Custers D, Van Hoeck E, Courselle P, Apers S, Deconinck E
Division of Food, Medicines and Consumer Safety, Section Medicinal Products, Scientific Institute of Public Health (WIV-ISP), J. Wytsmanstraat 14, B-1050, Brussels, Belgium.
Research group NatuRA (Natural products and Food - Research and Analysis), Department of Pharmaceutical Sciences, University of Antwerp, Universiteitsplein 1, B-2610, Wilrijk, Belgium.
Drug Test Anal. 2017 Feb;9(2):230-242. doi: 10.1002/dta.1964. Epub 2016 Mar 22.
Herbal medicines and food supplements intended as slimming aids are increasingly gaining popularity worldwide, especially for treating obesity. In this study, an ultra-performance liquid chromatography coupled to photodiode array detection (UPLC-PDA) and an ultra-performance liquid chromatography mass spectrometry (UPLC-MS) method were developed to analyze 92 slimming aids (confiscated by customs), aimed at acquiring highly informative fingerprints. Three types of fingerprints were acquired (PDA, Total Ion Chromatograms (TIC), and MS fingerprints) which were used in the chemometric data analysis. Both unsupervised (i.e., Hierarchical Cluster Analysis (HCA)) and supervised techniques (i.e., Classification and Regression Tree (CART) and Partial Least Squares - Discriminant Analysis (PLS-DA)) were applied. The aim was to perform an in-depth study of the samples, thereby exploring potential patterns present in the data. HCA was able to generate a clustering which was mainly defined by chemical compounds detected in the samples, i.e., sibutramine, phenolphthalein and amfepramone. PLS-DA generated the best diagnostic models for both PDA and TIC fingerprints, characterized by correct classification rates of external validation of 85% and 80%, respectively. For the MS fingerprints, the best model was obtained by CART (65% correct classification rate of external validation). Despite a lower correct classification rate, exploration of the concerned misclassifications revealed that the MS fingerprints proved to be superior since even very low concentrations of sibutramine could be detected. This study shows that reliable chemometric models can be obtained, based on the presence of prohibited chemical substances, which allow high-throughput data analysis of such samples. Moreover, they generate a prime notion of potential threat to a patient's health posed by these kinds of slimming aids. Copyright © 2016 John Wiley & Sons, Ltd.
作为减肥辅助品的草药和食品补充剂在全球范围内越来越受欢迎，尤其是用于治疗肥胖症。在本研究中，开发了一种超高效液相色谱-光电二极管阵列检测联用（UPLC-PDA）和超高效液相色谱-质谱联用（UPLC-MS）方法，用于分析92种减肥辅助品（海关查获），旨在获取信息量丰富的指纹图谱。获得了三种类型的指纹图谱（PDA、总离子色谱图（TIC）和质谱指纹图谱），并用于化学计量学数据分析。同时应用了无监督技术（即层次聚类分析（HCA））和有监督技术（即分类与回归树（CART）和偏最小二乘判别分析（PLS-DA））。目的是对样品进行深入研究，从而探索数据中存在的潜在模式。HCA能够生成一个聚类，该聚类主要由样品中检测到的化学化合物定义，即西布曲明、酚酞和安非拉酮。PLS-DA为PDA和TIC指纹图谱生成了最佳诊断模型，外部验证的正确分类率分别为85%和80%。对于质谱指纹图谱，CART获得了最佳模型（外部验证的正确分类率为65%）。尽管正确分类率较低，但对相关错误分类的探索表明，质谱指纹图谱被证明更具优势，因为即使是极低浓度的西布曲明也能被检测到。本研究表明，基于违禁化学物质的存在，可以获得可靠的化学计量学模型，从而实现对此类样品的高通量数据分析。此外，它们还能让人们初步了解这类减肥辅助品对患者健康构成的潜在威胁。版权所有© 2016约翰威立父子有限公司。
