Contribution of Endothelial Changes and Increased Cardiovascular Risk to Alzheimer's Disease Pathogenesis

点击翻译按钮获取中文摘要

Abstract According to recent estimates, close to 6 million Americans are living with Alzheimer's disease (AD), leading to an estimated health cost of $290 billion. With the aging of the population these numbers are expected to substantially increase over time. Although AD has traditionally been considered to be a disease affecting only neurons, there is an increasing appreciation for a vascular component; patients with AD often display cerebrovascular alterations, and classical risk factors for cardiovascular diseases such as hypertension, have been independently associated with an increased risk for dementia and AD. Although the exact mechanisms underlying these observations are not fully understood, both disorders have been shown to affect the vasculature leading to alterations in cerebral blood flow and degradation of the blood-brain barrier (BBB). The goal of the studies proposed in this application is to test the hypothesis that high blood pressure acts in a synergistic manner with AD-related pathology to augment endothelial dysfunction and subsequent BBB degradation. To test this, we will evaluate changes in endothelial cell (EC) gene expression programs using an in vivo EC-specific translating ribosome affinity purification (TRAP) approach, and correlate these to alteration in BBB permeability during the onset and progression of AD-related amyloidogenesis and hypertension, either as separate entities or combined. The results of these studies will lead to a better understanding of the molecular mechanisms underlying the early pathologic changes in the BBB. In addition, these data may result in the identification of early (preclinical) targets for future studies to assess their application as a potential (blood-based) biomarker or as a target for therapeutic interventions. Particularly for AD, as there is currently no cure and treatment options are mostly focused on reducing or controlling symptoms, being able to identify the disorder in the preclinical stage would enable an early intervention and thus increase the probability of therapeutic success.