Clinical utility of self- and informant-reported memory, attention, and spatial navigation in detecting biomarkers associated with Alzheimer disease in clinically normal adults

Taylor F Levine; Samantha L Allison; Steven J Dessenberger; Denise Head; Alzheimer’s Disease Neuroimaging Initiative

doi:10.1017/S1355617723000528

Clinical utility of self- and informant-reported memory, attention, and spatial navigation in detecting biomarkers associated with Alzheimer disease in clinically normal adults

J Int Neuropsychol Soc. 2024 Mar;30(3):232-243. doi: 10.1017/S1355617723000528. Epub 2023 Aug 29.

Authors

Taylor F Levine¹, Samantha L Allison², Steven J Dessenberger¹, Denise Head^{1

3

4}; Alzheimer’s Disease Neuroimaging Initiative

Affiliations

¹ Department of Psychological and Brain Sciences, Washington University, St. Louis, MO, USA.
² Neurosciences Institute at Intermountain Medical Center, Murray, UT, USA.
³ Charles F. and Joanna Knight Alzheimer Disease Research Center, Washington University, St. Louis, MO, USA.
⁴ Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA.

PMID: 37642015
DOI: 10.1017/S1355617723000528

Abstract

Objective: Preclinical Alzheimer disease (AD) has been associated with subtle changes in memory, attention, and spatial navigation abilities. The current study examined whether self- and informant-reported domain-specific cognitive changes are sensitive to AD-associated biomarkers.

Method: Clinically normal adults aged 56-93 and their informants completed the memory, divided attention, and visuospatial abilities (which assesses spatial navigation) subsections of the Everyday Cognition Scale (ECog). Reliability and validity of these subsections were examined using Cronbach's alpha and confirmatory factor analysis. Logistic regression was used to examine the ability of ECog subsections to predict AD-related biomarkers (cerebrospinal fluid (CSF) ptau₁₈₁/Aβ₄₂ ratio (N = 371) or hippocampal volume (N = 313)). Hierarchical logistic regression was used to examine whether the self-reported subsections continued to predict biomarkers when controlling for depressive symptomatology if available (N = 197). Additionally, logistic regression was used to examine the ability of neuropsychological composites assessing the same or similar cognitive domains as the subsections (memory, executive function, and visuospatial abilities) to predict biomarkers to allow for comparison of the predictive ability of subjective and objective measures.

Results: All subsections demonstrated appropriate reliability and validity. Self-reported memory (with outliers removed) was the only significant predictor of AD biomarker positivity (i.e., CSF ptau₁₈₁/Aβ₄₂ ratio; p = .018) but was not significant when examined in the subsample with depressive symptomatology available (p = .517). Self-reported memory (with outliers removed) was a significant predictor of CSF ptau₁₈₁/Aβ₄₂ ratio biomarker positivity when the objective memory composite was included in the model.

Conclusions: ECog subsections were not robust predictors of AD biomarker positivity.

Keywords: Everyday Cognition Scale; attention; biomarkers; memory; preclinical Alzheimer disease; spatial navigation.

MeSH terms

Alzheimer Disease* / psychology
Amyloid beta-Peptides / cerebrospinal fluid
Attention
Biomarkers / cerebrospinal fluid
Cognitive Dysfunction* / psychology
Humans
Neuropsychological Tests
Peptide Fragments / cerebrospinal fluid
Reproducibility of Results
Spatial Navigation*
tau Proteins / cerebrospinal fluid

Substances

Amyloid beta-Peptides
tau Proteins
Biomarkers
Peptide Fragments