Researchers have developed an artificial intelligence model that could potentially use electrocardiogram data to detect premature aging and cognitive decline, according to a preliminary study to be presented at the American Stroke Association's International Stroke Conference 2025. The study analyzed data from over 63,000 participants in the UK Biobank, examining the relationship between ECG-determined biological age and cognitive performance. By using a deep neural network, researchers classified participants into three groups: normal aging, accelerated ECG-aging, and decelerated ECG-aging.
Bernard Ofosuhene, the study's lead author, explained that ECG-age reflects the functional status of the heart and potentially the entire organism at the tissue level, providing unique insights into aging and health status. Unlike chronological age, which simply counts years lived, ECG-age offers a more nuanced view of an individual's biological aging process. This distinction between chronological and biological aging represents a significant advancement in how medical professionals might assess overall health and aging trajectories in clinical settings.
The analysis revealed significant cognitive performance differences among the groups. Participants with decelerated ECG-aging performed better on 6 of 8 cognitive tests, while those with accelerated ECG-aging performed worse on the same tests. This suggests a strong correlation between heart health indicators and cognitive function. The findings indicate that cardiovascular health, as measured through ECG data, may serve as a proxy for brain health and cognitive preservation, potentially offering clinicians a new tool for assessing patients' neurological status through cardiac evaluation.
Fernando D. Testai, who was not involved in the study, noted the potential implications of this research. The approach could enable cognitive assessments using ECG data collected in doctors' offices or through wearable devices, potentially providing more accessible and objective evaluations, especially in areas with limited neuropsychiatric specialists. This accessibility factor is particularly important given the growing global burden of age-related cognitive disorders and the uneven distribution of specialized neurological care across different regions and healthcare systems.
However, the study has limitations. The research was conducted on participants aged 43 to 85 and primarily involved individuals of European ancestry, which may restrict the generalizability of the findings. Future research aims to investigate potential gender differences and explore the results' applicability in more diverse populations. While promising, the researchers emphasize that the study is preliminary and requires further validation. The key question remains whether ECG data can predict future cognitive decline, which could lead to valuable early interventions and treatments. This predictive capability would represent a significant advancement in preventive neurology and geriatric medicine, potentially allowing for earlier lifestyle interventions or pharmacological treatments before significant cognitive impairment occurs.
