Edmonds Emily C, Eppig Joel, Bondi Mark W, Leyden Kelly M, Goodwin Bailey, Delano-Wood Lisa, McDonald Carrie R
From the Department of Psychiatry (E.C.E., M.W.B., K.M.L., B.G., L.D.-W., C.R.M.), School of Medicine, University of California San Diego, La Jolla; Joint Doctoral Program in Clinical Psychology (J.E.), San Diego State University/University of California San Diego; and Veterans Affairs San Diego Healthcare System (M.W.B., L.D.-W.), CA.
Neurology. 2016 Nov 15;87(20):2108-2116. doi: 10.1212/WNL.0000000000003326. Epub 2016 Oct 19.
We investigated differences in regional cortical thickness between previously identified empirically derived mild cognitive impairment (MCI) subtypes (amnestic MCI, dysnomic MCI, dysexecutive/mixed MCI, and cluster-derived normal) in order to determine whether these cognitive subtypes would show different patterns of cortical atrophy.
Participants were 485 individuals diagnosed with MCI and 178 cognitively normal individuals from the Alzheimer's Disease Neuroimaging Initiative. Cortical thickness estimates were computed for 32 regions of interest per hemisphere. Statistical group maps compared each MCI subtype to cognitively normal participants and to one another.
The pattern of cortical thinning observed in each MCI subtype corresponded to their cognitive profile. No differences in cortical thickness were found between the cluster-derived normal MCI subtype and the cognitively normal group. Direct comparison between MCI subtypes suggested that the cortical thickness patterns reflect increasing disease severity.
There is an ordered pattern of cortical atrophy among patients with MCI that coincides with their profiles of increasing cognitive dysfunction. This heterogeneity is not captured when patients are grouped by conventional diagnostic criteria. Results in the cluster-derived normal group further support the premise that the conventional MCI diagnostic criteria are highly susceptible to false-positive diagnostic errors. Findings suggest a need to (1) improve the diagnostic criteria by reducing reliance on conventional screening measures, rating scales, and a single memory measure in order to avoid false-positive errors; and (2) divide MCI samples into meaningful subgroups based on cognitive and biomarkers profiles-a method that may provide better staging of MCI and inform prognosis.
我们研究了先前通过经验确定的轻度认知障碍(MCI)亚型(遗忘型MCI、命名性MCI、执行功能障碍/混合型MCI以及聚类衍生正常组)之间区域皮质厚度的差异,以确定这些认知亚型是否会表现出不同的皮质萎缩模式。
参与者包括来自阿尔茨海默病神经影像倡议组织的485名被诊断为MCI的个体和178名认知正常的个体。计算每个半球32个感兴趣区域的皮质厚度估计值。统计组图比较了每种MCI亚型与认知正常参与者以及相互之间的差异。
在每种MCI亚型中观察到的皮质变薄模式与其认知特征相对应。聚类衍生正常MCI亚型与认知正常组之间未发现皮质厚度差异。MCI亚型之间的直接比较表明,皮质厚度模式反映了疾病严重程度的增加。
MCI患者中存在一种有序的皮质萎缩模式,与他们认知功能障碍加重的特征相吻合。当根据传统诊断标准对患者进行分组时,这种异质性并未被捕捉到。聚类衍生正常组的结果进一步支持了传统MCI诊断标准极易出现假阳性诊断错误这一前提。研究结果表明需要:(1)通过减少对传统筛查措施、评定量表和单一记忆测量的依赖来改进诊断标准,以避免假阳性错误;(2)根据认知和生物标志物特征将MCI样本分为有意义的亚组——这种方法可能会为MCI提供更好的分期并为预后提供信息。