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

机译:多样的脑MRI和基于血液的生物标记物对预测老年人认知功能下降的相对价值

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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:认知能力下降伴随着许多使人衰弱的疾病,包括阿尔茨海默氏病(AD)。在老年时,脑组织损失也与认知能力下降一起发生。尽管血液检查比脑部MRI更容易执行,但很少有研究将脑部扫描与标准血液检查相比较,以了解哪种信息最能预测未来的下降。在阿尔茨海默氏病神经影像学倡议(ADNI)的504位成年人中,我们首先使用线性回归评估了不同类型数据的相对价值,以预测认知能力下降,包括196种血液板生物标志物,249种从FreeSurfer软件获得的MRI生物标志物,人口统计数据,以及具有AD风险的基因APOE。 MRI生物标志物的一个子集是最强的预测因子。没有能够自己提高预测准确性的特定血液标志物,我们发现一种新颖的无监督学习方法CorEx捕获了血液标志物之间的弱相关性,并且所得簇提供了独特的预测能力。

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