Dr. Gagan Wig, Associate Professor of Psychology and Director of the Wig Neuroimaging Lab at the Center for Vital Longevity, and his team are trying to figure out why some people age relatively gracefully while others experience rapid cognitive decline.
Scientists from the University of Texas at the Dallas School of Behavioral and Brain Sciences (BBS) have shown that a key indicator of aging brain health varies based on level of education, which can indicate the likelihood and severity of later dementia.
Their findings, published Nov. 11 in Nature Aging, suggest that environmental factors related to socioeconomic status may accelerate brain aging.
“We have known for some time that there are differences in brain health that relate to socioeconomic status, and educational level is a good indicator of that status,” said correspondent author Dr. Gagan Wig, Associate Professor of Psychology and Director of the Wig Neuroimaging Lab at the Center for Vital Longevity (CVL). “But there was no understanding of the brain changes we can relate to the socio-economic status that lead to these diseases in old age.”
Micaela Chan MS’12, PhD’16, is a researcher at CVL and lead author of the article “Nature Aging”. Her previous doctoral thesis, done with Wig, used resting functional MRI to determine that as you age, areas of the brain that had not previously worked together work more together. The separation of functional networks collapses; Scientists call this desegregation.
“People with this pattern of reduced segregation tend to have worse performance on memory tests,” she said. “So this change has an impact on 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 Washington University School of Medicine in St. Louis. The study focused on adults aged 45 to 86 years who had two to five MRI scans.
“We have scans of people for whom we have clinical data up to 10 years later. What we see is that those who decreased in this measurement of the network organization of the brain are more likely to have cognitive impairments in the future, ”said Wig. “It is independent of other known prognostic indicators for 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 characteristic indicators of Alzheimer’s disease. Wig said that a decrease in the segregation of the brain’s functional networks predicts impending cognitive and functional impairment even in patients lacking these other Alzheimer’s disease biomarkers.
Micaela Chan MS’12, PhD’16
Additional data collected on the patients indicated that those with a lower level of education were more likely to have this pattern of desegregation in their brain network. However, the researchers emphasized that education itself is not a direct cause.
“These education-based differences are a proxy for something,” said Chan. “Education is a tangible, objective data point that represents many hard-to-measure benefits that are likely to be granted to people with higher education or as a result of their education. This list includes many things: diet and food security, stress levels, likelihood of exposure to toxins, quality of sleep. There are many things that can play a role. “
Researchers also had access to patient data on cardiovascular health, mental health, and a history of traumatic brain injuries.
“To understand how these factors interact, you need longitudinal measurements,” said Wig. “This amazingly rich dataset gave us the opportunity to learn more about individuals with multiple scans over long periods of time. These images show that the decrease in functional segregation appears to act on pathways that are independent of other indicators of dementia.
“This research serves two big purposes,” said Wig. “We show that the organization of brain networks measured with fMRI varies depending on the level of education. Second, the patterns we see in the pictures indicate dementia and its severity early on – in some cases even years before symptoms appear. “
Wig said the group’s next step will be figuring out what features in the environment might most likely be related to those brain patterns and further developing measures to organize brain networks for clinical use.
“It’s exciting that we’ve identified a brain signal that predicts dementia and appears to be linked to environmental variables, paving the way for us to discover these causes,” said Wig. “To answer this question, you really have to understand a person’s environment and lifestyle along with their neurological and mental health.”
As life expectancy increases around the world, Alzheimer’s and dementia will become more common, he said.
“With the devastating threat to the elderly and the burden on public health systems, there is an urgent need to elucidate the causes of Alzheimer’s disease,” said Wig. “We actively study these and other groups of people to understand how brain health changes over time and how it relates to things that people are exposed to.”
Other study authors affiliated with UT Dallas include cognitive and neuroscience graduate students Liang Han and Ziwei Zhang, research assistant Claudia Carreno MS’17, and Rebekah Rodriguez BS’20, currently a graduate student at the University of North Carolina Greensboro . Other authors are Dr. Jason Hassenstab, associate professor of neurology at Washington University; and Megan LaRose, now a PhD student at Ohio State University.
The research was supported by the National Institutes of Health (Grant R01AG063930) and the James S. McDonnell Foundation.
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