A study led by UC San Francisco and Beth Israel Deaconess Medical Center reports on Mar. 26 that analyzing brain waves recorded during sleep may help identify people at higher risk of developing dementia.
Researchers found that when a person’s “brain age,” as estimated from sleep signals using electroencephalogram (EEG), was older than their actual age, the risk of developing dementia rose. Specifically, for every 10-year increase in brain age compared to chronological age, the risk increased by nearly 40%. Conversely, those whose brain age was younger than their actual age had a lower risk.
The findings are based on data from approximately 7,000 participants aged between 40 and 94 years old who did not have dementia at the start of the study. Participants were followed for periods ranging from three and a half to seventeen years; about 1,000 developed dementia during this time. The research team used a machine-learning model that integrated thirteen microstructural features of EEG-recorded brain waves collected during sleep.
According to senior author Yue Leng, MBBS, Ph.D., associate professor of psychiatry at UCSF School of Medicine: “Broad sleep metrics don’t fully capture the complex multidimensional nature of sleep physiology.” The study notes that earlier analyses using conventional measures such as time spent in different stages or overall efficiency did not find significant links with dementia risk.
Several specific EEG patterns associated with cognitive health were highlighted in the research. Delta waves—linked to deep sleep—and spindles—associated with memory consolidation—were among those analyzed. Notably, sudden large spikes known as kurtosis on EEGs were linked to lower dementia risk. The association between an older-appearing brain and increased dementia remained significant even after accounting for factors like education level, smoking status, body mass index (BMI), physical activity levels, other health conditions and genetic risks.
Because EEG signals can be collected noninvasively—including through wearable technology—the authors suggest this approach could eventually allow early detection outside clinical settings. “Brain age is calculated from sleep brain waves,” Leng said. “We know that brain activity during sleep provides a measurable window into how well the brain is aging.” First author Haoqi Sun, Ph.D., assistant professor of neurology at Beth Israel Deaconess Medical Center added: “Better body management, such as lowering body mass index and increasing exercise to reduce the likelihood of apnea, may have an impact… But there’s no magic pill to improve brain health.”
