Computational integration of nanoscale physical biomarkers and cognitive assessments for Alzheimer's disease diagnosis and prognosis.
Computational integration of nanoscale physical biomarkers and cognitive assessments for Alzheimer's disease diagnosis and prognosis.
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DOI：
10.1126/sciadv.1700669
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发表时间：
2017-07
期刊：
影响因子：
13.6
通讯作者：
Zhang M
中科院分区：
文献类型：
--
作者：
Yue T;Jia X;Petrosino J;Sun L;Fan Z;Fine J;Davis R;Galster S;Kuret J;Scharre DW;Zhang M
AD患者的蛋白质特性可以与行为评估进行计算整合，用于AD诊断和预后。随着阿尔茨海默病（AD）的日益流行，已经针对开发可以增强AD检测和管理的新型诊断和生物标志物做出了重大努力。AD通过仍在阐明的机制影响患者的认知、行为、功能和生理。目前的AD诊断取决于评估患者显示或不显示哪些症状和体征。人们担心AD诊断可能会受到这些测量结果分析方式的影响。使用整合多学科输入的计算算法诊断AD的无偏见手段，从纳米级生物标志物到认知评估，并整合生物化学和物理变化，可以为这些限制提供解决方案，因为缺乏对疾病动态进展的了解，加上多尺度的多种症状。我们表明，从脑脊液和血液中的患者的蛋白质聚集体的纳米级物理性质的改变，在AD发病机制，这些属性可以被用作一类新的“物理生物标志物。”使用计算算法，开发整合这些生物标志物和认知评估，我们展示了一种公正诊断AD并预测其进展的方法。可以根据患者的身体生物标志物和认知评估评分随时间的变化进行实时进展诊断更新。此外，Nyquist-Shannon采样定理用于确定有效预测疾病进展所需的最少患者检查次数。这种集成的计算方法可以生成用于AD诊断和预后的患者特异性的个性化签名。
Protein properties of AD patients can be computationally integrated with behavioral assessments for AD diagnosis and prognosis. With the increasing prevalence of Alzheimer’s disease (AD), significant efforts have been directed toward developing novel diagnostics and biomarkers that can enhance AD detection and management. AD affects the cognition, behavior, function, and physiology of patients through mechanisms that are still being elucidated. Current AD diagnosis is contingent on evaluating which symptoms and signs a patient does or does not display. Concerns have been raised that AD diagnosis may be affected by how those measurements are analyzed. Unbiased means of diagnosing AD using computational algorithms that integrate multidisciplinary inputs, ranging from nanoscale biomarkers to cognitive assessments, and integrating both biochemical and physical changes may provide solutions to these limitations due to lack of understanding for the dynamic progress of the disease coupled with multiple symptoms in multiscale. We show that nanoscale physical properties of protein aggregates from the cerebral spinal fluid and blood of patients are altered during AD pathogenesis and that these properties can be used as a new class of “physical biomarkers.” Using a computational algorithm, developed to integrate these biomarkers and cognitive assessments, we demonstrate an approach to impartially diagnose AD and predict its progression. Real-time diagnostic updates of progression could be made on the basis of the changes in the physical biomarkers and the cognitive assessment scores of patients over time. Additionally, the Nyquist-Shannon sampling theorem was used to determine the minimum number of necessary patient checkups to effectively predict disease progression. This integrated computational approach can generate patient-specific, personalized signatures for AD diagnosis and prognosis.
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影响因子：
168.9
作者：
Ballard, Clive;Gauthier, Serge;Jones, Emma
通讯作者：
Jones, Emma
DOI：
10.1016/s0140-6736(20)32205-4
发表时间：
2021-04-24
期刊：
Lancet (London, England)
影响因子：
--
作者：
Scheltens P;De Strooper B;Kivipelto M;Holstege H;Chételat G;Teunissen CE;Cummings J;van der Flier WM
通讯作者：
van der Flier WM
影响因子：
3.9
作者：
Cizas, Paulius;Budvytyte, Rima;Morkuniene, Ramune;Moldovan, Radu;Broccio, Matteo;Loesche, Mathias;Niaura, Gediminas;Valincius, Gintaras;Borutaite, Vilmante
通讯作者：
Borutaite, Vilmante
影响因子：
14
作者：
Brookmeyer, Ron;Johnson, Elizabeth;Arrighi, H. Michael
通讯作者：
Arrighi, H. Michael
影响因子：
6.1
作者：
GORDON, K
通讯作者：
GORDON, K