Characterizing heterogeneity in the progression of Alzheimer's disease using longitudinal clinical and neuroimaging biomarkers.
Characterizing heterogeneity in the progression of Alzheimer's disease using longitudinal clinical and neuroimaging biomarkers.
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DOI：
10.1016/j.dadm.2018.06.007
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发表时间：
2018-01-01
期刊：
影响因子：
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通讯作者：
Wiens, Jenna
中科院分区：
文献类型：
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作者：
Goyal, Devendra;Tjandra, Donna;Wiens, Jenna
前言：描述阿尔茨海默病(AD)中间疾病阶段的模型是为临床护理和预后提供信息所必需的。然而，目前的模型只使用了可用的生物标志物的一小部分，只捕捉到了沿着疾病发展的整个谱系的粗略变化。我们建议使用机器学习技术以及临床、生化和神经成像生物标记物来表征进展到AD的特征。方法：我们使用了来自阿尔茨海默病神经成像计划的1624名参与者的大型多模式纵向生物标记物以及人口统计学和基因信息。使用隐马尔可夫模型，我们描述了疾病的中间阶段。我们通过比较首次临床诊断为阿尔茨海默病的时间来验证推断的疾病轨迹。我们训练了L2正则化Logistic回归模型来预测疾病轨迹，并在测试集上评估了其判别性能。结果：我们识别了12种不同的疾病状态。进展为AD通常是通过这些状态的两种可能途径之一发生的。不同路径在疾病进展速度(平均5.44岁)、淀粉样蛋白和总tau(t-tau)负担(分别为10%和69%)以及海马神经变性(P
INTRODUCTION: Models characterizing intermediate disease stages of Alzheimer's disease (AD) are needed to inform clinical care and prognosis. Current models, however, use only a small subset of available biomarkers, capturing only coarse changes along the complete spectrum of disease progression. We propose the use of machine learning techniques and clinical, biochemical, and neuroimaging biomarkers to characterize progression to AD.METHODS: We used a large multimodal longitudinal data set of biomarkers and demographic and genotype information from 1624 participants from the Alzheimer's Disease Neuroimaging Initiative. Using hidden Markov models, we characterized intermediate disease stages. We validated inferred disease trajectories by comparing time to first clinical AD diagnosis. We trained an L2-regularized logistic regression model to predict disease trajectory and evaluated its discriminative performance on a test set.RESULTS: We identified 12 distinct disease states. Progression to AD occurred most often through one of two possible paths through these states. Paths differed in terms of rate of disease progression (by 5.44years on average), amyloid and total-tau (t-tau) burden (by 10% and 69%, respectively), and hippocampal neurodegeneration (P