P2–200: Self‐ versus informant‐based cognitive complaints: Relation of E‐Cog scores to imaging, biomarkers and clinical Status in ADNI‐2

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/152591/1/alzjjalz201305845.pd

P3‐185: Predictors of longitudinal cognitive decline in a community‐based sample of Spanish‐ and English‐speaking older adults

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153025/1/alzjjalz2008051751.pd

Education amplifies brain atrophy effect on cognitive decline: implications for cognitive reserve.

Level of education is often regarded as a proxy for cognitive reserve in older adults. This implies that brain degeneration has a smaller effect on cognitive decline in those with more education, but this has not been directly tested in previous research. We examined how education, quantitative magnetic resonance imaging-based measurement of brain degeneration, and their interaction affect cognitive decline in diverse older adults spanning the spectrum from normal cognition to dementia. Gray matter atrophy was strongly related to cognitive decline. While education was not related to cognitive decline, brain atrophy had a stronger effect on cognitive decline in those with more education. Importantly, high education was associated with slower decline in individuals with lesser atrophy but with faster decline in those with greater atrophy. This moderation effect was observed in Hispanics (who had high heterogeneity of education) but not in African-Americans or Caucasians. These results suggest that education is an indicator of cognitive reserve in individuals with low levels of brain degeneration, but the protective effect of higher education is rapidly depleted as brain degeneration progresses

Vascular Risk Predicts Plasma Amyloid β 42/40 Through Cerebral Amyloid Burden in Apolipoprotein E ε4 Carriers

BackgroundUnderstanding the neurobiological underpinnings between established multimodal dementia risk factors and noninvasive blood-based biomarkers may lead to greater precision and earlier identification of older adults at risk of accelerated decline and dementia. We examined whether key vascular and genetic risk impact the association between cerebral amyloid burden and plasma aβ (amyloid β) 42/40 in nondemented older adults.MethodsWe used nondemented older adults from the UCD-ADRC (University of California, Davis-Alzheimer's Disease Research Center) study (n=96) and Alzheimer's Disease Neuroimaging Initiative (n=104). Alzheimer's Disease Neuroimaging Initiative was examined as confirmatory study cohort. We followed a cross-sectional design and examined linear regression followed by mediation analyses. Vascular risk score was obtained as the sum of hypertension, diabetes, hyperlipidemia, coronary artery disease, and cerebrovascular disease. Apolipoprotein E (APOE) ε4+ risk was genotyped, and plasma aβ42 and aβ40 were assayed. Cerebral amyloid burden was quantified using Florbetapir-PET scans. Baseline age was included as a covariate in all models.ResultsVascular risk significantly predicted cerebral amyloid burden in Alzheimer's Disease Neuroimaging Initiative but not in the UCD-ADRC cohort. Cerebral amyloid burden was associated with plasma aβ 42/40 in both cohorts. Higher vascular risk increased cerebral amyloid burden was indirectly associated with reduced plasma aβ 42/40 in Alzheimer's Disease Neuroimaging Initiative but not in UCD-ADRC cohort. However, when stratified by APOE ε4+ risk, we consistently observed this indirect relationship only in APOE ε4+ carriers across both cohorts.ConclusionsVascular risk is indirectly associated with the level of plasma aβ 42/40 via cerebral amyloid burden only in APOE ε4+ carriers. Nondemented older adults with genetic vulnerability to dementia and accelerated decline may benefit from careful monitoring of vascular risk factors directly associated with cerebral amyloid burden and indirectly with plasma aβ 42/40

The Latent Factor Structure Underlying Regional Brain Volume Change and Its Relation to Cognitive Change in Older Adults

ObjectiveLate-life changes in cognition and brain integrity are both highly multivariate, time-dependent processes that are essential for understanding cognitive aging and neurodegenerative disease outcomes. The present study seeks to identify a latent variable model capable of efficiently reducing a multitude of structural brain change magnetic resonance imaging (MRI) measurements into a smaller number of dimensions. We further seek to demonstrate the validity of this model by evaluating its ability to reproduce patterns of coordinated brain volume change and to explain the rate of cognitive decline over time.MethodWe used longitudinal cognitive data and structural MRI scans, obtained from a diverse sample of 358 participants (Mage = 74.81, SD = 7.17), to implement latent variable models for measuring brain change and to estimate the effects of these brain change factors on cognitive decline.ResultsResults supported a bifactor model for brain change with four group factors (prefrontal, temporolimbic, medial temporal, and posterior association) and one general change factor (global atrophy). Atrophy in the global (β = 0.434, SE = 0.070), temporolimbic (β = 0.275, SE = 0.085), and medial temporal (β = 0.240, SE = 0.085) factors were the strongest predictors of global cognitive decline. Overall, the brain change model explained 59% of the variance in global cognitive slope.ConclusionsThe current results suggest that brain change across 27 bilateral regions of interest can be grouped into five change factors, three of which (global gray matter, temporolimbic, and medial temporal lobe atrophy) are strongly associated with cognitive decline. (PsycInfo Database Record (c) 2021 APA, all rights reserved)