血浆脂质过氧化生物标志物在阿尔茨海默病早期和非侵入性检测中的应用。
Plasma lipid peroxidation biomarkers for early and non-invasive Alzheimer Disease detection.
机构信息
Neonatal Research Unit, Health Research Institute La Fe, Valencia, Spain.
Institut des Biomolécules Max Mousseron, IBMM, University of Montpellier, CNRS ENSCM, Montpellier, France.
出版信息
Free Radic Biol Med. 2018 Aug 20;124:388-394. doi: 10.1016/j.freeradbiomed.2018.06.038. Epub 2018 Jun 30.
INTRODUCTION
Alzheimer Disease (AD) standard diagnosis is based on evaluations and biomarkers that are non-specific, expensive, or requires invasive sampling. Therefore, an early, and non-invasive diagnosis is required. As regards molecular mechanisms, recent research has shown that lipid peroxidation plays an important role.
METHODS
Well-defined participants groups were recruited. Lipid peroxidation compounds were determined in plasma using a validated analytical method. Statistical studies consisted of an elastic-net-penalized logistic regression adjustment.
RESULTS
The regression model fitted to the data included six variables (lipid peroxidation biomarkers) as potential predictors of early AD. This model achieved an apparent area under the receiver operating characteristics (AUC-ROCs) of 0.883 and a bootstrap-validated AUC-ROC of 0.817. Calibration of the model showed very low deviations from real probabilities.
CONCLUSION
A satisfactory early diagnostic model has been obtained from plasma levels of 6 lipid peroxidation compounds, indicating the individual probability of suffering from early AD.
简介
阿尔茨海默病（AD）的标准诊断基于非特异性、昂贵或需要侵入性采样的评估和生物标志物。因此，需要进行早期、非侵入性的诊断。关于分子机制，最近的研究表明脂质过氧化起着重要作用。
方法
招募了明确界定的参与者组。使用经过验证的分析方法在血浆中测定脂质过氧化化合物。统计研究包括弹性网络惩罚逻辑回归调整。
结果
拟合数据的回归模型包括 6 个变量（脂质过氧化生物标志物）作为早期 AD 的潜在预测因子。该模型在接受者操作特征（ROC）曲线下的明显面积为 0.883，经过 bootstrap 验证的 ROC 曲线下面积为 0.817。该模型的校准显示与真实概率的偏差非常小。
结论
从 6 种脂质过氧化化合物的血浆水平获得了令人满意的早期诊断模型，表明个体患有早期 AD 的概率。
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