Pre-clinical cognitive phenotypes for Alzheimer disease: a latent profile approach.
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.
Joseph and Kathleen Bryan ADRC, Duke University Medical Center, Durham, NC. Electronic address: khayden@duke.edu.
Kathleen M
KM
Hayden
Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC.
Maragatha
M
Kuchibhatla
Joseph and Kathleen Bryan ADRC, Duke University Medical Center, Durham, NC.
Heather R
HR
Romero
Joseph and Kathleen Bryan ADRC, Duke University Medical Center, Durham, NC.
Brenda L
BL
Plassman
Joseph and Kathleen Bryan ADRC, Duke University Medical Center, Durham, NC.
James R
JR
Burke
Joseph and Kathleen Bryan ADRC, Duke University Medical Center, Durham, NC.
Jeffrey N
JN
Browndyke
Joseph and Kathleen Bryan ADRC, Duke University Medical Center, Durham, NC.
Kathleen A
KA
Welsh-Bohmer
D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000175:diagnosis / Q000209:etiology*; D001288:Attention; D003071:Cognition; D060825:Cognitive Dysfunction / Q000175:diagnosis / Q000209:etiology; D056344:Executive Function; D005163:Factor Analysis, Statistical; D005260:Female; D006801:Humans; D007802:Language; D008297:Male; D008568:Memory; D009483:Neuropsychological Tests; D010641:Phenotype; D062706:Prodromal Symptoms; D012307:Risk Factors
Latent profile analysis; factor analysis; longitudinal study; neuropsychological test