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Brain scans may be able to identify people at the highest risk of Alzheimer’s disease years before noticeable memory problems emerge, according to new research that, for a first time, compares brain activity with that of exceptionally healthy older adults.
“By comparing brain activity in SuperAgers and people with Alzheimer’s, we identified a pattern linked to faster cognitive decline even in adults whose memory and thinking were still normal at the time of their scan,” Kanhao “Alex” Zhao of Stanford University, the study’s lead author, told Newsweek. “We hope this gives researchers an earlier window to identify who may be at higher risk and test whether intervening sooner can help preserve memory and thinking.”
The California-based researchers developed a machine-learning framework called the Alzheimer’s Resilience-Vulnerability Connectome, or ARC, designed to place individuals along a spectrum ranging from unusually robust cognitive patterns to Alzheimer’s disease.
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Rather than simply comparing people with Alzheimer’s with cognitively unimpaired adults, the researchers used SuperAgers, older people who retain unusually strong cognitive abilities, as the healthy end of that spectrum. The approach could give scientists a clearer picture of subtle changes in brain function that emerge before clinical symptoms of Alzheimer’s become apparent.
Looking Beyond Traditional Comparisons
Alzheimer’s research has previously linked the disease to factors including the proteins amyloid-beta and tau, as well as genetic risk. The new study examined whether differences in the way brain regions function and communicate could provide additional information about future cognitive decline.
Researchers trained and evaluated ARC using resting-state functional magnetic resonance imaging, or fMRI, data from 180 SuperAgers and 110 people diagnosed with Alzheimer’s disease. All participants were at least 75 years old. The model was also tested in an independent group of 143 people.
The researchers then applied ARC to 818 slightly younger adults who showed no signs of cognitive impairment and had not been classified as SuperAgers.
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By measuring patterns of brain function, the system estimated where each person fell on the spectrum between SuperAger-like and Alzheimer’s-like brain activity.
Follow-up data covering periods of five to 15 years showed that people whose brain patterns appeared more Alzheimer’s-like experienced faster cognitive decline, greater amyloid-beta accumulation and a higher likelihood of progressing to clinical Alzheimer’s disease.
Potential Early Warning Signs
Dr. Elena Gross, a neuroscientist and founder of Swiss biotechnology company KetoSwiss, told Newsweek the research was notable because it changed the reference point for assessing Alzheimer’s risk.
“What makes this study particularly interesting is that it changes how we approach Alzheimer's risk,” Gross said. “Instead of simply comparing people with Alzheimer's disease to those aging normally, the researchers looked at two extremes: people with Alzheimer's and SuperAgers, individuals who maintain exceptional memory well into later life.”
Gross said one of the most significant findings was that people who initially had similarly healthy cognitive performance nevertheless showed different patterns of brain connectivity and subsequently experienced markedly different outcomes.
“Those with more Alzheimer's-like patterns experienced faster cognitive decline, greater amyloid accumulation and a higher likelihood of developing cognitive impairment or Alzheimer's disease,” she said. “This suggests that changes in how different regions of the brain communicate may be detectable years before conventional cognitive assessments reveal significant problems.”
Gross added that the brain-connectivity patterns provided predictive information beyond established Alzheimer’s biomarkers, including amyloid and tau.
The findings suggest brain function could eventually give researchers another way to identify people at elevated risk while memory and thinking remain intact, potentially creating a longer window in which to study whether early intervention can delay cognitive decline.
Reference
Zhao, K., et al. (2026). A functional connectome identifies vulnerability to cognitive decline and Alzheimer’s disease progression. Science Advances. https://doi.org/10.1126/sciadv.aed9351.
Contact Newsweek editors on this story: Kara Dolman and Emma Lee-Sang
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