A Conformation Variant of p53 Combined with Machine Learning Identifies Alzheimer Disease in Preclinical and Prodromal Stages.
A Conformation Variant of p53 Combined with Machine Learning Identifies Alzheimer Disease in Preclinical and Prodromal Stages.
复制标题
DOI：
10.3390/jpm11010014
复制
发表时间：
2020-12-26
影响因子：
--
通讯作者：
Uberti D
中科院分区：
文献类型：
--
作者：
Abate G;Vezzoli M;Polito L;Guaita A;Albani D;Marizzoni M;Garrafa E;Marengoni A;Forloni G;Frisoni GB;Cummings JL;Memo M;Uberti D
阿尔茨海默病(AD)的早期诊断是疾病管理的重要起点。以血液为基础的生物标记物在初级保健环境中提供AD风险信息方面具有相当大的优势。在这里，我们报告了一种相对未知的血液生物标志物的新数据，该生物标志物有望用于AD诊断。我们评估了由抗体2D3A8识别的P53错误折叠构象，也称为未折叠P53(U-p532D3A8+)，来自InveCe.Ab和PharmaCog/E-ADNI纵向研究的375份血浆样本。采用机器学习的方法将U-p532D3A8+血浆水平与简易智力状态检查和载脂蛋白E-4(ApoEε-4)相结合，能够预测InveCE.Ab中AD的可能性风险，与临床诊断的总体符合率为86.67%。这些算法还根据脑脊液AD标志物(A-β42和p-β)对PharmaCog/E-ADNI中将发展为AD的AMCI+-遗忘性轻度认知障碍患者进行了准确的分类(AUC=0.92A-MCI)。结果支持U-p532D3A8+血浆水平作为AD的新的候选血液生物标志物。
Early diagnosis of Alzheimer’s disease (AD) is a crucial starting point in disease management. Blood-based biomarkers could represent a considerable advantage in providing AD-risk information in primary care settings. Here, we report new data for a relatively unknown blood-based biomarker that holds promise for AD diagnosis. We evaluate a p53-misfolding conformation recognized by the antibody 2D3A8, also named Unfolded p53 (U-p532D3A8+), in 375 plasma samples derived from InveCe.Ab and PharmaCog/E-ADNI longitudinal studies. A machine learning approach is used to combine U-p532D3A8+ plasma levels with Mini-Mental State Examination (MMSE) and apolipoprotein E epsilon-4 (APOEε4) and is able to predict AD likelihood risk in InveCe.Ab with an overall 86.67% agreement with clinical diagnosis. These algorithms also accurately classify (AUC = 0.92) Aβ+—amnestic Mild Cognitive Impairment (aMCI) patients who will develop AD in PharmaCog/E-ADNI, where subjects were stratified according to Cerebrospinal fluid (CSF) AD markers (Aβ42 and p-Tau). Results support U-p532D3A8+ plasma level as a promising additional candidate blood-based biomarker for AD.
登录
查看更多内容
DOI：
10.1038/s41582-018-0079-7
发表时间：
2018-11
期刊：
Nature reviews. Neurology
影响因子：
--
作者：
Hampel H;O'Bryant SE;Molinuevo JL;Zetterberg H;Masters CL;Lista S;Kiddle SJ;Batrla R;Blennow K
通讯作者：
Blennow K
影响因子：
--
作者：
Feng, Zhaohui;Lin, Meihua;Wu, Rui
通讯作者：
Wu, Rui
影响因子：
11
作者：
Lanni, C.;Racchi, M.;Uberti, D.
通讯作者：
Uberti, D.
DOI：
10.1186/s13195-020-00732-0
发表时间：
2020-12-03
期刊：
Alzheimer's research & therapy
影响因子：
--
作者：
Abate G;Frisoni GB;Bourdon JC;Piccirella S;Memo M;Uberti D
通讯作者：
Uberti D
影响因子：
3
作者：
Checler, Frederic;Dunys, Julie;da Costa, Cristine Alves
通讯作者：
da Costa, Cristine Alves