Monday, May 29, 2023
5/29/2023
PROJECT SUMMARY Age-related cognitive decline is a significant public health concern as the population over the age of 60 continues to grow sharply. Advances in understanding the mechanisms that underlie this decline will allow for effective interventions and substantially reduce the burden on families as well as government and social programs. We will be faced with 50 trillion dollars in Medicare costs as the baby boomers age, thus magnifying the size of the concern and the significance of our proposed work. Aging is a major risk factor for Alzheimer's disease (AD), which currently affects over five million Americans. If no prevention or treatment is discovered, this number could increase to 16 million by 2050. Establishing early indicators of the disease process during the preclinical stage is a critical goal of biomedical research. Our project goal is to determine the neural features (i.e. biomarkers) associated with amyloid pathology accumulation, and determine objectively how to combine these biomarkers to identify individuals with preclinical AD. We will combine state-of- the-art high-resolution multimodal MRI tools with targeted, innovative cognitive testing approaches and leverage our local UCI Alzheimer's Disease Research Center (ADRC) for (1) recruitment of asymptomatic older adults (Clinical Core), (2) sample enrichment based on ApoE genotype (Pathology Core), (3) detailed cognitive evaluation of all participants (Clinical Core), and (4) development of statistical models to optimally combine imaging and cognitive measures for prediction of cognitive decline (Data Management and Statistics Core). We will recruit asymptomatic older adults (60-85 years old, n=150) from the ADRC and from the local community and will enrich the sample for amyloid positivity via ApoE genotype. We will conduct PET amyloid scans with [18F] AV-45 (florbetapir) on all participants to determine amyloid status (targeting 50% positivity across the whole sample). We will conduct high-resolution multimodal MRI and targeted cognitive examinations in all participants at baseline, and repeat the cognitive examinations contemporaneously with ADRC annual and bi-annual follow-up visits. In Aim 1, we will use a set of newly developed cognitive tests that focus on memory function attributed to medial temporal lobe (MTL) processes, particularly “pattern separation”. These tests vary mnemonic interference in the object, spatial and temporal domains. In Aim 2, we will use high resolution resting state fMRI (1.5 mm), ultrahigh resolution microstructural diffusion tensor imaging (DTI, 0.66 mm), and high resolution structural MRI (0.55 mm), to assess structure, function and connectivity of the MTL. In Aim 3, we will use statistical prediction modeling to determine the optimal combination of measures that predicts longitudinal cognitive/clinical decline. Collectively, the proposed studies will significantly inform our understanding of cognitive decline in the aging brain in the presence and absence of amyloid pathology and allow us to better define preclinical AD and make recommendations for future intervention trials.
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