Alzheimer Center and Department of Neurology, VUmc, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands.
Alzheimer Center and Department of Neurology, VUmc, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands.
Neurobiol Aging. 2018 Jan;61:75-81. doi: 10.1016/j.neurobiolaging.2017.09.011. Epub 2017 Sep 20.
We studied whether gray matter network parameters are associated with rate of clinical progression in nondemented subjects who have abnormal amyloid markers in the cerebrospinal fluid (CSF), that is, predementia Alzheimer's disease. Nondemented subjects (62 with subjective cognitive decline; 160 with mild cognitive impairment (MCI); age = 68 ± 8 years; Mini-Mental State Examination (MMSE) = 28 ± 2.4) were selected from the Amsterdam Dementia Cohort when they had abnormal amyloid in CSF (<640 pg/mL). Networks were extracted from gray matter structural magnetic resonance imaging (MRI), and 9 parameters were calculated. Cox proportional hazards models were used to test associations between each connectivity predictor and rate of progression to MCI or dementia. After a median time of 2.2 years, 122 (55%) subjects showed clinical progression. Lower network parameter values were associated with increased risk for progression, with the strongest hazard ratio of 0.29 for clustering (95% confidence interval = 0.12-0.70; p < 0.01). Results remained after correcting for tau, hippocampal volume, and MMSE scores. Our results suggest that at predementia stages, gray matter network parameters may have use to identify subjects who will show fast clinical progression.
我们研究了灰质网络参数是否与脑脊液（CSF）中存在异常淀粉样蛋白标志物的非痴呆受试者的临床进展速度有关，即前驱期阿尔茨海默病。从阿姆斯特丹痴呆队列中选择了非痴呆受试者（62 名有主观认知下降；160 名有轻度认知障碍（MCI）；年龄= 68 ± 8 岁；迷你精神状态检查（MMSE）= 28 ± 2.4），当他们的 CSF 中有异常淀粉样蛋白时（<640 pg/mL）。从灰质结构磁共振成像中提取网络，并计算了 9 个参数。使用 Cox 比例风险模型来测试每个连接预测因子与向 MCI 或痴呆进展的速度之间的关联。在中位数为 2.2 年的时间后，122 名（55%）受试者出现了临床进展。较低的网络参数值与进展风险增加相关，聚类的最强风险比为 0.29（95%置信区间= 0.12-0.70；p < 0.01）。在校正了 tau、海马体积和 MMSE 评分后，结果仍然存在。我们的结果表明，在前驱期阶段，灰质网络参数可能有助于识别表现出快速临床进展的受试者。
