Investigating Resistance and Resilience Mechanisms in Alzheimer’s Disease

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PROJECT SUMMARY / ABSTRACT Cognitive Aging and risk of Alzheimer's disease, and Alzheimer's related dementias (AD/ADRD) is due to multiple aging and pathological processes that are driven by several upstream brain mechanisms and risk factors. The success of recent multi-domain interventions and our preliminary data suggests that multiple mechanisms need to be targeted for effective dementia prevention. In 2018, we proposed a simplistic conceptual framework that builds on existing concepts using the nomenclature of resistance in the context of avoiding AD pathology and resilience in the context of coping with AD pathology for investigating these distinct mechanisms. This proposal addresses an important barrier for developing effective therapeutic or preventive strategies for AD dementia - the poor understanding of how upstream risk factors and brain mechanisms (resistance and resilience) that could contribute to or protect from protein accumulation and neurodegeneration. Our central hypothesis is that identifying upstream brain mechanisms of resistance and resilience and modeling the complex inter-relationships between protective factors, brain mechanisms, and longitudinal changes in amyloid, tau, and cognition will aid in effective design of dementia prevention strategies. To test this hypothesis, our primary aim is to identify mechanisms of resistance and resilience using the existing infrastructure of the population-based Mayo Clinic Study of Aging (MCSA) (individuals aged ≥50 years) and Rochester Epidemiology Project (REP) which maintains a comprehensive medical records-linkage system. We will collect the following variables for this proposal: Genetics, Social Determinants of Health (SDoH), and systemic health (up to 20 years prior to scan from REP), longitudinal PiB and tau PET, baseline cutting edge MRI (high resolution T1/T2/FLAIR and multi-shell diffusion MRI to assess perivascular spaces, microstructural integrity, and cortical thickness), and cognitive decline. Our secondary aim is to develop and validate MRI- based resilience markers that can be used in the NIA-AA research framework alongside with AT(N) biomarkers to adjust for individual variability in cognition. Considering brain health measures (other than those included in the evaluation of N) as resilience markers will improve the prediction of cognitive decline across all aging and dementia studies. These measures will be able to capture biological variability due to SDoH and systemic health and facilitate better comparison of biomarkers across populations.