Brain Structure-Function Associations in Predicting Cognitive Resilience

Cleveland Clinic Foundation, Cleveland OH

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Abstract

Alzheimer’s disease and Alzheimer’s disease-related dementias (AD/ADRD) are the most common forms of neurodegenerative disease, affecting millions of older U.S. adults. Established AD/ADRD risk factors for neurodegeneration and cognitive declines that precede frank dementia onset include physiological, genetic, and sociodemographic influences. Critically, some individuals at increased AD/ADRD risk or with apparent neurodegeneration and measurable neuropathological features maintain higher levels of cognitive function despite these deleterious influences. Currently, the neural mechanisms that underlie such cognitive resilience (CR) to neurodegeneration are poorly understood. Extant conceptual frameworks suggest CR results from more redundant patterns of connectivity in brain networks, but the limited empirical support comes primarily from single-modality neuroimaging studies of structural or functional connectivity. Moreover, recent findings show bidirectional interactions between cortical activity and white matter myelination are necessary to maintain synchronous patterns of brain activity in development; however, dynamic structure-function relationships have received little attention in neuroimaging investigations of CR. Thus, we propose that modeling longitudinal patterns of coupling between dynamic functional connectivity (dFC) and white matter structural connectivity in older adults at risk for AD/ADRD will shed new light on neural dynamics responsible for CR. The current project will utilize existing longitudinal data from participants enrolled in the Center for Neurodegeneration and Translational Neuroscience (CNTN), including those clinically diagnosed as cognitively unimpaired (CU) or with mild cognitive impairment (MCI). Using data from resting state functional MRI (RSfMRI) and diffusion MRI (dMRI) we will model interactions between dynamic functional connectivity and structural connectivity. We propose to model CR based on 1) longitudinal trajectories of performance on neuropsychological tests of perceptual-motor speed, episodic memory, executive functioning and working memory, and 2) the modifying influences of individual and combined AD/ADRD risk factors including age, biological sex, neurodegeneration, and Apolipoprotein E genotype, as well as biomarkers of neuropathology, cardiometabolic and inflammatory risk. Data analysis will utilize advanced data modeling techniques to assess dFC and structural connectivity as combined predictors of change in cognitive function in the presence of AD/ADRD risk. We hypothesize dFC–white matter network coupling is normally attenuated by elevated AD/ADRD risk, but that such coupling is maintained in those exhibiting higher levels of CR. This project is expected to provide critical evidence that interactions between structural and functional brain networks underlie differences in CR. The project will generate preliminary data for new funding proposals for largerscale investigations from multiple ongoing studies of AD/ADRD risk provide new neuroimaging measures of functional and structural connectivity and neurodegeneration for use by CNTN collaborators.