Inc.
MRI scans may reveal subtle brain changes years before Alzheimer’s-linked amyloid reaches detectable high levels.
Researchers Analyzed 1,000 People Over 16 Years. They Found an Unexpected Alzheimer’s-Linked Pattern
Author: Liyana Illyas
Researchers found measurable changes after analyzing scans from more than 1,000 people over a 16-year period.
MRI scans may be able to detect brain changes linked to Alzheimer’s disease years earlier than previously thought, according to a new study from the University of Oslo in Norway.
The study, published in peer-reviewed journal Nature Neuroscience, reported that differences in the brain’s cortex, or outer layer, could be detected at least seven years before people developed high levels of amyloid-beta, a protein closely associated with Alzheimer’s disease.
Researchers analyzed thousands of MRI scans from more than 1,000 cognitively healthy adults over several years. Using PET scans, they compared changes in the participants’ brain structure with their later amyloid buildup.
The level of amyloid buildup is a key metric doctors use to identify Alzheimer’s disease. The researchers wanted to understand what happens in the brain before someone reaches that threshold.
“I think the main message is that brain changes related to later amyloid accumulation may begin earlier, and may be more complex, than we can capture by looking at when somebody crosses the set threshold for amyloid-PET positivity,” study co-author Anders Martin Fjell, a neuroscientist at the University of Oslo, told Inc.
Amyloid accumulation happens gradually, Fjell said, so the point at which someone is classified as amyloid-positive does not mark the beginning of the process. Brain changes may already be happening before that threshold is reached.
The study found that people who showed a buildup of amyloid had a thicker cortex and less cortical thinning in the years before reaching the threshold, according to Yunpeng Wang, a senior author and co-corresponding author of the study.
“This is quite different from the cortical thinning and atrophy that we usually associate with later stages of Alzheimer’s disease,” Wang told Inc. “At this point, we do not know exactly what biological processes underlie these early MRI changes. That is one of the questions raised by the study.”
But Wang emphasized that amyloid positivity itself should not be confused with an Alzheimer’s diagnosis, as “individuals can have elevated amyloid while remaining cognitively healthy.” That distinction is important because the study looked at structural changes that occurred before people crossed the threshold for amyloid positivity, not before they received a clinical Alzheimer’s diagnosis.
Structural MRI can show how the brain is changing but it cannot tell researchers whether those changes are caused by Alzheimer’s. Cortical thickness can also be affected by normal aging, vascular factors, and other biological processes, Wang said.
“Structural MRI is likely to be more informative in combination with other measures, such as blood-based biomarkers, PET, genetics, and cognitive assessment,” Fjell said.
Wang added that AI could eventually help researchers detect subtle patterns across brain scans. However, he said those tools would still need to demonstrate that they can improve predictions or clinical decisions. The study also used conventional structural MRI, suggesting existing scans could potentially be useful for future research.
For now, though, the findings should not be interpreted as evidence that MRI can provide an clear, early diagnosis of Alzheimer’s.
Researchers still need to replicate the findings in larger and more diverse populations and determine whether the MRI patterns can reliably predict later amyloid buildup in individuals.
“The main message of the study is therefore not that MRI is ready to diagnose Alzheimer’s years in advance,” Wang said. “Rather, it suggests that the brain may already be undergoing measurable changes well before amyloid reaches the conventional PET threshold. Understanding what these early changes represent, and whether they can eventually help us identify different trajectories toward Alzheimer’s disease, is the important next step.”
Credits: TCA, LLC.