New grant funds AI search for genetic targets to treat Alzheimer's

With a new $6.2 million, five-year grant from the National Institute on Aging, researchers at Case Western Reserve University will use artificial intelligence (AI) and machine learning to identify possible genetic targets to treat Alzheimer's disease.

The intent, said principal investigator Jonathan L. Haines, chair of the Department of Population and Quantitative Health Sciences at the Case Western Reserve School of Medicine, is to provide doctors and drugmakers new information that could prevent, slow or even cure the disease.

Medications approved by the U.S. Food and Drug Administration to treat Alzheimer's disease work by clearing abnormal protein clusters-called amyloid plaques-that build up between nerve cells (neurons) in the brain, disrupting cell-to-cell communication.

While the medications may slow cognitive decline in mild cases, they often have serious side effects and don't address the disease's root causes.

Alzheimer's disease now claims more American lives annually than breast cancer and prostate cancer combined, according to the Alzheimer's Association.

Haines and his research team believe the answer lies in our DNA. By following the genetic roadmap, they will be the first to use AI and machine learning to examine more than 1,800 potential genes that have been identified as suitable new targets for treatment.

We plan to harness the power of massive whole-genome datasets from two of the most comprehensive Alzheimer's genetic research initiatives in the world-the Alzheimer's Disease Sequencing Project and the Alzheimer's Disease Genetics Consortium." 

Jonathan L. Haines, chair of the Department of Population and Quantitative Health Sciences, Case Western Reserve School of Medicine

These datasets combine information from diverse populations so any findings would be racially and ethnically relevant nationally.

Advanced computational tools, AI and machine learning will allow the team to use algorithms and statistical models to analyze and draw inferences from patterns in the data. More specifically, they hope to identify genetic variations responsible for causing the disease.

"At the end of this five-year project," Haines said, "we will deliver a prioritized, genetically validated list of drug targets for pharmaceutical developers and clinicians to build the next generation of Alzheimer's therapies."