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Cited by 121Genetics, Aging, and Longevity in Model OrganismsTelomeres, Telomerase, and SenescenceSingle-cell and spatial transcriptomics

Asynchronous, contagious and digital aging

Open access
Rando, Thomas A., Wyss-Coray, Tony·2021·Nature Aging
DOI 10.1038/s43587-020-00015-1PMC PMC8248898
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Abstract

Aging has largely been defined by analog measures of organ and organismal dysfunction. This has led to the characterization of aging processes at the molecular and cellular levels that underlie these gradual changes. However, current knowledge does not fully explain the growing body of data emerging from large epidemiological, systems biology, and single cell studies of entire organisms pointing to varied rates of aging between individuals (different functionality and lifespan), across lifespan (asynchronous aging), and within an organism at the tissue and organ levels (aging mosaicism). Here we consider these inhomogeneities in the broader context of the rate of aging and from the perspective of underlying cellular changes. These changes reflect genetic, environmental, and stochastic factors that cells integrate to adopt new homeostatic, albeit less functional, states, such as cellular senescence. In this sense, cellular aging can be viewed, at least in part, as a quantal process we refer to as "digital aging". Nevertheless, analog declines of tissue dysfunction and organ failure with age could be the sum of underlying digital events. Importantly, cellular aging, digital or otherwise, is not uniform across time or space within the organism or between organisms of the same species. Certain tissues may exhibit earliest signs of cellular aging, acting as drivers for organismal aging as signals from those driver cells within those tissues may accelerate the aging of other cells locally or even systemically. Advanced methodologies at the systems level and at the single cell level are likely to continue to refine our understanding to the processes of how cells and tissues age and how the integration of those processes leads to the complexities of individual, organismal aging.

AI snapshot

Written from the paper’s full text.

TL;DR

This Perspective argues that aging is asynchronous across individuals, across the lifespan, and among tissues, with discrete cellular state transitions (“digital aging”) and local/systemic spread (“contagious aging”) contributing to organismal decline. It calls for biomarkers and single-cell/systems approaches to measure rates of aging rather than relying on lifespan alone.

Key findings

  • Aging is non-uniform over time: cited studies report non-linear trajectories, including DNA methylation changing 24 times faster in the first few years of life than after puberty, inflection points around ages 70 and 85 in an 845-person Swedish cohort, two rapid epigenomic-change peaks around ages 40 and 60–70 in peripheral blood mononuclear cells, four “phases of aging” in skin from 121 humans aged 21–76, and brain-connectivity transitions around ages 40 and 70–75.
  • Aging is non-uniform across tissues and individuals: transcriptomic changes in 17 mouse organs across 10 ages show different trajectories; a human multi-omics study suggested different individuals manifest different “ageotypes”; single-cell studies show mosaicism, and in old versus young mice the proportion of cells expressing the senescence marker p16 more than doubled in multiple tissues.
  • Cellular aging can be viewed partly as “digital” or quantal: cell death and cellular senescence are discrete states, and analog tissue decline may be the sum of underlying digital events; senescent-cell secretome can induce senescence in neighboring cells.
  • Aging may be “contagious” locally and systemically: parabiosis and plasma-infusion studies show blood-borne factors can promote or reverse aging phenotypes, with aged plasma accelerating and young plasma reversing brain endothelial cell transcriptome aging; chronic diseases such as cancer, diabetes, and HIV/AIDS are linked to later co-morbidities, consistent with “aging begets aging.”

Methods

  • Design: Perspective/review article; no new experiments, primary data, or formal meta-analysis reported.
  • Evidence base: synthesizes cited epidemiological, omics, single-cell, parabiosis, and plasma-infusion studies across model organisms and humans.
  • Analysis: conceptual synthesis proposing “asynchronous,” “digital,” and “contagious” aging frameworks; no statistical methods or systematic search strategy are described.

Limitations

  • Stated: No unified theory of the molecular basis of cellular aging has emerged; the authors explicitly do not attempt to define aging, its causes, or when underlying changes begin, and identifying non-genetic/non-environmental determinants of individual aging rates remains a major challenge.
  • Stated: The relative contribution of analog versus digital cellular aging as drivers of tissue aging, and whether lifespan/healthspan interventions shift digital states, remain to be determined by further single-cell studies.
  • Evident: As a Perspective, it presents a selective conceptual synthesis rather than a systematic review or primary analysis; many cited examples come from model organisms, limiting direct generalizability to humans.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1038/s43587-020-00015-1

Cites

86 of 86 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 70 cited sources checked · 0 supported · 0 flagged

  • Premisecitation

    Genetic interventions that extend lifespan in C. elegans may do so without comparably altering the relevant aging phenotypes.

    “Evidence in C. elegans has provided support for this idea by demonstrating that genetic interventions that extend lifespan may do so without comparably altering the relevant aging phenotypes.17”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [17] Bansal, A., Zhu, L. J., Yen, K. & Tissenbaum, H. A. Uncoupling lifespan and healthspan in Caenorhabditis elegans longevity mutants. Proc. Natl Acad. Sci. USA 112, E277–E286 (2015). source

      Not checked in the free run.

  • Premisecitation

    Almost no aspects of anatomy or physiology do not exhibit declines as an individual ages.

    “as there are almost no aspects of anatomy or physiology that do not exhibit declines as an individual ages.23”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [23] Khan, S. S., Singer, B. D. & Vaughan, D. E. Molecular and physiological manifestations and measurement of aging in humans. Aging Cell 16, 624–633 (2017). source

      Not checked in the free run.

  • Premisecitation

    Even for genetically identical organisms maintained in identical environments, there remains a large variability of aging trajectories as determined by lifespan.

    “Furthermore, even for genetically identical organisms maintained in identical environments, there remains a large variability of aging trajectories (presumably related to different rates of aging) as determined by lifespan.22”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [22] Kirkwood, T. B. et al. What accounts for the wide variation in life span of genetically identical organisms reared in a constant environment? Mech. Ageing Dev. 126, 439–443 (2005). source

      Not checked in the free run.

  • Interpretationreasoning

    Analog declines of tissue dysfunction and organ failure with age could be the sum of underlying digital events.

    “Nevertheless, analog declines of tissue dysfunction and organ failure with age could be the sum of underlying digital events.”
    Quote in the paperNot a substantial claim
  • Premisecitation

    The determinants of longevity are distinct from those that influence the rate at which an organism ages.

    “While lifespan is a measure that incorporates the impacts of aging, the determinants of longevity are distinct from those that influence the rate at which an organism ages.14”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [14] Hayflick, L. Entropy explains aging, genetic determinism explains longevity, and undefined terminology explains misunderstanding both. PLoS Genet. 3, e220 (2007). source

      Not checked in the free run.

  • Classified as probably not a substantial claim. 14
  • May combine two claims. 10

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    The decline of tissue function is commonly illustrated as gradual and steady, perhaps with a more rapid decline toward the end of life.

    “In general, the decline of tissue function is commonly illustrated as gradual and steady,23 perhaps with a more rapid decline toward the end of life.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [23] Khan, S. S., Singer, B. D. & Vaughan, D. E. Molecular and physiological manifestations and measurement of aging in humans. Aging Cell 16, 624–633 (2017). source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Ultrastructural studies in C. elegans showed vastly different rates of aging of tissues and cells in individual worms, ascribed largely to stochastic events, and the onset of degenerative changes was neither linear nor synchronized.

    “Ultrastructural studies in C. elegans almost two decades ago hinted that it might not.30 The authors noted not only vastly different rates of aging of tissues and cells in individual worms, which they ascribed largely to stochastic events, but the onset of degenerative changes was neither linear nor synchronized.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [30] Herndon, L. A. et al. Stochastic and genetic factors influence tissue-specific decline in ageing C. elegans. Nature 419, 808–814 (2002). source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Interpretationreasoning

    Cellular aging can be viewed, at least in part, as a quantal process referred to as 'digital aging'.

    “In this sense, cellular aging can be viewed, at least in part, as a quantal process we refer to as “digital aging”.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationnone given

    Within any tissue, changes in the cellular composition could be a result of changes in proportions of resident cells or to intrinsic changes to subpopulations without any change in cellular proportions.

    “Within any tissue, changes in the cellular composition could be a result of changes in proportions of resident cells (such as, for example, an increase in the proportion of fibroblasts or resident macrophages) or to intrinsic changes to subpopulations without any change in cellular proportions.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    RNA isolated from individual cardiomyocytes of young and old mice showed broad mosaicism in gene expression among cells within individual mice and increased differences in expression between cells.

    “In a groundbreaking single cell study, RNA isolated from individual cardiomyocytes of young and old mice showed broad mosaicism in gene expression among cells within individual mice and increased differences in expression between cells.45.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [45] Bahar, R. et al. Increased cell-to-cell variation in gene expression in ageing mouse heart. Nature 441, 1011–1014 (2006). source

      Not checked in the free run.

  • May combine two claims.

    Interpretationreasoning

    Spatially, there is clear heterogeneity of aging rates among tissues, and the aging of members of one species may be driven by functional loss of tissues that are different from those in another species.

    “Thus, spatially, there is clear heterogeneity of aging rates among tissues, and the aging of members of one species may be driven by functional loss of tissues that are different from those in another species.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationnone given

    Such cellular states are routinely determined as discrete and quantal rather than continuous.

    “Nevertheless, such cellular states are routinely determined as discrete and quantal rather than continuous.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Interpretationreasoning

    The death of a cell can be considered a digital readout - cells are either alive or dead.

    “The death of a cell can be considered one such digital readout – cells are either alive or dead.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    Aging is associated with changes in the population of immune cell infiltrates, and caloric restriction can reverse those trends.

    “Aging is associated with changes in the population of immune cells infiltrates,51 and caloric restriction can reverse those trends.50”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [51] Kimmel, J. C. et al. Murine single-cell RNA-seq reveals cell-identity- and tissue-specific trajectories of aging. Genome Res. 29, 2088–2103 (2019). source

      Not checked in the free run.

    • cites [50] Ma, S. et al. Caloric restriction reprograms the single-cell transcriptional landscape of Rattus norvegicus aging. Cell 180, 984–1001 (2020). source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based).

    Interpretationreasoning

    The notion of aging by quantal steps can be extended to the subcellular world to explore proximal causes of age-related changes in cellular phenotypes.

    “This notion of aging by quantal steps can clearly be extended to the subcellular world to explore proximal causes of age-related changes in cellular phenotypes.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Interpretationreasoning

    The analog decline of the function of a tissue can be modeled as a result of the gradual accumulation of cells that have transitioned from a functional to one or more dysfunctional states.

    “With this model taken to its extreme, the analog decline of the function of a tissue can be modeled as a result of the gradual accumulation of cells that have transitioned from a functional to one or more dysfunctional states.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning

    At the cellular level, the possibility of a certain amount of 'digital aging' needs also to be considered, digital in the sense of discrimination by discrete units, not necessarily binary units.

    “However, at the cellular level, the possibility of a certain amount “digital aging” needs also to be considered, digital in the sense of discrimination by discrete units, not necessarily binary units (Figure 3).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    Single cell RNA sequencing studies show greater cell-to-cell variability in gene expression in human T cells and pancreatic cells, as well as differences in cellular mutation rates with age.

    “These observations are supported by a rapidly growing number of single cell RNA sequencing studies showing greater cell-to-cell variability in gene expression in human T cells and pancreatic cells, as well as differences in cellular mutation rates with age.47,48”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [47] Martinez-Jimenez, C. P. et al. Aging increases cell-to-cell transcriptional variability upon immune stimulation. Science 355, 1433–1436 (2017). source

      Not checked in the free run.

    • cites [48] Enge, M. et al. Single-cell analysis of human pancreas reveals transcriptional signatures of aging and somatic mutation patterns. Cell 171, 321–330 (2017). source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).

    Interpretationreasoning

    The extent to which cellular aging is due to digital versus analog changes at the molecular level is certain to depend on which cellular phenotype is under consideration.

    “The extent to which cellular aging is due to digital versus analog changes at the molecular level is certain to depend of which cellular phenotype is under consideration in the same way that different tissues may exhibit age-related changes as a result of digital cellular aging to different degrees.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    None of these transitions occurs instantaneously, and there are clearly intermediate states.

    “None of these transitions occurs instantaneously, and there are clearly intermediate states.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    Cells of the same type have vastly different ages based on DNA dating (including postmitotic cells), some as old as the animal, and subcellular structures within individual neurons or pancreatic beta cells have different ages based on protein dating.

    “Cells of the same type have vastly different ages based on DNA dating (including postmitotic cells), some as old as the animal, and subcellular structures within individual neurons or pancreatic beta cells have different ages based on protein dating.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [46] Arrojo e Drigo, R. et al. Age mosaicism across multiple scales in adult tissues. Cell Metab. 30, 343–351 (2019). source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Premisecitation

    Cellular senescence is a digital cellular state in the sense that cells can be classified by various markers as being either senescent or non-senescent.

    “Likewise, cellular senescence is another digital cellular state in the sense that cells can be classified by various markers as being either senescent or non-senescent.54”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [54] Gorgoulis, V. et al. Cellular senescence: defining a path forward. Cell 179, 813–827 (2019). source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Single-cell RNAseq studies of brain endothelial cell aging showed that infusion of aged plasma can accelerate while young plasma can reverse aging as a function of the transcriptome.

    “Indeed, single cell RNAseq studies of brain endothelial cell aging showed that infusion of aged plasma can accelerate while young plasma can reverse aging as a function of the transcriptome.70”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [70] Chen, M. B. et al. Brain endothelial cells are exquisite sensors of age-related circulatory cues. Cell Rep. 30, 4418–4432 (2020). source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    The major risk factor for the vast majority of chronic diseases is age itself.

    “It has long been known that the major risk factor for the vast majority of chronic diseases is age itself.71”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [71] Niccoli, T. & Partridge, L. Ageing as a risk factor for disease. Curr. Biol. 22, R741–R752 (2012). source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning

    A more thorough understanding of the molecular processes of aging, the cellular basis of tissue aging, and the local and systemic communication networks that can accelerate or decelerate the rate of aging will certainly increase the number and diversity of interventions to extend healthspan.

    “A more thorough understanding of the molecular processes of aging, the cellular basis of tissue aging, and the local and systemic communication networks that can accelerate or decelerate the rate of aging will certainly increase the number and diversity interventions to extend healthspan.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning

    Such a model provides a framework for incorporating findings that highlight phenotypes of aging that deviate from models of uniform and synchronized processes throughout an organism.

    “Such a model provides a framework for incorporating findings that highlight phenotypes of aging that deviate from models of uniform and synchronized processes throughout an organism.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    If successful, targeting cellular and tissue drivers of organismal aging would slow the structural and functional declines of organismal aging and reduce the incidence of age-related diseases.

    “If successful, this would not only slow the structural and functional declines that are the quintessential features of the organismal aging, but also would reduce the incidence of age-related diseases.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationnone given

    As the number of distinct measures and biomarkers of aging increases and as the technologies to quantify them develop, the picture of the patterns of aging will continue to become increasingly more complex.

    “As the number of distinct measures and biomarkers of aging increases and as the technologies to quantify them develop, the picture that emerges of the patterns of aging will continue to become increasingly more complex.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).

    Interpretationreasoning

    Coupled with technological advances to measure aging phenotypes and rates of aging at the cellular, tissue, and organismal levels, this will likely increase the pace of translation from the laboratory to the clinic.

    “Coupled with technological advances to measure aging phenotypes and rates of aging at the cellular, tissue, and organismal levels, this will also likely increase the pace of the translation from the laboratory to the clinic.”
    Quote in the paperNot a substantial claim
24 of 24

  • The paper relies on this without support.

    Aging has largely been defined by analog measures of organ and organismal dysfunction.

    “Aging has largely been defined by analog measures of organ and organismal dysfunction.”

  • The paper relies on this without support.

    Current knowledge does not fully explain the growing body of data emerging from large epidemiological, systems biology, and single cell studies of entire organisms pointing to varied rates of aging between individuals, across lifespan, and within an organism at the tissue and organ levels.

    “However, current knowledge does not fully explain the growing body of data emerging from large epidemiological, systems biology, and single cell studies of entire organisms pointing to varied rates of aging between individuals (different functionality and lifespan), across lifespan (asynchronous aging), and within an organism at the tissue and organ levels (aging mosaicism).”

  • The paper relies on this without support.

    Within any given species, there will be individuals that age more rapidly and those that age more slowly.

    “Within any given species, there will be individuals that age more rapidly and those that age more slowly.”

  • The authors state this as an assumption.

    Nearly all animals in a protected environment will age before dying.

    “Assuming that nearly all animals in a protected environment will age before dying, it is almost tautological that members of a species whose maximal lifespan is 100 days age more rapidly than those from a species whose maximal lifespan is 100 years.”

  • The paper relies on this without support.

    Identifying which factors determine individual rates of aging remains a major challenge to the field.

    “Identifying which factors (especially if not genetic and not environmental) determine individual rates of aging remains a major challenge to the field.”

  • The paper relies on this without support.

    In many diseases, including Alzheimer’s disease, Huntington’s disease, and Parkinson’s disease, intracellular aggregation of proteins is a cardinal feature of the pathology.

    “In many diseases, including Alzheimer’s disease, Huntington’s disease, and Parkinson’s disease, a cardinal feature of the pathology is intracellular aggregation of proteins.”

  • The paper relies on this without support.

    Some prions are truly contagious, in the sense of being transmissible between individuals or across species.

    “Of course, some prions are truly contagious, in the sense of being transmissible between individuals or across species”

  • The paper relies on this without support.

    Protein aggregation can be self-propagating.

    “since protein aggregation can be self-propagating”

  • The paper relies on this without support.

    Protein aggregation is one of the key features of cellular aging.

    “As protein aggregation is one of the key features of cellular aging”
9 of 9

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • In aging tissues, molecular and cellular changes disrupt spatial organization, resulting in uneven functional decline.

    “In aging tissues, molecular and cellular changes disrupt spatial organization, resulting in uneven functional decline.”

    From Spatial transcriptomic landscape unveils immunoglobin-associated senescence as a hallmark of aging (2024) · cites this paper as [6]

    The section “Variations in the rate of aging in an individual across time and space” reports molecular and cellular differences among aging tissues and uneven rates of functional decline. It does not say that those changes disrupt the tissues’ spatial organization or establish that disruption as the cause of uneven decline. Page numbers are not available in our copy. (LLM, conf=0.87)

    Experimental — accuracy not yet measured

  • As tissues age at different rates, there is likely a limit to how well ageing of blood cells can measure and explain mechanisms of ageing of the rest of the body.

    “However, as tissues age at different rates41,42,75,76, there is likely a limit to how well ageing of blood cells can measure and explain mechanisms of ageing of the rest of the body; perhaps this is evidenced by the small (albeit statistically significant) associations between second-generation ageing clocks and organ-specific measures of age-related dysfunction.”

    From Measuring biological age using omics data (2022) · cites this paper as [75]

  • Ageing is characterized by a decline in all organ function and a striking increase in multi-organ diseases.

    “Ageing is characterized by a decline in all organ function and a striking increase in multi-organ diseases1.”

    From Ageing and rejuvenation of tissue stem cells and their niches (2023) · cites this paper as [1]

Cites

Flagged first, then by citations

Research works printed but not linked: 1

  1. Pearl, R. The Rate of Living (University of London Press, 1928).

Cited by

Sorted by citations

Related

Authors
Rando, T. A., & Wyss-Coray, T.
Affiliations
VA Palo Alto Health Care System (US)
Corresponding author
Rando, Thomas A.
ORCID
Venue
Nature Aging
Publisher
Springer Science and Business Media LLC
Published
2021-01-14
Volume
1
Issue
1
Pages
29-35
ISSN
2662-8465 (ISSN-L)
DOI
10.1038/s43587-020-00015-1
PMC
PMC8248898
OpenAlex
W3119607554
Cited by
121
References
86
Citations by year
2026: 20 · 2025: 21 · 2024: 24 · 2023: 19 · 2022: 29 · 2021: 8
FWCI
7.15
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Aging (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • NOMIS Stiftung (n/a)
  • Nan Fung Life Sciences
  • The Glenn Foundation for Medical Research
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
  • Health Sciences › Medicine › Physiology › Telomeres, Telomerase, and Senescence
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
Keywords
digital aging, cellular senescence, cellular aging, aging rate, tissue-specific aging, organ dysfunction, lifespan variation, stochastic aging
MeSH terms
Aging, Humans, Longevity, Cellular Senescence

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