Researchers use AI to understand Alzheimer's disease, identify drug targets
An estimated 6.5 million people in the US are living with Alzheimer's disease
{{#rendered}} {{/rendered}}A team of researchers from the University of Arizona and institutions across the country are using artificial intelligence to hopefully pinpoint the cause of Alzheimer's disease and potential drug targets.
Led by Dr. Rui Chang, an associate professor of neurology at the University of Arizona College of Medicine, the study's authors have looked into the brain to map molecular changes that healthy neurons undergo as the disease progresses.
The work was published in the journal Nature Communications Biology.
{{#rendered}} {{/rendered}}Using tissue samples from more than 2,000 brains impacted by the disease that were taken from a national database, Chang’s AI algorithm drew from information about genetic and molecular processes. That method returned what the university said in a release was a "computational network model" of the human brain.
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"There are multiple pathways involved in Alzheimer’s disease," Dr. Chang said in a statement, referring to the chain of events that occur within cells to trigger changes in the body. (The University of Arizona Health Sciences, Kris Hanning)
His team is now able to see maps of genes that work together across the human genome. The genome is the entire set of DNA instructions found in a cell.
{{#rendered}} {{/rendered}}Furthermore, they have the ability to follow the sequential changes in these genes’ relationships as Alzheimer’s develops, providing hints about the disease’s origins and "tracing the molecular path from health to disease."
"This is not studying one gene by one gene — it’s 6,000 targets all at the same time, which will significantly accelerate drug development and discovery," Chang said in a statement. "This is the first study showing that the AI and big data-driven approach could open the door to develop treatment for Alzheimer’s by targeting new pathways or combinations of pathways."
The team was led by team led by Rui Chang, PhD, associate professor of neurology at the University of Arizona College of Medicine. (The University of Arizona Health Sciences, Kris Hanning)
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{{#rendered}} {{/rendered}}The AI was used to help flag 19 neuron-specific genetic points on the Alzheimer's pathway that appear to push neurons closer toward a disease state.
Collaborators to the study at Harvard University found that 10 genes could be investigated as targets for drugs to treat Alzheimer’s.
Using 3D computer models, the team virtually screen millions of Food and Drug Administration-approved, natural product and small-molecule compounds against more than 6,000 targets. They zeroed in on around 3,000 drug candidates of interest and the team already has a National Institutes of Health grant enabling clinical trials on three of the compounds.
{{#rendered}} {{/rendered}}Chang's AI algorithm had a deep well of information to draw from, including more the tissue samples of more than 2,000 Alzheimer's brains taken from a national database. (The University of Arizona Health Sciences, Kris Hanning)
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"We’re hopeful that AI is a game changer," Chang said. "In five years, I hope there are more clinical trials for drugs for treatment of Alzheimer’s disease, and in 10 years, I hope there will be a couple of FDA-approved drugs to stop or potentially reverse disease progression."
Chang told Fox 10 Phoenix that his grandmother was diagnosed with Alzheimer’s disease.
{{#rendered}} {{/rendered}}Alzheimer's disease is the most common type of dementia. It impacts an estimated 6.5 million people, according to the Centers for Disease Control and Prevention. It is the fifth leading cause of death for adults aged 65 and older, and the seventh leading cause of death for all adults.