The Role of White Matter Injury in Alzheimer's Disease

The project goal is to use a unique data set to identify imaging patterns marking the contribution of specific factors in white matter injury and evaluating these patterns as predictors of disease risk.

In this project, Zahra Shirzadi, PhD, and her colleagues will take a novel approach to assessing injury to the brain’s white matter and its links to Alzheimer’s disease. Bundles of axons, the signaling extensions of nerve cells, make up the white matter and connect different parts of the brain so that they can function together. White matter damage can disrupt these important connections. This damage is often seen on brain images from people who have Alzheimer’s disease, even before they experience symptoms.

Dr. Shirzadi and her colleagues will evaluate three factors related to white matter damage: buildup of amyloid in the brain’s blood vessels, shrinking of the brain, or atrophy, and blood vessel health. Amyloid is one of the two main proteins implicated in Alzheimer’s disease. If it builds up in the brain’s blood vessels, a condition known as cerebral amyloid angiopathy, affected vessels may rupture and bleed. Dr. Shirzadi and her colleagues will use a unique resource for this work: many MRI images taken over a long period of time in several patient cohorts to determine how much each factor is involved in white matter injury.

Based on these findings, the team plans to develop tools that use these patterns to identify people at high risk for cerebral amyloid angiopathy or progressive cognitive decline.

This project will investigate white matter injury (WMI) from a novel perspective by examining the relative contributions of brain atrophy, vessel amyloidosis, and vascular risk to WMI. We will combine routine clinical MRI sequences to build accessible multi-modal neuroimaging tools that can be used in routine clinical settings for differential diagnosis of WMI. We will use a unique longitudinal multi-cohort dataset that covers a wide range of age and vascular risks, neurodegeneration, and amyloidosis to dissect different underlying etiologies of WMI.

This project will leverage multi-cohort longitudinal datasets to (1) develop white matter injury metrics that better separate the diverse impacts of vessel amyloidosis, brain atrophy, and vascular risk factors; and (2) develop white matter injury metrics that have prospective utility in identifying individuals at imminent risk of cerebral amyloid angiopathy before the appearance of hemorrhagic lesions, and in identifying white matter injury patterns that presage accelerated cognitive decline. This novel approach will inform the interpretation of a common neuroimaging finding in aging and AD.