German Center for Neurodegenerative Diseases (DZNE)-Rostock/Greifswald, Rostock, Germany.
Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany.
Alzheimers Dement. 2018 Sep;14(9):1126-1136. doi: 10.1016/j.jalz.2018.04.004. Epub 2018 May 21.
Cognitive change in people at risk of Alzheimer's disease (AD) such as subjective memory complainers is highly variable across individuals.
We used latent class growth modeling to identify distinct classes of nonlinear trajectories of cognitive change over 2 years follow-up from 265 subjective memory complainers individuals (age 70 years and older) of the INSIGHT-preAD cohort. We determined the effect of cortical amyloid load, hippocampus and basal forebrain volumes, and education on the cognitive trajectory classes.
Latent class growth modeling identified distinct nonlinear cognitive trajectories. Education was associated with higher performing trajectories, whereas global amyloid load and basal forebrain atrophy were associated with lower performing trajectories.
Distinct classes of cognitive trajectories were associated with risk and protective factors of AD. These associations support the notion that the identified cognitive trajectories reflect different risk for AD that may be useful for selecting high-risk individuals for intervention trials.
在有患阿尔茨海默病（AD）风险的人群中，如主观记忆抱怨者，其认知变化在个体间具有高度可变性。
我们使用潜在类别增长建模来确定 265 名主观记忆抱怨者个体（年龄在 70 岁及以上）的 INSIGHT-preAD 队列在 2 年随访期间认知变化的非线性轨迹的不同类别。我们确定了皮质淀粉样蛋白负荷、海马体和基底前脑体积以及教育对认知轨迹类别的影响。
潜在类别增长建模确定了不同的非线性认知轨迹。教育与表现较好的轨迹相关，而总体淀粉样蛋白负荷和基底前脑萎缩与表现较差的轨迹相关。
不同的认知轨迹类别与 AD 的风险和保护因素相关。这些关联支持了这样一种观点，即所确定的认知轨迹反映了不同的 AD 风险，这可能有助于为干预试验选择高风险个体。
