Scientists from The University of Texas at Dallas School of Behavioral and Brain Sciences (BBS) have demonstrated that a key measure of the health of the aging brain varies in relation to education level, which can indicate the likelihood and severity of later dementia.
Their results, published in Nature Aging on Nov. 11, suggest that environmental factors related to socioeconomic status might accelerate brain aging.
“We’ve known for some time that there are disparities in brain health that relate to socioeconomic status, and education level is a good proxy for that status,” said corresponding author Dr. Gagan Wig, associate professor of psychology and director of the Wig Neuroimaging Lab at the Center for Vital Longevity (CVL). “But there hasn’t been an understanding of the brain changes that we can link to socioeconomic status that lead to those diseases in older age.”
Micaela Chan MS’12, PhD’16, is a research scientist at CVL and lead author of the Nature Aging article. Her earlier doctoral work, which was conducted with Wig, used resting-state functional MRI to help establish that, as people get older, areas of the brain that had not previously worked together begin to collaborate more. The separation of functional networks breaks down; scientists call this desegregation.
“People who have this pattern of reduced segregation tend to have worse performance on memory tests,” she said. “So, this change has implications for cognitive processing.”
In the current study, the CVL researchers used an archive of brain images from the Charles F. and Joanne Knight Alzheimer’s Disease Research Center at the Washington University School of Medicine in St. Louis. The study focused on adults ages 45 to 86 who underwent two to five MRI scans.
“We have scans of people for whom we have clinical data up to 10 years later. What we’re seeing is that those who started declining in this measure of brain network organization were more likely to have cognitive impairment in the future,” Wig said. “It’s independent of other known prognostic indicators of Alzheimer’s disease, such as genetic risk and pathology.”
Each patient’s profile also included additional brain scans of beta amyloid plaques and tau protein measured from cerebrospinal fluid, the two hallmark indicators of Alzheimer’s pathology. Wig said that a decrease in segregation of the brain’s functional networks predicts impending cognitive and functional impairment even in patients lacking these other biomarkers of Alzheimer’s disease.
Additional data collected on the patients indicated that those with a lower education level are more likely to have this pattern of desegregation in their brain network. But researchers emphasized that education itself is not a direct cause.
“These education-based differences are a proxy for something,” Chan said. “Education is a concrete, objective data point that represents many harder-to-measure advantages likely afforded to those who also happen to be more educated, or as a consequence of their education. That list includes a lot of things: diet and food security, stress levels, likelihood of exposure to toxins, sleep quality. There are many things that can be a factor.”
Researchers also had access to patient data on cardiovascular health, mental health and history of traumatic brain injury.
“Understanding how these factors interact requires longitudinal measures,” Wig said. “This amazingly rich data set gave us an opportunity to learn about individuals with multiple scans across long periods of time. These images demonstrate that the decrease in functional segregation seems to be operating on paths that are independent of other indicators of dementia.
“This research is serving two big purposes,” Wig said. “We are showing that brain network organization as measured using fMRI varies as a function of educational attainment. Secondly, those patterns we see in the images are predictive of dementia and its severity quite early — in some cases, years before symptoms appear.”
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Wig said the group’s next step will be to address what features in the environment might be most related to these brain patterns, and to further develop the measures of brain network organization for clinical use.
“It’s exciting that we have identified a brain signal that is prognostic of dementia and seems to be linked to environmental variables, giving us a path toward discovery of those causes,” Wig said. “To answer that question, you really have to understand an individual’s environment and lifestyle, in parallel to their neurological and mental health.”
As life expectancy climbs worldwide, Alzheimer’s disease and dementia will become more prevalent, he said.
“Due to its devastating threat to older adults and the strain it puts on public health systems, there is an urgent need to elucidate the causes of Alzheimer’s disease,” Wig said. “We’re actively studying these and other groups of individuals to understand how brain health changes over time and how it relates to things that people are exposed to.”
Other UT Dallas-affiliated authors of the study include cognition and neuroscience doctoral students Liang Han and Ziwei Zhang, research assistant Claudia Carreno MS’17, and Rebekah Rodriguez BS’20, currently a doctoral student at the University of North Carolina Greensboro. Other authors include Dr. Jason Hassenstab, associate professor of neurology at Washington University, and Megan LaRose, now a graduate student at The Ohio State University.
The research was supported by the National Institutes of Health (grant R01AG063930) and the James S. McDonnell Foundation.