Researchers Are Using AI to Find New Alzheimer’s Risk Factors

Brain experts have a pretty good handle on some of the major risk factors that contribute to Alzheimer’s—from a person’s genes to their physical activity levels, how much formal education they’ve received, and how socially engaged they are.

But one promise of AI in medicine is that it can spot less obvious links that humans can’t always see. Could AI help uncover conditions linked to Alzheimer’s that have so far been overlooked?

To find out, Marina Sirota and her team at University of California San Francisco (UCSF) ran a machine-learning program on a database of anonymous electronic health records from patients. The AI algorithm was trained to pull out any common features shared by people who were ultimately diagnosed with Alzheimer’s over a period of seven years. The database includes clinical data, such as lab and imaging test results and diagnoses of medical conditions.

“There were some things we saw that were expected, given the knowledge that we have about Alzheimer’s, but some of things we found were novel and interesting,” says Sirota. The results were published in Nature Aging.

Heart disease, high cholesterol, and inflammatory conditions all emerged as Alzheimer’s risk factors—not surprising, since they’re known to contribute to the buildup of protein plaques in the brain. But the less expected conditions included osteoporosis in women and depression in both men and women. The researchers also saw unexpected patterns emerge closer to when people are diagnosed, such as having lower levels of vitamin D.

Sirota and Alice Tang, a medical student in bioengineering who is the lead author of the paper, stress that these factors do not always mean that a person will develop Alzheimer’s. But they could be red flags that a patient can address to potentially lower their risk. “Picking up these factors gives us clues that a diagnosis of Alzheimer’s might be coming, and things like [high cholesterol] and osteoporosis are modifiable [with treatments],” says Tang.

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