Peña-Bautista Carmen, Álvarez Lourdes, Durand Thierry, Vigor Claire, Cuevas Ana, Baquero Miguel, Vento Máximo, Hervás David, Cháfer-Pericás Consuelo
Neonatal Research Unit, Health Research Institute La Fe, 46026 Valencia, Spain.
Neurology Unit, University and Polytechnic Hospital La Fe, 46026 Valencia, Spain.
Antioxidants (Basel). 2020 Jul 22;9(8):649. doi: 10.3390/antiox9080649.
Differential diagnosis of Alzheimer's disease (AD) is a complex task due to the clinical similarity among neurodegenerative diseases. Previous studies showed the role of lipid peroxidation in early AD development. However, the clinical validation of potential specific biomarkers in minimally invasive samples constitutes a great challenge in early AD diagnosis.
Plasma samples from participants classified into AD ( = 138), non-AD (including MCI and other dementias not due to AD) ( = 70) and healthy ( = 50) were analysed. Lipid peroxidation compounds (isoprostanes, isofurans, neuroprostanes, neurofurans) were determined by ultra-performance liquid chromatography coupled with tandem mass spectrometry. Statistical analysis for biomarkers' clinical validation was based on Elastic Net.
A two-step diagnosis model was developed from plasma lipid peroxidation products to diagnose early AD specifically, and a bootstrap validated AUC of 0.74 was obtained.
A promising AD differential diagnosis model was developed. It was clinically validated as a screening test. However, further external validation is required before clinical application.
由于神经退行性疾病之间存在临床相似性，阿尔茨海默病（AD）的鉴别诊断是一项复杂的任务。先前的研究表明脂质过氧化在AD早期发展中的作用。然而，在微创样本中对潜在特异性生物标志物进行临床验证在AD早期诊断中构成了巨大挑战。
对分为AD组（n = 138）、非AD组（包括轻度认知障碍和其他非AD所致痴呆）（n = 70）和健康组（n = 50）的参与者的血浆样本进行分析。通过超高效液相色谱-串联质谱法测定脂质过氧化化合物（异前列腺素、异呋喃、神经前列腺素、神经呋喃）。生物标志物临床验证的统计分析基于弹性网络。
从血浆脂质过氧化产物建立了一个两步诊断模型以特异性诊断早期AD，自展验证的AUC为0.74。
开发了一个有前景的AD鉴别诊断模型。它作为一种筛查试验得到了临床验证。然而，在临床应用之前需要进一步的外部验证。
