AI Analysis of ECG Data Reveals Link Between Heart Aging and Cognitive Performance

An artificial intelligence model designed to predict biological age from electrocardiogram data has revealed a significant association between heart aging and cognitive performance, according to preliminary research to be presented at the American Stroke Association's International Stroke Conference 2025. The study analyzed data from more than 63,000 participants in the UK Biobank, a large ongoing study available at https://www.ukbiobank.ac.uk, finding that those with accelerated ECG aging performed worse on cognitive tests than those with normal aging patterns.

Researchers developed a deep neural network AI model to predict biological age from ECG data, which reflects the functional status of the heart and potentially the entire organism at the tissue level. Unlike chronological age based on years lived, ECG-age provides insights into aging and health status. Participants were divided into three groups based on their ECG-age compared to chronological age: normal aging, accelerated aging (older than chronological age), and decelerated aging (younger than chronological age).

The analysis demonstrated that compared to the normal aging group, participants with accelerated ECG aging performed worse on six of eight cognitive tests, while those with decelerated aging performed better on six of eight tests. This finding suggests that the biological age of the heart, as determined by AI analysis of ECG data, may serve as an indicator of cognitive health. The research builds on previous studies showing that ECG-age can help predict heart disease and death, but this is among the first to explore its relationship to cognitive impairment.

Bernard Ofosuhene, B.A., lead author and clinical research coordinator at UMass Chan Medical School, emphasized the potential clinical applications: "There is a lot of ECG-data available for stroke treatment and I encourage health care professionals to use this data to look for signs of cognitive decline. Doing so may help with early diagnosis and timely intervention." The study's findings align with growing recognition of the strong connection between heart and brain health, as highlighted in the American Heart Association scientific statement available at https://www.heart.org/en/professional/science-and-research.

However, the study has several limitations. The analysis was conducted on people between ages 43 and 85, so it's unclear whether the findings apply to other age groups. As a cross-sectional study with all measures taken simultaneously, it cannot provide information about changes in cognitive function over time. Additionally, most participants were of white European descent, limiting generalizability to other populations. Future research aims to investigate gender differences and determine if findings can be replicated in more diverse populations.

Fernando D. Testai, M.D., Ph.D., FAHA, chair of the American Heart Association's cardiac contributions to brain health statement, noted that if validated, this approach could have significant implications: "ECG data collected in a doctor's office or remotely with wearables could help assess cognition at home or in rural areas lacking neuropsychiatric specialists. Additionally, using ECG data and AI might be quicker and more objective than traditional neuropsychological assessments." The critical remaining question is whether ECG data can predict future cognitive decline, which could lead to valuable treatments since some ECG issues can be addressed medically.