Mild Cognitive Impairment: A Prospective Community Study

Mild Cognitive Impairment: A Prospective Community Study. Dementia is a leading cause of disability and death in older adults. Its incidence increases exponentially with age. Identifying independent risk factors and valid disease markers are critical steps towards prevention, improved diagnosis, and treatment. To enhance clinical and public health care, these factors must be identified in population settings. We seek to extend, for a further five years, a 15-year prospective population-based study of mild cognitive impairment (MCI) and dementia in a low SES-area of southwestern Pennsylvania. The original richly characterized cohort is now aged 80+, and at maximum risk for dementia; we have replenished the cohort by recruiting additional participants currently aged 65-74, for a total current sample ~1100. Our objective remains to identify, at the population level, risk factors for clinically relevant adverse cognitive outcomes of MCI, cognitive decline, and progression to dementia. We propose a new set of specific aims investigating novel disease markers in relation to these outcomes. Our new high performing mass-spectrometry-based plasma β amyloid (Aβ) assay holds potential for affordable non-invasive screening for Alzheimer's disease. 7T MRI brain scans will allow in-depth imaging of cerebrovascular integrity in a subgroup and help understand the role of small vessel disease (SVD) in cognitive decline and dementia. Non- invasive wrist actigraphy will measure sleep-wake rhythms which we will examine in relation to the cognitive outcomes, Aβ and SVD. GWAS and transcriptomics will allow us to examine genome-wide genetic and gene expression data. We will assess the relationships of these three biomarkers (Aβ, SVD, sleep), along with genomics and gene expression, and their mutual interactions, to the clinically relevant outcomes of cognitive decline and dementia. New light shed on mechanisms underlying these disorders, using modeling techniques to account for biases and generalize results from sub-samples back to the entire cohort, will lead to new insights to help reduce the public health burden of dementia.