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Neurology:大脑皮质厚度与认知能力相关

来源:生物谷 2011-12-22 10:58

麻省总医院的Bradford Dickerson博士等人近日在《神经学》(Neurology)杂志上报道称,大脑皮质变薄与认知能力下降有关。该报道中研究人员观察了大脑的9个区域,发现这些区域大脑皮质厚度较低而认知能力正常的患者,其认知能力在3年后有所下降。

此前研究人员发现了一种名为ADsig的生物标记,可用来标记大脑皮质的厚度,并证实大脑皮质变薄是轻度阿尔茨海默病性痴呆的可靠标记,并能预测阿尔茨海默病患者的认知障碍。

该研究中,通过MRI检查受试者的脑皮质厚度,并将159名认知能力正常者依照ADsig分为3组。19名脑皮质厚度至少比平均水平低一个标准差者被认为是发生认知障碍的高风险者,称为低ADsig组;另外116名受试者为平均ADsig组,其脑皮质厚度在平均水平上下一个标准差范围内;最后24名为高ADsig组,其脑皮质厚度比平均水平至少高一个标准差。

3年后,125名受试者的测试数据被认为有认知能力改变,其中包括:9名受试者的综合测试结果显示有认知能力下降;高危险组的14名受试者中有3名发生了认知能力下降,占21.4%;平均ADsig组的90名受试者中有6名发生了认知能力下降,占6.6%;高ADsig组的21名受试者其认知能力均没有下降。Logistic回归分析发现,基线ADsig水平与认知能力下降的相关性较强,其脑皮质厚度每下降一个标准差,认知能力的下降程度约为3倍。

作者称,该研究为检测发生阿尔茨海默病的风险提供了新的方法,在老年痴呆疾病的检测及预后判断中具有重要意义。(生物谷bioon.com)

MRI cortical thickness biomarker predicts AD-like CSF and cognitive decline in normal adults

Bradford C. Dickerson, MD and David A. Wolk, MD On behalf of the Alzheimer's Disease Neuroimaging Initiative.

Objective: New preclinical Alzheimer disease (AD) diagnostic criteria have been developed using biomarkers in cognitively normal (CN) adults. We implemented these criteria using an MRI biomarker previously associated with AD dementia, testing the hypothesis that individuals at high risk for preclinical AD would be at elevated risk for cognitive decline.

Methods: The Alzheimer's Disease Neuroimaging Initiative database was interrogated for CN individuals. MRI data were processed using a published set of a priori regions of interest to derive a single measure known as the AD signature (ADsig). Each individual was classified as ADsig-low (≥1 SD below the mean: high risk for preclinical AD), ADsig-average (within 1 SD of mean), or ADsig-high (≥1 SD above mean). A 3-year cognitive decline outcome was defined a priori using change in Clinical Dementia Rating sum of boxes and selected neuropsychological measures.

Results: Individuals at high risk for preclinical AD were more likely to experience cognitive decline, which developed in 21% compared with 7% of ADsig-average and 0% of ADsig-high groups (p = 0.03). Logistic regression demonstrated that every 1 SD of cortical thinning was associated with a nearly tripled risk of cognitive decline (p= 0.02). Of those for whom baseline CSF data were available, 60% of the high risk for preclinical AD group had CSF characteristics consistent with AD while 36% of the ADsig-average and 19% of the ADsig-high groups had such CSF characteristics (p = 0.1).

Conclusions: This approach to the detection of individuals at high risk for preclinical AD-identified in single CN individuals using this quantitative ADsig MRI biomarker-may provide investigators with a population enriched for AD pathobiology and with a relatively high likelihood of imminent cognitive decline consistent with prodromal AD.

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