Microstructural Markers of Cognitive Aging and Mild Cognitive Impairment
As age-related cognitive impairment and dementia become increasingly common health concerns for our aging population, it's important to develop tools to accurately detect and distinguish these other aspects of aging from the earliest signs of Alzheimer's disease (AD). Although imaging methods, such as magnetic resonance imaging (MRI), have shown promise at measuring changes in brain structure associated with cognitive impairment and dementia, these approaches are relatively insensitive to the earliest disease stages, when treatments will likely be most effective. A new brain imaging technique, restriction spectrum imaging (RSI), has shown promise at revealing smaller-scale features of brain structure than standard techniques. This project will test whether new RSI-based measures can identify small-scale pathways thought to be affected by AD; accurately predict which individuals will decline cognitively; and correlate with other known markers of AD.
Our research aims to characterize the small-scale structural changes that occur during the earliest stages of Alzheimer’s disease (AD), and describe how they relate to cognitive decline during aging and neurodegenerative disease.
The first goal of our project is to identify brain pathways that deteriorate early in AD, a degenerative process that may underlie cognitive impairments. To accomplish this, we are using an advanced neuroimaging technique called restriction spectrum imaging (RSI) to evaluate small-scale tracks in brain regions targeted early in the disease. We are comparing the integrity of these pathways in the brains of healthy older individuals to those with mild cognitive impairment (MCI) or early AD. We are also evaluating how these new measures of brain microstructure relate to cognitive function in order to assess whether they are sensitive to behavioral symptoms of the disease.
Our second goal is to determine whether brain microstructure predicts or tracks cognitive change associated with aging or disease. RSI and cognitive testing are being performed on a group of healthy and cognitively impaired older individuals, with repeat imaging and testing taking place multiple times over several years. We are testing whether measures of brain microstructure are able to track cognitive decline during this time period or can predict who will go on to develop more severe cognitive impairment.
We anticipate that our new, advanced tools will be more sensitive than current neuroimaging biomarkers to both AD onset and cognitive decline related to aging. Our final goal is therefore to compare the sensitivity of our new measures of brain microstructure to that of existing biomarkers. In particular, RSI metrics are being evaluated against measures from standard structural and diffusion MRI, as well as cerebral spinal fluid measures of amyloid beta and tau.
One of the major challenges to accurately diagnosing AD at its early stages is the inability to detect subtle, often microscopic, brain changes that may signal the beginnings of a pathological process. Largely from post-mortem studies, we know what these changes are, yet it is difficult to identify them in living humans and to distinguish them from changes that may simply result from normal aging. Our research aims to overcome these obstacles by applying advanced brain imaging tools that are able to capture detailed images of brain structure at resolutions impossible using other techniques.
We expect our research to significantly improve our understanding of the brain changes underlying cognitive decline in both normal and pathological aging. The development of accurate and sensitive biomarkers of Alzheimer’s disease is crucial for both early disease detection and identifying those who may be at risk for cognitive impairment, even before symptoms appear. Ultimately, these advances will facilitate the earliest possible intervention and optimal care for those suffering from AD.
About the Researcher
Emilie Reas, PhD, is a post-doctoral fellow in the Radiology Department at the University of California, San Diego. She studied cognitive neuroscience at the University of California, Berkeley, before completing her PhD in neuroscience at the University of California, San Diego. As a graduate student, she used functional MRI to understand how the brain's medial temporal lobe supports long-term memory retrieval. As a post-doctoral fellow, she transitioned to the field of aging. Her current work aims to understand the small-scale structural brain changes that occur in normal aging and in the early stages of AD, and how they related to decline in cognitive function.
I have long been intrigued by the integral role memory plays in our identity and how it contributes to a rich life experience. Without the ability to revisit the past, we lose our sense of self and our connections to friends and family. This fascination inspired me to learn about the brain in college, and later to study memory and aging-related memory disorders in my PhD and post-doctoral work.
This scientific quest became personal when my grandfather was diagnosed with Alzheimer's disease. The importance of advancing research on dementia became painfully clear; without ongoing efforts from scientists, and support from the community and organizations like BrightFocus, the devastating impact of neurodegenerative memory disorders will only continue to worsen as our aging population grows. I believe everyone, not just scientists, deserves the rich knowledge that research yields, and thus I am an active science writer and strong advocate of effective science communication.
After neuroscience, my second greatest passion is distance running, which often fuels my research. I do my best thinking on long runs and hope this habit will keep my brain healthy for many years to come. I use my running to further complement my work on aging and memory, having twice run the Boston Marathon in support of the Alzheimer's Association and our ongoing battle to preserve our memory and quality of life into old age.
First published on: August 1, 2016
Last modified on: July 1, 2018