Research indicates that electrocardiogram (ECG) tests, which monitor the heart’s electrical activity, may one day be used alongside artificial intelligence (AI) to identify signs of premature aging and cognitive decline. The study revealed that individuals with an ECG age that suggested accelerated aging scored lower on cognitive tests compared to those with normal aging. These preliminary findings are scheduled to be presented at the International Stroke Conference hosted by the American Stroke Association in Los Angeles. It’s important to note that the results remain preliminary until they undergo full publication in a peer-reviewed journal.
Bernard Ofosuhene, the lead author and a clinical research coordinator at UMass Chan Medical School, explained in a statement that unlike chronological age, which is simply a count of years lived, ECG age gives a picture of the heart’s functional status and potentially reflects overall health at a cellular level. This measurement provides valuable insights into both aging and general health condition.
The heart generates electrical impulses with each beat, which are translated into a visual representation through an ECG, commonly referred to as an EKG. This technique allows healthcare providers to identify potential heart issues. For this investigation, researchers developed an AI model to predict biological age based on ECG data, which indicates how well an individual’s cells and tissues are functioning. Previous research has established a correlation between ECG age, heart disease, and mortality, but its connection to cognitive impairment had been largely unexplored until now. Given the widespread use of ECGs in diagnosing heart conditions and strokes, the new AI tool could prove beneficial in identifying individuals who are at risk for cognitive decline.
In this study, data from 63,800 participants aged 40 to 69 was analyzed from the UK Biobank, which continues to collect health information from over half a million volunteers in the United Kingdom. These individuals underwent ECG tests and cognitive assessments during their medical visit from August 2023 to July 2024. The AI model was applied to evaluate their ECG age.
The results showed that 15,563 participants experienced normal aging, while 24,671 showed signs of accelerated aging, and 23,566 demonstrated decelerated aging. Notably, those classified in the accelerated aging category exhibited significantly poorer cognitive test results compared to those in the normal aging group. Conversely, participants whose ECGs indicated slower aging performed better on the assessment.
Specifically, individuals whose ECG age appeared younger than their chronological age outperformed their counterparts in six out of eight cognitive evaluations, while those with an older ECG age struggled on six tests. Ofosuhene emphasized the importance of utilizing available ECG data in stroke treatment to look for early signs of cognitive decline, which could assist in timely diagnosis and intervention.
The team plans to explore whether factors such as gender impact the relationship between ECG age and cognitive performance in future research. Additionally, since most participants in the UK Biobank are of white European descent, the research team aims to evaluate if similar outcomes are observed in more diverse demographics.
This research contributes to the increasing recognition of the relationship between cardiovascular and cognitive health. Dr. Fernando D. Testai, a neurology professor at the University of Illinois College of Medicine and chair of a committee focused on cardiovascular diseases and cognitive functions, expressed that using ECG data for cognitive assessments, while it might seem innovative, could yield significant benefits if validated. He noted that ECG data, whether obtained during visits to a healthcare provider or remotely through wearable devices, might provide a means to assess cognitive health more efficiently, especially in rural areas where neuropsychiatric specialists are scarce. The incorporation of AI into this data collection could streamline the process better than traditional methods. However, Testai raised a critical question: Can ECG data be utilized to predict future cognitive decline? Addressing this query could unlock potential therapies for those at risk.
Overall, the study underscores the evolving connection between heart health and cognitive function, highlighting a pertinent area for future research and exploration.
