National Institute on Aging funds research identifying early signs of Alzheimer’s disease and related dementia

Zita Oravecz, associate professor of human development and family studies and faculty co-hire for the Institute for Computational and Data Sciences, has received R01 funding from the National Institute on Aging (NIA) to develop statistical modeling tools to identify and capture early signs of Alzheimer’s disease and related dementia (ADRD).

“Our goal is to capture cognitive change and subtle cognitive decline,” Oravecz said. “By capturing these changes earlier, we can identify risks for ADRD much earlier in life, maybe even 20 years before an official, clinical diagnosis would be possible. That would allow us to evaluate early interventions for ADRD and hopefully mitigate more advanced cognitive decline.”

The project, titled “Multi-timescale process models to disentangle subtle cognitive decline and learning effects,” will combine a methodological approach with identifiers of change to describe data about both immediate learning processes and long-term cognitive change and decline. The data will help researchers extract novel cognitive markers related to ADRD risk.

“We will combine two different models together—one that describes the decision-making process and one that describes the change process over time—a modern approach with high sensitivity,” Oravecz said. “This approach, enhanced with cutting-edge statistical methods, allows us to be very person-focused in analyzing the data, which will be very applicable and impactful to real people.”

Oravecz’s research team will collect data from 200 participants in mid-life, aged 40-65, who will complete up to three years of high-frequency testing delivered on a mobile device, in addition to providing a blood sample for blood-based biomarkers at baseline.

The app used to deliver the digital testing was previously developed by Penn State researchers in the Center for Healthy Aging (CHA) as part of the NIA-funded Mobile Monitoring of Cognitive Change project, which developed flexible and accurate digital tools to measure cognitive change.

“By using digital tools on a person’s own mobile device, we lower the barrier to entry for people to access this early testing and detection process,” Oravecz said. “They don’t have to go to a clinic for testing but can still benefit from impactful research and interventions to detect ADRD early, mitigate further decline, and prepare for future health and wellness needs.”  

Sharon Kim, a graduate student in the Department of Human Development and Family Studies at Penn State, will also work on this study. Martin Sliwinski, Jonathan Hakun, and John Felt of the CHA will collaborate as co-investigators.

Originally published in August 2024.