A similarity-based approach to leverage multi-cohort medical data on the diagnosis and prognosis of Alzheimer's disease.
A similarity-based approach to leverage multi-cohort medical data on the diagnosis and prognosis of Alzheimer's disease.
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DOI：
10.1093/gigascience/giy085
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发表时间：
2018-07-01
期刊：
影响因子：
9.2
通讯作者：
Alzheimer's Disease Neuroimaging Initiative
中科院分区：
文献类型：
--
作者：
Zhang H;Zhu F;Dodge HH;Higgins GA;Omenn GS;Guan Y;Alzheimer's Disease Neuroimaging Initiative
异质性疾病如阿尔茨海默病（AD）在人群中表现出多种表型。早期诊断和有效治疗可带来成本效益。许多关于生化和影像学标记物的研究已经显示出改善诊断的潜力，但建立辅助试验的定量诊断标准仍然具有挑战性。我们开发了一种基于相似性的方法，将个体与具有相似条件的受试者相匹配。我们用高斯过程模拟了这种疾病，并在阿尔茨海默病大数据梦想挑战赛中测试了这种方法。在提交的方法中排名最高，我们的诊断模型在独立数据集测试中预测认知障碍评分，相关性评分为0.573。它区分AD患者与对照受试者，受试者工作曲线下面积为0.920。在不了解受试者纵向信息的情况下，该模型通过相似性网络预测了容易从轻度认知障碍转化为AD的患者。该诊断框架可应用于具有临床异质性的其他疾病，例如帕金森病。
Heterogeneous diseases such as Alzheimer's disease (AD) manifest a variety of phenotypes among populations. Early diagnosis and effective treatment offer cost benefits. Many studies on biochemical and imaging markers have shown potential promise in improving diagnosis, yet establishing quantitative diagnostic criteria for ancillary tests remains challenging. We have developed a similarity-based approach that matches individuals to subjects with similar conditions. We modeled the disease with a Gaussian process, and tested the method in the Alzheimer's Disease Big Data DREAM Challenge. Ranked the highest among submitted methods, our diagnostic model predicted cognitive impairment scores in an independent dataset test with a correlation score of 0.573. It differentiated AD patients from control subjects with an area under the receiver operating curve of 0.920. Without knowing longitudinal information about subjects, the model predicted patients who are vulnerable to conversion from mild-cognitive impairment to AD through the similarity network. This diagnostic framework can be applied to other diseases with clinical heterogeneity, such as Parkinson's disease.
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DOI：
10.1016/j.jalz.2014.04.513
发表时间：
2014-11
期刊：
Alzheimer's & dementia : the journal of the Alzheimer's Association
影响因子：
--
作者：
Dodge HH;Zhu J;Harvey D;Saito N;Silbert LC;Kaye JA;Koeppe RA;Albin RL;Alzheimer's Disease Neuroimaging Initiative
通讯作者：
Alzheimer's Disease Neuroimaging Initiative
影响因子：
4
作者：
Banerjee, Sube;Wittenberg, Raphael
通讯作者：
Wittenberg, Raphael
影响因子：
38.1
作者：
Frisoni, Giovanni B.;Fox, Nick C.;Jack, Clifford R., Jr.;Scheltens, Philip;Thompson, Paul M.
通讯作者：
Thompson, Paul M.
影响因子：
3.7
作者：
Dodds PS;Harris KD;Kloumann IM;Bliss CA;Danforth CM
通讯作者：
Danforth CM
DOI：
10.1016/j.jalz.2011.03.004
发表时间：
2011-05
期刊：
Alzheimer's & dementia : the journal of the Alzheimer's Association
影响因子：
--
作者：
Jack CR Jr;Albert MS;Knopman DS;McKhann GM;Sperling RA;Carrillo MC;Thies B;Phelps CH
通讯作者：
Phelps CH