Contribution of Cerebral Iron Load to Cognitive Function in Older Adults with High Risk to Develop Alzheimer's Disease

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Project Summary: Dementia has a high global prevalence due to the aging population and places an enormous burden on health care systems. Alzheimer’s disease (AD) is the most common cause of dementia, and it is widely believed that the accumulation of Amyloid beta (Aβ) peptide is a key event in the pathogenesis of AD, representing preclinical disease stages. Cerebral iron is also strongly implicated as a cofactor in the pathogenesis of AD, and its overload accelerates Aβ production and promotes the toxicity of the Aβ peptide. However, the impact of brain iron load, and its combined effect with regional Aβ-plaque-load on cognitive impairment in AD and its precursor, mild cognitive impairment (MCI), is lacking. Our overall aim is to study the role of brain iron load and its possible synergistic effect with Aβ-plaque-load in the development of cognitive decline, MCI and dementia, in particular AD. We will perform such study using data from two prospective cohort studies: the Atherosclerosis Risk in Communities (ARIC) study, which has collected clinical data from cohort participants over the past 30 years and the UK biobank study, which collects extensive clinical, imaging and genetic data in the UK adult population. In the ARIC study, a biracial sample of elderly adults was evaluated by brain MRI, florbetapir positron emission tomography (PET), and cognitive tests at study visit 5 with repeat testing underway at visit 6. We will utilize the phase signal from gradient echo MRI data at visit 6 (n=1,000) to compute quantitative susceptibility mapping (QSM). Brain iron load will be automatically quantified using our recent developed susceptibility multi-atlas tool. We will then for Aim 1 determine if increased cerebral iron measures are independently associated with cognitive performance with the presence of MCI or dementia in these ARIC participants aged 73-94 years. We will also assess possible associations between known midlife vascular risk factors with cerebral iron as measured in late-life. For Aim 2, we will estimate the combined effects of Aβ-plaque-load as measured by florbetapir PET in the ARIC-PET study (n=300) and increased cerebral iron-load as measured by QSM on the progression of cognitive impairment with adjustment for contributions from demographic, contemporary vascular risk factors, small vessel diseases and APOE-e4 status. To further establish the causality between brain iron and cognitive function in Aim 3, we will perform a genome-wide association study (GWAS) with Mendelian randomization to find genetic determinants of cerebral iron and their association with cognitive function. Cerebral iron as measured by QSM will be calculated from UK biobank brain MRI data (n~=35,000), while genetic variants associated with cerebral iron load will tested against the cognitive function measures in the remaining ~465,000 independent samples.