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结合多基因风险评分与体积磁共振成像和认知测量可改善对从轻度认知障碍进展为阿尔茨海默病的预测。

Combining Polygenic Hazard Score With Volumetric MRI and Cognitive Measures Improves Prediction of Progression From Mild Cognitive Impairment to Alzheimer's Disease.

作者信息

Kauppi Karolina, Fan Chun Chieh, McEvoy Linda K, Holland Dominic, Tan Chin Hong, Chen Chi-Hua, Andreassen Ole A, Desikan Rahul S, Dale Anders M

机构信息

Department of Radiology, University of California, San Diego, La Jolla, CA, United States.

Department of Radiation Sciences, University of Umea, Umea, Sweden.

出版信息

Front Neurosci. 2018 Apr 30;12:260. doi: 10.3389/fnins.2018.00260. eCollection 2018.

Abstract

Improved prediction of progression to Alzheimer's Disease (AD) among older individuals with mild cognitive impairment (MCI) is of high clinical and societal importance. We recently developed a polygenic hazard score (PHS) that predicted age of AD onset above and beyond . Here, we used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to further explore the potential clinical utility of PHS for predicting AD development in older adults with MCI. We examined the predictive value of PHS alone and in combination with baseline structural magnetic resonance imaging (MRI) data on performance on the Mini-Mental State Exam (MMSE). In survival analyses, PHS significantly predicted time to progression from MCI to AD over 120 months ( = 1.07e-5), and PHS was significantly more predictive than alone ( = 0.015). Combining PHS with baseline brain atrophy score and/or MMSE score significantly improved prediction compared to models without PHS (three-factor model = 4.28e-17). Prediction model accuracies, sensitivities and area under the curve were also improved by including PHS in the model, compared to only using atrophy score and MMSE. Further, using linear mixed-effect modeling, PHS improved the prediction of change in the Clinical Dementia Rating-Sum of Boxes (CDR-SB) score and MMSE over 36 months in patients with MCI at baseline, beyond both and baseline levels of brain atrophy. These results illustrate the potential clinical utility of PHS for assessment of risk for AD progression among individuals with MCI both alone, or in conjunction with clinical measures of prodromal disease including measures of cognitive function and regional brain atrophy.

摘要

改善对轻度认知障碍(MCI)老年个体发展为阿尔茨海默病(AD)的预测具有高度的临床和社会重要性。我们最近开发了一种多基因风险评分(PHS),它能预测AD发病年龄,且超出了其他因素的预测能力。在此,我们使用来自阿尔茨海默病神经影像倡议(ADNI)的数据,进一步探索PHS在预测MCI老年成人AD发展方面的潜在临床效用。我们单独检查了PHS的预测价值,并将其与基线结构磁共振成像(MRI)数据相结合,以评估简易精神状态检查表(MMSE)的表现。在生存分析中,PHS显著预测了120个月内从MCI进展到AD的时间( = 1.07e - 5),并且PHS的预测能力显著高于单独使用其他因素( = 0.015)。与不使用PHS的模型相比,将PHS与基线脑萎缩评分和/或MMSE评分相结合显著改善了预测效果(三因素模型 = 4.28e - 17)。与仅使用萎缩评分和MMSE相比,在模型中纳入PHS也提高了预测模型的准确性、敏感性和曲线下面积。此外,使用线性混合效应模型,PHS改善了对基线为MCI的患者在36个月内临床痴呆评定量表-方框总和(CDR - SB)评分和MMSE变化的预测,超过了其他因素和基线脑萎缩水平。这些结果说明了PHS在评估MCI个体AD进展风险方面的潜在临床效用,无论是单独使用,还是与前驱疾病的临床指标(包括认知功能和区域脑萎缩指标)结合使用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1826/5937163/11a45e3a59c4/fnins-12-00260-g0001.jpg

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