Universal molecular ‘clocks’ of ageing and mortality identified in mammals

Ageing is the main risk factor for most chronic diseases, from cancer to cardiovascular and neurodegenerative disorders. However, we still only partially understand its cellular and molecular mechanisms. In this context, the present study represents an important advance by integrating transcriptomic analyses from more than 11,000 samples across different organs and mammalian species, together with experimental data and large-scale bioinformatic analyses, to propose a potential molecular ‘clock’ of ageing and lifespan. The fact that many of these pathways are conserved across species reinforces their biological relevance and suggests that they may represent fundamental mechanisms of ageing. Among the biomarkers identified, Cdkn1a stands out, as it encodes the p21 protein, which plays a key role in the regulation of cellular senescence.

These findings could have important applications in preventive medicine, enabling earlier identification of individuals at greater risk of developing age-related diseases and allowing more refined clinical monitoring. They could also help address one of the major challenges in the field: the lack of reliable biomarkers to assess the effectiveness of anti-senescence or anti-ageing therapies in humans. This study provides promising candidates in that direction.

Nevertheless, the results should be interpreted with caution, as they are likely to reflect both mechanisms driving ageing and the consequences of the ageing process itself. In this regard, it would be particularly interesting to investigate how these biomarkers behave in populations that are exceptionally resilient to ageing, such as centenarians.

The study can be considered high quality owing to its scale (more than 11,000 transcriptomes), its comparative multi-species design (mouse, rat, macaque and human), and its extensive validation across both in vivo and in vitro models as well as longitudinal human data. In addition, it integrates multiple tissues and employs different methodological approaches — including statistical models, machine learning and network analysis — which strengthens the robustness of the findings.

Nevertheless, there are important limitations. The study is correlational in nature, and its observational design prevents the establishment of causality; the transcriptomic changes observed could be consequences rather than drivers of ageing. Potential technical biases between heterogeneous datasets also remain, and although human data are included, much of the mechanistic evidence derives from animal models.

In terms of prior evidence, the work is consistent with existing ‘epigenetic clocks’, but it provides greater functional interpretability by directly linking genes and biological pathways to ageing, mortality and responses to interventions.

The implications of identifying universal transcriptomic signatures are profound. They suggest that ageing and mortality share a conserved molecular architecture across mammals, dominated by processes such as inflammation, cellular senescence and mitochondrial dysfunction, reinforcing the idea of common underlying ageing mechanisms. Inflammation is already known to be a marker of many diseases, including obesity and cancer. It is therefore not particularly surprising that it also emerges as a marker of ageing, probably as a response to the DNA damage that accumulates as cells grow older.

However, clinical translation remains limited. Although the transcriptomic clocks predict mortality in humans with accuracy comparable to epigenetic clocks, their practical application will require standardisation, cost reduction and prospective validation in clinical populations.

Overall, the study represents an important conceptual advance, but its clinical impact remains uncertain and will depend on demonstrating predictive utility and the capacity to guide interventions in real-world settings.

How old is our body really? The remarkable increase in life expectancy that humanity has experienced over the last century has made ageing the main risk factor for numerous conditions, such as neurodegenerative diseases, cardiovascular diseases and cancer. Thus, the development of tools to quantify the biological deterioration of the body and evaluate gerotherapeutics capable of slowing down some of the biological processes associated with old age could have a decisive impact on the prevention and treatment of these conditions.

With this aim in mind, more than 11,000 transcriptomes from biological tissue samples of humans, primates and rodents of different ages have been used by Vadim Gladyshev’s group at Brigham and Women’s Hospital and Harvard Medical School to construct so-called ‘ageing clocks’: mathematical models that allow the ‘biological age’ of an organism to be estimated, a measure of accumulated biological decline that may reflect actual health status better than the number of years elapsed since birth. Furthermore, unlike the well-known ‘epigenetic clocks’, which are based on chemical modifications to DNA that occur over time, this study is based on changes in gene activity, providing more direct information on how cells function and, consequently, offering a highly useful additional layer of insight.

One of the most striking findings of the study is that certain interventions — such as calorie restriction without malnutrition or the controlled administration of certain nutritional supplements — manage to mitigate or even reverse some of these biological processes associated with old age. Furthermore, the study stands out for its high technical quality, underpinned by the large scale and diversity of the data analysed, and demonstrates the scientific and medical potential of ageing clocks.

Its translation into clinical practice will require overcoming certain obstacles, such as the technical challenges associated with working with RNA, a molecule that is more easily degraded than DNA and therefore requires more stringent protocols. In any case, this study represents a solid contribution that reinforces the importance of quantifying biological ageing and consolidates the role of ageing clocks as benchmark tools in this field.

This study provides an unprecedented integration of gene expression data in the context of ageing, encompassing mice, rats, macaques and humans across more than 11,000 samples and 25 tissues. It reports gene expression modules related to molecular ageing that are shared across these mammals and are linked to a multitude of biological processes associated with ageing, morbidity and mortality. Furthermore, the study provides experimental evidence beyond mere associations to validate its findings.

This study demonstrates, once again, that ageing is a highly complex process and occurs at different rates in each organ and tissue. Furthermore, each layer of molecular information provides us with a different perspective. We have molecular ageing clocks based on DNA methylation (epigenetics), on blood plasma proteins (proteomics) and now also on gene expression (transcriptomics). The challenge now is to understand what each molecular layer tells us and to use this information to design therapeutic strategies that improve the natural ageing process.