Background: Treatment of children with classic congenital adrenal hyperplasia (CAH) is a difficult balance between hypercortisolism and hyperandrogenism. Biochemical monitoring of treatment is not well defined.
Objective: Retrospective software-assisted analysis of urinary steroid metabolome analysis obtained by gas chromatography-mass spectrometry (GC-MS) for treatment monitoring of children with CAH.
Methods: We evaluated 24-hour urinary steroid metabolome analyses of 63 prepubertal children aged 6.9 ± 1.5 years with classic CAH due to 21-hydroxylase deficiency treated with hydrocortisone (HC) and fludrocortisone. We divided the subjects into five distinctive groups by k-means clustering using MetaboAnalyst 3.0 software. Steroidal fingerprints and clinical data of patients in each cluster were analyzed.
Results: Five unique clusters were generated by invoking the k-means clustering algorithm. Cluster #1 (N=5 (8%)) showed over-treatment consisting of a combination of high urinary cortisol metabolites and low metabolites of androgens and 17-hydroxyprogesterone (17OHP). Cluster #2 (N=18 (29%)) revealed good disease control due to moderate cortisol metabolites and suppressed androgen and 17-hydroxyprogesterone (17OHP) metabolites. Cluster #3 (N=15; 24%) demonstrated under-treatment through a combination of low cortisol metabolites and very high metabolites of androgens and 17OHP. Cluster #4 (N=6 (10%)) and cluster #5 (N=19 (30%) both revealed differently kinds of treatment failures. Cluster #4 revealed unsuppressed very high androgen- and 17OHP metabolites despite appropriate urinary cortisol metabolites. In cluster #5, metabolites of androgens and 17OHP were moderately elevated although cortisol metabolites were markedly increased.
Conclusion: Software-assisted analysis of urinary metabolomes helps to monitor treatment of children with CAH. This method allows classification in under-, over-, and adequate-treated children as well as in patients with treatment failure.
19 - 21 Sep 2019
European Society for Paediatric Endocrinology