New Computational Tool Estimates Cell Age by Analyzing Gene Activity Patterns

Scientists at Karolinska Institutet and Stockholm University have created an innovative tool that determines cellular biological age through gene activity analysis. In the study published in Advanced Science, the team also showed how the tool identifies compounds that can affect the rate of cellular aging.

Although aging is a major risk factor for many health conditions, reliable techniques for measuring cellular aging rates remain scarce. The investigators introduce Pasta – an open-access tool that computes cellular age by evaluating active and silent gene patterns.

To build this tool, the scientific team processed gene expression profiles gathered from over 17,000 healthy tissue samples. They subsequently validated the resulting model against multiple external data sources.

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. With this tool, we can track how cells change over time and gain insights into the mechanisms driving aging.

Jérôme Salignon, Study Lead Author and Researcher, Department of Medicine, Huddinge, Karolinska Institutet

Jérôme Salignon headed the research along with Federico Pietrocola, a senior researcher at the Department of Cell and Molecular Biology, Karolinska Institutet, and Christian G. Riedel, a professor at Stockholm University and a senior researcher at the Department of Medicine, Huddinge, Karolinska Institutet.

Investigators noted that cells with high biological age often showed heightened activity in genes tied to DNA damage and cellular stress. The tool also distinguished between mature, senescent-type cells and younger, stem-like cell populations.

Next, Pasta analyzed over three million gene profiles from open repositories detailing cells subjected to thousands of drugs and genetic modifications. This evaluation pinpointed compounds and biochemical pathways that seemed to accelerate or reduce cellular biological age. Researchers later verified some of these findings through lab experiments using human cell cultures.

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.

Christian G. Riedel, Professor, Stockholm University

“Pasta opens up entirely new possibilities for understanding the mechanisms behind aging and for systematically searching for genes and substances that can influence it,” says Christian Riedel.

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 aging, and piperlongumine, which made the cells more youthful. However, our results are based on cell-based experiments, so further research is needed before they can be translated into treatments for patients.

Jérôme Salignon, Study Lead Author and Researcher, Department of Medicine, Huddinge, Karolinska Institutet