Search

Adults with Down syndrome (DS) are at risk for Alzheimer's disease. Despite sharing trisomy 21, however, there is variability in the age of disease onset. This variability may mean that other factors, such as lifestyle, influence cognitive aging and disease timing. The present study assessed the association between everyday life physical activity using an actigraph accelerometer and cognitive functioning and early Alzheimer's disease pathology via positron emission tomography amyloid-β and tau and diffusion tension imaging measures of white matter integrity in 61 non-demented adults with DS. Percent time in sedentary behavior and in moderate-to-vigorous activity were associated (negatively and positively, respectively) with cognitive functioning (r = -.472 to .572, p < 0.05). Neither sedentary behavior nor moderate-to-vigorous activity were associated with amyloid-β or tau, but both were associated with white matter integrity in the superior and inferior longitudinal fasciculus (Fractional Anisotropy: r = -.397 to -.419, p < 0.05; Mean Diffusivity: r = .400, p < 0.05). Longitudinal studies are needed to determine if physical activity promotes healthy aging in DS., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Introduction: This study examines the utility of a multipanel of cerebrospinal fluid (CSF) biomarkers complementing Alzheimer's disease (AD) biomarkers in a clinical research sample. We compared biomarkers across groups defined by clinical diagnosis and pTau 181 /Aβ 42 status (+/-) and explored their value in predicting cognition., Methods: CSF biomarkers amyloid beta (Aβ) 42 , pTau 181 , tTau, Aβ 40 , neurogranin, neurofilament light (NfL), α-synuclein, glial fibrillary acidic protein (GFAP), chitinase-3-like protein 1 (YKL-40), soluble triggering receptor expressed on myeloid cells 2 (sTREM2), S100 calcium binding protein B (S100B), and interleukin 6 (IL6), were measured with the NeuroToolKit (NTK) for 720 adults ages 40 to 93 years (mean age = 63.9 years, standard deviation [SD] = 9.0; 50 with dementia; 54 with mild cognitive impairment [MCI], 616 unimpaired)., Results: Neurodegeneration and glial activation biomarkers were elevated in pTau 181 /Aβ 42 + MCI/dementia participants relative to all pTau 181 /Aβ 42 - participants. Neurodegeneration biomarkers increased with clinical severity among pTau 181 /Aβ 42 + participants and predicted worse cognitive performance. Glial activation biomarkers were unrelated to cognitive performance., Discussion: The NTK contains promising markers that improve the pathophysiological characterization of AD. Neurodegeneration biomarkers beyond tTau improved statistical prediction of cognition and disease stages., (© 2020 the Alzheimer's Association.)

Background: Studies have suggested associations between self-reported engagement in health behaviors and reduced risk of cognitive decline. Most studies explore these relationships using one health behavior, often cross-sectionally or with dementia as the outcome. In this study, we explored whether several individual self-reported health behaviors were associated with cognitive decline when considered simultaneously, using data from the Wisconsin Registry for Alzheimer's Prevention (WRAP), an Alzheimer's disease risk-enriched cohort who were non-demented and in late midlife at baseline., Method: We analyzed longitudinal cognitive data from 828 participants in WRAP, with a mean age at baseline cognitive assessment of 57 (range = 36-78, sd = 6.8) and an average of 6.3 years (standard deviation = 1.9, range = 2-10) of follow-up. The primary outcome was a multi-domain cognitive composite, and secondary outcomes were immediate/delayed memory and executive function composites. Predictors of interest were self-reported measures of physical activity, cognitive activity, adherence to a Mediterranean-style diet (MIND), and interactions with each other and age. We conducted linear mixed effects analyses within an Information-theoretic (IT) model averaging (MA) approach on a set of models including covariates and combinations of these 2- and 3-way interactions. The IT approach was selected due to the large number of interactions of interest and to avoid pitfalls of traditional model selection approaches., Results: Model-averaged results identified no significant self-reported health behavior*age interactions in relationship to the primary composite outcome. In secondary outcomes, higher MIND diet scores associated with slower decline in executive function. Men showed faster decline than women on delayed memory, independent of health behaviors. There were no other significant interactions among any other health behaviors and cognitive trajectories., Conclusions: When multiple covariates and health behaviors were considered simultaneously, there were limited weak associations with cognitive decline in this age range. These results may be explained alone or in combination by three alternative explanations: 1) the range of cognitive decline is in middle age is too small to observe relationships with health behaviors, 2) the putative associations of these health behaviors on cognition may not be robust in this age range, or 3) the self-reported measures of the health behaviors may not be optimal for predicting cognitive decline. More study may be needed that incorporates sensitive measures of health behaviors, AD biomarker profiles, and/or other disease comorbidities., Competing Interests: The authors have declared that no competing interests exist.

Objective: To evaluate the relationship between sensory and cognitive decline, particularly with respect to speed of processing, memory span, and fluid intelligence. In addition, the common cause, sensory degradation and speed of processing hypotheses were compared., Method: Structural equation modeling was used to investigate the complex relationships among age-related decrements in these areas., Results: Cross-sectional data analyses included 842 older adult participants (M = 73 years). After accounting for age-related declines in vision and processing speed, the direct associations between age and memory span and between age and fluid intelligence were nonsignificant. Older age was associated with visual decline, which was associated with slower speed of processing, which in turn was associated with greater cognitive deficits., Discussion: The findings support both the sensory degradation and speed of processing accounts of age-related, cognitive decline. Furthermore, the findings highlight positive aspects of normal cognitive aging in that older age may not be associated with a loss of fluid intelligence if visual sensory functioning and processing speed can be maintained.