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Relative Value of Diverse Brain MRI and Blood-Based Biomarkers for Predicting Cognitive Decline in the Elderly

机译:不同脑MRI和血液生物标志物的相对价值预测老年人认知下降

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Cognitive decline accompanies many debilitating illnesses, including Alzheimer's disease (AD). In old age, brain tissue loss also occurs along with cognitive decline. Although blood tests are easier to perform than brain MRI, few studies compare brain scans to standard blood tests to see which kinds of information best predict future decline. In 504 older adults from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we first used linear regression to assess the relative value of different types of data to predict cognitive decline, including 196 blood panel biomarkers, 249 MRI biomarkers obtained from the FreeSurfer software, demographics, and the AD-risk gene APOE. A subset of MRI biomarkers was the strongest predictor. There was no specific blood marker that increased predictive accuracy on its own, we found that a novel unsupervised learning method, CorEx, captured weak correlations among blood markers, and the resulting clusters offered unique predictive power.
机译:认知次数伴随着许多衰弱的疾病,包括阿尔茨海默病(广告)。在晚年中,脑组织损失也发生在认知下​​降之外。虽然血液测试比脑MRI更容易进行,但很少有研究比较大脑扫描对标准血液检查,以了解哪种信息最能预测未来的下降。在504名来自阿尔茨海默病神经影像倡议(ADNI)的老年人中,我们首先使用线性回归来评估不同类型数据的相对价值,以预测认知下降,包括196个血板生物标志物,从FreeSurfer软件,人口统计学中获得的249个MRI生物标志物。和AD风险基因Apoe。 MRI生物标志物的子集是最强的预测因子。没有特定的血迹,以其自身提高预测准确性,我们发现一种小型无监督的学习方法,Corex,捕获血迹之间的相关性,并且所产生的集群提供独特的预测力。

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