A groundbreaking study presented at the upcoming American Stroke Association's International Stroke Conference reveals how artificial intelligence could transform understanding of cognitive aging through electrocardiogram (ECG) analysis. Researchers at UMass Chan Medical School developed a deep neural network capable of predicting biological age and correlating it with cognitive performance.
The study analyzed data from 63,000 United Kingdom Biobank participants, examining the relationship between ECG-derived biological age and cognitive test results. Participants were categorized into three groups: normal aging, accelerated ECG-aging, and decelerated ECG-aging based on their ECG data compared to chronological age.
Significant findings emerged from the research. Participants with ECG ages younger than their chronological age performed better on six out of eight cognitive tests. Conversely, those with accelerated ECG aging scored worse on the same cognitive assessments, suggesting a potential link between heart health markers and cognitive function.
Lead researcher Bernard Ofosuhene emphasized the study's innovative approach, noting that ECG-age reflects the functional status of the heart and potentially the entire organism at the tissue level. This method offers insights into aging and health status beyond traditional chronological age measurements.
The research has profound implications for early cognitive decline detection. By utilizing widely available ECG data and artificial intelligence, healthcare professionals might soon have a quick, objective method to assess cognitive health. This could be particularly valuable in rural areas or settings with limited access to neuropsychiatric specialists.
However, the study acknowledges several limitations. The research focused on participants aged 43-85 of predominantly European descent, which may limit generalizability. Future research aims to investigate potential gender differences and explore the findings' applicability across diverse populations.
Fernando D. Testai, an independent expert not involved in the study, highlighted the growing recognition of the connection between heart and brain health. He suggested that if validated, this approach could provide a revolutionary method for cognitive assessment using existing medical technology.
While the findings are preliminary and require further validation, they represent a significant step toward understanding the intricate relationship between cardiovascular health, aging, and cognitive performance. The potential for early intervention and personalized health monitoring makes this research a promising avenue for future medical diagnostics.
