New way to predict life expectancy has been discovered

Now, a team of researchers led by Alexander Tyshkovsky and Vadim Gladyshev has proposed a new approach. They analyzed more than 11,000 samples of genetic transcripts (i.e., data on which genes are turned on and actively producing RNA) from 25 types of tissues in mice, rats, macaques, and humans. They found that the age-related changes in the transcriptome were similar across these species, allowing them to identify universal biomarkers of mammalian aging.

It turned out that as cells age, the activity of genes associated with cell aging, inflammation, and programmed cell death increases. At the same time, the genes responsible for wound healing, cell differentiation, and extracellular matrix synthesis are reduced. These patterns persisted regardless of the type and type of tissue.

Based on the data obtained, scientists have developed a multi-species and multi-tissue molecular clock. They not only determine the chronological age of an organism, but also predict life expectancy. The accuracy of such predictions is comparable to that of the modern second-generation epigenetic clock.
The advantage of the new method is that transcriptomes reflect current processes in the body — unlike epigenetic markers, they allow for real-time assessment of the effectiveness of life-prolonging agents. For example, they can be used to quickly understand how potential geroprotectors work at the molecular level.

In an accompanying article, João Pedro de Magalhães notes that the discovered biomarkers will help to more accurately track how various interventions or diseases affect the mechanisms of aging. However, it is still unclear whether these markers are the cause of age-related changes or simply a side effect, and further research is needed to determine this.