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, 17β-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.

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, 11β-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.

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.

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).
RESULTS: 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)/(11β-OH-An + 11β-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%.
CONCLUSIONS: GC-MS based urinary steroid metabotyping allows excellent identification of patients with endogenous CS and differentiation of its subtypes.
BACKGROUND: The study was funded by the Else Kröner-Fresenius-Stiftung and the Eva-Luise-und-Horst-Köhler-Stiftung.

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.

Although 17β-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.

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.
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.
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).
Serum steroid profiles can be valuable biomarkers for estimating metabolic risk in adult patients with CAH.

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.

Human adrenocortical H295R cells have been validated by the OECD Test Guideline 456 to detect chemicals disrupting testosterone and 17β-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.

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.
CONCLUSIONS: 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.