Heterogeneous ability profiles may be a unique indicator of impending cognitive decline

Examining the Stability and Predictive Utility of Across- and Within-Domain Intra-Individual Variability in Mild Cognitive Impairment

OBJECTIVE

Dispersion is a form of intra-individual variability across neuropsychological tests that has been shown to predict cognitive decline. However, few studies have investigated the stability and predictive utility of both across- and within-domain dispersion. The current study aims to fill these gaps in the literature by examining multiple indices of dispersion in a longitudinal clinical sample of individuals diagnosed with mild cognitive impairment (MCI) at baseline.

METHOD

Two hundred thirty-eight MCI patients from a cognitive disorders clinic underwent testing at baseline and after approximately 1.5 years. Linear regression was used to examine whether baseline across- and within-domain dispersion predicted cognitive decline in individuals whose diagnostic classification progressed to dementia (i.e., MCI-Decline) and those who retained an MCI diagnosis at follow-up (i.e., MCI-Stable). Cognitive decline was operationalized dichotomously using group status and continuously using standardized regression-based (SRB) z-scores.

RESULTS

Dispersion variables at baseline and follow-up were positively correlated in both groups, with the exception of within-domain executive functioning and language dispersion in the MCI-Decline group. None of the dispersion variables predicted diagnostic conversion to MCI. Using SRB z-scores, greater across-domain dispersion predicted greater overall cognitive decline at follow-up, but this was not the case for within-domain variables with the exception of visuospatial skills.

CONCLUSIONS

Results suggest that across- and within-domain dispersion are relatively stable across time, and that across-domain dispersion is predictive of subtle cognitive decline in patients with MCI. However, these results also highlight that findings may differ based on the tests included in dispersion calculations.

A Latent Transition Analysis Model to Assess Change in Cognitive States over Three Occasions: Results from the Rush Memory and Aging Project

BACKGROUND

Conceptualizing cognitive aging as a step-sequential process is useful in identifying particular stages of cognitive function and impairment.

OBJECTIVE

We applied latent transition analysis (LTA) to determine 1) whether the underlying structure of cognitive profiles found at every measurement occasion are uniform across three waves of assessment, 2) whether class-instability is predictive of distal outcomes, and 3) whether class-reversions from impaired to non-impaired using latent modelling is lower than when using clinical criteria of mild cognitive impairment (MCI).

METHODS

A mover-stayer LTA model with dementia as a distal outcome was specified to model transitions of ten neuropsychological measures over three annual waves in the Rush Memory and Aging Project (n = 1,661). The predictive validity of the mover-stayer status for incident Alzheimer's disease (AD) was then assessed.

RESULTS

We identified a five-class model across the three time-points: Mixed-Domain Impairment, Memory-Specific Impairment, Frontal Impairment, Average, and Superior Cognition. None of the individuals in the Impairment classes reverted to the Average or Superior classes. Conventional MCI classification identified 26.4% and 14.1% at Times 1 and 2 as false-positive cases. "Movers" had 87% increased risk of developing dementia compared to those classified as "Stayers".

CONCLUSION

Our findings support the use of latent variable modelling that incorporates comprehensive neuropsychological assessment to identify and classify cognitive impairment.

Cognitive dispersion is a sensitive marker for early neurodegenerative changes and functional decline in nondemented older adults

OBJECTIVE

Intraindividual cognitive variability (IIV), a measure of within-person variability across cognitive measures at a single time point, is associated with mild cognitive impairment (MCI) and Alzheimer's disease (AD). Little is known regarding brain changes underlying IIV, or the relationship between IIV and functional ability. Therefore, we investigated the association between IIV and cerebral atrophy in AD-vulnerable regions and everyday functioning in nondemented older adults.

METHOD

736 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants (285 cognitively normal [CN]; 451 MCI) underwent neuropsychological testing and serial MRI over 2 years. Linear mixed effects models examined the association between baseline IIV and change in entorhinal cortex thickness, hippocampal volume, and everyday functioning.

RESULTS

Adjusting for age, sex, apolipoprotein E genotype, amyloid-β positivity, and mean level of cognitive performance, higher baseline IIV predicted faster rates of entorhinal and hippocampal atrophy, as well as functional decline. Higher IIV was associated with both entorhinal and hippocampal atrophy among MCI participants but selective vulnerability of the entorhinal cortex among CN individuals.

CONCLUSIONS

IIV was associated with more widespread medial temporal lobe (MTL) atrophy in individuals with MCI relative to CN, suggesting that IIV may be tracking advancing MTL pathologic changes across the continuum of aging, MCI, and dementia. Findings suggest that cognitive dispersion may be a sensitive marker of neurodegeneration and functional decline in nondemented older adults. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Cognitive Variability Predicts Incident Alzheimer's Disease and Mild Cognitive Impairment Comparable to a Cerebrospinal Fluid Biomarker

BACKGROUND

Alzheimer's disease (AD) biomarkers are emerging as critically important for disease detection and monitoring. Most biomarkers are obtained through invasive, resource-intense procedures. A cognitive marker, intra-individual cognitive variability (IICV) may provide an alternative or adjunct marker of disease risk for individuals unable or disinclined to undergo lumbar puncture.

OBJECTIVE

To contrast risk of incident AD and mild cognitive impairment (MCI) associated with IICV to risk associated with well-established biomarkers: cerebrospinal fluid (CSF) phosphorylated tau protein (p-tau181) and amyloid-β 42 (Aβ42) peptide.

METHODS

Dispersion in cognitive performance, IICV, was estimated with a published algorithm, and included Trail Making Test A and B, Rey Auditory Verbal Learning Test (RAVLT), and the American National Adult Reading Test (ANART). CSF biomarkers were expressed as a ratio: p-tau181/Aβ42, wherein high values signified pathognomonic profiles. Logistic regression models included longitudinal data from 349 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants who completed lumbar puncture. All subjects were cognitively healthy (n = 105) or diagnosed with MCI (n = 244) at baseline. We examined odds of conversion associated with baseline elevations in IICV and/or ratio of CSF p-tau181/Aβ42.

RESULTS

When included in models alone or in combination with CSF p-tau181/Aβ42, one standard IICV unit higher was associated with an estimated odds ratio for incident AD or MCI of 2.81 (95% CI: 1.83-4.33) in the most inclusive sample, and an odds ratio of 3.41 (95% CI: 2.03-5.73) when restricted to participants with MCI. Iterative analyses suggested that IICV independently improved model fit even when individual index components were included in comparative models.

CONCLUSIONS

These analyses provide preliminary support for IICV as a marker of incident AD and MCI. This easily-disseminated, non-invasive marker compared favorably to well-established CSF biomarkers.

Inhibition and Switching in Healthy Aging: A Longitudinal Study

OBJECTIVES

Discrepant findings of age-related effects between cross-sectional and longitudinal studies on executive function (EF) have been described across different studies. The aim of the present study was to examine longitudinal age effects on inhibition and switching, two key subfunctions of EF, calculated from results on the Color Word Interference Test (CWIT).

METHODS

One hundred twenty-three healthy aging individuals (average age 61.4 years; 67% women) performed the CWIT up to three times, over a period of more than 6 years. Measures of inhibition, switching, and combined inhibition and switching were analyzed. A longitudinal linear mixed effects models analysis was run including basic CWIT conditions, and measures of processing speed, retest effect, gender, education, and age as predictors.

RESULTS

After taking all predictors into account, age added significantly to the predictive value of the longitudinal models of (i) inhibition, (ii) switching, and (iii) combined inhibition and switching. The basic CWIT conditions and the processing speed measure added to the predictive value of the models, while retest effect, gender, and education did not.

CONCLUSIONS

The present study on middle-aged to older individuals showed age-related decline in inhibition and switching abilities. This decline was retained even when basic CWIT conditions, processing speed, attrition, gender, and education were controlled. (JINS, 2017, 23, 90-97).

Intraindividual Cognitive Variability in Middle Age Predicts Cognitive Impairment 8-10 Years Later: Results from the Wisconsin Registry for Alzheimer's Prevention

OBJECTIVES

Intraindividual cognitive variability (IICV) has been shown to differentiate between groups with normal cognition, mild cognitive impairment (MCI), and dementia. This study examined whether baseline IICV predicted subsequent mild to moderate cognitive impairment in a cognitively normal baseline sample.

METHODS

Participants with 4 waves of cognitive assessment were drawn from the Wisconsin Registry for Alzheimer's Prevention (WRAP; n=684; 53.6(6.6) baseline age; 9.1(1.0) years follow-up; 70% female; 74.6% parental history of Alzheimer's disease). The primary outcome was Wave 4 cognitive status ("cognitively normal" vs. "impaired") determined by consensus conference; "impaired" included early MCI (n=109), clinical MCI (n=11), or dementia (n=1). Primary predictors included two IICV variables, each based on the standard deviation of a set of scores: "6 Factor IICV" and "4 Test IICV". Each IICV variable was tested in a series of logistic regression models to determine whether IICV predicted cognitive status. In exploratory analyses, distribution-based cutoffs incorporating memory, executive function, and IICV patterns were used to create and test an MCI risk variable.

RESULTS

Results were similar for the IICV variables: higher IICV was associated with greater risk of subsequent impairment after covariate adjustment. After adjusting for memory and executive functioning scores contributing to IICV, IICV was not significant. The MCI risk variable also predicted risk of impairment.

CONCLUSIONS

While IICV in middle-age predicts subsequent impairment, it is a weaker risk indicator than the memory and executive function scores contributing to its calculation. Exploratory analyses suggest potential to incorporate IICV patterns into risk assessment in clinical settings. (JINS, 2016, 22, 1016-1025).

Cognitive variability-A marker for incident MCI and AD: An analysis for the Alzheimer's Disease Neuroimaging Initiative

Introduction

The potential of intra-individual cognitive variability (IICV) to predict incident mild cognitive impairment (MCI) or Alzheimer's disease (AD) was examined and compared to well-established neuroimaging and genetic predictors.

Methods

IICV was estimated using four neuropsychological measures for n = 1324 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants who were cognitively healthy or diagnosed with MCI at baseline. IICV was used to predict time to incident MCI or AD, and compared to hippocampal volume loss and APOE ε4 status via survival analysis.

Results

In survival analyses, controlling for age, education, baseline diagonosis, and APOE ε4 status, likelihood ratio tests indicate that IICV is associated with time to cognitive status change in the full sample (P < .0001), and when the sample was restricted to individuals with MCI at baseline (P < .0001).

Discussion

These findings suggest IICV may be a low-cost, noninvasive alternative to traditional AD biomarkers.