Published on: May 07, 2025
In a study published this month in eBioMedicine, researchers from the University of Maryland School of Public Health and the School of Medicine at the University of Maryland, Baltimore, utilized artificial intelligence (AI) and a large dataset to explore how heart-healthy habits impact brain aging. The dataset included MRI brain scans of nearly 20,000 individuals, aged 40-69, from a United Kingdom database.
The researchers focused on white matter, which is vital for communication between brain regions and can deteriorate over time, potentially leading to memory and cognitive issues. Using machine learning, they estimated each participant’s brain age by analyzing MRI scans of white matter and compared this with their actual age.
Next, they evaluated participants based on eight factors promoted by the American Heart Association (AHA) known as Life’s Essential 8 (LE8), which includes diet, exercise, smoking, sleep, body mass index, lipids, hemoglobin, and blood pressure. The study found that higher LE8 scores were linked to less white matter loss, suggesting a delay in brain aging.
Tianzhou Charles Ma, associate professor of epidemiology and biostatistics at UMD and the study’s lead researcher, explained, Those who want to avoid early-onset dementia may benefit from more exercise or quitting smoking, which could be more effective than medication. It’s better not to wait until the disease sets in, as treatment becomes much more difficult.
The team also examined the APOE4 allele, the strongest genetic risk factor for Alzheimer’s disease. As expected, APOE4 carriers experienced more white matter loss. However, those adhering to AHA-promoted lifestyles showed reduced white matter loss, regardless of their APOE4 status.
This study, funded by the National Institutes of Health and supported by a UMD Grand Challenges grant, was made possible through a partnership between the University of Maryland, College Park (UMCP) and the University of Maryland, Baltimore (UMB).
In collaboration with Shuo Chen, a professor at the School of Medicine and expert in applying machine learning to neurological imaging, Ma’s team found that the combination of AI and large datasets allows for a deeper understanding of brain aging that would be impossible through manual analysis.
Chen added, We enhance each other's work, which accelerates the research and helps us mentor students in the process.
The UMD team’s work also extends to another paper published by the American Journal of Epidemiology, where they applied similar AI methods to match white matter scans with chronic stress levels. This study revealed that long-term stress accelerates brain aging, independent of other factors like sex, socioeconomic status, and lifestyle habits.
Together, these studies highlight the powerful role of AI in analyzing neuroimaging data, providing insights into brain health that could lead to more personalized prevention strategies. Ma emphasized the importance of long-term management in preserving brain health and preventing dementia.
Source: https://today.umd.edu/heart-healthy-lifestyles-can-also-delay-brain-aging-umd-researchers-find
Back to News
Empowering Innovation Through Global Conferences and Events.
© 2025 SciInov. All Rights Reserved.