The science of longevity has been searching for years for clocks capable of measuring the biological age of organisms: not the one marked by the birth date, but the molecular traces left by cellular deterioration over time, with the aspiration to understand these processes to stop or reverse them. A powerful study published this Wednesday in Nature has taken a significant step in this path by analyzing more than 11,000 genetic activity profiles of tissues from four mammal species, including humans, and concluding that they share molecular signatures of aging and mortality.
Besides building a new biological clock, the authors have linked it to something more ambitious: they have developed models capable of reading in gene activity a signal associated with chronological age, expected mortality, and the effects of interventions that in animals shorten or extend life. In other words: the more biologically aged a tissue is — which does not always correspond to chronological age — the closer it is to death. And this new clock is capable of predicting this mortality quite accurately: not in a specific person, but in terms of risks and trends from a statistical point of view.
The work proposes a tool to measure how different tissues age and which cellular processes — inflammation, mitochondrial function, extracellular matrix organization — weigh more in that deterioration.
There is no “aging gene.” There is a constellation of signals that have been identified as markers of deterioration through 11,000 transcriptomes: the reading of all the instructions being executed in a cell at a given moment. They mention several genes in which the authors identify activity associated with aging, mortality, and chronic diseases in different tissues and species. In humans, their proteins are related to higher mortality and multimorbidity.
What is this discovery for? In the very short term, nothing will change, but it opens the door to measuring these aging markers in clinical routine and acting on them through lifestyle habits, gene therapies (something more complicated), or drugs that can slow deterioration.
Some of these interventions have already been tested in rodents. Drugs like rapamycin or strategies like caloric restriction, which in animal models have been associated with greater longevity, also leave a detectable trace in the clocks developed by the authors. Neither approach has shown effectiveness, so far, in humans.
Mario Fernández Fraga, who works on similar lines of research at CSIC, points out that, although there were many studies and works related to biological aging clocks, it had never been done systematically with so many samples and in several different species: mouse, rat, macaque, and human.
The most relevant contribution, in this scientist’s opinion, is conceptual: “What has the most impact is that it identifies molecular aging modules. If you talk about aging very generally, it is probably not correct. There is an immunological one, another metabolic, and these processes do not occur the same in all tissues. And these processes are influenced by lifestyles, such as diet or caloric restriction.”
This modular architecture helps interpret why not all interventions act the same. Caloric restriction, for example, is reflected mainly in metabolic modules. Other factors may weigh more on inflammatory ones.
“Almost none of the interventions is universal to slow down all modules,” points out Manuel Collado, researcher at CNB-CSIC at the Singular Research Center in Molecular Medicine and Chronic Diseases (CIMUS) of the University of Santiago de Compostela. In his view, that is one of the most useful ideas of the work: aging does not progress as a compact block, but as a set of processes that can deteriorate, slow down, or accelerate partially. “It is like a kind of set of different modules that, more or less simultaneously, progress towards deterioration,” he explains.
Collado highlights another advance pointed out by the publication: “It was not so clear that it was possible to reverse, that is, to go from an advanced molecular aging state to an earlier one,” he notes. The work finds signals of that reversal in very specific models, such as early embryogenesis — the process by which a new organism starts with the biological marker practically at zero — and cellular reprogramming.
This is just an open door to interventions, which today remain very far from the clinic. It does not seem possible to interfere directly in the genes that change in aging processes. As Ana O’Loghlen, from CIB Margarita Salas-CSIC, recalls, touching one of them would “directly cause cancer,” so “it makes no sense” to think about genetic interventions based on the publication.
Its usefulness, in the opinion of Salvador Macip, professor of Molecular Medicine at the Universitat Oberta de Catalunya and the University of Leicester, is that in the medium term it contributes “substantially” to designing a panel of markers that can be measured to predict aging, whether it is accelerating, or if interventions slow it down. “It is a step to have a blood test that tells us how old we are, if deterioration is greater in the liver, muscles, brain, and apply what is known and new drugs that may arrive,” he summarizes.
The study is not an isolated revolution, but another layer to understand the processes that give rise to cellular aging. The most widespread techniques until now were epigenetic clocks, a biomarker that allows estimating biological age by analyzing DNA methylation levels (a chemical mark that can change gene activity without altering the genetic sequence).
A survey among attendees at an aging biology congress showed just two months ago that there is no consensus among experts when defining what it is, whether it is a disease, when it begins, or if it is possible to slow it down alone or reverse it. For Collado, “this study makes it clear that there is a universal biological basis that can be described, delimited, and measured.”
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