Aging is a major risk factor for many diseases, but reliable methods for measuring how quickly cells age have been lacking. Now, researchers at Karolinska Institutet and Stockholm University have developed a new tool called Pasta that estimates a cell’s biological age by analyzing its gene activity, and in a study published in Advanced Science, they also demonstrate how the tool can identify substances that influence cellular aging.
To build Pasta, the researchers analyzed gene activity data from more than 17,000 tissue samples taken from healthy people, then tested the model on several independent datasets. “Previous tools for measuring biological age often only work for a single tissue or type of data, which limited their usefulness. We built Pasta to be broadly applicable across many tissues, cell types and laboratory techniques, so that all research groups can apply it to the data they already have,” said first author Jérôme Salignon. “With this tool, we can track how cells change over time and gain insights into the mechanisms driving ageing,” Salignon added.
The researchers found that cells with high biological age often showed increased activity in genes linked to DNA damage and cellular stress, and the tool could distinguish between older, senescent cells and more youthful, stem cell-like cells. Pasta was then used to analyze more than three million gene profiles from public databases where cells had been exposed to thousands of drugs and genetic alterations, identifying substances and biological signaling pathways that appeared to increase or decrease cells’ biological age; some results were subsequently confirmed in laboratory experiments on human cells.
“Reliably determining the biological age of cells has long been a major challenge. We can now do this using gene expression data—a type of data that is already routinely generated in a great many research studies. I believe we are thus entering a new era in which biological age can be used as an experimental measure in many different types of studies. Pasta opens up entirely new possibilities for understanding the mechanisms behind ageing and for systematically searching for genes and substances that can influence it,” senior author Christian G. Riedel said.
Salignon added that the tool can help identify candidates for future treatments of age-related diseases and cancer. In laboratory experiments, the team validated two new candidates: pralatrexate, which accelerated cellular ageing, and piperlongumine, which made cells more youthful. He cautioned that the results are based on cell-based experiments, so further research is needed before they could be translated into patient treatments.
To build Pasta, the researchers analyzed gene activity data from more than 17,000 tissue samples taken from healthy people, then tested the model on several independent datasets. “Previous tools for measuring biological age often only work for a single tissue or type of data, which limited their usefulness. We built Pasta to be broadly applicable across many tissues, cell types and laboratory techniques, so that all research groups can apply it to the data they already have,” said first author Jérôme Salignon. “With this tool, we can track how cells change over time and gain insights into the mechanisms driving ageing,” Salignon added.
The researchers found that cells with high biological age often showed increased activity in genes linked to DNA damage and cellular stress, and the tool could distinguish between older, senescent cells and more youthful, stem cell-like cells. Pasta was then used to analyze more than three million gene profiles from public databases where cells had been exposed to thousands of drugs and genetic alterations, identifying substances and biological signaling pathways that appeared to increase or decrease cells’ biological age; some results were subsequently confirmed in laboratory experiments on human cells.
“Reliably determining the biological age of cells has long been a major challenge. We can now do this using gene expression data—a type of data that is already routinely generated in a great many research studies. I believe we are thus entering a new era in which biological age can be used as an experimental measure in many different types of studies. Pasta opens up entirely new possibilities for understanding the mechanisms behind ageing and for systematically searching for genes and substances that can influence it,” senior author Christian G. Riedel said.
Salignon added that the tool can help identify candidates for future treatments of age-related diseases and cancer. In laboratory experiments, the team validated two new candidates: pralatrexate, which accelerated cellular ageing, and piperlongumine, which made cells more youthful. He cautioned that the results are based on cell-based experiments, so further research is needed before they could be translated into patient treatments.