Non-Invasive Imaging Markers to Elicit the Role of Vascular Involvement in Alzheimer’s Disease

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ABSTRACT Alzheimer's disease (AD) is the 6th leading cause of death in the United States and its prevalence continues to rise. AD has no clinically available curative treatments and findings from active clinical trials testing novel disease-modifying therapeutics have thus far been disappointing. There is, therefore, a growing urgency to identify early markers of AD, causative factors leading to dementia, and alternative treatment approaches for halting the global crisis posed by this debilitating condition. Cardiovascular disease, as well as cerebrovascular disease (CVD), has a strong link with both mild cognitive impairment and AD dementia; however, the question of whether CVD modulates underlying pathophysiology of AD has only recently begun receiving attention. To provide insights into AD relationships, non-invasive Magnetic Resonance Imaging (MRI) is being utilized in longitudinal studies of AD risk-enriched populations. The present project goes far beyond currently available MRI techniques which lack sensitivity and specificity to address key vascular hypotheses in AD. MRI methods commonly employed today such as fluid attenuation and susceptibility imaging only indirectly measure CVD and cannot inform on the dynamic vascular motion and hemodynamic phenomena that have been indicated in animal models to affect AD pathology. To address these gaps, the overarching objective of this project is to enable characterization of cerebrovascular involvement in AD through the development and study integration of a novel battery of non-invasive, MRI-based measures of cerebrovascular health. Building upon foundational studies at our institution, this work proposes innovative MRI technology to improve characterization of CVD in AD, specifically vascular stiffening and its relationship with cerebrovascular flow dynamics. We propose an ensemble of motion encoded MRI techniques which provide detailed depiction of autoregulatory flow dynamics and vascular stiffness in both the macro and micro vasculature. In this project, the novel methods will be technically developed harnessing deep learning from vast prior imaging data, validated with optical imaging, and characterized in healthy human subjects. We then will obtain key data characterizing cerebrovascular changes in a study of AD biomarker confirmed subjects with the overall goal of identifying the modifying effect of vascular disease on the symptom expression of cognitive impairment, AD biomarker accumulation, and neurodegeneration. Our pilot data suggest subjects with AD have a premature increase in arterial stiffness and decreased fluctuations in cerebral blood flow. Upon completion, this study will provide insights into which specific aspects of CVD are primary factors moderating AD interactions. Participants targeted for this study have extensive existing AD biomarker data and are being followed longitudinally through studies within the Wisconsin Alzheimer's Disease Research Center. The methodologies will be uniquely positioned for incorporation into large longitudinal cohort studies investigating AD mechanisms and evaluating putative risk and protective factors.