Non-invasive biochemical monitoring for congenital adrenal hyperplasia (CAH) using 24-hour urinary steroid profiles

Tonge oseph J; Irina Bacila; Lawrence Neil R; Ahmed S Faisal; Sabah Alvi; Cheetham Timothy D; Elizabeth Crowne; Urmi Das; Dattani Mehul T; Davies Justin H; Evelien Gevers; Brian Keevil; Krone Ruth E; Leena Patel; Tabitha Randell; Ryan Fiona J; Ajay Thankamony; Denham Scott G; Simpson Joanna P; Homer Natalie ZM; Krone Nils P

doi:10.1530/endoabs.111.P4

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Endocrine Abstracts (2025) 111 P4 | DOI: 10.1530/endoabs.111.P4

BSPED2025 Poster Presentations Adrenal 1 (10 abstracts)

Non-invasive biochemical monitoring for congenital adrenal hyperplasia (CAH) using 24-hour urinary steroid profiles

Joseph J Tonge ¹ , Irina Bacila ¹ , Neil R Lawrence ¹ , S Faisal Ahmed ² , Sabah Alvi ³ , Timothy D Cheetham ⁴ , Elizabeth Crowne ⁵ , Urmi Das ⁶ , Mehul T Dattani ⁷ , Justin H Davies ^8,9 , Evelien Gevers ^10,11 , Brian Keevil ¹² , Ruth E Krone ¹³ , Leena Patel ¹⁴ , Tabitha Randell ¹⁵ , Fiona J Ryan ¹⁶ , Ajay Thankamony ¹⁷ , Scott G Denham ¹⁸ , Joanna P Simpson ¹⁸ , Natalie ZM Homer ¹⁸ & Nils P Krone ¹

Author affiliations

¹Division of Clinical Medicine, School of Medicine and Population Health, University of Sheffield, Sheffield, United Kingdom; ²Developmental Endocrinology Research Group, University of Glasgow, Glasgow, United Kingdom; ³Leeds General Infirmary, Leeds, United Kingdom; ⁴Great North Children’s Hospital, University of Newcastle, Newcastle, United Kingdom; ⁵Bristol Royal Hospital for Children, University Hospitals Bristol Foundation Trust, Bristol, United Kingdom; ⁶Alder Hey Children’s Hospital, Liverpool, United Kingdom; ⁷Great Ormond Street Hospital, London, United Kingdom; ⁸University Hospital Southampton, Southampton, United Kingdom; ⁹University of Southampton, Southampton, United Kingdom; ¹⁰Centre for Endocrinology, William Harvey Research Institute, Queen Mary University London, London, United Kingdom; ¹¹London and Barts Health NHS Trust - The Royal London Hospital, London, United Kingdom; ¹²Department of Biochemistry, Manchester University NHS Foundation Trust, Manchester, United Kingdom; ¹³Birmingham Women’s & Children’s Hospital, Birmingham, United Kingdom; ¹⁴Paediatric Endocrine Service, Royal Manchester Children’s Hospital, Manchester University NHS Foundation Trust, Manchester, United Kingdom; ¹⁵Nottingham Children’s Hospital, Nottingham, United Kingdom; ¹⁶Oxford Children’s Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom; ¹⁷Department of Paediatrics, University of Cambridge, Cambridge, United Kingdom; ¹⁸Mass Spectrometry Core, Edinburgh Clinical Research Facility, Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, United Kingdom

Background: Monitoring disease control in congenital adrenal hyperplasia (CAH) using random serum 17-hydroxyprogesterone (17OHP) measurements is invasive and may not reflect overall daily adrenal steroid production. Urinary steroid profiling offers a non-invasive alternative that may better reflect cumulative steroid output. This study aimed to evaluate whether urinary steroid metabolites, quantified using a novel approach of liquid chromatography–high resolution mass-spectrometry (LC-HRMS), could predict serum 17OHP and identify the most informative urinary biomarkers of biochemical control.

Methods: Twenty-four-hour urine samples were collected from 92 children with CAH, due to 21-hydroxylase deficiency, across 13 UK centres and analysed at the University of Edinburgh using LC-HRMS. A panel of 15 urinary metabolites was measured, including tetrahydro-glucocorticoids, cortol/cortolone derivatives, androgen and 11-oxygenated androgen metabolites, and pregnane metabolites. Paired serum and salivary samples were collected post-morning glucocorticoid dose and analysed for 17OHP, cortisol, and cortisone using LC-MS. Missing data were addressed using multiple imputation using Amelia II package in R, applying expectation-maximisation with bootstrapping. Multivariate linear regression was used to evaluate model performance (R²).

Results: The cohort (49 female, 43 male) ranged from 8 to 18 years, with 95% receiving oral hydrocortisone 2–4 times daily. Mean daily hydrocortisone equivalent was 18.7 mg (SD 6.7), or 13.5 mg/m² (SD 3.8). A multivariable model including 15 urinary steroid metabolites and glucocorticoid dose explained 54.9% of the variance in serum 17OHP (R² = 0.55, P < 0.001). Salivary cortisol/cortisone, sex, age, and body surface area did not significantly improve model performance (p > 0.05). Two urinary metabolites were independently associated with serum 17OHP: androsterone (P = 0.033) and pregnanetriol (P = 0.005). Pearson’s correlation confirmed these associations: pregnanetriol showed a strong positive correlation with serum 17OHP (R² = 0.63, P < 0.001), and androsterone showed a moderate positive correlation (R² = 0.46, P < 0.001). The two metabolites were moderately correlated with each other (R² = 0.65), suggesting overlapping but distinct contributions.

Conclusions: Urinary steroid profiling, combined with glucocorticoid dose, predicts serum 17OHP with good accuracy. Androsterone and pregnanetriol emerged as key urinary biomarkers reflecting adrenal androgen and progesterone metabolism, supporting their potential utility in non-invasive disease monitoring.