Metabolomic Biomarkers in Urine of Cushing’s Syndrome Patients

Abstract

Cushing’s syndrome (CS) is a disease which results from excessive levels of cortisol in the human body. The disorder is associated with various signs and symptoms which are also common for the general population not suffering from compound hypersecretion. Thus, more sensitive and selective methods are required for the diagnosis of CS. This follow-up study was conducted to determine which steroid metabolites could serve as potential indicators of CS and possible subclinical hypercortisolism in patients diagnosed with so called non-functioning adrenal incidentalomas (AIs). Urine samples from negative controls (n = 37), patients with CS characterized by hypercortisolism and excluding iatrogenic CS (n = 16), and patients with non-functioning AIs with possible subclinical Cushing’s syndrome (n = 25) were analyzed using gas chromatography-mass spectrometry (GC/MS) and gas chromatograph equipped with flame ionization detector (GC/FID). Statistical and multivariate methods were applied to investigate the profile differences between examined individuals. The analyses revealed hormonal differences between patients with CS and the rest of examined individuals. The concentrations of selected metabolites of cortisol, androgens, and pregnenetriol were elevated whereas the levels of tetrahydrocortisone were decreased for CS when opposed to the rest of the study population. Moreover, after analysis of potential confounding factors, it was also possible to distinguish six steroid hormones which discriminated CS patients from other study subjects. The obtained discriminant functions enabled classification of CS patients and AI group characterized by mild hypersecretion of cortisol metabolites. It can be concluded that steroid hormones selected by applying urinary profiling may serve the role of potential biomarkers of CS and can aid in its early diagnosis.

Modern Management of Mild Autonomous Cortisol Secretion

“…Authors reported increased urinary concentrations of androsterone, etiocholanolone, pregnenetriol, tetrahydrocorticosterone, tetrahydrocortisol, allo‐tetrahydrocortisol, and α‐cortol, as well as decreased concentrations of tetrahydrocortisone in patients with CS ( Table ). When urine steroid profiling of patients with NFAT was compared with healthy controls, authors observed similar differences, postulating that at least a subgroup of patients with adrenal incidentalomas may have had underlying MACS that was not detected by currently available biochemical tests . Surprisingly, authors have not demonstrated androgen decrease as expected in ACTH‐independent cortisol excess, possibly due to imperfect age and sex matching or due to inclusion of two patients with pituitary CS in analysis.…”

“…Urine profiling of 19 steroids by GC‐MS was reported in 25 patients with adrenal incidentalomas, 16 patients with overt CS (14 adrenal and 2 pituitary CS), and 37 healthy controls . Authors reported increased urinary concentrations of androsterone, etiocholanolone, pregnenetriol, tetrahydrocorticosterone, tetrahydrocortisol, allo‐tetrahydrocortisol, and α‐cortol, as well as decreased concentrations of tetrahydrocortisone in patients with CS ( Table ).…”

GC/MS in Recent Years Has Defined the Normal and Clinically Disordered Steroidome: Will It Soon Be Surpassed by LC/Tandem MS in This Role?

“…Kotłowska et al [ 76 ], studying Cushing disease, reported increased urinary levels of cortisol metabolites, androgens, and pregnanetriol and decreased level of tetrahydrocortisone. These data were similar to those reported in the 1990s [ 77 ]; however, they used heat maps to illustrate their data.…”

A role for metabolomics in the antidoping toolbox?

“…It is well known that anabolic hormone disorders cause several pathologies in humans including unnatural metabolic profiles 143 . Metabolomics has been proposed as a tool to diagnose hormonal deficiencies, 144 or to track metabolic changes in hormonally supplemented patients, 42,145,146 to evaluate the effect of the treatment. Starting from information on the general working principle of each hormone and gathering information from studies on hormonally treated patients, it is possible to speculate on the expected dose‐dependent effect on human metabolism of each class of hormones.…”