Mitochondrial Circular RNAs: New Players in Human Aging

During mammalian aging, there are changes in abundance of noncoding RNAs including microRNAs, long noncoding RNAs, and circular RNAs.”

The aging of an organism is reflected not only in the function of its organs but also in the molecular signatures written into its cells. For years, scientists have cataloged the changes in protein-coding genes and various non-coding RNAs that occur as we grow older. However, one class of molecules—circular RNAs originating from the genome of our cellular power plants, the mitochondria—has remained largely unexplored.

A new research paper, titled “Aging-associated mitochondrial circular RNAs” published in Volume 18 of Aging-US by a multi-institutional team of researchers, provides the first detailed profile of these molecules and reveals a surprising link to cellular energy metabolism. 

The team’s investigation demonstrates that a specific mitochondrial circular RNA, circMT-RNR2, is depleted in older individuals and plays a direct role in regulating the TCA cycle, the engine of cellular energy production.

The Discovery: A Mitochondrial Circular RNA Lost with Age

The researchers began by analyzing circular RNA junctions in peripheral blood mononuclear cells (PBMCs) from 11 young adults (average age 30) and 11 older adults (average age 64). Using RNA sequencing data, they identified hundreds of circular RNA species.

The most striking finding was the source of these molecules. In young individuals, the vast majority of circular RNA junctions originated from the mitochondrial chromosome (chrM). Specifically, the most abundant circular RNAs were derived from a mitochondrial ribosomal RNA gene called MT-RNR2. In older individuals, however, these same circular RNA junctions were sharply depleted—a loss of nearly 90%.

This age-associated decline was not just a statistical observation. When the team examined human fibroblasts (skin cells) as they aged in culture, they saw the same pattern: levels of circMT-RNR2 dropped progressively as the cells approached senescence, the point at which they permanently stop dividing.

The Regulator: An RNA-Binding Protein Called GRSF1

If circMT-RNR2 disappears with age, what controls its production? The team turned their attention to GRSF1, a protein known to localize to mitochondrial RNA granules—specialized compartments where mitochondrial RNAs are processed.

Using a split-GFP system, they confirmed that GRSF1 resides within mitochondria. They then performed a PAR-CLIP analysis, a technique that identifies precisely which RNAs a protein binds to. The results showed that GRSF1 binds directly to several mitochondrial transcripts, including both the linear and circular forms of MT-RNR2. A specific RNA motif—UGxxGGUU—was identified as the recognition sequence for GRSF1 on its target RNAs.

When the researchers depleted GRSF1 from human fibroblasts, circMT-RNR2 levels plummeted. This established GRSF1 as a critical factor for maintaining the abundance of this mitochondrial circular RNA.

The Function: Scaffolding the TCA Cycle

The discovery that a circular RNA is lost with age raised an obvious question: what does it actually do? Given that MT-RNR2 originates from the mitochondria, the team hypothesized it might be involved in mitochondrial metabolism.

They performed RNA immunoprecipitation assays to see if circMT-RNR2 interacts with metabolic enzymes. The results revealed that both linear and circular MT-RNR2 bind to two key enzymes of the TCA cycle: SUCLG1 (part of succinyl-CoA synthetase) and SDHA (a component of succinate dehydrogenase complex II).

This binding appears to have functional consequences. When the team depleted MT-RNR2 from cells, levels of the TCA cycle metabolites fumarate and alpha-ketoglutarate declined. Conversely, reintroducing circMT-RNR2 restored fumarate levels. The circular RNA seemed to be acting as a scaffold, helping to assemble or stabilize the enzyme complexes that drive the TCA cycle.

The Consequence: Suppressing Cellular Senescence

If circMT-RNR2 supports energy production, its loss should accelerate aging at the cellular level. To test this, the team measured markers of cellular senescence—p16 and p21—after manipulating GRSF1 and circMT-RNR2.

Depleting GRSF1, which reduced circMT-RNR2, caused a sharp increase in p16 and p21 mRNA levels. However, when they reintroduced circMT-RNR2 into these GRSF1-depleted cells, the senescence markers returned to normal. The circular RNA alone was sufficient to reverse the senescence phenotype.

Further analysis showed that GRSF1 depletion broadly suppressed mitochondrial transcripts, and reintroducing circMT-RNR2 partially rescued this defect. The model that emerges is one where GRSF1 promotes the production of circMT-RNR2, which then scaffolds TCA cycle enzymes to maintain efficient energy production and keep cells in a proliferating, non-senescent state.

Implications for Future Research

This study opens several new avenues for investigation. First, it establishes that mitochondria produce circular RNAs with distinct functions, expanding our understanding of mitochondrial biology. Second, it identifies GRSF1 as a key regulator of these molecules, linking RNA-binding proteins to mitochondrial metabolism.

The finding that a single circular RNA can influence the entire TCA cycle suggests that non-coding RNAs may play broader roles in metabolism than previously appreciated. The authors propose that circMT-RNR2 may act similarly to other scaffold non-coding RNAs, like NEAT1, which assemble metabolic enzymes to accelerate biochemical reactions.

The mechanism by which MT-RNR2 produces a circular RNA remains intriguing. Since the gene lacks introns, conventional back-splicing cannot explain its circularization. The authors speculate that trans-splicing—a process more common in plants and trypanosomes—may be at work, potentially mediated by GRSF1 within mitochondrial RNA granules.

Future Perspectives and Conclusion

This research does not claim to have fully mapped the landscape of mitochondrial circular RNAs or their functions. Rather, it offers a compelling proof-of-concept that these molecules exist, change with age, and have measurable biological effects.

By integrating transcriptomic profiling, biochemical analysis, and functional studies, the team demonstrates that circMT-RNR2 is depleted during human aging and senescence, that it is regulated by GRSF1, and that it supports the TCA cycle by scaffolding metabolic enzymes.

The perspective that emerges is one where the mitochondria are not just passive energy generators but active participants in the aging process through their non-coding RNA output. Continued research will be needed to determine whether other mitochondrial circular RNAs have similar functions, how precisely they are generated, and whether they might serve as therapeutic targets to preserve metabolic health in older age.

Click here to read the full research paper published in Aging-US.

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EDITORS’ CHOICE: Single-cell transcriptomics reveal intrinsic and systemic T cell aging in COVID-19 and HIV

Each month, we will highlight a paper published in Aging-US chosen as the “Editors’ Choice.” These selections are handpicked by our editors and accompanied by a brief summary, showcasing research with significant impact and novel insights in aging and age-related diseases.

Biomarkers of aging help researchers understand how diseases influence the body over time. However, most current biomarkers rely on measurements from mixed cell populations, making it difficult to distinguish between changes caused by shifts in cell types and aging processes occurring within individual cells.

In this study, titled “Single-cell transcriptomics reveal intrinsic and systemic T cell aging in COVID-19 and HIV” and published in Volume 18 of Aging-US, researchers used single-cell RNA sequencing to analyze aging-related changes in human T cells. They developed Tictock, a single-cell transcriptomic clock that predicts both cellular age and T cell type across six human T cell subsets.

Applying this tool, the researchers found that acute COVID-19 was associated with increased proportions of CD8⁺ cytotoxic T cells, while T cell composition remained relatively stable in individuals with HIV receiving antiretroviral therapy (HIV+ART). Despite these differences, both conditions showed signs of accelerated transcriptomic aging, particularly in naïve CD8⁺ T cells.

Further analysis identified shared aging-related genes and biological pathways linked to ribosomal components and TNF receptor binding. These findings demonstrate how single-cell transcriptomic biomarkers can help separate systemic immune changes from cell-intrinsic aging processes, providing new tools to measure immune aging in disease.

Click here to read the full research paper published in Aging-US.

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Tictock: A Single-Cell Clock Measures Immune Aging in Viral Infections

Biomarkers of aging offer insights into how diseases and interventions affect biological systems. However, most current biomarkers are based on bulk cell measurements, making it difficult to distinguish between changes driven by shifts in cell type composition (systemic effects) versus intrinsic changes within individual cells.”

Aging reshapes the immune system in two fundamental ways: it alters the proportions of different immune cell types circulating in the blood, and it induces molecular changes within each individual cell. For years, researchers have struggled to disentangle these two intertwined processes using standard “bulk” measurements, which average signals across millions of cells and obscure what is happening at the single-cell level.

A new research paper, titled “Single-cell transcriptomics reveal intrinsic and systemic T cell aging in COVID-19 and HIV” published in Volume 18 of Aging-US by researchers at the Buck Institute for Research on Aging in California, the University of Southern California, and the University of Copenhagen, introduces an innovative solution. 

The team of Alan Tomusiak, Sierra Lore, Morten Scheibye-Knudsen, and corresponding author Eric Verdin, developed a novel tool called Tictock (T immune cell transcriptomic clock) that uses single-cell RNA sequencing to separately measure systemic and cell-intrinsic components of immune aging, and then applied it to understand how COVID-19 and HIV affect T cells.

The Tictock Model

The challenge the researchers addressed is akin to a chicken-and-egg problem. When we see a change in the average gene expression of a T cell population with age, is it because the cells themselves are aging, or because the composition of the population has shifted to contain more aged cell types?

To solve this, the researchers built Tictock, a two-part model using a massive dataset of two million peripheral blood mononuclear cells from 166 individuals. The first component is an automated cell type predictor that classifies T cells into six canonical subsets with 97% accuracy. It identifies naïve CD8+ T cells, central memory CD8+ cells, effector memory CD8+ cells, naïve CD4+ cells, central memory CD4+ cells, and regulatory T cells based on the expression of key marker genes like CD4CD8ACCR7, and FOXP3.

The second component consists of six distinct age-prediction models—one trained specifically for each T cell subset. By applying the cell type predictor first, the researchers can isolate a pure population of, say, naïve CD8+ T cells, and then apply the age model for that specific cell type to calculate its “transcriptomic age.” This dual-layer design allows Tictock to separate the signal of aging cell populations from the signal of aging within a cell.

Evidence from Laboratory and Human Studies

The researchers first validated their model by confirming known trends in immune aging. They observed a significant increase in the CD4/CD8 ratio with age, a well-established phenomenon. More specifically, they found a sharp decline in the proportion of naïve CD8+ cytotoxic T cells as people grow older, which aligns with decades of immunological research.

Having validated the tool, the authors then applied Tictock to two disease contexts: acute COVID-19 and HIV infection managed with antiretroviral therapy (HIV+ART). The results revealed distinct patterns. In acute COVID-19, the model detected a significant change in cell type composition—a systemic shift toward increased proportions of CD8+ cytotoxic T cells, likely reflecting the body’s acute immune response to the virus.

However, both diseases shared a striking commonality at the cell-intrinsic level. In people with acute COVID-19 and in those with HIV+ART, Tictock detected a significant increase in the transcriptomic age of naïve CD8+ T cells. In other words, these naïve cells appeared biologically older than expected for the individual’s chronological age. This accelerated aging signature was specific; it was not observed in other T cell subsets like CD4+ helper cells.

Insights into Mechanisms

To understand what was driving these age predictions, the team analyzed the 209 genes that were consistently included across the six different cell-type age models. Gene Ontology enrichment analysis revealed that these shared genes were heavily involved in fundamental cellular processes, including components of the cytosolic small and large ribosomal subunits and pathways related to TNF receptor binding.

This points to a central role for protein synthesis machinery and inflammatory signaling in T cell aging. The authors also discovered a correlation between aging and mean transcript length within cells, suggesting that changes in RNA processing or stability may be a general feature of the aging process at the single-cell level. Across these examples, the recurring theme is the power of single-cell resolution to reveal distinct layers of aging—systemic shifts in cell populations versus intrinsic molecular aging within specific cell types.

Implications for Future Research

The development of Tictock opens several avenues for future investigation. One immediate application is as a tool to measure how different interventions, such as drugs or lifestyle changes, affect immune aging. Because the model can distinguish between effects on cell composition and effects on cell-intrinsic age, it could provide a more nuanced readout of whether a therapy is truly rejuvenating immune cells or simply altering their proportions.

The finding that both a chronic viral infection (HIV) and an acute viral infection (COVID-19) accelerate aging in naïve CD8+ T cells raises important questions about the long-term consequences of severe infections. It suggests that the immune system may carry a “memory” of these encounters in the form of prematurely aged T cells, which could impact future immune responses.

Future Perspectives and Conclusion

Tictock does not claim to be a universal clock for all tissues or all immune cells. Rather, it offers a proof-of-concept for a powerful approach: using single-cell transcriptomics to build interpretable biomarkers that can disentangle the multiple layers of a complex process like aging. By integrating automated cell typing with cell-type-specific age predictors, the model clarifies how systemic and intrinsic factors combine to shape the aging immune system.

This perspective suggests that immune aging is not a single process but a composite of changes at different levels of biological organization. Continued research will be needed to determine how broadly this model applies to other cell types and other diseases, and how it might guide future efforts to monitor and modulate immune health in older adults and in people living with chronic viral infections.

Click here to read the full research paper published in Aging-US.

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Acknowledgment of 2025 Reviewers

Aging-US sincerely thanks all reviewers who contributed their expertise and time during 2025.

Rigorous and constructive peer review is essential to scientific progress. Through their careful evaluations, our reviewers played a central role in maintaining the scientific quality, integrity, and credibility of the journal.

Their efforts also directly support one of the core missions of Aging-US, which is to increase the visibility and impact of high-quality research in the biology of aging and age-related disease.

We are deeply grateful for this commitment to excellence and to the aging research community, and we look forward to continued collaboration in the coming year.

Marco Demaria
Editor-in-Chief, Aging-US

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How Aging Leads to Chronic Disease: A Two-Stage Model

Aging (senescence) is characterized by development of diverse senescent pathologies and diseases, leading eventually to death.”

Aging has long been explained in different ways. One traditional view is that it results from the gradual accumulation of molecular damage over time. Another perspective, based on evolutionary theory, suggests that natural selection strongly protects health during youth and reproductive years but becomes less effective later in life. As a result, biological effects that appear in older age may persist because they have little impact on reproduction. 

Over the past two decades, researchers have also explored the idea that biological programs beneficial early in life may continue operating later in ways that become harmful. Processes that once supported growth, repair, and reproduction may, with time, contribute to chronic disease.

A recent review article, titled “Aging as a multifactorial disorder with two stages,” published in Aging-US by researchers at University College London and Queen Mary University of London, brings these different perspectives together into a unified model, to propose a broader explanation of how aging-related diseases develop. The review appears in a special issue honoring the late scientist Misha Blagosklonny, whose theoretical work on programmatic aging significantly influenced the field. 

The Two-Stage Model

The review by David Gems, Alexander Carver from University College London, and Yuan Zhao from Queen Mary University of London, brings together evidence from evolutionary biology, laboratory research, and human disease. It argues that most diseases associated with aging are multifactorial, meaning they arise from multiple interacting causes rather than a single trigger. The authors describe aging as a process that often develops in two main stages.

The first occurs earlier in life and involves disruptions in normal biological functions. It can include infections, physical injuries, environmental exposures, or DNA mutations. In many cases, the body repairs the damage or contains it effectively. However, not all disruptions are fully eliminated. Some remain in tissues in a controlled or dormant state without causing immediate symptoms.

The second stage takes place later in life, when normal age-related biological changes alter the body’s internal environment. Immune function tends to decline, inflammatory activity may increase, and tissue repair processes shift. Cells may enter a state known as senescence, in which they stop dividing but release signaling molecules that influence surrounding tissues. According to the review, these later-life changes can weaken the body’s ability to contain earlier disruptions. As a result, previously silent injuries or latent conditions may begin to develop into clinically recognizable disease.

In this model, aging is not explained only by accumulated damage or exclusively by genetic programming. Instead, disease emerges from the interaction between earlier disruptions and later biological changes.

Evidence from Laboratory and Human Studies

Part of the conceptual foundation for this model comes from studies in the roundworm Caenorhabditis elegans. In this organism, early mechanical damage to tissue can later contribute to fatal infections in old age, illustrating how early disruption and later biological change may interact. The authors suggest that similar patterns may occur in humans.

Several human conditions also fit this model. In shingles, the virus responsible for chickenpox remains dormant in nerve cells after childhood infection and may reactivate decades later as immune control weakens. Tuberculosis provides another example, as latent infections can become active in older age when immune defenses decline.

Osteoarthritis is more common in individuals who experienced joint injury earlier in life. Although the joint may initially recover, age-related changes in cartilage and surrounding tissues may allow earlier structural damage to progress. Traumatic brain injury in youth has also been associated with increased risk of dementia later in life, suggesting that early injury may interact with aging processes.

Cancer risk rises sharply with age as well. While genetic mutations accumulate over time, changes in the aging tissue environment, including altered inflammatory signaling and the presence of senescent cells, may increase the likelihood that mutated cells progress into tumors.

Across these examples, the recurring theme is the interaction between earlier contained disruption and later biological vulnerability.

Implications for Prevention and Intervention

The authors outline two broad approaches to reduce age-related disease. One approach focuses on preventing or minimizing early disruptions, for example through vaccination, injury prevention, and reduction of harmful environmental exposures. The other aims to modify later-life biological processes that contribute to loss of containment, including pathways involved in inflammation or excessive cellular activity.

At present, the most reliable and widely implemented measures in humans focus on preventing early disruptions. Interventions that directly target fundamental aging processes remain under investigation and require further research to establish their safety and effectiveness.

Future Perspectives and Conclusion

The two-stage model does not claim to provide a complete explanation of aging. Rather, it offers a structured model for understanding how multiple causes may combine over time to produce late-life disease. By integrating evolutionary theory, laboratory findings, and clinical observations, the review clarifies how early-life events and later biological changes may interact.

This perspective suggests that aging is neither purely passive decline nor solely genetically programmed deterioration. Instead, it may reflect a lifelong interaction between accumulated disruptions and evolving biological conditions. Continued research will be needed to determine how broadly this model applies and how it might guide future efforts to reduce the burden of chronic disease in older adults.

Click here to read the full review published in Aging-US.

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Aging-US is indexed by PubMed/Medline (abbreviated as “Aging (Albany NY)”), PubMed CentralWeb of Science: Science Citation Index Expanded (abbreviated as “Aging‐US” and listed in the Cell Biology and Geriatrics & Gerontology categories), Scopus (abbreviated as “Aging” and listed in the Cell Biology and Aging categories), Biological Abstracts, BIOSIS Previews, EMBASE, META (Chan Zuckerberg Initiative) (2018-2022), and Dimensions (Digital Science).

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Epigenetic Changes in Sperm May Explain Association Between Paternal Age and Autism Risk

“Research findings suggest that advanced paternal age is associated with an increased risk of autism spectrum disorder (ASD) in children.”

While maternal health has traditionally been central to research on pregnancy and child development, there is growing recognition that paternal factors also play a role, particularly the father’s age. Several studies have found a modest increase in risk of neurodevelopmental conditions, including autism spectrum disorder, among children born to older fathers. However, the biological mechanisms underlying this association are still not fully understood.

One emerging explanation involves epigenetics, chemical modifications that influence how genes are expressed without altering the underlying DNA sequence. Among these is DNA methylation. Earlier studies have suggested that sperm from older men may carry age-related changes in DNA methylation, but few have explored these patterns on a genome-wide scale or focused specifically on regions that are most likely to influence offspring development.

The Study: Exploring Age-Dependent Methylation at Imprint Control Regions in Human Sperm

In a study, titled Age-specific DNA methylation alterations in sperm at imprint control regions may contribute to the risk of autism spectrum disorder in offspring,” published in Aging-US and selected as the Editors’ Choice for January, 2026, researchers investigated how DNA methylation patterns in sperm change with age. The study was led by first authors Eugenia Casella and Jana Depovere, with corresponding author Adelheid Soubry from the University of Leuven.

The research focused specifically on imprint control regions (ICRs), genetic segments that regulate gene activity based on whether the genes are inherited from the mother or the father. These regions play a crucial role during early development and have been associated with developmental disorders when improperly regulated.

To conduct the analysis, the team examined sperm samples from 63 healthy, non-smoking men aged 18 to 35 years.

The Results:  Age-Dependent Epigenetic Changes in Sperm Detected Near Autism-Associated Genes

The researchers identified over 14,000 DNA sites (known as CpG sites) where methylation levels were significantly correlated with age. Most of these sites had reduced methylation in older individuals. Of particular interest were 747 sites near known imprint control regions, areas essential for regulating gene expression during early development. When cross-referenced with public databases of autism-associated genes, several of these age-sensitive sites overlapped with genes previously linked to autism spectrum disorder, including MAGEL2DLGAP2GNASKCNQ1, and PLAGL1.

The Breakthrough: Focus on Imprint Control Regions Reveals Epigenetic Role of Paternal Age

By concentrating on regions of the genome that remain active during the earliest stages of embryonic development, this study provides new evidence supporting the idea that paternal age may influence a child’s developmental outcomes through epigenetic changes in sperm, not just through genetic mutations. This is a step forward in understanding how non-genetic information carried by sperm can affect offspring.

The Impact: Findings Expand Understanding of Paternal Contributions to Offspring Health

These findings should not be interpreted as a reason for older men to avoid fatherhood. Rather, the study refines the understanding of the biological mechanisms that may contribute to autism risk and underscores the importance of considering paternal factors in reproductive health discussions. The research may support future studies aimed at developing early diagnostic tools, risk assessments, or potential interventions. However, such applications are still far from clinical use and require further validation.

Future Perspectives and Conclusion

This study adds to a growing body of evidence suggesting that age-related changes in sperm may play a role in the health of future generations. It is important to note that the observed DNA methylation changes were modest and, on their own, are unlikely to determine whether a child develops autism. Further research, particularly studies that follow these epigenetic patterns through conception, pregnancy, and child development, will be essential to assess their practical significance.

Overall, this work contributes to the broader understanding of reproductive planning and paternal health, offering a more complete picture of the factors that may influence child development.

Click here to read the full research paper published in Aging-US.

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Chocolate Compound Linked to Slower Biological Aging

“Theobromine, a commonly consumed dietary alkaloid derived from cocoa, has been linked to extended lifespan in model organisms and to health benefits in humans.”

When we think of aging, we often picture wrinkles or gray hair. But aging also occurs deep within our cells. One key area of research focuses on “epigenetic aging,” the gradual changes in how DNA is regulated over time. These changes are tracked using tools called epigenetic clocks, which estimate a person’s biological age based on specific molecular markers in the blood. Unlike chronological age, biological age reflects the body’s functional state and can be influenced by health, lifestyle, and environmental factors.

While chocolate and coffee have been associated with better health outcomes, pinpointing the responsible specific compounds has been difficult. These foods contain multiple bioactive substances that are often consumed together, and few studies have explored their individual effects on the human epigenome, the system of chemical modifications that control gene activity and change with age.

A recent study provides new insight, suggesting that theobromine, a compound naturally found in cocoa, may be associated with slower biological aging in humans.

The Study: Investigating Theobromine and Epigenetic Aging in TwinsUK and KORA Cohorts

The research titled “Theobromine is associated with slower epigenetic ageing,” was led by Ramy Saad from King’s College London and Great Ormond Street Hospital for Children NHS Foundation Trust, alongside Jordana T. Bell from King’s College London. The study was recently published in Aging-US

The team analyzed blood sample data from over 1,600 healthy individuals in two large population-based studies: TwinsUK in the United Kingdom and KORA in Germany. They investigated six compounds commonly found in coffee and cocoa, including caffeine, theophylline, and theobromine, to assess their potential relationship with two well-established epigenetic aging measures: GrimAge, which estimates the risk of early death, and DNAmTL, which reflects telomere length, a marker of cellular aging.

Results: Higher Theobromine Levels Are Associated With Slower Biological Aging

The study found that individuals with higher blood levels of theobromine had slower biological aging, as measured by both GrimAge and DNAmTL. This suggests that their cellular and molecular profiles appeared younger than their chronological age. The initial findings from the female twin cohort in the UK were confirmed in Germany’s KORA cohort that includes a larger and more diverse population.

Importantly, the researchers accounted for other compounds commonly found in cocoa and coffee, such as caffeine, and still observed the same effect. The association remained significant even after adjusting for variables such as diet quality and smoking history. Interestingly, the effect was particularly notable in individuals who had previously smoked. The researchers also ruled out potential biases related to differences in the timing of sample collection.

Breakthrough: Theobromine Shows a Unique Link to Slower Epigenetic Aging

Theobromine appeared to act independently of other similar molecules and showed a specific association with slower epigenetic aging. While structurally similar to caffeine, theobromine behaves differently in the body and is found in higher concentrations in cocoa-rich foods like dark chocolate. Previous research has associated it with improvements in blood pressure and cognitive function, but this study is among the first to connect it with molecular markers of aging.

Impact: Theobromine Identified as a Potential Dietary Target for Healthy Aging

If validated by future studies, theobromine could emerge as a promising target for dietary or therapeutic strategies aimed at supporting healthy aging. The findings strengthen the growing understanding that specific dietary components can influence the aging process, not only through visible, external signs, but also at the molecular and cellular levels. While theobromine is abundant in cocoa products, the study does not advocate increased chocolate consumption. Instead, it highlights the potential role of naturally occurring plant-based compounds in modulating biological aging and contributing to long-term health.

Future Perspectives and Conclusion

As with all observational studies, this research establishes association rather than causation. More studies, particularly randomized clinical trials, will be needed to determine whether increasing theobromine intake can directly slow biological aging.

Nevertheless, the results suggest that theobromine may be one reason cocoa-rich diets have been linked with cardiovascular and cognitive benefits. As scientific interest grows in how nutrition influences epigenetic aging, compounds like theobromine may play an increasingly important role in understanding and potentially extending human healthspan.

Click here to read the full research paper published in Aging-US.

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Aging-US is indexed by PubMed/Medline (abbreviated as “Aging (Albany NY)”), PubMed CentralWeb of Science: Science Citation Index Expanded (abbreviated as “Aging‐US” and listed in the Cell Biology and Geriatrics & Gerontology categories), Scopus (abbreviated as “Aging” and listed in the Cell Biology and Aging categories), Biological Abstracts, BIOSIS Previews, EMBASE, META (Chan Zuckerberg Initiative) (2018-2022), and Dimensions (Digital Science).

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How Aging Leads to Disease: New Two-Stage Model Explains Age-Related Illness

“Here we propose a general account of how different determinants of aging can interact to generate late-life disease.”

BUFFALO, NY — January 20, 2026 — A new review was published in Volume 17, Issue 12 of Aging-US on December 30, 2025, titled “Aging as a multifactorial disorder with two stages.”

“This article is a contribution to the special issue of Aging celebrating the life and work of Misha Blagosklonny (more formally, Mikhail Vladimirovich Blagosklonny), who died in October 2024.”

In this review, David Gems and Alexander Carver from University College London, together with Yuan Zhao from Queen Mary University of London, present a new theoretical model to explain how aging leads to the development of chronic diseases. Drawing on evolutionary theory and biological research, the authors propose that aging is driven by a combination of early-life damage and harmful genetic activity in later life. This framework helps explain why diseases such as cancer, arthritis, and infections often appear in old age and offers insight into how they might be prevented.

Aging is the biggest risk factor for most chronic diseases, but the biological reasons for this association are still debated. The authors address this by introducing a two-stage model. In the first stage, individuals experience disruptions early in life, such as infections, injuries, or genetic mutations. Although the body can often contain or repair this damage, it does not fully eliminate it. In the second stage, which begins in later life, normal genetic processes begin to act in ways that are no longer beneficial. These late-life changes weaken the body’s ability to contain earlier damage, allowing it to develop into disease.

The review emphasizes that aging is a multifactorial process, shaped by many interacting causes rather than a single underlying mechanism. The model suggests that early-life disruptions and later-life genetic activity work together to drive age-related diseases. For example, dormant viruses can re-emerge as infections like shingles due to weakened immunity in older adults. Similarly, injuries to joints in youth can lead to osteoarthritis as tissues change with age. Inherited mutations may also remain silent for decades before contributing to conditions such as cancer or fibrosis later in life.

This two-stage model builds on long-standing ideas from evolutionary biology, particularly the theory that aging occurs because natural selection has less influence in later life. The authors also draw on studies in the roundworm Caenorhabditis elegans, where early mechanical damage can lead to fatal infections in old age, suggesting similar patterns may occur in humans.

Overall, this review presents a new framework for understanding how different causes of aging interact over time. By identifying two key stages, early-life damage and late-life genetic activity, it highlights potential strategies for promoting healthier aging through prevention and targeted intervention.

Paper DOIhttps://doi.org/10.18632/aging.206339

Corresponding author: David Gems – [email protected]

Keywords: aging, C. elegans, disease, hyperfunction, multifactorial model

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EDITORS’ CHOICE: Age-specific DNA methylation alterations in sperm at imprint control regions may contribute to the risk of autism spectrum disorder in offspring

Each month, we will highlight a paper published in Aging-US chosen as the “Editors’ Choice.” These selections are handpicked by our editors and accompanied by a brief summary, showcasing research with significant impact and novel insights in aging and age-related diseases.


The results of studies revealed in the paper published in Volume 17, Issue 12, titled “Age-specific DNA methylation alterations in sperm at imprint control regions may contribute to the risk of autism spectrum disorder in offspring,” indicate that advanced paternal age increases the risk of autism spectrum disorder (ASD) in children, potentially due to sperm epigenetic changes.

To explore this, the authors performed an epigenome-wide association study on sperm from 63 men using the Illumina 450K array, identifying 14,622 age-related differentially methylated CpGs (DMCs), with many linked to imprinted genes and imprint control regions (ICRs). These alterations may disrupt gene expression and contribute to neurodevelopmental disorders like ASD. Several imprinted genes identified—including OTX1, PRDM16, and others—are associated with ASD, warranting further research into their role in paternal age effects on autism.

Further genetic research may clarify how paternal age affects autism. Changes in DNA methylation within ICRs before conception could add to ASD’s complexity. Though measured effects were small, even minor sperm epigenetic changes could influence populations as fatherhood is delayed. Preventive and educational programs could benefit public health.

Click here to read the full research paper published in Aging-US.

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A Common Aging Pattern: Changes in RNA Splicing and Processing Across Human Tissues

“Although transcriptomic changes are known to occur with age, the extent to which these are conserved across tissues is unclear.”

As we age, every tissue in the body undergoes gradual molecular changes. A long-standing question in aging research is whether these changes follow common patterns across tissues or whether each tissue ages on its own. While DNA-based “epigenetic clocks” can estimate age accurately across different tissues, identifying consistent patterns in gene expression has been much more challenging.

One reason for this difficulty is methodology. Most studies focus on whether genes increase or decrease their expression levels with age. However, genes do not function in isolation. They operate within complex networks, coordinating their activity with many others. Changes in these relationships may be important aspects of the aging process. 

To understand this, researchers from the University of São Paulo performed a study titled “A combination of differential expression and network connectivity analyses identifies a common set of RNA splicing and processing genes altered with age across human tissues.”

The Study: Gene Expression and Network Analysis Integration to Study Aging Across Human Tissues

Featured on the cover of Aging-US (Volume 17, issue 12), the study analyzed gene expression data from nearly 1,000 donors from the Genotype-Tissue Expression (GTEx) project. They focused on 8 tissues (blood, brain, adipose tissue, muscle, blood vessel, heart, skin, and esophagus) from individuals aged 20 to 70. 

Rather than relying only on traditional differential expression analysis, the team combined this approach with gene network analysis. This allowed them to check not only how strongly genes were expressed, but also how their patterns of coordination with other genes changed across aging. By integrating these two perspectives, the researchers aimed to capture age-related transcriptomic changes that might otherwise go undetected.

Results: Aging Alters Gene Networks and RNA Processing Across Human Tissues

The results revealed a clear and consistent pattern. Many genes showed little or no change in their average expression levels with age, yet their connectivity within gene networks changed substantially. In other words, aging often altered how genes interacted with one another rather than simply how active they were.

When gene expression and network connectivity were analyzed together, a core group of genes emerged as altered with age across nearly all studied tissues. These shared genes were not randomly distributed across biological functions. Instead, they were strongly enriched in processes related to RNA splicing and RNA processing, the steps that convert raw RNA transcripts into mature messages used to produce proteins.

These genes were also highly interconnected in protein–protein interaction networks, indicating that they function together as part of coordinated molecular systems. Many are components of known cellular complexes involved in RNA handling, suggesting that aging affects not just individual genes but entire functional groups.

Breakthrough: Network Analysis Reveals Hidden Conserved Aging Signatures Across Tissues

This study demonstrates that network-based analyses can uncover conserved aging-related changes that are largely invisible when analyzing gene expression alone. This approach helps explain why previous studies often failed to identify shared aging signatures across tissues.

Impact: Network Reorganization in RNA Processing Associated to Key Aging Mechanisms

Errors in RNA splicing can lead to the production of abnormal or malfunctioning proteins, which tend to accumulate as cells age. The study shows that tissues appear to respond to this by reorganizing networks involved in RNA processing, protein quality control, and degradation pathways such as autophagy. These coordinated changes align with well-known features of aging, including declining protein homeostasis.

Importantly, this network-based perspective helps reconcile conflicting findings in earlier research. Different tissues may show distinct gene-level changes, yet still be responding to the same underlying molecular stresses through different regulatory strategies.

Future Perspectives and Conclusion

This research highlights RNA splicing and processing as central and conserved features of transcriptomic aging across human tissues. It also underscores the importance of studying gene networks, rather than focusing exclusively on individual genes, when investigating complex biological processes such as aging.

While further work is needed to determine whether these changes actively drive aging or reflect adaptive responses to accumulating cellular damage, the findings offer a more integrated perspective on how aging develops at the molecular level. Ultimately, this knowledge may help guide strategies aimed at supporting healthier aging across multiple tissues rather than targeting isolated organs or pathways.

Click here to read the full research paper published in Aging-US.

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Aging-US is indexed by PubMed/Medline (abbreviated as “Aging (Albany NY)”), PubMed CentralWeb of Science: Science Citation Index Expanded (abbreviated as “Aging‐US” and listed in the Cell Biology and Geriatrics & Gerontology categories), Scopus (abbreviated as “Aging” and listed in the Cell Biology and Aging categories), Biological Abstracts, BIOSIS Previews, EMBASE, META (Chan Zuckerberg Initiative) (2018-2022), and Dimensions (Digital Science).

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