TurboFlow-LC-MS /MS检测儿童血清DHEA、DHEAS、17α-羟孕酮、Δ4-androstenedione和睾酮浓度

IF 2.9 3区 医学 Q2 MEDICAL LABORATORY TECHNOLOGY
T. Søeborg , H. Frederiksen , P. Fruekilde , T.H. Johannsen , A. Juul , A.M. Andersson
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引用次数: 57

摘要

诊断和管理患有性类固醇疾病的婴儿和儿童需要快速和同时评估血清中几种低浓度和小样本量的性类固醇代谢物。因此,我们建立了一种灵敏、选择性的TurboFlow-LC-MS /MS定量测定青春期前儿童血清中DHEA、DHEAS、17α-羟孕酮、Δ4-androstenedione和睾酮的方法。运行时间10.75 min。定量限为:DHEA, 0.88 nM;DHEAS, 48 nM;17α-羟基孕酮,0.19 nM;Δ4-androstenedione, 0.18 nM,睾酮,0.10 nM。日内相对标准差为4.6 ~ 13.8%,日内相对标准差为5.7 ~ 15.7%。对38份青春期前儿童血清样品中的类固醇浓度进行了DHEAS、Δ4-androstenedione和睾酮免疫测定结果的比较。DHEAS给出了总体相似的结果,但有几个异常值,而通过LC-MS /MS分析时发现Δ4-androstenedione的水平要低得多。使用灵敏的免疫分析法分析的任何样品中均未检测到睾酮,而38个样品中的30个可使用当前的LC-MS /MS方法进行定量。提出的方法适用于临床设置的同时量化五类固醇的重要管理与性发育障碍和类固醇生物合成缺陷的儿童。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Serum concentrations of DHEA, DHEAS, 17α-hydroxyprogesterone, Δ4-androstenedione and testosterone in children determined by TurboFlow-LC–MS/MS

Diagnosis and management of infants and children with sex steroid disorders require fast and simultaneous assessment of several sex steroid metabolites in serum at low concentrations and on small sample volumes. Therefore, we developed a sensitive and selective TurboFlow-LC–MS/MS method for quantification of DHEA, DHEAS, 17α-hydroxyprogesterone, Δ4-androstenedione and testosterone in serum from pre-pubertal children.

Run time was 10.75 min. Limits of quantification were as follows: DHEA, 0.88 nM; DHEAS, 48 nM; 17α-hydroxyprogesterone, 0.19 nM; Δ4-androstenedione, 0.18 nM and testosterone, 0.10 nM. Intra-day relative standard deviation ranged from 4.6 to 13.8% and inter-day relative standard deviation ranged from 5.7 to 15.7%. Steroid concentrations in 38 serum samples from pre-pubertal children were compared with results obtained by immunoassays for DHEAS, Δ4-androstenedione and testosterone. DHEAS gave overall similar results but with several outliers, while levels of Δ4-androstenedione were found to be much lower when analysed by LC–MS/MS. Testosterone was not detected in any of the samples analysed using a sensitive immunoassay, while 30 of 38 samples were quantifiable using the current LC–MS/MS method. The presented method is suitable in a clinical setting for simultaneous quantification of five steroids important for management of children with disorders of sex development and steroid biosynthesis defects.

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来源期刊
Clinica Chimica Acta
Clinica Chimica Acta 医学-医学实验技术
CiteScore
10.10
自引率
2.00%
发文量
1268
审稿时长
23 days
期刊介绍: The Official Journal of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Clinica Chimica Acta is a high-quality journal which publishes original Research Communications in the field of clinical chemistry and laboratory medicine, defined as the diagnostic application of chemistry, biochemistry, immunochemistry, biochemical aspects of hematology, toxicology, and molecular biology to the study of human disease in body fluids and cells. The objective of the journal is to publish novel information leading to a better understanding of biological mechanisms of human diseases, their prevention, diagnosis, and patient management. Reports of an applied clinical character are also welcome. Papers concerned with normal metabolic processes or with constituents of normal cells or body fluids, such as reports of experimental or clinical studies in animals, are only considered when they are clearly and directly relevant to human disease. Evaluation of commercial products have a low priority for publication, unless they are novel or represent a technological breakthrough. Studies dealing with effects of drugs and natural products and studies dealing with the redox status in various diseases are not within the journal''s scope. Development and evaluation of novel analytical methodologies where applicable to diagnostic clinical chemistry and laboratory medicine, including point-of-care testing, and topics on laboratory management and informatics will also be considered. Studies focused on emerging diagnostic technologies and (big) data analysis procedures including digitalization, mobile Health, and artificial Intelligence applied to Laboratory Medicine are also of interest.
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