Pre-clinical cognitive phenotypes for Alzheimer disease: a latent profile approach.

Published

Journal Article

BACKGROUND: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. OBJECTIVE: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. METHODS: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. RESULTS: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. CONCLUSIONS: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.

Full Text

Duke Authors

Cited Authors

  • Hayden, KM; Kuchibhatla, M; Romero, HR; Plassman, BL; Burke, JR; Browndyke, JN; Welsh-Bohmer, KA

Published Date

  • November 2014

Published In

Volume / Issue

  • 22 / 11

Start / End Page

  • 1364 - 1374

PubMed ID

  • 24080384

Pubmed Central ID

  • 24080384

Electronic International Standard Serial Number (EISSN)

  • 1545-7214

International Standard Serial Number (ISSN)

  • 1064-7481

Digital Object Identifier (DOI)

  • 10.1016/j.jagp.2013.07.008

Language

  • eng