Model maps ‘domino effect’ of Alzheimer’s protein misfolding | Digital Science

A new computer simulation shows how clumps of defective proteins in neurodegenerative diseases like Alzheimer’s disease can stealthily spread through the brain over as long as 30 years.

“We hope the ability to model neurodegenerative disorders will inspire better diagnostic tests and, ultimately, treatments to slow down their effects,” says Ellen Kuhl, a mechanical engineer at Stanford University.

The simulations focus on Alzheimer’s disease, Parkinson’s diseaase, and amyotrophic lateral sclerosis (ALS, or Lou Gehrig’s disease), but the researchers believe their technique is general enough to work for other brain disorders that involve misshapen proteins, including chronic traumatic encephalopathy. The findings appear in Physical Review Letters.

Connect the dots

The group knew that these three diseases produced hallmark clumps of defective, misfolded proteins that build up in the brain. To see how those toxic clumps spread over time, researchers looked at brain slices taken from people who died after developing one of the diseases. Prior researchers had stained those brain slices to reveal the presence of the various proteins of interest.

When the resulting data was put into a computer, researchers also did the mathematical modeling to simulate how the pattern of defective proteins spreads from the relatively sparse clumps in people who were early in the disease to much more widespread clumping in people with advanced disease—a process that can take up to 30 years.

“The real challenge is that cell death from toxic proteins occurs years, if not decades, before the first symptoms begin to show.”

“Imagine a domino effect,” says Kuhl, who is part of the Stanford Neurosciences Institute and Stanford Bio-X. “What our model does is connect the dots between the static data points, mathematically, to show disease progression in unprecedented detail.”

In the case of Alzheimer’s disease, the scientists modeled the progression of two misfolding proteins—known as tau and amyloid beta—both of which change shape and form toxic clumps in the brains of people with the disease. Prior researchers had stained brain slices for both proteins and, with the new model, Kuhl’s team was able to create two simulations showing the different way that each of these variants of that disease spread.

135 million people with dementia

Neuroscientists don’t know precisely how one clump of defective proteins affects its neighbors to spread the misfolding, although Kuhl says there are three prevailing theories. The virtue of the model, she says, is that it predicts the path of the disease regardless of which theory is correct.

Kuhl now plans to work with neuroscientists to better understand the mechanisms of how the proteins misfold. These insights would improve their model and perhaps lead to better ways of diagnosing the disease while it is still in stealth mode.

“The real challenge is that cell death from toxic proteins occurs years, if not decades, before the first symptoms begin to show,” Kuhl says.

Kuhl also plans to make the modeling software freely available to other scientists, repeating what she did a decade ago with similar models to study the heart—work now known as the Living Heart Project. The brain software will be known as the Living Brain Project.

“Given the aging of the population, by mid-century 135 million people worldwide will have some form of dementia,” Kuhl says. “We have to find new ways to spur research toward diagnostics and interventions, and computer modeling can play a key role in identifying new therapeutic targets.”

Additional coauthors are from Oxford University and Stevens Institute of Technology. Stanford Bio-X, the National Science Foundation, and the Engineering and Physical Sciences Research Council of Great Britain funded the work.

Source: Stanford University

Original Study DOI: 10.1103/PhysRevLett.121.158101

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