoride mobile phase additive to improve sensitivity, followed by electrospray ionisation and constant polarity switching•Aqueous calibration standards that cover physiologically relevant ranges - high nanomolar glucocorticoids, low nanomolar androgens and picomolar ranges for estrogens and steroid intermediates.

Plasma Steroid Profiling Combined With Machine Learning for the Differential Diagnosis in Mild Autonomous Cortisol Secretion From Nonfunctioning Adenoma in Patients With Adrenal Incidentalomas.

OBJECTIVE: To assess the diagnostic value of combining plasma steroid profiling with machine learning (ML) in differentiating between mild autonomous cortisol secretion (MACS) and nonfunctioning adenoma (NFA) in patients with adrenal incidentalomas. METHODS: The plasma steroid profiles data in the laboratory information system were screened from January 2021 to December 2023. EXtreme Gradient Boosting was applied to establish diagnostic models using plasma 24-steroid panels and/or clinical characteristics of the subjects. The SHapley Additive exPlanation (SHAP) method was used for explaining the model. RESULTS: Seventy-six patients with MACS and 86 patients with NFA were included in the development and internal validation cohort while the external validation cohort consisted of 27 MACS and 21 NFA cases. Among 5 ML models evaluated, eXtreme Gradient Boosting demonstrated superior performance with an area under the curve of 0.77 using 24 steroid hormones. The SHAP method identified 5 steroids that exhibited optimal performance in distinguishing MACS from NFA, namely dehydroepiandrosterone, 11-deoxycortisol, 11ß-hydroxytestosterone, testosterone, and dehydroepiandrosteronesulfate. Upon incorporating clinical features into the model, the area under the curve increased to 0.88, with a sensitivity of 0.77 and specificity of 0.82. Furthermore, the results obtained through SHAP revealed that lower levels of testosterone, dehydroepiandrosterone, low-density lipoprotein cholesterol, body mass index, and adrenocorticotropic hormone along with higher level of 11-deoxycortisol significantly contributed to the identification of MACS in the model. CONCLUSIONS: We have elucidated the utilization of ML-based steroid profiling to discriminate between MACS and NFA in patients with adrenal incidentalomas. This approach holds promise for distinguishing these 2 entities through a single blood collection.

Steroid profiling in adrenal disease.

The measurement of steroid hormones in blood and urine, which reflects steroid biosynthesis and metabolism, has been recognized as a valuable tool for identifying and distinguishing steroidogenic disorders. The application of mass spectrometry enables the reliable and simultaneous analysis of large panels of steroids, ushering in a new era for diagnosing adrenal diseases. However, the interpretation of complex hormone results necessitates the expertise and experience of skilled clinicians. In this scenario, machine learning techniques are gaining worldwide attention within healthcare fields. The clinical values of combining mass spectrometry-based steroid profiles analysis with machine learning models, also known as steroid metabolomics, have been investigated for identifying and discriminating adrenal disorders such as adrenocortical carcinomas, adrenocortical adenomas, and congenital adrenal hyperplasia. This promising approach is expected to lead to enhanced clinical decision-making in the field of adrenal diseases. This review will focus on the clinical performances of steroid profiling, which is measured using mass spectrometry and analyzed by machine learning techniques, in the realm of decision-making for adrenal diseases.

Delineating endogenous Cushing's syndrome by GC-MS urinary steroid metabotyping.

BACKGROUND: Diagnosing Cushing's syndrome (CS) is highly complex. As the diagnostic potential of urinary steroid metabolome analysis by gas chromatography-mass spectrometry (GC-MS) in combination with systems biology has not yet been fully exploited, we studied a large cohort of patients with CS. METHODS: We quantified daily urinary excretion rates of 36 steroid hormone metabolites. Applying cluster analysis, we investigated a control group and 168 patients: 44 with Cushing's disease (CD) (70% female), 18 with unilateral cortisol-producing adrenal adenoma (83% female), 13 with primary bilateral macronodular adrenal hyperplasia (PBMAH) (77% female), and 93 ruled-out CS (73% female). FINDINGS: Cluster-Analysis delineated five urinary steroid metabotypes in CS. Metabotypes 1, 2 and 3 revealing average levels of cortisol and adrenal androgen metabolites included patients with exclusion of CS or and healthy controls. Metabotype 4 reflecting moderately elevated cortisol metabolites but decreased DHEA metabolites characterized the patients with unilateral adrenal CS and PBMAH. Metabotype 5 showing strong increases both in cortisol and DHEA metabolites, as well as overloaded enzymes of cortisol inactivation, was characteristic of CD patients. 11-oxygenated androgens were elevated in all patients with CS. The biomarkers THS, F, THF/THE, and (An + Et)/(11ß-OH-An + 11ß-OH-Et) correctly classified 97% of patients with CS and 95% of those without CS. An inverse relationship between 11-deoxygenated and 11-oxygenated androgens was typical for the ACTH independent (adrenal) forms of CS with an accuracy of 95%. INTERPRETATION: GC-MS based urinary steroid metabotyping allows excellent identification of patients with endogenous CS and differentiation of its subtypes. FUNDING: The study was funded by the Else Kröner-Fresenius-Stiftung and the Eva-Luise-und-Horst-Köhler-Stiftung.

The use of liquid chromatography-tandem mass spectrometry in newborn screening for congenital adrenal hyperplasia: improvements and future perspectives.

Newborn screening for congenital adrenal hyperplasia using 17-hydroxyprogesterone by immunoassay remains controversial despite screening been available for almost 40 years. Screening is confounded by poor immunoassay specificity, fetal adrenal physiology, stress, and illness which can result in a large number of false positive screening tests. Screening programmes apply higher screening thresholds based on co-variates such as birthweight or gestational age but the false positive rate using immunoassay remains high. Mass spectrometry was first applied to newborn screening for congenital adrenal hyperplasia over 15 years ago. Elevated 17-hydroxprogesterone by immunoassay can be retested with a specific liquid chromatography tandem mass spectrometry assay that may include additional steroid markers. Laboratories register with quality assurance programme providers to ensure accurate steroid measurements. This has led to improvements in screening but there are additional costs and added laboratory workload. The search for novel steroid markers may inform further improvements to screening. Studies have shown that 11-oxygenated androgens are elevated in untreated patients and that the adrenal steroidogenesis backdoor pathway is more active in babies with congenital adrenal hyperplasia. There is continual interest in 21-deoxycortisol, a specific marker of 21-hydroxylase deficiency. The measurement of androgenic steroids and their precursors by liquid chromatography tandem mass spectrometry in bloodspots may inform improvements for screening, diagnosis, and treatment monitoring. In this review, we describe how liquid chromatography tandem mass spectrometry has improved newborn screening for congenital adrenal hyperplasia and explore how future developments may inform further improvements to screening and diagnosis.

Serum steroid metabolite profiling by LC-MS/MS in two phenotypic male patients with HSD17B3 deficiency: Implications for hormonal diagnosis.

Although 17ß-hydroxysteroid dehydrogenase type 3 (HSD17B3) deficiency is diagnosed when a testosterone/androstenedione (T/A-dione) ratio after human chorionic gonadotropin (hCG) stimulation is below 0.8, this cut-off value is primarily based on hormonal data measured by conventional immunoassay (IA) in patients with feminized or ambiguous genitalia. We examined two 46,XY Japanese patients with undermasculinized genitalia including hypospadias (patient 1 and patient 2). Endocrine studies by IA showed well increased serum T value after hCG stimulation (2.91 ng/mL) and a high T/A-dione ratio (4.04) in patient 1 at 2 weeks of age and sufficiently elevated basal serum T value (2.60 ng/mL) in patient 2 at 1.5 months of age. Despite such partial androgen insensitivity syndrome-like findings, whole exome sequencing identified biallelic ″pathogenic″ or ″likely pathogenic″ variants in HSD17B3 (c .188 C>T:p.(Ala63Val) and c .194 C>T:p.(Ser65Leu) in patient 1, and c.139 A>G:p.(Met47Val) and c.672 + 1 G>A in patient 2) (NM_000197.2), and functional analysis revealed reduced HSD17B3 activities of the missense variants (∼ 43% for p.Met47Val, ∼ 14% for p.Ala63Val, and ∼ 0% for p.Ser65Leu). Thus, we investigated hCG-stimulated serum steroid metabolite profiles by liquid chromatography-tandem mass spectrometry (LC-MS/MS) in patient 1 at 7 months of age and in patient 2 at 11 months of age as well as in five control males with idiopathic micropenis aged 1 - 8 years, and found markedly high T/A-dione ratios (12.3 in patient 1 and 5.4 in patient 2) which were, however, obviously lower than those in the control boys (25.3 - 56.1) and sufficiently increased T values comparable to those of control males. The elevated T/A-dione ratios are considered be due to the residual HSD17B3 function and the measurement by LC-MS/MS. Thus, it is recommended to establish the cut-off value for the T/A-dione ratio according to the phenotypic sex reflecting the residual function and the measurement method.

Serum steroid profile captures metabolic phenotypes in adults with classic congenital adrenal hyperplasia.

OBJECTIVES: Adult patients with classic congenital adrenal hyperplasia (CAH) due to 21-hydroxylase deficiency have an increased risk of metabolic diseases. We aimed to investigate whether liquid chromatography-mass spectrometry (LC-MS)-based serum steroid profiling reveals metabolic phenotypes in adults with classic CAH. DESIGN AND METHODS: This study prospectively enrolled 63 adult patients with CAH and 38 healthy volunteers. The levels of the 24 steroids were quantified in the morning serum using LC-MS. Unsupervised clustering algorithms were applied to the serum steroid profiles to identify unique patterns associated with metabolic syndrome. RESULTS: Serum steroid profiles of patients with CAH were clearly delineated from those of healthy controls with a higher degree of interindividual heterogeneity. The unsupervised clustering algorithm divided CAH patients into two clusters based on serum steroid profile. Cluster 2 showed higher serum levels of glucocorticoids and androgens than cluster 1. The prevalence of metabolic syndrome was significantly higher in cluster 2 than in cluster 1 (37.8 % vs. 5.6 %, P = 0.011). Other clinical characteristics, including age, sex, body mass index, CAH subtypes, and glucocorticoid dose, did not differ between the two clusters. The multivariate logistic regression model of selective 15 steroids could discriminate metabolic syndrome in patients with CAH with an area under the receiver operating characteristic curve of 0.832 (95 % confidence interval:0.732-0.933). CONCLUSIONS: Serum steroid profiles can be valuable biomarkers for estimating metabolic risk in adult patients with CAH.

Pilot study shows suppression of mineralocorticoid precursors under high-dose glucocorticoid therapy in pediatric acute lymphoblastic leukemia.

Glucocorticoids represent a key element in the treatment of pediatric acute lymphoblastic leukemia (ALL) and lead to adrenal suppression. We aimed to assess the differential response profile of adrenal steroids in children with ALL during BFM (Berlin-Frankfurt-Münster) induction treatment. Therefore, we performed liquid chromatography tandem-mass spectrometry (LC-MS/MS)-based steroid profiling of up to seven consecutive leftover morning serum samples derived from 11 patients (pts) with ALL before (day 0) and during induction therapy at days 1-5, 6-12, 13-26, 27-29, 30-35 and 36-40. 17-hydroxyprogesterone (17OHP), 11-deoxycortisol (11S), cortisol, 11-deoxycorticosterone (DOC), corticosterone and aldosterone were determined in parallel. Subsequently, steroid concentrations were normalized by multiples of median (MOM) to adequately consider pediatric age- and sex-specific reference ranges. MOM-cortisol and its precursors MOM-11S and MOM-17OHP were significantly suppressed by glucocorticoid treatment until day 29 (P < 8.06 × 10-10, P < 5.102 × 10-5, P < 0.0076, respectively). Cortisol recovered in one of four pts at days 27-29 and in two of five pts at days 36-40. Among the mineralocorticoids, corticosterone was significantly suppressed (P < 3.115 × 10-6). Aldosterone and DOC showed no significant changes when comparing day 0 to the treatment time points. However, two ALL patients with ICU treatment due to the sepsis showed significantly lower MOM-DOC (P = 0.006436) during that time and almost always the lowest aldosterone compared to all other time points. Suppression of mineralocorticoid precursors under high-dose glucocorticoid therapy suggests a functional cross talk of central glucocorticoid regulation and adrenal mineralocorticoid synthesis. Our data should stimulate prospective investigation to assess potential clinical relevance.

Extended steroid profiling in H295R cells provides deeper insight into chemical-induced disturbances of steroidogenesis: Exemplified by prochloraz and anabolic steroids.

Human adrenocortical H295R cells have been validated by the OECD Test Guideline 456 to detect chemicals disrupting testosterone and 17ß-estradiol (estradiol) biosynthesis. This study evaluated a novel approach to detect disturbances of steroidogenesis in H295R cells, exemplified by prochloraz and five anabolic steroids. Steroid profiles were assessed by an untargeted LC-MS-based method, providing a relative quantification of 57 steroids annotated according to their accurate masses and retention times. Such a panel of steroids included several mineralocorticoids, glucocorticoids, progestins and adrenal androgens. The coverage of a high number of metabolites in this extended steroid profiling facilitated grouping of chemicals with similar effects and detecting subtler differences between chemicals. It allowed, for example, distinguishing between the effects of turinabol and oxymetholone, supposed to act similarly in a previous characterization including only nine adrenal steroids. Furthermore, the results revealed that product/substrate ratios can provide superior information on altered enzyme activities compared to individual metabolite levels. For example, the 17α-hydroxypregnenolone/pregnenolone ratio was found to be a more sensitive marker for detecting 17α-hydroxylase inhibition by prochloraz than the corresponding individual steroids. These results illustrate that chemical grouping and calculation of product/substrate ratios can provide valuable information on mode-of-action and help prioritizing further experimental work.

Steroid profiling for the diagnosis of congenital adrenal hyperplasia by microbore ultra-performance liquid chromatography-tandem mass spectrometry.

BACKGROUND: A rapid and accurate measurement approach for 17α-hydroxyprogesterone (17-OHP) and related steroids in amount/volume-limited clinic samples is of importance for precise newborn diagnosis of congenital adrenal hyperplasia (CAH) and its subtypes in clinic. METHODS: Sixteen steroids (17-OHP, androstenedione, cortisol, tetrahydro-11-deoxycortisol, pregnenolone, progesterone, 11-deoxycorticosterone, corticosterone, 21-deoxycortisol, 11-deoxycortisol, dehydroepiandrosterone, testosterone, aldosterone, 17α-hydroxypregnenolone, dihydrotestosterone and 18-hydroxycorticosterone) were included in the panel of high-throughput microbore ultra-performance liquid chromatography-tandem mass spectrometry. Samples were collected from 126 normal subjects and 65 patients including different subtypes of CAH. RESULTS: The method was validated with satisfactory analytical performance in linearity, repeatability, recovery and limit of detection. Reference intervals for 16 steroids were established by quantifying the level of steroids detected in normal infants. The applicability of the method was tested by differentiating steroid metabolic characteristics between normal infants and infants with CAH, as well as between infants with different CAH subtypes. The relevance of 17-OHP, 21-deoxycortisol, and 17-OHP/11-deoxycortisol for 21-hydroxylase deficiency screening was demonstrated. The level of 11-deoxycorticosterone, 11-deoxycortisol, progesterone and androstenedione can be used for the diagnosis of different rare subtypes of CAH. CONCLUSION: This study provides a strategy for highly efficient steroid analysis of amount/volume-limited clinic samples and holds great potential for clinical diagnosis of CAH.

Simplified urinary steroid profiling by LC-MS as diagnostic tool for malignancy in adrenocortical tumors.

OBJECTIVES: Preoperative identification of malignant adrenal tumors is challenging. 24-h urinary steroid profiling by LC-MS/MS and machine learning has demonstrated high diagnostic power, but the unavailability of bioinformatic models for public use has limited its routine application. We here aimed to increase usability with a novel classification model for the differentiation of adrenocortical adenoma (ACA) and adrenocortical carcinoma (ACC). METHODS: Eleven steroids (5-pregnenetriol, dehydroepiandrosterone, cortisone, cortisol, α-cortolone, tetrahydro-11-deoxycortisol, etiocholanolone, pregnenolone, pregnanetriol, pregnanediol, and 5-pregnenediol) were quantified by LC-MS/MS in 24-h urine samples from 352 patients with adrenal tumor (281 ACA, 71 ACC). Random forest modelling and decision tree algorithms were applied in training (n = 188) and test sets (n = 80) and independently validated in 84 patients with paired 24-h and spot urine. RESULTS: After examining different models, a decision tree using excretions of only 5-pregnenetriol and tetrahydro-11-deoxycortisol classified three groups with low, intermediate, and high risk for malignancy. 148/217 ACA were classified as being at low, 67 intermediate, and 2 high risk of malignancy. Conversely, none of the ACC demonstrated a low-risk profile leading to a negative predictive value of 100% for malignancy. In the independent validation cohort, the negative predictive value was again 100% in both 24-h urine and spot urine with a positive predictive value of 87.5% and 86.7%, respectively. CONCLUSIONS: This simplified LC-MS/MS-based classification model using 24-h-urine provided excellent results for exclusion of ACC and can help to avoid unnecessary surgeries. Analysis of spot urine led to similarly satisfactory results suggesting that cumbersome 24-h urine collection might be dispensable after future validation.

Semi-automated serum steroid profiling with tandem mass spectrometry.

Objectives: Highly selective and sensitive multi-analyte methods for the analysis of steroids are attractive for the diagnosis of endocrine diseases. Commercially available kits are increasingly used for this purpose. These methods involve laborious solid phase extraction, and the respective panels of target analytes are incomplete. We wanted to investigate whether an improvement of kit solutions is possible by introducing automated on-line solid phase extraction (SPE) and combining originally separate analyte panels. Methods: Sample preparation was performed using automated on-line SPE on a high-pressure stable extraction column. Chromatographic separation, including isobaric compounds, was achieved using a 0.25 mM ammonium fluoride-methanol gradient on a small particle size biphenyl column. Standard compounds and internal standard mixtures of two panels of a commercially available kit were combined to achieve an optimized and straightforward detection of 15 endogenous steroids. Validation was performed according to the European Medicines Agency (EMA) guidelines with slight modifications. Results: Validation was successfully performed for all steroids over a clinically relevant calibration range. Deviations of intra- and inter-assay accuracy and precision results passed the criteria and no relevant matrix effects were detected due to highly effective sample preparation. External quality assessment samples showed the applicability as a routine diagnostic method, which was affirmed by the analyses of anonymized clinical samples. Conclusions: It was found possible to complement a commercially available kit for quantitative serum steroid profiling based on isotope dilution LC-MS/MS by implementing automated on-line SPE, thereby improving the practicality and robustness of the measurement procedure.

Comparison of three different blood matrices for the quantification of endogenous steroids using UHPLC-MS/MS.

Urine is currently the matrix of choice for the detection of exogenous substances but also for the application of the steroidal module of the Athlete Biological Passport (ABP) consisting in a longitudinal monitoring of steroid biomarkers. To fill the limitations related to urine, the longitudinal monitoring of serum steroids concentration in the so-called 'blood steroid profile' has recently been proposed. Although serum samples are collected much less than urine samples, plasma derived from ABP whole blood samples used for the full blood count could be exploited for the quantification of endogenous steroids. Alternatively, dried blood spots (DBS) that are much easier to collect could also serve as matrix for the steroid profile. In this study, we compared the concentration levels of several endogenous steroids measured in three different blood matrices (serum, plasma and DBS) collected from 100 elite athletes participating in the 2019 Doha World Athletics Championships using UHPLC-MS/MS. Plasma and serum samples were collected by venipuncture, whereas DBS were generated from whole blood samples. Although steroids demonstrated a good agreement between the three matrices, a slight but acceptable underestimation (10%-20%) was observed in plasma compared with serum. The difference between DBS and the two other matrices was dependent of the bias between serum and plasma. We also showed that a generic HCT correction for DBS could be a valuable approach for quantitative measurements. This study demonstrates the possibility to use three different matrices for the quantification of endogenous steroids although the slight discrepancies should be considered for longitudinal evaluation.

A comprehensive UHPLC-MS/MS method for the analysis of endogenous and exogenous steroids in serum for anti-doping purposes.

In the context of steroid analyses, the use of blood could represent a valuable complement to urine. While the blood steroid profile is currently being established to aid unveiling testosterone (T) doping, this matrix is also well suited for detection of exogenous anabolic steroids and steroid esters. In this study, a method to determine a simplified blood steroid profile in combination with the direct detection of exogenous anabolic steroids and steroid esters using just one serum aliquot was developed to obtain a comprehensive analytical workflow. Following the first chromatographic analysis of endogenous and exogenous steroids, samples were derivatised with Girard's reagent T (GT) to improve the ionisation of steroid esters and re-injected. The quantitative performance for T, androstenedione (A4) and 5α-dihydrotestosterone (DHT) was evaluated and the method was validated for qualitative analysis of exogenous analogues with estimated limits of detection (LOD) between 50 and 500 pg/ml. To demonstrate the applicability of the method, samples collected from a clinical study with an oral administration of testosterone undecanoate (TU) to 19 male volunteers were then analysed. The individual serum steroid profiles with the endogenous markers T, A4 and DHT were established as well as the concentrations of TU. TU was detected in all 19 volunteers up to 24 h, while DHT represented the most promising biomarker in endogenous steroid profile for the detection of oral TU administration. These results showed that the selected approach to combine exogenous and endogenous steroid analysis has the potential to strengthen T doping detection in the future.

Targeted metabolic profiling of urinary steroids with a focus on analytical accuracy and sample stability.

Introduction: Preoperative diagnostic workup of adrenal tumors is based on imaging and hormone analyses, but charged with uncertainties. Steroid profiling by liquid chromatography tandem mass spectrometry (LC-MS/MS) in 24-h urine has shown potential to discriminate benign and malignant adrenal tumors. Our aim was to develop and validate a specific and accurate LC-MS/MS method for the quantification of deconjugated urinary marker steroids, to evaluate their pre-analytical stability and to apply the method to clinical samples of patients with adrenal tumors. Methods: A method for the quantification of 11 deconjugated steroids (5-pregnenetriol, dehydroepiandrosterone, cortisone, cortisol, α-cortolone, tetrahydro-11-deoxycortisol, etiocholanolone, pregnenolone, pregnanetriol, pregnanediol, and 5-pregnenediol) in human urine was developed and validated based on international guidelines. Steroids were enzymatically deconjugated and extracted by solid phase extraction before LC-MS/MS quantification in positive electrospray ionization mode. Results: Excellent linearity with R2 > 0.99 and intra- and inter-day precisions of < 10.1 % were found. Relative matrix effects were between 96.4 % and 101.6 % and relative recovery was between 98.2 % and 115.0 %. Sufficient pre-freeze stability for all steroids in urine was found at 20-25 °C for seven days and at 4-6 °C for up to 28 days. Samples were stable during long-term storage at -20 °C and -80 °C for 6 months. Conclusions: A sensitive and robust LC-MS/MS method for the quantification of 11 urinary steroids was developed and validated according to international guidelines. Pre-analytical matrix stability was evaluated and the suitability of the method for the analysis of clinical samples and prospective validation studies was shown.

Isoflurane stress induces region-specific glucocorticoid levels in neonatal mouse brain.

The profound programming effects of early life stress (ELS) on brain and behavior are thought to be primarily mediated by adrenal glucocorticoids (GCs). However, in mice, stressors are often administered between postnatal days 2 and 12 (PND2-12), during the stress hyporesponsive period (SHRP), when adrenal GC production is greatly reduced at baseline and in response to stressors. During the SHRP, specific brain regions produce GCs at baseline, but it is unknown if brain GC production increases in response to stressors. We treated mice at PND1 (pre-SHRP), PND5 (SHRP), PND9 (SHRP), and PND13 (post-SHRP) with an acute stressor (isoflurane anesthesia), vehicle control (oxygen), or neither (baseline). We measured a panel of progesterone and six GCs in the blood, hippocampus, cerebral cortex, and hypothalamus via liquid chromatography tandem mass spectrometry. At PND1, baseline corticosterone levels were high and did not increase in response to stress. At PND5, baseline corticosterone levels were very low, increases in brain corticosterone levels were greater than the increase in blood corticosterone levels, and stress had region-specific effects. At PND9, baseline corticosterone levels were low and increased similarly and moderately in response to stress. At PND13, blood corticosterone levels were higher than those at PND9, and corticosterone levels were higher in blood than in brain regions. These data illustrate the rapid and profound changes in stress physiology during neonatal development and suggest that neurosteroid production is a possible mechanism by which ELS has enduring effects on brain and behavior.