Neural Mechanisms for Associations Between Fitness and Cognition in Aging

Univ Of Maryland, College Park, College Park MD

Investigators

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Abstract

Declining memory function is not only a common complaint of healthy aging adults. It is also a primary indicator of Alzheimer's disease (AD). The apolipoprotein-E epsilon4 (APOE-ε4) allele is the only clearly identified candidate gene for late-onset AD and is associated with an earlier age of onset of cognitive decline and brain atrophy. Nevertheless, APOE-ε4 allele inheritance is an imperfect predictor of who will develop AD, suggesting that modifiable lifestyle factors such as Physical Activity (PA), and metabolic health indicators such as Cardiorespiratory Fitness (CRF), might influence cognitive trajectory with age. It is not yet known, however, if CRF modifies indices of neural network integrity in healthy asymptomatic older adults at increased genetic risk for AD. In response to NOT-MH-21-175, we will utilize the longitudinal high-quality functional, structural, and diffusion-weighted MR imaging data from the Lifespan Human Connectome Project Aging (HCP-Aging) dataset to determine the moderating role of CRF on cognitive function and human brain network integrity. We will use two innovative approaches to examine how CRF impacts neural connectivity and brain microstructure with age to determine potential neural mechanisms whereby CRF provides neuroprotection in older adults. We will also test the hypothesis that greater CRF protects episodic memory performance, memory network connectivity, and brain microstructural integrity from the harmful impacts of the APOE-4 allele. By leveraging all available functional data in the HCP-Aging dataset (increasing the reproducibility and impact of our work), we will define indices of neural network integrity within the hippocampal cortical memory system that are known to decrease with age and cognitive decline, including network segregation – an index of within-network correlations compared to between-network correlations; and the clustering coefficient - the fraction of a network node's neighbors that are neighbors to each other. We will also utilize the high angular resolution diffusion imaging (HARDI) diffusion- weighted MRI methods provided by the HCP, which are more histologically meaningful and sensitive to underlying tissue microstructure and function than traditional diffusion tensor imaging. We will calculate the Neurite Density Index in gray matter and the Orientation Dispersion Index in white matter to examine associations with CRF. We hypothesize CRF will moderate the relationship of age-related decline in episodic memory, neural network connectivity, and neurite density (and age-related increases in orientation dispersion) such that High CRF will attenuate the reduction with age. Moreover, we hypothesize that High CRF will attenuate the combined impact of the APOE-4 allele and age on the cognitive, network connectivity, and microstructural integrity outcomes in High CRF versus Low CRF ε4-carriers over time. This project is expected to have a high impact through the use of high-quality neuroimaging data from the HCP-Aging, and the determination of mediators of the association between CRF and brain health in older adults. Substantiating these mechanisms will inform evidence-based practice and prevention efforts in healthy aging and those at increased genetic risk for AD.