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. 2019 Mar:75:178-186.
doi: 10.1016/j.neurobiolaging.2018.10.024. Epub 2018 Nov 2.

Predictors of neurodegeneration differ between cognitively normal and subsequently impaired older adults

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Predictors of neurodegeneration differ between cognitively normal and subsequently impaired older adults

Nicole M Armstrong et al. Neurobiol Aging. 2019 Mar.

Abstract

Effects of Alzheimer's disease (AD) risk factors on brain volume changes may partly explain what happens during the preclinical AD stage in people who develop subsequent cognitive impairment (SI). We investigated predictors of neurodegeneration, measured by MRI-based volume loss, in older adults before diagnosis of cognitive impairment. There were 623 cognitively normal and 65 SI Baltimore Longitudinal Study of Aging participants (age 55-92 years) enrolled in the neuroimaging substudy from 1994 to 2015. Mixed-effects regression was used to assess the associations of AD risk factors (age, APOE e4 carrier status, diabetes, hypertension, obesity, current smoking, and elevated cholesterol) with brain regional volume change among the overall sample and by diagnostic status. Older age, APOE e4 carrier status, hypertension, and HDL cholesterol were predictors of volumetric change. Among SI participants only, hypertension, obesity, and APOE e4 carrier status were associated with greater declines in selected brain regions. SI individuals in the preclinical AD stage are vulnerable to risk factors that have either a protective or null effect in cognitively normal individuals.

Keywords: Cardiovascular risk factors; Cognitive impairment; Neurodegeneration.

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Conflict of interest statement

Conflicts of Interest: The authors report no conflicts of interest.

Figures

Figure 1.
Figure 1.
Associations of diagnostic status (subsequently impaired vs. cognitively healthy) and baseline age with gray matter volume change in the overall sample from the Baltimore Longitudinal Study of Aging (N=688). The color bar represents t-values from the results of the linear mixed effects models. These models consisted of fixed effects (baseline intracranial volume (ICV), image type [1.5-T SPGR vs. 3-T MPRAGE], age, sex, diagnostic status, race, time since first MRI, and two-way interactions of image type, age, sex, diagnostic status, and race with time) and random effects (intercept and time) with unstructured covariance. We used a threshold of ±1.96 to highlight areas of either volume expansion (positive t-values) or volume loss (negative t-values). Note that the colors are uniform within regional labels since the figures depict ROI rather than voxel-based analyses.

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