Cited by 603Genetics, Aging, and Longevity in Model OrganismsTelomeres, Telomerase, and SenescenceSingle-cell and spatial transcriptomics

The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.

Increased cell-to-cell variation in gene expression in ageing mouse heart

Open access

Bahar, Rumana, Hartmann, Claudia H., Rodriguez, Karl A., Denny, Ashley D., Busuttil, Rita A., Dollé, Martijn E. T., Calder, R. Brent, Chisholm, Gary B., Pollock, Brad H., Klein, Christoph A., Vijg, Jan·2006·Nature

DOI 10.1038/nature04844

Open this paper in CoChat — free account

Abstract

The accumulation of somatic DNA damage has been implicated as a cause of ageing in metazoa. One possible mechanism by which increased DNA damage could lead to cellular degeneration and death is by stochastic deregulation of gene expression. Here we directly test for increased transcriptional noise in aged tissue by dissociating single cardiomyocytes from fresh heart samples of both young and old mice, followed by global mRNA amplification and quantification of mRNA levels in a panel of housekeeping and heart-specific genes. Although gene expression levels already varied among cardiomyocytes from young heart, this heterogeneity was significantly elevated at old age. We had demonstrated previously an increased load of genome rearrangements and other mutations in the heart of aged mice. To confirm that increased stochasticity of gene expression could be a result of increased genome damage, we treated mouse embryonic fibroblasts in culture with hydrogen peroxide. Such treatment resulted in a significant increase in cell-to-cell variation in gene expression, which was found to parallel the induction and persistence of genome rearrangement mutations at a lacZ reporter locus. These results underscore the stochastic nature of the ageing process, and could provide a mechanism for age-related cellular degeneration and death in tissues of multicellular organisms.

Integrity signals

Registry

Crossref · 10.1038/nature04844

Cites

20 of 20 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

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?

Stochasticity in gene expression: from theories to phenotypes
Kærn, M., Elston, T. C., Blake, W. J., & Collins, J. J. (2005) · Nature Reviews Genetics · doi:10.1038/nrg1615 · Cited by 2,318
Understanding the odd science of aging
Kirkwood, T. B. L. (2005) · Cell · doi:10.1016/j.cell.2005.01.027 · Cited by 1,984
Oxygen sensitivity severely limits the replicative lifespan of murine fibroblasts
Parrinello, S., Samper, E., Krtolica, A., Goldstein, J., Melov, S., & Campisi, J. (2003) · Nature Cell Biology · doi:10.1038/ncb1024 · Cited by 1,116
THE MAINTENANCE OF THE ACCURACY OF PROTEIN SYNTHESIS AND ITS RELEVANCE TO AGEING
Orgel, L. E. (1963) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.49.4.517 · Cited by 968
Single-Cell Gene Expression Profiling
Levsky, J. M., Shenoy, S. M., Pezo, R. C., & Singer, R. H. (2002) · Science · doi:10.1126/science.1072241 · Cited by 526
Noise Minimization in Eukaryotic Gene Expression
Fraser, H. B., Hirsh, A. E., Giaever, G. N., Kumm, J., & Eisen, M. B. (2004) · PLoS Biology · doi:10.1371/journal.pbio.0020137 · Cited by 429
A stress-sensitive reporter predicts longevity in isogenic populations of Caenorhabditis elegans
Rea, S. L., Wu, D., Cypser, J. R., Vaupel, J. W., & Johnson, T. E. (2005) · Nature Genetics · doi:10.1038/ng1608 · Cited by 414
Morphological and Molecular Characterization of Adult Cardiomyocyte Apoptosis During Hypoxia and Reoxygenation
Kang, P. M., Haunstetter, A., Aoki, H., Usheva, A., & Izumo, S. (2000) · Circulation Research · doi:10.1161/01.res.87.2.118 · Cited by 323
Contributions of low molecule number and chromosomal positioning to stochastic gene expression
Becskei, A., Kaufmann-Malaga, B., & van Oudenaarden, A. (2005) · Nature Genetics · doi:10.1038/ng1616 · Cited by 321
Combined transcriptome and genome analysis of single micrometastatic cells
Klein, C. A., Seidl, S., Petat‐Dutter, K., Offner, S., Geigl, J. B., Schmidt‐Kittler, O., Wendler, N., Passlick, B., Huber, R. M., Schlimok, G., et al. (2002) · Nature Biotechnology · doi:10.1038/nbt0402-387 · Cited by 303
Self-citation

Show all 20 references

Sorted by citations

Items 501–600 of 603

Computational approaches for the systematic analysis of aging-associated molecular alterations
Debès, C., Leote, A. C., & Beyer, A. (2018) · Drug Discovery Today Disease Models · doi:10.1016/j.ddmod.2019.03.003 · Cited by 1
Genome and Transcriptome Analysis of Single Tumor Cells
Polzer, B. M., Hartmann, C. H., & Klein, C. A. (2009) · doi:10.1002/9783527626649.ch12 · Cited by 1
Self-citation
Dynamic proteomics in mammalian cells: capabilities and challenges
Milo, R. (2007) · Molecular BioSystems · doi:10.1039/b703639f · Cited by 1
Une cellule type?
Izu, L. T., & Chen‐Izu, Y. (2012) · Journal of Molecular and Cellular Cardiology · doi:10.1016/j.yjmcc.2012.01.014 · Cited by 1
“The Molecular Basis of Aging”: The Boehringer Ingelheim Fonds 95th International Titisee Conference
Garinis, G. A., Patil, C. K., & Schumacher, B. (2007) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2007.06.002 · Cited by 1
An efficient algorithm for multiple polony detection
Cortes, H. L., & Snyder, G. (2008) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2008.4541096 · Cited by 1
Nonspecific transcription factor binding reduces variability in transcription factor and target protein expressionPreprint
Soltani, M., Bokes, P., Fox, Z., & Singh, A. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1405.2596 · Cited by 1
Epistasis and destabilizing mutations shape gene expression variability in humans via distinct modes of actionPreprint
Yang, E., Wang, G., Yang, J., Zhou, B., Tian, Y., & Cai, J. J. (2015) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/026393 · Cited by 2
The Evolutionary Implication of Gene Expression Variation in Eukaryotes: From Yeast to Human
Li, J. (2012) · Library and Archives Canada (Government of Canada) · Cited by 1
A constraints-based theory of the primary cause of senescence: imbalance of epigenetic and non-epigenetic information in histone crosstalkPreprint
Veloso, F. A. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/310300 · Cited by 1
Human genetic analyses of organelles highlight the nucleus in age-related trait heritabilityPreprint
Gupta, R., Karczewski, K. J., Howrigan, D., Neale, B. M., & Mootha, V. K. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.01.22.427431 · Cited by 2
FEATURES
(2014) · Asia-Pacific Biotech News · doi:10.1142/s0219030314000275 · Cited by 1
Correction: Teasing Apart Translational and Transcriptional Components of Stochastic Variations in Eukaryotic Gene Expression
Salari, R., Wójtowicz, D., Zheng, J., Levens, D., Pilpel, Y., & Przytycka, T. M. (2012) · PLoS Computational Biology · doi:10.1371/annotation/4498943d-525d-4ac1-8375-ae78e67ea0c8 · Cited by 1
Oxidative Stress Induced Senescence Gives Rise to Transcriptionally Distinct Physiological StatesPreprint
Burnaevskiy, N., Oshima, J., & Mendenhall, A. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.05.18.492555 · Cited by 1
Decay in Transcriptional Information Flow Is a Hallmark of Cellular AgingPreprint
Emison, B., Lynn, C. W., Mugler, A., Ambrosio, F., & Dixit, P. D. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.10.30.685689 · Cited by 1
The aging transcriptome: a condition-dependent response to a deteriorating somaPreprint
Syed, Z. A., Brengdahl, M., Shenoi, V. N., Mital, A., Kimber, C. M., Ekman, H., Mirabello, C., Larsson, M., Berger, D., & Friberg, U. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.22.696078 · Cited by 1
Studying the evolution of bacterial micro-organisms by modeling and numerical simulation approaches
Rocabert, C. (2017) · theses.fr (ABES) · doi:10.70675/273b3895z1c44z4ed9z9eccze815e1fa7c7f · Cited by 1
Aging and Cancer: Caretakers and Gatekeepers
van Heemst, D. (2009) · Springer eBooks · doi:10.1007/978-3-642-02112-1_21
Genomics of Coeliac Disease - Molecular Signatures of the Pathogenesis
Wapenaar, M. C. (2006) · Utrecht University Repository (Utrecht University)
Amplification of cDNA from single or rare cells by global PCR (exponential amplification)
Klein, C. A., & Hartmann, C. H. (2008) · Birkhäuser Basel eBooks · doi:10.1007/978-3-7643-8334-3_9
Self-citation
RNA Memory Model: A RNA-Mediated Transcriptional Activation Mechanism Involved in Cell Identity
Arancio, W. (2010) · Rejuvenation Research · doi:10.1089/rej.2009.0957
The murmur of old broken heartstrings
Tower, J. (2006) · Cell Metabolism · doi:10.1016/j.cmet.2006.07.004
The genetic architecture of gene expression in Caenorhabditis elegans
Rodriguez, A. V. (2011) · doi:10.18174/163345
Methods for Identifying Pathway Epistasis and the Effects of Aging on the Human Methylome
Hannum, G. (2012) · eScholarship (California Digital Library)
Comparative Genomics of Aging
Vijg, J., Garcı́a, A. M., Calder, B. R., & Dollé, M. E. T. (2009) · Springer eBooks · doi:10.1007/978-90-481-3465-6_9
Self-citation
Characteristics of Promoter Architecture-Dependent Expression Noise and Bursting Kinetics
Tan, H., Yuan, Z., Zhang, J., & Zhou, T. (2016) · International Journal of Bifurcation and Chaos · doi:10.1142/s0218127416500164
The role of Kat2a during memory formation and chromatin plasticity in the aging murine hippocampus
Stilling, R. M. (2013) · eDiss (Georg-August-Universität Göttingen) · doi:10.53846/goediss-3945
Molecular and Cellular Methodologies: A Primer
Marı́n-Garcı́a, J., Goldenthal, M. J., & Moe, G. W. P. L. (2007) · Springer eBooks · doi:10.1007/978-0-387-74072-0_3
Developing a Comprehensive Taxonomy for Human Cell Types
Conroy, R., & Pai, V. M. (2015) · CRC Press eBooks · doi:10.1201/b18024-5
Altersspezifische Mechanismen der Karzinogenese
Wellner, U. F. (2016) · Springer eBooks · doi:10.1007/978-3-662-48712-9_4
The Cellular Senescence Program
Shivshankar, P., & Saux, C. J. L. (2014) · Wiley eBooks · doi:10.1002/9781118396292.ch5
Bioinformatics Approaches to Biomarker and Drug Discovery in Aging and Disease
Fortney, K. (2012) · TSpace (University of Toronto)
Ageing: Biomarkers get physical
Dong, X., & Vijg, J. (2017) · Nature Biomedical Engineering · doi:10.1038/s41551-017-0102
Self-citation
Evolutionary Systems Biology in Yeast
Wang, G. (2010) · Univ. Duesseldorf: Duesseldorfer Dokumenten- und Publikationsserver
The Aging Heart
Marı́n-Garcı́a, J. (2014) · Elsevier eBooks · doi:10.1016/b978-0-12-404599-6.00019-6
Single-Cell Whole-Genome Sequencing Reveals B Lymphocyte Mutational Landscapes Across the Human LifespanPreprint
Zhang, L., Dong, X., Lee, M., Maslov, A. Y., & Vijg, J. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3155603
Self-citation
A mosaic of old and young nucleoporins
Shimi, T., & Kimurâ, H. (2019) · The Journal of Cell Biology · doi:10.1083/jcb.201811170
A Statistical Method on DNA Methylation Calling and its Application with Next generation sequencing technique
허익수 (2015) · Seoul National University Open Repository (Seoul National University)
Autoregulation of pre-mRNA processing for buffering noisy gene expressionPreprint
Smith, M. E., Ghusinga, K. R., & Singh, A. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/623181
Mitochondrial control of gene expression and extrinsic apoptosis
Colunga, J. D. (2019) · LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)
Noise Propagation in Chemical Reaction Networks: Analysis of a Molecular Subtractor Module
Cosentino, C., Manes, C., Palombo, G., & Palumbo, P. J. (2019) · European Control Conference (ECC) · doi:10.23919/ecc.2019.8795976
Advancing transcriptome analysis in models of disease and ageing
de Jong, T. V. (2019) · doi:10.33612/diss.99203371
Exploration of the role of chromatin modification in human ageing: The dream of immortality
Annema, S. (2020)
Transcription and Aging
Saint, M., & Rath, P. C. (2020) · Springer eBooks · doi:10.1007/978-981-32-9005-1_3
RNA and aging
Mušo, M. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-817193-6.00015-7
Molecular and Cellular Phenotypes of Cardiovascular Aging
Marı́n-Garcı́a, J., Goldenthal, M. J., & Moe, G. W. P. L. (2007) · Springer eBooks · doi:10.1007/978-0-387-74072-0_4
Development of DNA Methylation Markers to Infer Age, Smoking Status and Body Fluid Types for Forensic Application
Alghanim, H. (2019) · doi:10.25148/etd.fidc008888
Annotation and function of switch-like genes in health and disease
Ertel, A., & Tözeren, A. (2008) · doi:10.17918/etd-2813
Introduction
Kulasiri, D., & Kosarwal, R. (2021) · Springer eBooks · doi:10.1007/978-981-16-5351-3_1
Multi-omic analysis of the aging mouse brain
Kluever, V. (2021) · eDiss (Georg-August-Universität Göttingen) · doi:10.53846/goediss-9022
Faculty Opinions recommendation of The hallmarks of aging.
Hickson, I. D., & Mankouri, H. W. (2013) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.718061760.793481794
Stochastic Fluctuations at Cellular and Molecular Level
Roy, S., & Majumdar, S. (2022) · Springer eBooks · doi:10.1007/978-981-16-9583-4_6
BIBLIOGRAPHY
(2007) · Elsevier eBooks · doi:10.1016/b978-012373657-4/50008-8
Faculty Opinions recommendation of Distinctive roles of age, sex, and genetics in shaping transcriptional variation of human immune responses to microbial challenges.
Teichmann, S. A., & Hagai, T. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.732374149.793555978
Faculty Opinions recommendation of Puma is required for p53-induced depletion of adult stem cells.
Kumar, S. (2010) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.5159956.5097054
Diseases of an aging population (Vol. 18, No. 04, Full Issue)
(2014) · Asia-Pacific Biotech News · doi:10.1142/s0219030314001037
Faculty Opinions recommendation of The Systems Biology of Single-Cell Aging.
Schumacher, B. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.733936717.793563349
Faculty Opinions recommendation of Distinctive roles of age, sex, and genetics in shaping transcriptional variation of human immune responses to microbial challenges.
Doherty, M. T. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.732374149.793556975
Papers of Note
(2006) · Science of Aging Knowledge Environment · doi:10.1126/sageke.2006.10.nw10
Spurious intragenic transcription is a hallmark of mammalian cellular senescence and tissue agingPreprint
Sen, P., Donahue, G., Li, C., Lan, Y., Egervári, G., Robertson, N., Shah, P. P., Kerkhoven, E., Schultz, D., Adams, P. D., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.05.20.492816
Proteomic analysis of human keratinocytes under UVA-induced stress
Valerio, H. P. (2021) · Digital Library of Theses and Dissertations (Universidade de São Paulo) · doi:10.11606/t.46.2021.tde-28042022-144138
Machine learning applications on biological data
Xu, Y. (2022) · DR-NTU (Nanyang Technological University) · doi:10.32657/10356/159232
Allelic Transcription Factor binding shape transcriptional kinetics observed with scRNA-seq in human cell linesPreprint
Jin, B., Feng, H., & Bush, W. S. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.09.21.508743
Role of heterogeneity in dictating tumorigenesis in epithelial tissuesPreprint
Sindhu, M., & vishwakarna, M. (2022) · doi:10.22541/au.166613285.50954604/v1
ImAge: an imaging approach to quantitate aging and rejuvenationPreprint
Alvarez-Kuglen, M., Rodriguez, D., Qin, H., Ninomiya, K., Fiengo, L., Farhy, C., Hsu, W.-M., Havas, A. P., Feng, G., Roberts, A. J., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.10.16.512441
Cell age drives asynchronous transcriptome aging
Yang, M., Harrison, B. R., & Promislow, D. E. L. (2023) · doi:10.1101/2023.05.31.543091
Association between the XRCC3 rs861539 Polymorphism and Breast Cancer Risk: An Updated Meta-Analysis
Hu, G., Gong, L. L., Chen, Y., Xu, L., & Ye, C. (2023) · Russian Journal of Genetics · doi:10.1134/s1022795423140053
EXOSC4 is recruited by histone H3 co-modified with K9me3 and acetylations to surveil non-coding transcriptionPreprint
Stransky, S., Cutler, R. R., Aguilan, J. T., DeAngelo, J. D., Shechter, D., & Sidoli, S. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.08.05.606680
Beyond Differential Expression: Embracing Cell-to-Cell Variability in Single-Cell Gene Expression Data AnalysisPreprint
Gatlin, V., Gupta, S., Romero, S., Chapkin, R. S., & Cai, J. J. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.08.08.607086
Age-associated changes in gene regulatory relationships affect basic cellular processes
(2024) · Nature Aging · doi:10.1038/s43587-024-00706-z
Genes and Antiaging Medicine: Genome Instability and Antiaging
Katsuya, T. (2024) · Springer eBooks · doi:10.1007/978-981-97-8514-8_16
Robust and adaptive non-parametric tests for detecting general distributional shifts in gene expression
Zhou, F., Aw, A. J., Erdmann-Pham, D. D., Fischer, J. D., & Song, Y. S. (2025) · Cell Reports Methods · doi:10.1016/j.crmeth.2025.101147
A multiscale chromatin collapse underlies vascular pathology in Hutchinson–Gilford progeria syndromePreprint
Ngubo, M., Ahuja, N., Karimpour, R., Shrestha, A., Hendzel, M. J., Perkins, T. J., & Stanford, W. L. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.11.693713
Consequences of Endogenous Mitochondrial Oxidative Stress in the Heart
Koenig, K. (2014) · doi:10.33015/dominican.edu/2014.bio.03
How the naked mole-rat resists senescence: a constraints-based theoryPreprint
Veloso, F. A. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.09.22.461400
Additional file 1 of Measuring cell-to-cell expression variability in single-cell RNA-sequencing data: a comparative analysis and applications to B cell aging
Zheng, H., Vijg, J., Fard, A. T., & Mar, J. C. (2024) · Figshare · doi:10.6084/m9.figshare.26629645
Self-citation
Additional file 2 of Measuring cell-to-cell expression variability in single-cell RNA-sequencing data: a comparative analysis and applications to B cell aging
Zheng, H., Vijg, J., Fard, A. T., & Mar, J. C. (2024) · Figshare · doi:10.6084/m9.figshare.26629648
Self-citation
Cellular autophagy and aging: role in intermittent fasting-induced health benefits
Singh, V., Kashif, M., Singh, T., Pahwa, R., Singh, A. K., & Singh, A. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-30060-8.00008-x
A divergent mutational and clonal landscape in aged HSCs is not linked to aging-associated clonal hematopoiesisPreprint
Florian, M. C., Amoah, A., Nattamai, K., Soller, K., Vollmer, A., Hoenicka, M., Liebold, A., Bauer, K., Mallm, J., Geiger, H., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.01.24.701060
Systems Biology of Aging: Opportunities for Parkinson’s Disease
Kriete, A. (2012) · Springer eBooks · doi:10.1007/978-1-4614-3411-5_3
Recherche de nouveaux déterminants génétiques et épigénétiques de susceptibilité à la tumorigenèse intestinale au moyen du modèle murin Apcd14
Quesada, S. (2013) · theses.fr (ABES) · doi:10.70675/5ca6f4fez5c06z4eb3zb5b7z0cffd3b770d8
Investigation of E. coli genome complexity by means of fluorescent reporters of gene expression
Brambilla, E. (2014) · theses.fr (ABES) · doi:10.70675/9ef281afzaf9dz4424zb084ze3fa8699d2d8
MicroARNs et vieillissement épidermique : identification et exploration fonctionnelle de nouvelles cibles anti-âge
Muther, C. (2017) · theses.fr (ABES) · doi:10.70675/b6e606d7zca99z42a3z9029zbe711dffea44
Implication of the receptor for advanced glycation end-products (RAGE) during inflammation and ageing
Teissier, T. (2019) · theses.fr (ABES) · doi:10.70675/f49bc069z5ee6z4c49zb46fz0a1413dbba95
Rôle et régulation de l'haptoglobine adipocytaire au cours du vieillissement
Astre, G. (2018) · theses.fr (ABES) · doi:10.70675/91523d31z8a53z44e6z8f1dzf0a02840a7e5
Characterization of the gene expression changes associated with the age-related Smurf phenotype in Drosophila melanogaster
Zane, F. (2022) · theses.fr (ABES) · doi:10.70675/4b5177f4z3f58z4886za072z5a0cf277cf05
Thriving in an acidic hot spring : The eukaryotic-like cell cycle, viral manipulation, and turtle-like aging of a Saccharolobus cell
Gomez-Raya-Vilanova, M. V. (2024) · theses.fr (ABES) · doi:10.70675/426feb97z7f5ez4a21z911ezefbbc5456dc5
Étude de l'évolution des interactions moléculaires chez les Eucaryotes par des méthodes de comparaison de réseaux dans le but d'identifier des processus ancestraux partagés associés au vieillissement
Bonnefous, H. (2025) · theses.fr (ABES) · doi:10.70675/67742b4az1242z4d30z964ezd8bf9300d4ac
Multimodal analysis of molecular remodeling in aging spleen identified global and cell type specific changesPreprint
Vlajic, K., Luciano, A., Merrihew, G. E., Sanchez, C. R., Riffle, M. E., Tsantilas, K. A., Attar, S., Beliveau, B. J., Sweetwyne, M. T., MacCoss, M. J., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.04.17.719305
Aging as the degradation of conjunctive coupling: A triadic framework S = F × E × N for biological senescence
Farreny, H. (2026) · Ageing Research Reviews · doi:10.1016/j.arr.2026.103184
Transcriptomic phase transitions along the Alzheimer’s disease continuum using riemmaninan tensor model: a bifurcation-intermediate variance framework on the ROSMAP cohortPreprint
Choi, M., Bauermeister, S., & Kim, D.-G. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.05.26.727786
Cybernetic Attractor Decay: A Regulatory-Fidelity Framework for AgingPreprint
Bhak, J. (2026) · Qeios · doi:10.32388/49w9ou.2
Cybernetic Attractor Decay: A Regulatory-Fidelity Framework for AgingPreprint
Bhak, J. (2026) · Qeios · doi:10.32388/49w9ou.3
SIEVEseq: unified differential expression, variability, and skewness analyses using RNA-Seq data
Li, H., & Khang, T. F. (2026) · DNA Research · doi:10.1093/dnares/dsag012
Embracing non-linearity in human ageing
Grolaux, R., Teschendorff, A. E., & Eynon, N. (2026) · Nature Reviews Genetics · doi:10.1038/s41576-026-00993-9
Somatic mutations and genome mosaicism in aging and disease
Pan, E., Maslov, A. Y., & Vijg, J. (2026) · Experimental & Molecular Medicine · doi:10.1038/s12276-026-01791-3
Self-citation
Assessing mechanisms and evidence of a causal role for cellular senescence and somatic mutations in aging
Trastus, L. A., & di Fagagna, F. D. (2026) · Aging · doi:10.18632/aging.206414
An information-theoretic framework for transcriptional regulation reveals declining communication fidelity in aging
Emison, B., Lynn, C. W., Mugler, A., Ambrosio, F., & Dixit, P. D. (2026) · Cell Reports Physical Science · doi:10.1016/j.xcrp.2026.103516 · Cited by 1
Control theory of aging and longevity for gerotherapeutic drug discovery: state space, vector fields, modalities, safety, and the minimum safe cost of functional restoration
Zhavoronkov, A. A., & Mishra, B. (2026) · Aging · doi:10.18632/aging.206422
Biological age uncertainty reveals discordant aging and predicts human healthspanPreprint
Li, Y., Feng, G., Yan, S., Huang, Q., Jin, J., Wang, Y., Pei, Z., Tay, L. X., Li, K., Yuan, Z., et al. (2026) · medRxiv · doi:10.64898/2026.09.26.26364091

Authors: Bahar, R., Hartmann, C. H., Rodriguez, K. A., Denny, A. D., Busuttil, R. A., Dollé, M. E. T., Calder, R. B., Chisholm, G. B., Pollock, B. H., Klein, C. A., & Vijg, J.
Affiliations: Buck Institute for Research on Aging (US)
Institut für Immunologie (DE)
The University of Texas at San Antonio Health Science Center (US)
National Institute for Public Health and the Environment (NL)
Corresponding author: Vijg, Jan
ORCID: Hartmann, Claudia H.
Busuttil, Rita A.
Dollé, Martijn E. T.
Calder, R. Brent
Chisholm, Gary B.
Pollock, Brad H.
Klein, Christoph A.
Vijg, Jan
Venue: Nature
Publisher: Springer Science and Business Media LLC
Published: 2006-06
Volume: 441
Issue: 7096
Pages: 1011-1014
ISSN: 0028-0836 (ISSN-L)
1476-4687
DOI: 10.1038/nature04844
OpenAlex: W2067432938
Cited by: 603
References: 20
Citations by year: 2026: 22 · 2025: 20 · 2024: 26 · 2023: 38 · 2022: 25 · 2021: 29 · 2020: 35 · 2019: 42 · 2018: 29 · 2017: 40 · 2016: 28 · 2015: 35 · 2014: 28 · 2013: 22 · 2012: 29
FWCI: 10.70
Type: journal article
Language: en
Open access: green
hdl.handle.net
Licence: other-oa
www.springer.com/tdm (tdm)
Locations: Nature (publishedVersion)
PubMed (publishedVersion)
RePEc: Research Papers in Economics (submittedVersion)
Rivm Repository (Netherlands National Institute for Public Health and the Environment) (submittedVersion)
Rivm (National Institute for Public Health and the Environment) (submittedVersion, other-oa)
Funders: National Institute on Aging (R36AG033401, P01AG017242)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Telomeres, Telomerase, and Senescence
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
Keywords: aging, transcriptional noise, cardiomyocytes, genome rearrangement, genotoxic stress, hydrogen peroxide, stochastic gene expression, heart
MeSH terms: Aging, Animals, Heart, Hydrogen Peroxide, Male, Mice, Inbred C57BL, Myocardium, RNA, Messenger, Gene Expression, Reverse Transcriptase Polymerase Chain Reaction, Mice

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Increased cell-to-cell variation in gene expression in ageing mouse heart

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks