Early brain activity changes in healthy adults, linked to Alzheimer’s proteins, predict cognitive decline .
In our latest study, published in open access by Nature Neuroscience, we have discovered how early changes in brain activity—linked to the buildup of amyloid-beta and tau proteins—could predict the onset of cognitive decline in Alzheimer’s disease, years before symptoms like memory loss appear. These findings pave the way for early detection and intervention in individuals at risk of developing the disease.
Amyloid-beta and tau proteins have long been associated with Alzheimer’s disease. Amyloid-beta tends to accumulate early in the aging brain, while tau follows later, leading to neurodegenerative changes. Until now, the exact relationship between the early buildup of these proteins and brain activity was poorly understood.
“Our goal was to contribute to a better understanding of whether early changes in brain activity are related to the accumulation of these proteins, even in people who are symptom-free,” said the study’s lead co-author, Prof. Sylvain Baillet. “We did observe such alterations in brain activity. Consistent with predictions from animal models, we found that amyloid-beta was related to a form of acceleration in brain activity, while a synergy between amyloid and tau led to a considerable slowing of brain activity.”
We conducted magnetoencephalography (MEG) brain scans on participants, following them over a period of three to four years. We discovered that the early changes in brain activity were stronger in those participants who eventually developed memory or attention deficits. According to Baillet, “This means that even before symptoms like memory loss or attention deficits become obvious, the brain is already showing signs of dysfunction, which in principle could be detected by a rapid MEG scan of only five minutes.”
The significance of this finding lies in its potential for early detection. “Brain activity changes could serve as an early warning system,” Baillet explained. “By identifying these subtle shifts in brain function, we might be able to predict who is at higher risk for developing cognitive problems later on. This could open the door to earlier interventions, including treatments against amyloid deposits that are currently emerging, and more specific therapies before Alzheimer’s symptoms fully emerge.”
As a next step, Baillet and his team are continuing to follow participants from the PREVENT-AD cohort, a unique group of individuals at risk of developing Alzheimer’s. Over nearly ten years, these participants have undergone follow-up MEG scans, amyloid and tau PET imaging, and in-depth cognitive testing.
“Our goal now is to refine how well we can predict cognitive decline and Alzheimer’s symptoms from short MEG scans, potentially up to a decade before they appear,” Baillet said. “We also want to emphasize that the PREVENT-AD datasets will be released to all researchers, encouraging replication and novel findings.”
The research community stands to benefit greatly from this data-sharing effort, and the study’s findings offer a promising avenue for future Alzheimer’s therapies. “We are deeply grateful to the participants for their dedication and involvement in this research, which has made these insights possible,” Baillet added.
As the scientific world looks for ways to tackle Alzheimer’s before irreversible damage occurs, this research highlights the importance of understanding how the disease begins, offering hope for more targeted and effective treatment strategies in the years to come.
This research was led in collaboration with Prof Sylvia Villeneuve’s group, also at McGill.
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