Body Composition in Early Alzheimer's Disease

Background: Alzheimer's disease (AD) is associated with unintended weight loss. We examined body composition in early AD and nondemented aging and its relation to brain volume and cognition. Methods: Brain magnetic resonance imaging (MRI) and neuropsychological testing were performed on nondemented (CDR 0, n=70) and early-stage AD (CDR 0.5 or 1, n=70) subjects. Dual energy x-ray absorptiometry (DEXA) determined whole-body fat mass and lean mass. Body mass index (BMI) was determined from height and weight. Linear regression analyses controlling for age and sex assessed the relationship between body composition, cognition, and brain volume. Results: Lean mass was reduced in early AD compared to nondemented controls (F=7.73, p=0.006) after controlling for sex. Lean mass was associated with whole-brain volume (beta=0.20, p<0.001) and white matter volume (beta=0.19, p<0.001) when controlling for age and sex. Lean mass was also associated with global cognitive performance (beta=0.12, p=0.007) when controlling for age and sex. Total body fat and percent body fat were not different across groups or related to cognition and brain volume. Conclusion: Loss of lean mass is accelerated in AD and associated with brain atrophy. AD and sarcopenia may share common underlying mechanisms or sarcopenia may be a direct or indirect consequence of AD pathophysiology

Body Mass Index and Cognitive Decline in Mild Cognitive Impairment

This is the author's accepted manuscript.Objective To examine the relationship between body mass index (BMI) and cognitive decline in subjects diagnosed with mild cognitive impairment (MCI). Methods Neuropsychologic and clinical evaluations were conducted at baseline, 6-months, and 1-year on 286 MCI subjects enrolled in the Alzheimer’s Disease Neuroimaging Initiative. A global cognitive composite score was derived (mean Z-score) from performance on 9 neuropsychologic subtests. Height and weight were assessed at baseline and used to calculate BMI. Generalized estimating equations (linear and logistic) assessed the relationships of baseline BMI with cognitive outcomes, clinician judgment of “clinically significant decline” over 1-year, and diagnostic progression from MCI to Alzheimer disease. Results Lower baseline BMI was associated with significant declines in cognitive performance in individuals with MCI over 1 year (Mini-Mental State Examination, Alzheimer Disease Assessment Scale-Cognitive subscale, and a global cognitive composite; all P<0.05). We observed a significant protective effect of baseline BMI in reducing the risk of a clinically significant decline in Alzheimer Disease Assessment Scale-Cognitive subscale and mini-mental state examination (P<0.05). No association was found between BMI and changes in the clinical dementia rating sum of boxes or conversion to Alzheimer disease. Conclusions Lower baseline BMI is associated with more rapid cognitive decline in MCI. This relationship suggests either body composition may influence the rate of cognitive decline in MCI or factors related to MCI influence body composition

Neighborhood Integration and Connectivity Predict Cognitive Performance and Decline

Objective: Neighborhood characteristics may be important for promoting walking, but little research has focused on older adults, especially those with cognitive impairment. We evaluated the role of neighborhood characteristics on cognitive function and decline over a 2-year period adjusting for measures of walking. Method: In a study of 64 older adults with and without mild Alzheimer’s disease (AD), we evaluated neighborhood integration and connectivity using geographical information systems data and space syntax analysis. In multiple regression analyses, we used these characteristics to predict 2-year declines in factor analytically derived cognitive scores (attention, verbal memory, mental status) adjusting for age, sex, education, and self-reported walking. Results: Neighborhood integration and connectivity predicted cognitive performance at baseline, and changes in cognitive performance over 2 years. The relationships between neighborhood characteristics and cognitive performance were not fully explained by self-reported walking. Discussion: Clearer definitions of specific neighborhood characteristics associated with walkability are needed to better understand the mechanisms by which neighborhoods may impact cognitive outcomes. These results have implications for measuring neighborhood characteristics, design and maintenance of living spaces, and interventions to increase walking among older adults. We offer suggestions for future research measuring neighborhood characteristics and cognitive function

COMMUNICATION: Electrochemical polymerization of conducting polymers in living neural tissue

A number of biomedical devices require extended electrical communication with surrounding tissue. Significant improvements in device performance would be achieved if it were possible to maintain communication with target cells despite the reactive, insulating scar tissue that forms at the device–tissue interface. Here, we report that the conducting polymer poly(3,4-ethylenedioxythiophene) (PEDOT) can be polymerized directly within living neural tissue resulting in an electrically conductive network that is integrated within the tissue. Nano and microscale PEDOT filaments extend out from electrode sites, presumably forming within extracellular spaces. The cloud of PEDOT filaments penetrates out into the tissue far enough that it should be possible to bypass fibrous scar tissue and contact surrounding healthy neurons. These electrically functional, diffuse conducting polymer networks grown directly within tissue signify a new paradigm for creating soft, low impedance implantable electrodes.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/58177/2/jne7_2_l02.pd

Metabolic Syndrome and Cognitive Decline in Early Alzheimer’s Disease and Healthy Older Adults

This is the author's accepted manuscript. The original is available at http://content.iospress.com/articles/journal-of-alzheimers-disease/jad121168Metabolic syndrome (MetS) is a cluster of risk factors (i.e., abdominal obesity, hypertension, dyslipidemia, glucose and insulin dysregulation) that is associated with cardiovascular disease, diabetes, and dementia. Recent studies addressing the association of MetS with cognitive performance and risk for dementia report mixed results. An important step in clarifying these conflicting results is determining whether cognition is influenced by the effects of individual MetS components versus the additive effects of multiple components. We assessed the effect of MetS on cognitive performance and decline over two years in 75 cases of early Alzheimer’s disease (AD) and 73 healthy older adult controls in the Brain Aging Project. Using factor analytic techniques, we compared the effect of a combined MetS factor to the effect of individual MetS components on change in attention, verbal memory, and mental status. In healthy controls, a combined MetS factor did not significantly predict cognitive performance, though higher insulin predicted poorer cognitive performance outcomes. In the AD group, higher scores on a combined MetS factor predicted better cognitive outcomes. Our findings suggest that MetS does not have the same association with cognitive decline in healthy older adults and those with early AD. We suggest that individual MetS components should not be evaluated in isolation and that careful methodological approaches are needed to understand the timing and non-linear relationships among these components over time