Hayden Kathleen M, Kuchibhatla Maragatha, Romero Heather R, Plassman Brenda L, Burke James R, Browndyke Jeffrey N, Welsh-Bohmer Kathleen A
Joseph and Kathleen Bryan ADRC, Duke University Medical Center, Durham, NC.
Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC.
Am J Geriatr Psychiatry. 2014 Nov;22(11):1364-74. doi: 10.1016/j.jagp.2013.07.008. Epub 2013 Sep 27.
Cognitive profiles for pre-clinical Alzheimer disease (AD) can be used to identify groups of individuals at risk for disease and better characterize pre-clinical disease. Profiles or patterns of performance as pre-clinical phenotypes may be more useful than individual test scores or measures of global decline.
To evaluate patterns of cognitive performance in cognitively normal individuals to derive latent profiles associated with later onset of disease using a combination of factor analysis and latent profile analysis.
The National Alzheimer Coordinating Centers collect data, including a battery of neuropsychological tests, from participants at 29 National Institute on Aging-funded Alzheimer Disease Centers across the United States. Prior factor analyses of this battery demonstrated a four-factor structure comprising memory, attention, language, and executive function. Factor scores from these analyses were used in a latent profile approach to characterize cognition among a group of cognitively normal participants (N = 3,911). Associations between latent profiles and disease outcomes an average of 3 years later were evaluated with multinomial regression models. Similar analyses were used to determine predictors of profile membership.
Four groups were identified; each with distinct characteristics and significantly associated with later disease outcomes. Two groups were significantly associated with development of cognitive impairment. In post hoc analyses, both the Trail Making Test Part B, and a contrast score (Delayed Recall - Trails B), significantly predicted group membership and later cognitive impairment.
Latent profile analysis is a useful method to evaluate patterns of cognition in large samples for the identification of preclinical AD phenotypes; comparable results, however, can be achieved with very sensitive tests and contrast scores.
临床前阿尔茨海默病（AD）的认知概况可用于识别有患病风险的个体群体，并更好地描述临床前疾病特征。作为临床前表型的表现概况或模式可能比个体测试分数或整体衰退指标更有用。
使用因子分析和潜在类别分析相结合的方法，评估认知正常个体的认知表现模式，以得出与疾病后期发病相关的潜在类别。
国家阿尔茨海默病协调中心从美国29个由美国国立衰老研究所资助的阿尔茨海默病中心的参与者那里收集数据，包括一系列神经心理学测试。此前对该测试组合进行的因子分析显示出一个四因子结构，包括记忆、注意力、语言和执行功能。这些分析得出的因子分数被用于潜在类别分析方法，以描述一组认知正常参与者（N = 3911）的认知情况。使用多项回归模型评估潜在类别与平均3年后疾病结局之间的关联。类似的分析用于确定类别归属的预测因素。
识别出四组；每组都有不同的特征，并且与疾病后期结局显著相关。两组与认知障碍的发展显著相关。在事后分析中，连线测验B部分以及一个对比分数（延迟回忆 - 连线测验B）均显著预测了类别归属和后期认知障碍。
潜在类别分析是评估大样本认知模式以识别临床前AD表型的有用方法；然而，使用非常敏感的测试和对比分数也可以获得类似的结果。
