Human Biomonitoring Research Unit, Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg.
L'Oréal Research and Innovation, Aulnay sous Bois, France.
Eur J Endocrinol. 2022 Mar 18;186(5):K9-K15. doi: 10.1530/EJE-22-0081.
Endogenous hormones regulate numerous physiological processes in humans. Some of them are routinely measured in blood, saliva and/or urine for the diagnosis of disorders. The analysis of fluids may, however, require multiple samples collected at different time points to avoid the high variability in the concentration of some hormones. In contrast, hair analysis has been proposed as an interesting alternative to reveal average hormone levels over a longer period. In this work, we developed and validated an analytical method for analyzing 36 endogenous steroid and thyroid hormones and one pineal hormone in human hair using ultra-performance liquid chromatography (UPLC)-tandem mass spectrometry (MS/MS).
Sample preparation involved hair decontamination, pulverization, methanol extraction, and purification with C18-solid phase extraction. Extracts were then divided into two portions, respectively injected into an UPLC-MS/MS system, and analyzed using two different instrumental methods. The method was applied to a healthy female population aged 25-45 years.
The method was validated on supplemented hair samples for the 37 targeted hormones, and its application to the population under study allowed to detect 32 compounds in 2-100% of the samples. Complete reference intervals (2.5-97.5th percentiles) were established for estrone, 17β-estradiol, androstenedione, dehydroepiandrosterone, progesterone, 17α-hydroxyprogesterone, cortisone, cortisol and 3,3',5-triiodo-L-thyronine. Hair cortisone, cortisol, tetrahydrocortisone and tetrahydrocortisol concentrations were highly correlated with each other, with Kendall's τ correlation coefficients ranging from 0.52 to 0.68.
Allowing the detection of 32 hormones from different chemical classes, the present method will allow to broaden hormonal profiling for better identifying endocrine disorders.
内源性激素调节着人体的许多生理过程。其中一些激素在血液、唾液和/或尿液中常规检测,用于诊断疾病。然而,为了避免某些激素浓度的高度变异性,分析这些体液可能需要采集不同时间点的多个样本。相比之下,毛发分析已被提出作为一种揭示较长时间内平均激素水平的有趣替代方法。在这项工作中,我们开发并验证了一种使用超高效液相色谱(UPLC)-串联质谱(MS/MS)分析人发中 36 种内源性甾体和甲状腺激素以及一种松果腺激素的分析方法。
样品制备包括毛发去污染、粉碎、甲醇提取以及 C18-固相萃取净化。然后将提取物分为两部分,分别注入 UPLC-MS/MS 系统,并使用两种不同的仪器方法进行分析。该方法应用于年龄在 25-45 岁的健康女性人群。
该方法在补充的毛发样品上对 37 种目标激素进行了验证,其在研究人群中的应用可在 2-100%的样本中检测到 32 种化合物。建立了雌酮、17β-雌二醇、雄烯二酮、脱氢表雄酮、孕酮、17α-羟孕酮、皮质酮、皮质醇和 3,3',5-三碘-L-甲状腺素的完整参考区间(2.5-97.5 百分位数)。发皮质酮、皮质醇、四氢皮质酮和四氢皮质醇浓度之间高度相关,Kendall's τ 相关系数范围为 0.52 至 0.68。
本方法能够检测来自不同化学类别的 32 种激素,将有助于扩大激素谱分析,以更好地识别内分泌紊乱。