Fully Automated Method For Quantitative Determination Of Steroids In Serum: An Approach To Evaluate Steroidogenesis

TALANTA(2021)

引用 9|浏览5
暂无评分
摘要
Steroidogenesis is a set of metabolic reactions where the enzymes play a key role to control the physiological levels of steroids. A deficiency in steroidogenesis induces an accumulation and/or insufficiency of steroids in human blood and can lead to different pathologies. This issue added to the low levels of steroids (pg mL(-1) to ng mL(-1)) in this biofluid make of their determination an analytical challenge. In this research, we present a high-throughtput and fully automated method based on solid-phase extraction on-line coupled to liquid chromatography with tandem mass spectrometry detection (SPE-LC-MS/MS) to quantify estrogens (estrone and estradiol), androgens (testosterone, androstenedione, dihydrotestosterone and dehydroepiandrosterone), progestogens (progesterone, pregnenolone, 17-hydroxyprogesterone and 17-hydroxypregnenolone), glucocorticoids (21-hydroxyprogesterone, 11-deoxycortisol, cortisone, corticosterone and cortisol) and one mineralocorticoid (aldosterone) in human serum. The performance of the SPE step and the multiple reaction monitoring (MRM) mode allowed reaching a high sensitivity and selectivity levels without any derivatization reaction. The fragmentation mechanisms of the steroids were complementary studied by LC-MS/MS in high-resolution mode to confirm the MRM transitions. The method was characterized with two SPE sorbents with similar physicochemical properties. Thus, limits of quantification were at pg mL(-1) levels, the variability was below 25% (except for pregnenolone and cortisone), and the accuracy, expressed as bias, was always within +/- 25%. The proposed method was tested in human serum from ten volunteers, who reported levels for the sixteen target steroids that were satisfactorily in agreement with the physiological ranges reported in the literature.
更多
查看译文
关键词
Steroids, Serum, SPE-LC-MS/MS, Steroidogenesis, Hormones, Automation
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要