Researchers have launched a new database dedicated to mapping and understanding the complexity of cellular senescence in a bid to help us fully understand this age-related phenomenon.

Introducing the CellAge database

The Human Ageing Genomic Resources (HAGR) is a series of databases and tools that have been developed to aid researchers on aging and help them study the genetic elements of human aging. The databases utilize modern techniques, such as functional genomics, network analyses, systems biology, and evolutionary analyses, to build what is one of the most valuable resources available today.

A team of researchers, including Dr. João Pedro de Magalhães, has just announced that the already impressive HAGR resource will be supplemented with a new database that is focused on the genes associated with cellular senescence.

Thes researchers have published the results of their new study in Biorxiv, a preprint website for biology research [1]. Biorxiv is interesting in that it allows researchers to publish their data prior to peer review, thus facilitating the faster sharing of knowledge; the caveat is that such data has not yet passed the peer review process.







The aim of the new CellAge database is to collect as much information on the biochemistry of senescent cells as possible in order to help speed up progress towards a full understanding of these cell populations and their interactions with the rest of the body in the context of aging.

Charting the complexity of senescent cells

As you age, increasing numbers of your cells enter into a state known as senescence. Senescent cells do not divide or support the tissues of which they are part; instead, they emit a range of potentially harmful chemical signals that encourage nearby healthy cells to enter the same senescent state. Their presence causes many problems: they reduce tissue repair, increase chronic inflammation, and can even eventually raise the risk of cancer and other age-related diseases.

While the understanding of senescent cells and how they work has increased dramatically in the last decade or so, it is still not totally clear where the dividing line between a normal and senescent cell lies, so determining if a cell has entered senescence is not as clear-cut as one might think.

At one time, the gold standard for indicating cellular senescence was the presence of senescence-associated β-galactosidase (SA-β-gal) or cyclin-dependent kinase inhibitor 2A (p16INK4A). However, our understanding of cellular senescence has advanced beyond this, and we now know that other types of healthy functional cells also display β-galactosidase activity, including macrophages, osteoclasts, and cells undergoing autophagy. There are also types of cellular senescence that occur independently of p16INK4A expression, and healthy cells can also express it.







Therefore, there is a critical need for more sophisticated biomarkers of cellular senescence in order to better understand and develop therapies that can remove them from the body efficiently. With over two hundred genes associated with cellular senescence in humans, the need to chronicle the data is becoming ever-more important, and this is why CellAge was built.

Cellular senescence, a permanent state of replicative arrest in otherwise proliferating cells, is a hallmark of ageing and has been linked to ageing-related diseases like cancer. Senescent cells have been shown to accumulate in tissues of aged organisms which in turn can lead to chronic inflammation. Many genes have been associated with cell senescence, yet a comprehensive understanding of cell senescence pathways is still lacking. To this end, we created CellAge, a manually curated database of 279 human genes associated with cellular senescence, and performed various integrative and functional analyses. We observed that genes promoting cell senescence tend to be overexpressed with age in human tissues and are also significantly overrepresented in anti-longevity and tumour-suppressor gene databases. By contrast, genes inhibiting cell senescence overlapped with pro-longevity genes and oncogenes. Furthermore, an evolutionary analysis revealed a strong conservation of senescence-associated genes in mammals, but not in invertebrates. Using the CellAge genes as seed nodes, we also built protein-protein interaction and co-expression networks. Clusters in the networks were enriched for cell cycle and immunological processes. Network topological parameters also revealed novel potential senescence-associated regulators. We then used siRNAs and observed that of 26 candidates tested, 19 induced markers of senescence. Overall, our work provides a new resource for researchers to study cell senescence and our systems biology analyses provide new insights and novel genes regarding cell senescence.

Conclusion

The HAGR database just keeps on getting bigger and better and is, without a shadow of a doubt, a highly valuable resource in the quest to fully understand aging and how we might intervene upon those processes to delay, prevent, or even reverse age-related diseases.







Literature

[1] Avelar, R. A., Ortega, J. G., Tacutu, R., Tyler, E., Bennett, D., Binetti, P., … & Shields, S. (2019). A Multidimensional Systems Biology Analysis of Cellular Senescence in Ageing and Disease.