Urine metabolomics analysis for adrenal incidentaloma activity detection and biomarker discovery

Abstract

This study describes the development of a method suitable for the analysis of nineteen major urinary steroid metabolites in human urine. The analytes of interest were isolated from urine using solid phase extraction, subjected to enzymatic hydrolysis and again extracted applying solid phase extraction. After derivatization, methyloxime-trimethylsilyl ether derivatives of steroid hormones were identified by gas chromatography-mass spectrometry (GC/MS) and quantified by gas chromatography with flame ionization detector (GC/FID). The quantification method was validated for linearity, trueness, precision and selectivity. The limits of detection were between 6.2 and 7.2 ng/mL and limits of quantification were between 12.3 and 14.8 ng/mL. The established method was applied to analyze 28 urine samples from patients diagnosed with non-functioning adrenal incidentalomas (AIs) and 30 healthy subjects. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) were employed to visualize the differences between metabolic profiles of patients and the control group and to determine possible markers of AIs activity. Both multivariate methods separated seven patients from the rest of the examined individuals. Five urinary metabolites including α-cortol, tetrahydrocorticosterone, tetrahydrocortisol, allo-tetrahydrocortisol and etiocholanolone were identified as potential biomarkers of pathological adrenal function. The altered metabolites reflected pathological metabolism mainly of cortisol and cortisone. This research proved that metabolomics is a suitable tool for disease research.