Malek-Ahmadi Michael, Lu Sophie, Chan YanYan, Perez Sylvia E, Chen Kewei, Mufson Elliott J
Banner Alzheimer's Institute, Phoenix, AZ, USA.
Williams College, Williamstown, MA, USA.
J Alzheimers Dis. 2017;58(2):575-583. doi: 10.3233/JAD-161233.
Within neuropsychology, the term dispersion refers to the degree of variation in performance between different cognitive domains for an individual. Previous studies have demonstrated that cognitively normal individuals with higher dispersion are at an increased risk for progressing to mild cognitive impairment (MCI) and Alzheimer's disease (AD). Therefore, we determined 1) whether increased dispersion in older adults was associated with amyloid plaques and neurofibrillary tangles (NFTs) and 2) whether increased cognitive dispersion accurately differentiated MCI and AD from non-cognitively impaired (NCI) individuals. The intra-subject standard deviation (ISD) was used to quantify cognitive dispersion, and receiver operator characteristic (ROC) analysis determined whether ISD differentiated MCI and AD from NCI. Neuropathological scores for diffuse plaques (DPs), neuritic plaques (NPs), and NFTs were used as outcome measures in a series of negative binomial regression models. Regression analyses found that increased ISD was associated with increased NFT pathology (β= 10.93, SE = 3.82, p = 0.004), but not with DPs (β= 1.33, SE = 8.85, p = 0.88) or NPs (β= 14.64, SE = 8.45, p = 0.08) after adjusting for age at death, gender, education, APOE ɛ4 status, and clinical diagnosis. An interaction term of ISD with age at death also showed a significant negative association (β= -0.13, SE = 0.04, p = 0.004), revealing an age-dependent association between ISD with NFTs. The ISD failed to show an acceptable level of diagnostic accuracy for MCI (AUC = 0.60). These findings suggest that increased cognitive dispersion is related to NFT pathology where age significantly affects this association.
在神经心理学中，“离散度”一词指个体不同认知领域之间表现的变化程度。先前的研究表明，离散度较高的认知正常个体进展为轻度认知障碍（MCI）和阿尔茨海默病（AD）的风险增加。因此，我们确定了：1）老年人离散度增加是否与淀粉样斑块和神经原纤维缠结（NFTs）相关；2）认知离散度增加是否能准确区分MCI和AD与非认知障碍（NCI）个体。采用受试者内标准差（ISD）来量化认知离散度，并通过受试者工作特征（ROC）分析确定ISD是否能区分MCI和AD与NCI。在一系列负二项回归模型中，将弥漫性斑块（DPs）、神经炎斑块（NPs）和NFTs的神经病理学评分用作结果指标。回归分析发现，在调整死亡年龄、性别、教育程度、APOE ε4状态和临床诊断后，ISD增加与NFT病理学增加相关（β = 10.93，SE = 3.82，p = 0.004），但与DPs（β = 1.33，SE = 8.85，p = 0.88）或NPs（β = 14.64，SE = 8.45，p = 0.08）无关。ISD与死亡年龄的交互项也显示出显著的负相关（β = -0.13，SE = 0.04，p = 0.004），揭示了ISD与NFTs之间的年龄依赖性关联。ISD未能显示出对MCI的可接受诊断准确性水平（AUC = 0.60）。这些发现表明，认知离散度增加与NFT病理学相关，年龄对这种关联有显著影响。
