Stanford Medicine scientists, in collaboration with colleagues from other American institutions, have developed a method that can predict the risk of developing Alzheimer’s disease and cognitive decline based on brain activity patterns years before clinical symptoms appear.
According to the study, features of functional connections between different brain regions may be an early indicator of brain resilience or vulnerability to Alzheimer’s.
“Super-Agers” and People with Alzheimer’s Disease
As part of the study, scientists used functional magnetic resonance imaging (fMRI) to examine resting-state brain activity in people aged 75 and older. Two distinct groups were compared: individuals diagnosed with Alzheimer’s disease and so-called “SuperAgers” — older adults whose memory abilities match those of 45-year-olds, while their executive functions remain within the normal range for their age. Analysis of the brain’s functional connectome, or functional connections between different regions, showed that these two groups have distinct patterns of brain activity. Based on these differences, the scientists created an assessment model that they were also able to use in younger people without cognitive impairments.
ARC Score — A New Measure of Brain Resilience and Vulnerability to Alzheimer’s
Researchers developed a special evaluation system — the Alzheimer’s Resilience-Vulnerability Connectome score (ARC score). It evaluates the features of functional connections in the brain and determines how closely an individual’s brain activity patterns resemble those characteristic of “SuperAgers” or individuals with Alzheimer’s disease. To assess the discriminative ability of the evaluation system, the AUC (area under the curve) value was 0.85, indicating a clear ability to reveal differences between these two groups.
The researchers then evaluated how well this system (ARC score) could predict cognitive decline in 1,315 people aged 55 to 70. Participants had no cognitive impairments at the start of the study. Participants were observed for varying durations.
The observation period lasted up to 12 years, though in most cases it was 5–6 years.
Although the cognitive abilities of individuals with high and low scores did not differ significantly at the beginning of the study, long-term observation showed different results. Participants with a high ARC score experienced faster decline in memory, attention, and executive functions over time. In contrast, individuals with low scores, whose functional brain connections resembled those of “SuperAgers,” experienced the slowest cognitive decline.
Scientists compared the predictive ability of the ARC score with existing demographic, genetic, and biological indicators, including amyloid-beta and tau biomarkers (the main biomarkers for Alzheimer’s). It turned out that the ARC score could predict cognitive decline as well as, or in some cases better than, these indicators. Furthermore, when scientists used the ARC score in combination with data from other biomarkers, predictive capability increased even further.
Prevention Prospects and Significance of the Method
Alzheimer’s disease begins developing long before cognitive symptoms appear. That is why assessing disease risk at an early stage is particularly important — it creates the opportunity to plan targeted interventions in the future. These include cognitive exercises and transcranial magnetic stimulation (a non-invasive neuromodulation technique), which might influence brain activity patterns.
However, these approaches have not yet been tested for the prevention of cognitive decline, and it remains unknown whether changing brain activity can alter the course of disease development.
At this stage, the ARC score is not a diagnostic tool. It is an additional instrument for assessing the brain’s functional state and vulnerability to cognitive decline. Moreover, the score reflects only a temporary snapshot of a person’s condition rather than an unchangeable future — brain activity patterns can change with age and under the influence of various factors.
The ultimate goal of the study’s authors is to determine whether it is possible to cultivate brain activity patterns that promote cognitive resilience and reduce the risk of developing Alzheimer’s disease.
