Determination of Urinary Androgens in Women with Polycystic Ovary Syndrome Using LC-QqQ/MS and the Application of Thin Film Solid-Phase Microextraction (TF-SPME).

Hyperandrogenism is one of the most pronounced symptoms of Polycystic Ovary Syndrome (PCOS) and seems to play a key role in the pathogenesis of this complex disorder. Nevertheless, there is still a lack of consistent results regarding common steroid predictors of PCOS. Therefore, a liquid chromatography tandem mass spectrometry (HPLC-QqQ/MS) method was developed and validated to determine the concentrations of four classic androgens: androstenedione (An-dione), testosterone (T), 5α-dihydrotestosterone (DHT) and androsterone (An) in urine samples obtained from women with PCOS and healthy controls. The limits of detection were between 0.04 and 0.09 ng/mL, while the limits of quantification ranged from 0.1 to 0.3 ng/mL respectively. As a pre-treatment procedure prior to analysis, hydrolysis using β-glucuronidase and thin film solid-phase microextraction (TF-SPME) was applied. The methodology was employed to perform targeted metabolomics of urinary steroids in women with PCOS and healthy controls. All measured androgens: An-dione (p < 0.0001), T (p = 0.0001), DHT (p < 0.0001) and An (p = 0.0002) showed significantly higher concentrations in the urine of women with PCOS. The largest difference in the mean concentration was found for DHT, which was 2.8 times higher in the PCOS group (13.9 ± 14.1 ng/mg creatinine) in comparison to healthy controls (4.9 ± 3.4 ng/mg creatinine). The results of receiver operating characteristic curve indicated that determination of the panel of three urinary androgens: T+DHT+An-dione with, under the study assumptions, was the best predictor of PCOS diagnosis (AUC of ROC curve = 0.91 (95 % CI: 0.8212-0.9905). The application of an LC-MS/MS-based analysis, together with highly sensitive extraction techniques like TF-SPME, is a suitable approach to perform fast assays and obtain reliable results - crucial in the search for valuable and significant steroids predictors of PCOS.