Deciphering aldosterone deficiency and pseudodeficiency in infancy by targeted GC-MS urinary steroid metabotyping

Disorders of isolated deficient aldosterone action involve insufficient production of aldosterone caused by aldosterone synthase deficiency (ASD) type I or type II (formerly named corticosterone methyl oxidase (CMO) deficiency type I or type II), as well as pseudohypoaldosteronism (PHA) featuring end-organ hormone resistance. Aldosterone is a key regulator of sodium-potassium homeostasis and blood pressure. Deficient action is characterized by arterial hypotension, hyponatremia, hyperkalemia, and dehydration. We investigated whether gas chromatographic-mass spectrometry (GC-MS) urinary steroid metabolome analysis allows for delineation of these entities. 44 urinary steroid metabolites from spot urine (µg/L) were quantified by targeted GC-MS from 124 infants with aldosterone deficient states and 138 matched controls. Relative enzymatic activities were calculated from precursor-to-product metabolite ratios. Decision tree analysis identified tetrahydroaldosterone (TH-aldo), tetrahydro-11-dehydro-corticosterone (6α-OH-THA), and 18-hydroxy-tetrahydro-11-dehydro-corticosterone (18-OH-THA) as sequential biomarkers distinguishing controls, PHA, ASD I and ASD II, with high specificity (94%) and sensitivities (97%, 92%, and 73%), respectively. PHA showed grossly elevated metabolites of aldosterone and its precursors. With respect to precursor-to-product metabolite ratios characterizing relative enzyme activities, the ratio for aldosterone synthase activity discriminated best between PHA and both ASD groups, whereas the ratios for 18-hydroxylase activity and 18-oxidase activity differentiated ASD I from ASD II. Targeted GC-MS urinary steroid metabotyping from spot urine provides a non-invasive and highly reliable new diagnostic tool for delineating aldosterone deficient states in infants. Various metabolites and metabolite ratios effectively discerned controls, patients with ASD subtypes and PHA. The quantitative biomarkers we found allow for a steroid metabolomics based precision medicine approach.