New blood screening algorithm reduces unnecessary Alzheimer's PET scans

When the algorithm was used in recruiting participants for the study, it cut the rate of people who received a PET scan but did not qualify for the trial from more than 70% to 31%.

Using a blood-plasma screening algorithm for efficient clinical trial recruiting

In recent years, blood tests have shown increasing promise in helping to determine if someone is at risk for Alzheimer's disease. These tests measure proteins in blood plasma that are biomarkers of the disease.

The algorithmic screening tool developed by USC researchers incorporated two key blood plasma biomarkers: the amyloid-beta ratio, an earlier signal of amyloid accumulation, and p-tau217, a recently discovered marker that more reliably reflects amyloid burden in the brain.

The algorithm was developed using data from 1,080 AHEAD participants and validated in an independent dataset from the Wisconsin Registry for Alzheimer's Prevention study. In addition to blood biomarkers, the model incorporated age and APOE4 carrier status, both factors known to increase the risk of amyloid accumulation. The algorithm was refined across three successive versions during active recruitment for the study, which ran from 2020 to 2024.

First introduced in February 2022, the algorithm using the amyloid-beta ratio reduced the proportion of PET-ineligible participants from 71% to 50%. In May 2023, p-tau217 was integrated into a second version, and that figure dropped further to 31%. This enabled the trial to more efficiently enroll participants with both intermediate and elevated amyloid levels.

Central to the algorithm's design is a statistical technique called Mixture of Experts (MoE), which allows the model to account for the fact that amyloid doesn't accumulate uniformly. Rather than simply sorting participants into positive or negative categories, the team built a model that estimates where someone falls on a continuous spectrum of amyloid buildup.

"When we look at amyloid levels at a population level, we see a peak where people are amyloid-negative and another peak for those with elevated amyloid plaque buildup," said Langford. "There is a region in the intermediate range that isn't fully captured by the plasma marker alone. The Mixture of Experts approach helps model that uncertainty more effectively and is better suited to the type of data collected."

Blood testing as a tool for early detection and earlier intervention

The study's results add to a growing body of evidence that blood tests can serve as a practical first-pass filter before more intensive and costly testing.

"It's going to allow more people to access testing that can help determine whether they have Alzheimer's disease pathology," says Langford. "If you are able to go to your doctor and get a blood test done, you'll be able to understand whether you have the disease earlier."

"If we can intervene earlier," said Langford, "we'll have a larger effect and hopefully prevent people from having symptoms."

About this study

The AHEAD Study is supported by Alzheimer's Clinical Trials Consortium (ACTC), which is funded by a Cooperative Agreement from the National Institute on Aging (NIA), National Institutes of Health (NIH) under award number U24AG057437. The study is a public-private partnership funded by the National Institute on Aging of the National Institutes of Health, Eisai, the GHR Foundation, the Alzheimer's Association, and other philanthropic organizations.

Source:

Keck School of Medicine of USC

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