Connectome Biomarkers for Predicting Alzheimer s Risk in Traumatic Brain Injury
Abstract
Many Veterans have suffered a traumatic brain injury (TBI) and, frequently, this has long-term or devastating consequences on cognition and quality of life. Recent studies have shown that head injury is a risk factor for the development of dementia or Alzheimer s disease (AD). Some research has shown that, following brain trauma, there are molecular changes in the brain that are similar to the molecular changes observed in AD, even in young people with TBI. One of the most reliable ways to detect these changes is the use of positron emission tomography (PET) scanning. However, PET imaging is expensive and invasive and, therefore, is not ideal for detecting brain changes in people at risk for AD. Other neuroimaging approaches, in contrast, are not invasive and are significantly less costly. One such approach is functional magnetic resonance imaging (fMRI), which detects brain activity related to oxygenation changes in the brain. This approach has been used to detect regions of altered brain activity and function in a range of different cognitive, neurological, and psychiatric disorders. More recently, sophisticated computational techniques have been applied to fMRI data in order to understand how different regions of the brain are connected and communicate with each other. The brain is a complex network with many different regions that are highly interconnected. As an analogy, the U.S. interstate system represents a network with cities (nodes) connected by highways (edges). Although the basic architecture of the interstate system has remained fairly stable since it was first built, traffic patterns are dynamic and change with time of day, seasons, and environmental conditions. The flow of traffic in the interstate system can be quantified in different ways. For example, certain cities where several interstates intersect constitute hubs. Hubs have high influence on the network because they connect many cities with each other and, when a hub is blocked (due to an accident or construction), traffic flow is greatly disrupted. When hubs are blocked, additional roads can help traffic flow. In a similar way, some brain regions serve as hubs for information flow. When these hubs deteriorate, as in AD, alternate brain connections may be used to accomplish the same behavior that relied on the hub. But this alternate route is likely slower. This may be what happens in AD. The first goal of the present project will explore this idea using network analysis applied to fMRI data in AD. The second goal will be to determine whether the network organization in AD is already present in the TBI brain, even if the person does not have a diagnosis of AD. This would indicate that fMRI can be used to detect risk for AD due to TBI. Because fMRI is non-invasive and less costly than PET, this research may lead to the use of fMRI as an early biomarker of AD. Having biomarkers early in the disease state could lead to a better understanding of the risk for AD in TBI patients, which would enable families, caregivers, and physicians to engage in more aggressive monitoring of signs of cognitive decline. In turn, patients and caregivers may modify health behaviors and treatments in positive ways to slow cognitive decline.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Oct 29, 2018
- Source ID
- W81XWH1810816
Entities
People
- Jane Joseph
Organizations
- Medical University of South Carolina
- United States Army