Understanding brain activity can predict Alzheimer’s progression : Study

According to study were published in the Journal Cell Reports, patterns of brain activity can predict how far has Alzheimer's advanced. Read on to know more.

By: IANS | | Published: November 21, 2019 11:10 am

Microglia is a cell that first interprets the presence of Alzheimer's in the body. ©Shutterstock

For a person with Alzheimer’s disease, there’s no turning back the clock. By the time a person begins to experience memory loss and other worrisome signs, cognitive decline has already set in. Decades of clinical trials have failed to produce treatments that can help people regain their memory. Also Read - Beware! This could be an early sign of Alzheimer’s

Today, researchers at Gladstone Institutes are approaching this devastating disease from a different angle. In a study, they demonstrate that particular patterns of brain activity can predict far in advance whether a young mouse will develop Alzheimer’s-like memory deficits in old age. The results of the study were published in the Journal Cell Reports. Also Read - Traumatic brain injury can increase risk of Alzheimer's disease: Tips to avoid head injuries

“Being able to predict deficits long before they appear could open up new opportunities to design and test interventions that prevent Alzheimer’s in people,” said Gladstone Senior Investigator Yadong Huang, senior author of the study.

The new work builds on a 2016 study of mice engineered to carry the gene for apolipoprotein E4 (ApoE4). Carrying the gene is associated with an increased risk – but not a guarantee, of Alzheimer’s disease in humans. As they age, ApoE4 mice often, but not always, develop signs of memory loss similar to those seen in people with Alzheimer’s. Also Read - World Alzheimer's Day 2020: Misfolded proteins in the gut may be the culprit

In the previous study, Huang and his team investigated a type of brain activity called sharp-wave ripples (SWRs), which play a direct role in spatial learning and memory formation in mammals.

“SWRs have two important measurable components: abundance and short gamma (SG) power,” said Emily Jones, Ph.D., lead author of the new study and recent graduate of UC San Francisco’s (UCSF) Biomedical Sciences Graduate Program. “Broadly, SWR abundance predicts how quickly an ApoE4 mouse can learn and memorize how to get through a maze, and SG power predicts how accurate that memory will be.”

The earlier study revealed that aging ApoE4 mice have lower SWR abundance and weaker SG power than seen in healthy aging mice. Based on those results, Jones and her colleagues hypothesized that measuring SWR activity could predict the severity of demonstrable memory problems in ApoE4 mice during aging.

“We actually successfully replicated this experiment 2 years later with different mice,” said Huang, who is also a professor of Neurology and Pathology at UCSF. “What was striking is that we were able to use the results from the first cohort to predict with high accuracy the extent of learning and memory deficits in the second cohort, based on their SWR activity.”

Even more striking were the unexpected results of the team’s next experiment.

The researchers were curious about how SWR activity evolves over a mouse’s lifetime, which no one had previously investigated. So, they periodically measured SWRs in ApoE4 mice from an early age – long before memory deficits appeared – through middle age, and into old age.

“We thought that, if we got lucky, the SWR measurements we took when the mice were middle-aged might have some predictive relationship to later memory problems,” Jones said.

Surprisingly, the analysis revealed that deficits in SWR abundance and SG power at an early age-predicted which mice performed worse on memory tasks 10 months later – the equivalent of 30 years for a human.

“We were not betting on these results, the idea that young mice with no memory problems already have the seed of what’s going to lead to deficits in old age,” Jones said. “Although we would love to, we thought it would be ridiculous to be able to predict so far in advance.”

Since SWRs are also found in humans, these findings suggest that SWR abundance and SG power could potentially serve as early predictors of Alzheimer’s disease, long before memory problems arise.

As a next step toward evaluating that possibility, Huang will work with colleagues at the UCSF Memory and Aging Center to determine whether SWRs in Alzheimer’s patients show deficits in abundance and SG power similar to those seen in mouse models of the disease.

“A major advantage of this approach is that researchers have recently developed a non-invasive technique for measuring SWRs in people, without implanting electrodes in the brain,” Huang said.

Published : November 21, 2019 11:10 am

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