Reversing age by reprogramming gene expression networks

image: To read out the effects in their over-expression screen, the team had developed a “transcriptomic aging model” that can quantify age and the degree of rejuvenation based on changes in the expression of genes involved in different processes. Trained with gene expression data obtained from 464 fibroblast samples from donors across a wide range of ages, the machine learning-driven model provides an accurate overview of cells’ age and health. view more Credit: Wyss Institute at Harvard University (BOSTON) — Every organ and tissue progressively loses function and integrity as it ages.

In fact, researchers have identified “hallmarks of aging” that not only present specific processes impacted by age, but are also thought of as levers that, if successfully targeted, could help turn back the aging clock and result in tissue rejuvenation. In 2006, Shinya Yamanaka’s Nobel prize-winning discovery that the over-expression of four genes, the “Yamanaka factors,” can reprogram most mature cell types back to an undifferentiated, pluripotent ground state was a milestone in aging research.

Interestingly, when expressed only in short bursts, the Yamanaka factors can also partially reprogram old cells back to a more youthful state, reversing multiple hallmarks of aging while maintaining their specialized functions. This and other insights showed that aging does not need to be a one-way street and that aging cells retain a latent capacity for rejuvenation.

Unfortunately, the therapeutic use of Yamanaka factors is causing concern for some researchers because their overexpression also raises the risk of cancer formation. Researchers have therefore been hunting other factors for rejuvenating aging tissues in safer and more controllable ways.

However, “in reprogramming, there is a fundamental tradeoff between rejuvenation and cell identity; achieving one without losing the other requires walking a fine line,” said Alex Plesa , Ph.D., the first co-author on a study presenting a new potential avenue to solving this challenge.

In the study, which was led by George Church , Ph.D., Core Faculty member Wyss Institute at Harvard University and spearheaded by Wyss Institute Scientist Plesa, in collaboration with the computational biology group of Antonio del Sol , Ph.D. at CIC bioGUNE-BRTA , the Basque Research and Technology Alliance in Spain, the team first developed a novel age predictor.

Specifically, they designed a machine learning algorithm trained on gene expression (transcriptomic) profiles across multiple aging processes in human skin fibroblast cells spanning a wide age range. This predictor accurately pinpointed the “transcriptomic age” of skin cells obtained from several donors.

Leveraging this age predictor as a scorable readout then enabled the team to screen a focused collection of genes that were predicted to affect aging processes in one way or another. The goal was to identify candidates that, when over-expressed, could shift the originally assigned aging score of old fibroblast cell lines to a more youthful score.

The top-scoring gene, encoding an RNA processing factor known as SRSF1, was indeed able to reduce features that corresponded to several hallmarks of aging, such as a biological process where damaged cells stop dividing but do not die (cellular senescence), disruptions in the normal balance and turnover of proteins (proteostatic stress), and chronic low-grade inflammation (also dubbed “inflammaging”).

Importantly, when delivered to aged mice, where it primarily accumulated in the liver, SRSF1 reduced the animals’ rate of aging and extended their lifespan by 14%, highlighting SRSF1 as a “geroprotective” target. The findings are published in Nature Aging . “It has been a long-standing goal of my lab to devise clinically useful de-aging strategies by identifying genes that, when engineered in the genome for under or over-expression in aging target tissues, extend human health-span.

Our platform and findings on SRSF1 are an important step on that quest,” said Church, who is also Professor of Genetics at Harvard Medical School. “Aging research is transiting an inflection point where the exponential progress of biotech is impacting the core aging processes which would otherwise kill 90% of us." Predicting cell age through gene expression “The most prominently used ‘aging clock,’ the epigenetic aging clock, assesses chemical modifications to the genome that occur with age as one of the hallmarks of aging.

But it doesn’t scale well to screening approaches because of high costs and challenges with interpreting its widespread changes,” said Plesa. “The idea of predicting the age of cells based on their gene expression made a lot of sense since every rejuvenation process inevitably has to manifest itself in altered gene expression programs that lead to the recovery of more youthful cell functionalities,” said Plesa.

Following this instinct, Church and Plesa collaborated with del Sol, an Ikerbasque Research Professor, and Sascha Jung , Ph.D., a postdoctoral fellow and co-first author of the study, to develop a machine learning-driven algorithm that predicts age based on changes in the expression of genes involved in different processes, comparable to odometers for different parts of a car.

Integrating the changes across all processes in a transcriptomic aging model provided an accurate overview of cells’ health and age. This novel predictor accurately reported shifts in transcriptomic age in three fibroblast cell lines derived from donors 55, 65, and 79 years of age after the team treated them with different experimental lifespan-changing interventions, including the Yamanaka factors and others.

Envisioning rejuvenating gene therapy Taking full advantage of their transcriptomic age predictor, the researchers then designed a focused library of genes that were predicted to impact aging and could be over-expressed in aged fibroblast cell lines. “We were working on the premise that over-expressing a single gene with validated rejuvenation outcomes could eventually be advanced into an organ or tissue-specific gene therapy if combined with the right delivery system,” said Plesa.

The team scored all library genes using their novel age predictor and analyzed their effects on specific aging features. Coming out on top of this extensive campaign was a gene encoding the RNA processing factor SRSF1, which shifted multiple aging processes toward more youthful states.

These rejuvenation effects registered on the epigenetic aging clock and extended to functional hallmarks, reducing cellular senescence, inflammatory signaling, and proteostatic stress, while restoring DNA repair programs. Importantly, the rejuvenated fibroblasts maintained their identity: they kept their specific spindle-shaped morphology, continued the expression of genes that encode typical fibroblast functions and didn’t induce the pluripotency programs that Yamanaka factors turn on.

From rejuventating cells to rejuvenating a whole organism Finally, the team wanted to see if the observed rejuvenation effects resulting from SRSF1 over-expression also carried over into a much more complex in vivo system. Very intriguingly, when they packaged the SRSF1 gene in a liver-tropic adeno-associated virus (AAV) and used it to treat mice, they observed liver rejuvenation and systemic benefits: SRSF1-treated animals grew frail more slowly and lived longer, with median lifespan extended by 14% compared to controls.

The most prominent role of SRSF1 is that of an “RNA splicing factor” that helps include protein-coding, so-called alternative exon sequences in a subset of mature messenger RNA molecules (mRNAs). These can then be translated by protein-synthesizing ribosomes into proteins, many of which have altered functions.

“We observed a strong trend of alternatively spliced mRNAs, but we are only just starting to understand how these changes bring about the multi-faceted rejuvenation program in tissues,” said Plesa. “It is also very likely that primarily targeting the liver can reverse aging processes in other organs and tissues and that rejuvenation programs can be communicated and thus amplified within the body.” The authors think that SRSF1 is a promising anti-aging target, since it works through machinery that all cells already use, instead of overriding their identity.

Solving delivery and dosing could turn this geroprotective gene into a rejuvenation therapy, and further research into SRSF1’s systemic effects in vivo could uncover new insights, additional targets and viable rejuvenation strategies. Other authors on the study are Helen H. Wang, Fawad Omar, Michael Shadpour, David Choy Buentello, Maria C.

Perez-Matos, Naftali Horwitz, George Cai, Zhen Kai Ngian, Carol Magalhaes, Amy J. Wagers, and William B. Mair.

The study was funded by the Wyss Institute at Harvard University, Aging and Longevity-Related Research Fund, Astera Fund at the Silicon Valley Community Foundation, and Spanish Ministry of Science and Innovation (award # PID2020-118605RB-I00). PRESS CONTACT Wyss Institute for Biologically Inspired Engineering at Harvard University Benjamin Boettner, benjamin.boettner@wyss.harvard.edu ### The Wyss Institute for Biologically Inspired Engineering at Harvard University ( www.wyss.harvard.edu ) is a research and development engine for disruptive innovation powered by biologically-inspired engineering with visionary people at its heart.

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Journal Nature Aging Method of Research Experimental study Subject of Research Cells Article Title Transcriptomic reprogramming screen identifies SRSF1 as a regulator of aging Article Publication Date 14-Oct-2026 Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.