Publications by authors named "Brandon S Klinedinst"

Cognitive aging is described as the age-related decline in areas such as memory, executive function, reasoning, and processing speed. Super-Agers, adults over 80 years old, have cognitive function performance comparable to middle-aged adults. To improve cognitive reserve and potentially decrease Alzheimer's disease (AD) risk, it is essential to contrast changes in regional brain volumes between "Positive-Agers" who have superior cognitive performance compared to their age peers but are not 80 years old yet and aging adults who show cognitive decline (i.

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Article Synopsis
  • Limited research has examined how cardiovascular risk and amyloid levels influence cognitive decline in East Asians, specifically in a study involving 526 participants from the Korean Brain Aging Study.
  • Results showed that cognitively normal individuals without amyloid (Aβ-) but with high cardiovascular risk scores had significantly lower cognitive performance than their low-risk counterparts.
  • Ultimately, while managing vascular risk is important for early cognitive preservation in Aβ- individuals, amyloid pathology was found to be the main factor driving cognitive decline in both cognitively normal and mild cognitive impairment groups, regardless of vascular risk status.
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Introduction: Aging is often associated with cognitive decline. Understanding neural factors that distinguish adults in midlife with superior cognitive abilities (Positive-Agers) may offer insight into how the aging brain achieves resilience. The goals of this study are to (1) introduce an optimal labeling mechanism to distinguish between Positive-Agers and Cognitive Decliners, and (2) identify Positive-Agers using neuronal functional connectivity networks data and demographics.

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Introduction: Obesity and insulin resistance negatively influence neural activity and cognitive function, but electrophysiological mechanisms underlying these interrelationships remain unclear. This study investigated whether adiposity and insulin resistance moderated neural activity and underlying cognitive functions in young adults.

Methods: Real-time electroencephalography (EEG) was recorded in 38 lean (n = 12) and obese (n = 26) young adults with (n = 15) and without (n = 23) insulin resistance (18-38 years, 55.

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Communities across the globe are faced with a rapidly aging society, where age is the main risk factor for cognitive decline and development of Alzheimer's and related diseases. Despite extensive research, there have been no successful treatments yet. A rare group of individuals called "super-agers" have been noted to thrive with their exceptional ability to maintain a healthy brain and normal cognitive function even in old age.

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Background: Aging is characterized by body composition alterations, including increased visceral adiposity accumulation and bone loss. Alcohol consumption may partially drive these alterations, but findings are mixed. This study primarily aimed to investigate whether different alcohol types (beer/cider, red wine, white wine/Champagne, spirits) differentially associated with body composition.

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Aging has often been characterized by progressive cognitive decline in memory and especially executive function. Yet some adults, aged 80 years or older, are "super-agers" that exhibit cognitive performance like younger adults. It is unknown if there are adults in mid-life with similar superior cognitive performance ("positive-aging") versus cognitive decline over time and if there are blood biomarkers that can distinguish between these groups.

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Many risk factors have emerged for novel 2019 coronavirus disease (COVID-19). It is relatively unknown how these factors collectively predict COVID-19 infection risk, as well as risk for a severe infection (i.e.

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The Apolipoprotein E ε4 (APOE ε4) haplotype is the strongest genetic risk factor for late-onset Alzheimer's disease (AD). The Translocase of Outer Mitochondrial Membrane-40 (TOMM40) gene maintains cellular bioenergetics, which is disrupted in AD. TOMM40 rs2075650 ('650) G versus A carriage is consistently related to neural and cognitive outcomes, but it is unclear if and how it interacts with APOE.

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Background: Fluid intelligence (FI) involves abstract problem-solving without prior knowledge. Greater age-related FI decline increases Alzheimer's disease (AD) risk, and recent studies suggest that certain dietary regimens may influence rates of decline. However, it is uncertain how long-term food consumption affects FI among adults with or without familial history of AD (FH) or APOE4 (ɛ4).

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Introduction: Glucose hypometabolism and tau formation are key features of Alzheimer's disease (AD). Less is known about the relationship between fasting glucose and regional tau accumulation.

Methods: Cerebrospinal fluid (CSF) glucose was linearly regressed on regional tau (flortaucipir) among 169 Alzheimer's Disease Neuroimaging Initiative (ADNI3) participants.

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Background: Many risk factors have emerged for novel 2019 coronavirus disease (COVID-19). It is relatively unknown how these factors collectively predict COVID-19 infection risk, as well as risk for a severe infection (i.e.

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Objective: The high prevalence of vitamin D deficiency and obesity drives the need for successful strategies that elevate vitamin D levels, prevent adipogenesis, and stimulate lipolysis. This study provides a theoretical model to evaluate how physical activity (PA) and sunlight exposure influence serum vitamin D levels and regional adiposity. This study hypothesized a posteriori that sunlight is associated with undifferentiated visceral adiposity by increasing the ratio of brown to white adipose tissue.

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Background: Obesity in midlife and early late-life is associated with worse normal cognitive aging. Dual-energy X-ray absorptiometry (DEXA) suggests that visceral adipose mass (VAM) plays a predominant role, whereas non-visceral adipose mass (NVAM) and lean muscle mass (LMM) have shown conflicting relationships. It is unknown how longitudinal, cognitive changes in age-sensitive domains like fluid intelligence (FI) correspond to VAM, NVAM, and LMM in women and men.

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