Antiseizure Medication Use and Multidimensional Biological Aging: A UK Biobank Study
A UK Biobank cross-sectional study of over 320,000 participants found that antiseizure medication use is associated with accelerated multidimensional biological aging across multiple physiological and molecular indicators, though the cross-sectional design precludes causal conclusions.
Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
Most of us measure our age by the number of birthdays we have celebrated, a simple count of years since birth. But inside our bodies, the story is often different. Our cells, organs, and systems age at their own pace, sometimes speeding up or slowing down based on our health, environment, and the medicines we take. Scientists have developed ways to measure this "biological age," looking at markers like the length of protective caps on our DNA, the balance of chemicals in our blood, and how well our body maintains its internal stability. Understanding whether common long-term treatments speed up or slow down this internal clock is a crucial question for public health, especially for people who rely on daily medication to manage chronic conditions.
In a large study involving hundreds of thousands of people from the United Kingdom, researchers investigated how the use of antiseizure medications relates to this biological aging. These drugs, often prescribed for epilepsy but also for nerve pain and mood disorders, are taken for years or even decades. The team examined data from the UK Biobank, a massive health database, to see if people who took these medicines showed signs of being biologically older than their actual years would suggest. They focused on four specific indicators: a measure of how much the body's systems are out of balance, a score based on blood markers that predicts mortality, a calculation of how much older a person's body looks compared to their calendar age, and the length of telomeres, which are the protective tips on our DNA strands that shorten as we age.
The researchers identified nearly 322,000 participants, of whom about 5,000 had been taking antiseizure medications continuously for at least a year. To ensure a fair comparison, they matched these medication users with non-users who shared similar characteristics like age, sex, and lifestyle habits. When they compared the two groups, a clear pattern emerged. Those taking the medications showed signs of accelerated biological aging across the board. Specifically, they had higher scores for bodily imbalance and appeared biologically older by nearly one year on average compared to their non-using peers. They also had shorter telomeres, a molecular sign of aging, than those not taking the drugs.
However, the story became more complex when the researchers looked at specific drugs rather than the group as a whole. The effects were not uniform across all medications. Some drugs, such as gabapentin and pregabalin, were linked to more pronounced signs of aging, including shorter telomeres and higher levels of bodily stress. Others, like phenytoin and valproic acid, were also associated with higher aging scores. In contrast, medications like lamotrigine and topiramate showed a different pattern, with users appearing biologically younger or showing fewer signs of stress in certain measures compared to users of other drugs. Yet, even these "better" results were relative; the study did not prove that these drugs slow aging, only that they were associated with less unfavorable profiles than some other options in the group.
It is vital to understand what this study can and cannot tell us. Because the data was collected at a single point in time, the researchers cannot say that the medications caused the aging. It is possible that the underlying conditions requiring these drugs, or the severity of those conditions, are what drive the biological changes. The study authors explicitly state that their findings do not prove causation and that the observed links could be influenced by factors like disease severity or other health issues. Furthermore, the differences found, while statistically significant, were modest in size for any single individual. The research serves as a signal rather than a verdict, highlighting a need for future studies that track patients over time to see if these patterns hold up and to determine whether the medications themselves, the reasons they are prescribed, or a combination of both are responsible for the observed biological shifts.
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