News Release

USC researchers define brain scan marker to better classify Alzheimer’s disease-related changes

The findings, published in Imaging Neuroscience, provide an important step toward refining research standards in brain imaging across various populations.

Peer-Reviewed Publication

Keck School of Medicine of USC

PET scan cognitively unimpaired vs. Alzheimer's disease

image: 

This image shows average tau buildup in the brain using PI-2620. The tracer uptake in different regions is measured by a quantitative method called Standardized Uptake Value Ratio (SUVR), helping compare tau levels. Warm colors (yellow, orange, red) indicate higher SUVR and more tau, while cooler colors (green, blue) show lower SUVR and less tau. 

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Credit: USC Stevens INI

A team of researchers from the Keck School of Medicine of USC’s Mark and Mary Stevens Neuroimaging and Informatics Institute (Stevens INI) has identified a new brain imaging benchmark that may improve how researchers classify biologically meaningful changes associated with Alzheimer’s disease, especially in Hispanic and non-Hispanic white populations. The new study, published in Imaging Neuroscience, is part of the Health and Aging Brain Study–Health Disparities (HABS-HD), a multi-university collaboration led by the University of North Texas Health Science Center and supported by the National Institute on Aging.

Using an advanced brain imaging scan called tau PET, the research team studied over 675 older adults from HABS-HD, aiming to identify the optimal brain signal that distinguishes individuals with clinically-relevant biological markers of AD from those who are aging normally.

Tau PET enables researchers to visualize abnormal proteins in the brain which contribute to Alzheimer’s disease, known as tau, by using a small amount of a special radioactive tracer that highlights areas where tau has accumulated. With these scans, researchers can establish tau cut-points, a new type of biomarker used to determine whether a scan shows an amount of tau protein in the brain high enough to suggest possible early signs of Alzheimer’s disease or related conditions. This new benchmark could eventually inform the way clinicians interpret tau PET scans and better identify who may be at risk for AD.

In this study, researchers compared tau PET scans of study participants who were cognitively impaired with those who were not impaired  based on cognitive tests to establish a tau cut-point that would indicate a higher risk for Alzheimer’s disease. They found one—but it was only effective in certain circumstances.

“Our tau cut-point was able to distinguish whether study participants had cognitive impairment – but only when another abnormal protein, amyloid, was also present in those with cognitive impairment, and only in Hispanic and non-Hispanic White participants,”  said senior author Meredith N. Braskie, PhD, assistant professor of neurology. “In non-Hispanic Black participants, the tau cut-point did not perform as expected. This suggests that other pathologies or conditions may be driving cognitive decline in this group. Our study is an important step toward better understanding how tau relates to cognition in diverse populations and has important implications for future clinical trials that aim to target tau.”  

The team used a new imaging tracer called 18F-PI-2620, to measure tau protein buildup in the brain. They found that when tau levels in the medial temporal lobe­—a region deep in the brain—exceeded a certain threshold, it strongly indicated cognitive impairment related to AD.

“While our findings support prior research linking medial temporal lobe tau to cognitive impairment, establishing a cut-point in this region using 18F-PI-2620, marks an important step toward defining tau positivity for both research and clinical applications. At the same time, the limited reliability of tau as an indicator of cognitive impairment in non-Hispanic Black participants highlights the need for more diverse populations in research and for future studies to examine both biological and social determinants of Alzheimer’s disease,” said lead author Victoria R. Tennant, a PhD candidate in USC’s Neuroscience Graduate Program.

The findings reflect a growing focus in AD research on making sure diagnostic tools work for everyone—not just in narrow clinical trial populations. Alzheimer’s disease is known to affect the brain in stages. While amyloid plaques often build up early, tau tangles are more closely tied to memory loss and other symptoms.

“This type of imaging is critical for understanding who is at risk and how the disease develops,” said Stevens INI director Arthur W. Toga, PhD. “These findings are just the latest to come from HABS-HD, which is the most comprehensive study of Alzheimer’s disease and related dementias in diverse communities. HABS-HD has already produced key findings related to ethnic variations in AD biomarkers, the influences of social determinants on cognitive health, and vascular contributions to dementia, just to name a few. We hope this work will lead to more personalized care and better outcomes for all communities.”

You can find more information about accessing HABS-HD data here.

About the study

In addition to Tennant and Braskie, the study’s other authors are Koral V. Wheeler, Noelle N. Lee, Jamie A. Terner, Maxwell W. Hand, Suchita Ganesan, Patrick Walsh, Aisha Greene, Tyler Berkness, Tiantian Lei, Arthur W. Toga from the Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California; Rema Raman and Robert A. Rissman from the Alzheimer’s Therapeutic Research Institute, Keck School of Medicine of USC, University of Southern California; Bradley T. Christian from the Waisman Center, University of Wisconsin-Madison; Melissa Petersen, Ann D. Cohen, Karin L. Meeker, Zhengyang Zhou, Rajesh R. Nandy and Sid E. O’Bryant from the University of North Texas Health Science Center at Fort Worth; Beau M. Ances from the Washington University School of Medicine in St. Louis; and Kristine Yaffe from the Department of Psychiatry, Neurology, and Epidemiology/Biostatistics, University of California, San Francisco.

This research was supported by the National Institute on Aging of the National Institutes of Health [R01AG054073, R01AG058533, R01AG070862, P41EB015922, and U19AG078109], and by the Office of the Director, the National Institutes of Health, [S10OD032285].


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