Reversing age by reprogramming gene expression networks
Every organ and tissue progressively loses function and integrity as it ages. In fact, researchers have identified "hallmarks of aging" that not only present specific processes impacted by age, but are also thought of as levers that, if successfully targeted, could help turn back the aging clock and result in tissue rejuvenation.
Aging research has identified hallmarks of aging that impact specific processes and are considered potential levers for rejuvenating tissues. In 2006, Shinya Yamanaka's discovery that overexpressing four genes could reprogram mature cells to an undifferentiated, pluripotent state was a significant milestone. However, the therapeutic use of Yamanaka factors raises concerns about cancer risk. Researchers are now seeking safer and more controllable ways to rejuvenate aging tissues.
A team led by George Church and Alex Plesa at the Wyss Institute at Harvard University and the Basque Research and Technology Alliance in Spain developed a novel age predictor using machine learning. This predictor, trained on gene expression profiles across multiple aging processes in human skin fibroblast cells, accurately estimated the transcriptomic age of cells from various donors.
Using this predictor, the team screened genes predicted to affect aging processes and identified SRSF1 as a top candidate. SRSF1, an RNA processing factor, reduced features associated with aging, such as cellular senescence, proteostatic stress, and inflammaging. When delivered to aged mice, SRSF1 reduced the animals' rate of aging and extended their lifespan by 14%.
This study, published in Nature Aging, represents a significant step towards developing clinically useful de-aging strategies by identifying genes that can be engineered to extend human health span. The researchers aim to test SRSF1 as a geroprotective target in aging processes, offering a promising avenue for advancing aging research.
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