Department of Clinical Chemistry, Ghent University Hospital, Ghent, Belgium.
Department of Laboratory Medicine, Catholic University of Bukavu, Bukavu, Democratic Republic of the Congo.
Clin Chem Lab Med. 2018 Aug 28;56(9):1551-1558. doi: 10.1515/cclm-2018-0239.
Glycated keratin allows the monitoring of average tissue glucose exposure over previous weeks. In the present study, we wanted to explore if near-infrared (NIR) spectroscopy could be used as a non-invasive diagnostic tool for assessing glycation in diabetes mellitus.
A total of 52 patients with diabetes mellitus and 107 healthy subjects were enrolled in this study. A limited number (n=21) of nails of healthy subjects were glycated in vitro with 0.278 mol/L, 0.556 mol/L and 0.833 mol/L glucose solution to study the effect of glucose on the nail spectrum. Consequently, the nail clippings of the patients were analyzed using a Thermo Fisher Antaris II Near-IR Analyzer Spectrometer and near infrared (NIR) chemical imaging. Spectral classification (patients with diabetes mellitus vs. healthy subjects) was performed using partial least square discriminant analysis (PLS-DA).
In vitro glycation resulted in peak sharpening between 4300 and 4400 cm-1 and spectral variations at 5270 cm-1 and between 6600 and 7500 cm-1. Similar regions encountered spectral deviations during analysis of the patients' nails. Optimization of the spectral collection parameters was necessary in order to distinguish a large dataset. Spectra had to be collected at 16 cm-1, 128 scans, region 4000-7500 cm-1. Using standard normal variate, Savitsky-Golay smoothing (7 points) and first derivative preprocessing allowed for the prediction of the test set with 100% correct assignments utilizing a PLS-DA model.
Analysis of protein glycation in human fingernail clippings with NIR spectroscopy could be an alternative affordable technique for the diagnosis of diabetes mellitus.
糖化角蛋白可用于监测过去数周内组织的平均葡萄糖暴露水平。在本研究中,我们想探讨近红外(NIR)光谱是否可作为一种非侵入性诊断工具,用于评估糖尿病患者的糖化水平。
本研究共纳入 52 例糖尿病患者和 107 例健康受试者。将健康受试者的少量指甲(n=21)分别用 0.278 mol/L、0.556 mol/L 和 0.833 mol/L 葡萄糖溶液体外糖化,以研究葡萄糖对指甲光谱的影响。随后,使用 Thermo Fisher Antaris II 近红外分析仪和近红外(NIR)化学成像对患者的指甲屑进行分析。采用偏最小二乘判别分析(PLS-DA)对指甲光谱进行分类(糖尿病患者与健康受试者)。
体外糖化导致 4300-4400 cm-1 处的峰变尖锐,5270 cm-1 和 6600-7500 cm-1 处的光谱发生变化。在分析患者指甲时,类似区域也出现了光谱偏差。为了区分大数据集,有必要优化光谱采集参数。必须以 16 cm-1、128 次扫描、4000-7500 cm-1 区域收集光谱。使用标准正态变量、Savitzky-Golay 平滑(7 点)和一阶导数预处理,通过 PLS-DA 模型可实现对测试集 100%正确赋值的预测。
利用 NIR 光谱分析人手指甲屑中的蛋白质糖化可能是一种替代的、经济实惠的糖尿病诊断技术。