Researchers at Karolinska Institutet and Stockholm University have developed a computational tool named Pasta that estimates a cell's biological age by analyzing its gene activity patterns. The tool was described in a study published in the journal Advanced Science.
To build the model, the team analyzed gene expression data from more than 17,000 tissue samples collected from healthy individuals. The resulting algorithm was then tested on several independent datasets to verify its accuracy.
Unlike earlier biological-age clocks that often work only for a single tissue or data type, Pasta is designed to be broadly applicable across many tissues, cell types and laboratory techniques. This allows research groups to apply it to existing transcriptomic data without generating new measurements.
The researchers found that cells with high biological age showed increased activity in genes linked to DNA damage and cellular stress. The tool could also distinguish between senescent cells and more youthful, stem-cell-like populations.
In a subsequent screening, Pasta analyzed more than 3 million gene profiles from public databases where cells had been exposed to thousands of drugs and genetic alterations. The analysis highlighted substances and signaling pathways that appeared to increase or decrease cellular biological age.
Two candidates emerging from the screen were validated in laboratory experiments on human cells. Pralatrexate accelerated cellular aging, while piperlongumine made cells appear more youthful according to the model.
The authors emphasize that the findings are based on cell-based experiments and that further research is needed before any translation to patient treatments. The tool itself is freely available for use by other researchers.
Christian G. Riedel, a senior researcher at Karolinska Institutet and professor at Stockholm University, said the method enables biological age to be used as an experimental measure in many types of studies. Lead author Jérôme Salignon noted that the tool can help identify candidates for future treatments of age-related diseases and cancer.
New gene activity tool measures biological age of cells and screens aging-related compounds
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