New Delhi

Researchers have developed a tool that can estimates a cell's biological age by analysing its gene activity and determining which genes are active or inactive.

The tool, named 'Pasta' and described in a paper in the journal Advanced Science, can also identify substances that influence cellular ageing and distinguish between older, senescent cells, and more youthful, stem cell-like cells.

Researchers from Sweden's Karolinska Institutet and Stockholm University said while ageing is a major risk factor for many diseases, there is a lack of methods that can reliably measure how quickly cells age.

Cells with high biological age often exhibited an increased activity in genes linked to DNA damage and cellular stress, they found.

Gene activity data from more than 17,000 tissue samples taken from healthy people was analysed for developing the tool.

In the next stage, the researchers used Pasta to analyse more than three million gene profiles from public databases where cells had been exposed to thousands of drugs and genetic alterations.

The analysis identified substances and biological signalling pathways that appeared to increase or decrease a cell's biological age -- some of the results were subsequently confirmed in laboratory experiments on human cells.

"With this tool, we can track how cells change over time and gain insights into the mechanisms driving ageing," lead author Jérôme Salignon, a researcher at the Karolinska Institutet, said.

"The tool can help us identify candidates for future treatments of age-related diseases and cancer. In laboratory experiments, we validated two new candidates: pralatrexate, which accelerated cellular ageing, and piperlongumine, which made the cells more youthful," Salignon said.

However, our results are based on cell-based experiments. Further research is needed before they can be translated into treatments for patients, the lead author said.

Previous tools for measuring biological age often only work for a single tissue or type of data, which limited their usefulness, the researchers said.

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"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," they said.