View in EDS

Signatures of Neuropsychological Test Results in the Long Life Family Study: A Cluster Analysis: A Cluster Analysis

Saved in:
Bibliographic Details
Title: Signatures of Neuropsychological Test Results in the Long Life Family Study: A Cluster Analysis: A Cluster Analysis
Authors: Xiang, Qingyan, Andersen, Stacy L., Sweigart, Benjamin, Gunn, Sophia, Nygaard, Marianne, Perls, Thomas T., Sebastiani, Paola
Source: Journal of Alzheimer’s Disease. 93:1457-1469
Publisher Information: SAGE Publications, 2023.
Publication Year: 2023
Subject Terms: cognition, Male, Aging, Multifactorial Inheritance, Skin Neoplasms, Cognitive Dysfunction/diagnosis, Longevity, neuropsychology, Holistic Health, Neuropsychological Tests, survival, Cognition, longevity, Neuropsychological Tests/statistics & numerical data, 80 and over, Humans, Cluster Analysis, Cognitive Dysfunction, Cognitive Aging/physiology, Cognition/physiology, Aged, Aged, 80 and over, Family Health, Bayes Theorem, Middle Aged, 3. Good health, Cardiovascular Diseases, Cognitive Aging, Female, Dementia, Alzheimer's disease, Biomarkers, cluster analysis
Description: Background: Discovering patterns of cognitive domains and characterizing how these patterns associate with other risk factors and biomarkers can improve our understanding of the determinants of cognitive aging. Objective: To discover patterns of cognitive domains using neuropsychological test results in Long Life Family Study (LLFS) and characterize how these patterns associate with aging markers. Methods: 5,086 LLFS participants were administered neuropsychological tests at enrollment. We performed a cluster analysis of six baseline neuropsychological test scores and tested the association between the identified clusters and various clinical variables, biomarkers, and polygenic risk scores using generalized estimating equations and the Chi-square test. We used Cox regression to correlate the clusters with the hazard of various medical events. We investigated whether the cluster information could enhance the prediction of cognitive decline using Bayesian beta regression. Results: We identified 12 clusters with different cognitive signatures that represent profiles of performance across multiple neuropsychological tests. These signatures significantly correlated with 26 variables including polygenic risk scores, physical and pulmonary functions, and blood biomarkers and were associated with the hazard of mortality ( p Conclusion: The identified cognitive signatures capture multiple domains simultaneously and provide a holistic vision of cognitive function, showing that different patterns of cognitive function can coexist in aging individuals. Such patterns can be used for clinical intervention and primary care.
Document Type: Article
Language: English
ISSN: 1875-8908
1387-2877
DOI: 10.3233/jad-221025
Access URL: https://pubmed.ncbi.nlm.nih.gov/37212095
Rights: URL: https://journals.sagepub.com/page/policies/text-and-data-mining-license
Accession Number: edsair.doi.dedup.....46766f0b39cf61c5abf54924e3ad8a28
Database: OpenAIRE
Description
Abstract:Background: Discovering patterns of cognitive domains and characterizing how these patterns associate with other risk factors and biomarkers can improve our understanding of the determinants of cognitive aging. Objective: To discover patterns of cognitive domains using neuropsychological test results in Long Life Family Study (LLFS) and characterize how these patterns associate with aging markers. Methods: 5,086 LLFS participants were administered neuropsychological tests at enrollment. We performed a cluster analysis of six baseline neuropsychological test scores and tested the association between the identified clusters and various clinical variables, biomarkers, and polygenic risk scores using generalized estimating equations and the Chi-square test. We used Cox regression to correlate the clusters with the hazard of various medical events. We investigated whether the cluster information could enhance the prediction of cognitive decline using Bayesian beta regression. Results: We identified 12 clusters with different cognitive signatures that represent profiles of performance across multiple neuropsychological tests. These signatures significantly correlated with 26 variables including polygenic risk scores, physical and pulmonary functions, and blood biomarkers and were associated with the hazard of mortality ( p Conclusion: The identified cognitive signatures capture multiple domains simultaneously and provide a holistic vision of cognitive function, showing that different patterns of cognitive function can coexist in aging individuals. Such patterns can be used for clinical intervention and primary care.
ISSN:18758908
13872877
DOI:10.3233/jad-221025