Scientists make major breakthrough in early Alzheimer's detection
[Mar. 30, 2023: JD Shavit, The Brighter Side of News]
Medical University of South Carolina neuroscientists Dr. Andreana Benitez (in back) and Dr. Stephanie Fountain-Zaragoza, Ph.D. (in front) discuss a neuroimaging result. (CREDIT: Sarah Pack, Medical University of South Carolina)
Neuroscientists at the Medical University of South Carolina (MUSC) have made a breakthrough in detecting early signs of Alzheimer’s disease (AD) through individualized brain mapping.
The study, published in Brain Connectivity, identified subtle differences in brain function in older adults with preclinical AD – the earliest signs of the disease where amyloid-beta proteins build up in the brain, but cognitive decline remains unnoticed.
Lead researchers Andreana Benitez and Stephanie Fountain-Zaragoza used a new brain imaging analysis technique to create individualized maps of brain function, looking for links between these subtle changes and cognitive performance measured through behavior-based tests. Their approach could help to better understand the preclinical phase of AD.
“Prior studies have not found an association between brain function and behavior in preclinical AD,” said Benitez. “Using these individualized maps of brain function, we found a potential brain-based reason for very subtle cognitive changes in this early phase of the disease.”
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Detecting Subtle Changes with Improved Brain Mapping
Early changes in brain function related to preclinical AD are very subtle, making them difficult to study. The MUSC researchers used a new form of brain mapping to detect these subtle effects. They looked at brain activity using a functional connectome – a type of brain map that measures how different brain regions communicate with one another.
Fountain-Zaragoza described the brain as a big city where brain regions are clustered into neighborhoods connected by highways. The functional connectome measures the activity across that city – how much is going on within each neighborhood and how well traffic flows between them.
To detect subtle changes in brain function, the researchers relied on a highly sensitive form of image analysis. The individualized functional connectome, developed by collaborator Hesheng Liu, shows unique patterns of brain function for each individual.
Individualized functional networks, created by mapping a population-level atlas to each participant’s brain, were used to detect early Alzheimer’s-related changes in brain function and cognition. (CREDIT: Medical University of South Carolina, Dr. Stephanie Fountain-Zaragoza)
“We all have the same functional parts of our brain, but they're positioned slightly differently, sort of like a fingerprint,” said Fountain-Zaragoza. “This method creates an individualized brain fingerprint that more accurately reflects where the different functional regions are in each individual’s brain.”
Linking Subtle Changes in Brain Function to Behavior
The MUSC researchers used this novel brain fingerprinting technique to look for subtle changes in brain function in 149 participants aged 45 to 85 without signs of cognitive decline. Participants underwent PET scans of their brains and were divided into two groups – those with and without PET scan evidence of early amyloid-beta protein buildup. The participants also underwent MRI scans, which were used to generate the brain fingerprints.
The researchers then tested how well the participants in each group performed on behavior-based tests of information processing. They found that certain changes in the brain fingerprint were associated with worse information processing in participants with amyloid-beta buildup, or preclinical AD.
In participants with preclinical AD, information processing was worse in those with greater than usual between-network connectivity, or too much activity on the brain’s highways. In contrast, information processing was better in those with higher within-network connectivity, or more brain activity within important neighborhoods of the brain.
“A healthy brain typically has a balance of connectivity within and between its networks,” said Fountain-Zaragoza. “We found that in preclinical AD—when amyloid build-up is present in the brain—this balance can be disrupted, potentially leading to information no longer being processed as efficiently.”
What the Study Teaches Us
The study teaches us several important things about preclinical Alzheimer's disease (AD). Firstly, it highlights the potential of individualized functional connectomes to detect subtle variations in brain function that may not be identified using other conventional brain imaging analysis techniques. This method could therefore help us to better understand the earliest stages of AD, which could ultimately lead to more effective treatments.
Secondly, the study suggests that amyloid-beta buildup in the brain may affect the function of brain networks even before symptoms of cognitive decline become noticeable. This could be a crucial finding as it may help researchers to identify individuals who are at higher risk of developing AD before any symptoms occur. This could ultimately enable earlier intervention and treatment to improve outcomes for patients.
Thirdly, the study reveals that changes in connectivity within and between specific brain networks may indicate early problems with information processing. This imbalance in connectivity could therefore be a promising target for therapies to improve the outcomes for patients with AD.
By understanding how these networks function, researchers may be able to develop targeted interventions to correct or prevent these imbalances.
Overall, the study highlights the importance of continued research into the preclinical phase of AD. By understanding how the disease progresses from its earliest stages, researchers may be able to develop more effective interventions to slow or even halt its progression.
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