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| Item Type: | Review |
|---|---|
| Title: | How to measure and model cardiovascular aging |
| Creators Name: | Spray, Luke, Richardson, Gavin, Booth, Laura K., Haendeler, Judith, Altschmied, Joachim, Bromage, Daniel I., Wallis, Sienna B., Stellos, Konstantinos, Tual-Chalot, Simon and Spyridopoulos, Ioakim |
| Abstract: | Most acquired cardiovascular diseases are more common in older people, and the biological mechanisms and manifestations of aging provide insight into cardiovascular pathophysiology. Measuring aging within the cardiovascular system may help to better understand risk profiles for specific individuals and direct targeted preventative therapy. In this review, we explore telomere attrition, cellular senescence, epigenetic modifications, and mitochondrial dysfunction as key molecular mechanisms of aging. These phenomena are associated with cardiovascular disease through endothelial dysfunction and systemic inflammation, which are measurable in clinical practice with a variety of clinical, laboratory, and imaging techniques. Finally, we discuss that the next tools for modelling cardiovascular aging must be capable of incorporating a vast amount of diverse data from a given patient, pointing to recent developments in artificial intelligence and machine learning. |
| Keywords: | Aging, Inflammation, Senesence, Cardiovascular Disease, Modelling, Animals |
| Source: | Cardiovascular Research |
| ISSN: | 0008-6363 |
| Publisher: | Oxford University Press |
| Volume: | 121 |
| Number: | 10 |
| Page Range: | 1489-1508 |
| Date: | August 2025 |
| Official Publication: | https://doi.org/10.1093/cvr/cvaf138 |
| PubMed: | View item in PubMed |
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