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A complex systems approach to aging biology
Open accessAbstract
Having made substantial progress understanding molecules, cells, genes and pathways, aging biology research is now moving toward integration of these parts, attempting to understand how their joint dynamics may contribute to aging. Such a shift of perspective requires the adoption of a formal complex systems framework, a transition being facilitated by large-scale data collection and new analytical tools. Here, we provide a theoretical framework to orient researchers around key concepts for this transition, notably emergence, interaction networks and resilience. Drawing on evolutionary theory, network theory and principles of homeostasis, we propose that organismal function is accomplished by the integration of regulatory mechanisms at multiple hierarchical scales, and that the disruption of this ensemble causes the phenotypic and functional manifestations of aging. We present key examples at scales ranging from sub-organismal biology to clinical geriatrics, outlining how this approach can potentially enrich our understanding of aging. The authors discuss how adopting a complex systems perspective is a crucial step in advancing our understanding of the aging process and requires fundamental alteration of the questions being asked and the methods used to answer them.
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“During ageing, adaptive responses are weakened due to deficits in the CAS network.83”
From Antiageing strategy for neurodegenerative diseases: from mechanisms to clinical advances (2025) · cites this paper as [83]
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“When a stimulus is too intense and exceeds the regulatory capacity of the adaptive response or when the compromised adaptive response is insufficient to recover from stimulus-induced perturbations, homoeostasis is disrupted, leading to the onset of disease.83–85”
From Antiageing strategy for neurodegenerative diseases: from mechanisms to clinical advances (2025) · cites this paper as [83]
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1 retracted
Dementia prevention, intervention, and care: 2020 report of the Lancet Commission
Livingston, G., Huntley, J., Sommerlad, A., Ames, D., Ballard, C., Banerjee, S., Brayne, C., Burns, A., Cohen-Mansfield, J., Cooper, C., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30367-6 · Cited by 10,430
RetractedWGCNA: an R package for weighted correlation network analysis
Langfelder, P., & Horvath, S. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-559 · Cited by 27,252
López-Otín, C., Blasco, M. A., Partridge, L., Serrano, M., & Kroemer, G. (2013) · Cell · doi:10.1016/j.cell.2013.05.039 · Cited by 14,982
Efficacy and Safety of the mRNA-1273 SARS-CoV-2 Vaccine
Baden, L. R., El Sahly, H. M., Essink, B., Kotloff, K., Frey, S., Novak, R., Diemert, D., Spector, S. A., Rouphael, N., Creech, C. B., et al. (2021) · New England Journal of Medicine · doi:10.1056/nejmoa2035389 · Cited by 10,119
UMAP: Uniform Manifold Approximation and Projection
McInnes, L., Healy, J., Saul, N., & Großberger, L. (2018) · Journal of Open Source Software · doi:10.21105/joss.00861 · Cited by 9,826
Network biology: understanding the cell's functional organization
Barabási, A.-L., & Oltvai, Z. N. (2004) · Nature Reviews Genetics · doi:10.1038/nrg1272 · Cited by 7,903
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
McInnes, L., Healy, J., & Melville, J. (2018) · arXiv · doi:10.48550/arxiv.1802.03426 · Cited by 7,101
The Strategy of Ecosystem Development
Odum, E. P. (1969) · Science · doi:10.1126/science.164.3877.262 · Cited by 5,546 · cited 3×
“networks, impeding the organism’s ability to optimize regulation; (2) compensatory strategies, features of network robustness where a suboptimal regulatory strategy is adopted to mitigate one problem, but may create others; and (3) from trade-offs between robustness and other key features such as function or resource…”
BackgroundEarly-warning signals for critical transitions
Scheffer, M., Bascompte, J., Brock, W. A., Brovkin, V., Carpenter, S. R., Dakos, V., Held, H., van Nes, E. H., Rietkerk, M., & Sugihara, G. (2009) · Nature · doi:10.1038/nature08227 · Cited by 4,854
Pleiotropy, natural selection, and the evolution of senescence.
Williams, G. C. (1957) · Evolution · doi:10.1111/j.1558-5646.1957.tb02911.x · Cited by 4,279
Systems biology: a brief overview
Kitano, H. (2002) · Science · doi:10.1126/science.1069492 · Cited by 4,265
Nothing in Biology Makes Sense except in the Light of Evolution
Dobzhansky, T. (1973) · The American Biology Teacher · doi:10.2307/4444260 · Cited by 3,219
Accelerated telomere shortening in response to life stress
Epel, E. S., Blackburn, E. H., Lin, J., Dhabhar, F. S., Adler, N. E., Morrow, J. D., & Cawthon, R. M. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0407162101 · Cited by 3,002
Will a Large Complex System be Stable?
MAY, R. M. (1972) · Nature · doi:10.1038/238413a0 · Cited by 2,869
Geroscience: Linking Aging to Chronic Disease
Kennedy, B. K., Berger, S. L., Brunet, A., Campisi, J., Cuervo, A. M., Epel, E. S., Franceschi, C., Lithgow, G. J., Morimoto, R. I., Pessin, J. E., et al. (2014) · Cell · doi:10.1016/j.cell.2014.10.039 · Cited by 2,764
Computational systems biology.
Kitano, H. (2002) · Nature · doi:10.1038/nature01254 · Cited by 2,209
Understanding the odd science of aging
Kirkwood, T. B. L. (2005) · Cell · doi:10.1016/j.cell.2005.01.027 · Cited by 1,984
Bar-Yam, Y. (2019) · CRC Press eBooks · doi:10.1201/9780429034961 · Cited by 1,851
Biological Populations with Nonoverlapping Generations: Stable Points, Stable Cycles, and Chaos
May, R. M. (1974) · Science · doi:10.1126/science.186.4164.645 · Cited by 1,674 · cited 2×
“2d); (3) a multiscale or modular hierarchical structure (for example, organelles, nested in cells nested within tissues nested within organs, together with how damage propagates up, down or across such structures during aging39,40); (4) nonlinear dynamics (for example, accelerating decline in multiple systems at the e…”
BackgroundIntegrated Systems Approach Identifies Genetic Nodes and Networks in Late-Onset Alzheimer’s Disease
Zhang, B., Gaiteri, C., Bodea, L.-G., Wang, Z., McElwee, J., Podtelezhnikov, A. A., Zhang, C., Xie, T., Tran, L., Dobrin, R., et al. (2013) · Cell · doi:10.1016/j.cell.2013.03.030 · Cited by 1,657
Efficacy of an Adjuvanted Herpes Zoster Subunit Vaccine in Older Adults
Lal, H., Cunningham, A. L., Godeaux, O., Chlibek, R., Diez-Domingo, J., Hwang, S.-J., Levin, M. J., McElhaney, J. E., Poder, A., Puig-Barberà, J., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1501184 · Cited by 1,454
Architecture of the human interactome defines protein communities and disease networks
Huttlin, E. L., Bruckner, R. J., Paulo, J. A., Cannon, J. R., Ting, L., Baltier, K., Colby, G., Gebreab, F., Gygi, M. P., Parzen, H., et al. (2017) · Nature · doi:10.1038/nature22366 · Cited by 1,437
Inflammatory networks during cellular senescence: causes and consequences.
Freund, A., Orjalo, A. V., Desprez, P.-Y., & Campisi, J. (2010) · Trends in Molecular Medicine · doi:10.1016/j.molmed.2010.03.003 · Cited by 1,354
Rapamycin: one drug, many effects
Li, J., Kim, S. G., & Blenis, J. (2014) · Cell Metabolism · doi:10.1016/j.cmet.2014.01.001 · Cited by 1,287
Loss of 'Complexity' and Aging
Lipsitz, L. A. (1992) · JAMA · doi:10.1001/jama.1992.03480130122036 · Cited by 1,268
Self-citationCannon, W. B. (1932) · The American Journal of the Medical Sciences · doi:10.1097/00000441-193212000-00028 · Cited by 1,259
Stability criteria for complex ecosystems
Allesina, S., & Tang, S. (2012) · Nature · doi:10.1038/nature10832 · Cited by 1,232
Reverse engineering of biological complexity
Csete, M. E., & Doyle, J. C. (2002) · Science · doi:10.1126/science.1069981 · Cited by 1,215
Visualizing structure and transitions in high-dimensional biological data
Moon, K. R., van Dijk, D., Wang, Z., Gigante, S., Burkhardt, D. B., Chen, W. S., Yim, K., Elzen, A. V. D., Hirn, M. J., Coifman, R. R., et al. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0336-3 · Cited by 1,065
Diversity of ageing across the tree of life
Jones, O. R., Scheuerlein, A., Salguero‐Gómez, R., Camarda, C. G., Schaible, R., Casper, B. B., Dahlgren, J. P., Ehrlén, J., Garcia, M. B., Menges, E. S., et al. (2013) · Nature · doi:10.1038/nature12789 · Cited by 1,046 · cited 3×
“Such breakdowns might arise from: (1) problems with information flow in the”
BackgroundLadyman, J., Lambert, J., & Wiesner, K. (2013) · European Journal for Philosophy of Science · doi:10.1007/s13194-012-0056-8 · Cited by 846
Towards a theory of biological robustness
Kitano, H. (2007) · Molecular Systems Biology · doi:10.1038/msb4100179 · Cited by 829
Alzheimer's disease: experimental models and reality
Drummond, E., & Wisniewski, T. (2017) · Acta Neuropathologica · doi:10.1007/s00401-016-1662-x · Cited by 810
The Critical Role of Metabolic Pathways in Aging
Barzilai, N., Huffman, D. M., Muzumdar, R. H., & Bartke, A. (2012) · Diabetes · doi:10.2337/db11-1300 · Cited by 803
May, R. M., Levin, S. A., & Sugihara, G. (2008) · Nature · doi:10.1038/451893a · Cited by 797
Cell Fates as High-Dimensional Attractor States of a Complex Gene Regulatory Network
Huang, S., Eichler, G., Bar-Yam, Y., & Ingber, D. E. (2005) · Physical Review Letters · doi:10.1103/physrevlett.94.128701 · Cited by 775
Van Remmen, H., Ikeno, Y., Hamilton, M., Pahlavani, M., Wolf, N., Thorpe, S. R., Alderson, N. L., Baynes, J. W., Epstein, C. J., Huang, T.-T., et al. (2003) · Physiological Genomics · doi:10.1152/physiolgenomics.00122.2003 · Cited by 734
Network physiology reveals relations between network topology and physiological function
Bashan, A., Bartsch, R. P., Kantelhardt, J. W., Havlin, S., & Ivanov, P. C. (2012) · Nature Communications · doi:10.1038/ncomms1705 · Cited by 727
Why fishing magnifies fluctuations in fish abundance
Anderson, C. N. K., Hsieh, C., Sandin, S., Hewitt, R., Hollowed, A., Beddington, J., May, R., & Sugihara, G. (2008) · Nature · doi:10.1038/nature06851 · Cited by 713
Dynamics of stability: the physiologic basis of functional health and frailty
Lipsitz, L. A. (2002) · The Journals of Gerontology Series A: Biological Sciences and Medical Sciences · doi:10.1093/gerona/57.3.b115 · Cited by 646
Self-citationThe physical frailty syndrome as a transition from homeostatic symphony to cacophony
Fried, L. P., Cohen, A. A., Xue, Q., Walston, J. D., Bandeen‐Roche, K., & Varadhan, R. (2021) · Nature Aging · doi:10.1038/s43587-020-00017-z · Cited by 635
Self-citationTaking a good look at free radicals in the aging process
Hekimi, S., Lapointe, J., & Wen, Y. (2011) · Trends in Cell Biology · doi:10.1016/j.tcb.2011.06.008 · Cited by 606
Greer, E. L., & Brunet, A. (2009) · Aging Cell · doi:10.1111/j.1474-9726.2009.00459.x · Cited by 591
The Metabolic Syndrome: Inflammation, Diabetes Mellitus, and Cardiovascular Disease
Haffner, S. M. (2005) · The American Journal of Cardiology · doi:10.1016/j.amjcard.2005.11.010 · Cited by 568
Fried, L. P., Xue, Q.-L., Cappola, A. R., Ferrucci, L., Chaves, P., Varadhan, R., Guralnik, J. M., Leng, S. X., Semba, R. D., Walston, J. D., et al. (2009) · The Journals of Gerontology Series A: Biological Sciences and Medical Sciences · doi:10.1093/gerona/glp076 · Cited by 539
Self-citationConsequences of the selective blockage of chaperone-mediated autophagy
Massey, A. C., Kaushik, S., Sovak, G., Kiffin, R., & Cuervo, A. M. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0507436103 · Cited by 529
Tăcutu, R., Craig, T., Budovsky, A., Wuttke, D., Lehmann, G., Toren, D., Cósta, J., Fraifeld, V. E., & de Magalhães, J. P. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1155 · Cited by 516
AN ATTEMPT AT A RATIONAL CLASSIFICATION OF THEORIES OF AGEING
Медведев, Ж. А. (1990) · Biological reviews/Biological reviews of the Cambridge Philosophical Society · doi:10.1111/j.1469-185x.1990.tb01428.x · Cited by 515
Rattan, S. I. S. (2008) · Ageing Research Reviews · doi:10.1016/j.arr.2007.03.002 · Cited by 498
Bow ties, metabolism and disease
Csete, M., & Doyle, J. (2004) · Trends in biotechnology · doi:10.1016/j.tibtech.2004.07.007 · Cited by 468
Qualitative Stability in Model Ecosystems
May, R. M. (1973) · Ecology · doi:10.2307/1935352 · Cited by 462 · cited 3×
“2d); (3) a multiscale or modular hierarchical structure (for example, organelles, nested in cells nested within tissues nested within organs, together with how damage propagates up, down or across such structures during aging39,40); (4) nonlinear dynamics (for example, accelerating decline in multiple systems at the e…”
BackgroundSir2-Independent Life Span Extension by Calorie Restriction in Yeast
Kaeberlein, M., Kirkland, K. T., Fields, S., & Kennedy, B. K. (2004) · PLoS Biology · doi:10.1371/journal.pbio.0020296 · Cited by 441
Dendritic cell subsets and locations
Balan, S., Saxena, M., & Bhardwaj, N. (2019) · International review of cytology · doi:10.1016/bs.ircmb.2019.07.004 · Cited by 370
The degree of frailty as a translational measure of health in aging
Howlett, S. E., Rutenberg, A. D., & Rockwood, K. J. (2021) · Nature Aging · doi:10.1038/s43587-021-00099-3 · Cited by 357
Self-citationSterling, P. (2004) · Allostasis, Homeostasis, and the Costs of Physiological Adaptation · doi:10.1017/cbo9781316257081.004 · Cited by 353
Sirtuins Link Inflammation and Metabolism
Vachharajani, V., Liu, T., Wang, X., Hoth, J. J., Yoza, B. K., & McCall, C. E. (2016) · Journal of Immunology Research · doi:10.1155/2016/8167273 · Cited by 333
Measuring Resilience in Stochastic Systems
Ives, A. R. (1995) · Ecological Monographs · doi:10.2307/2937138 · Cited by 297
Inflamm-aging does not simply reflect increases in pro-inflammatory markers
Morrisette-Thomas, V., Cohen, A. A., Fülöp, T., Riesco, É., Legault, V., Li, Q., Milot, E., Dusseault-Bélanger, F., & Ferrucci, L. (2014) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2014.06.005 · Cited by 283
Self-citationDynamic causal modelling revisited
Friston, K. J., Preller, K. H., Mathys, C., Cagnan, H., Heinzle, J., Razi, A., & Zeidman, P. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2017.02.045 · Cited by 271
Viewing forests through the lens of complex systems science
Filotas, É., Parrott, L., Burton, P. J., Chazdon, R. L., Coates, K. D., Coll, L., Haeussler, S., Martin, K., Nocentini, S., Puettmann, K. J., et al. (2014) · Ecosphere · doi:10.1890/es13-00182.1 · Cited by 261
Kohl, P. K., Crampin, E. J., Quinn, T. A., & Noble, D. (2010) · Clinical Pharmacology & Therapeutics · doi:10.1038/clpt.2010.92 · Cited by 242
Underlying features of epigenetic aging clocks in vivo and in vitro.
Liu, Z., Leung, D., Thrush, K., Zhao, W., Ratliff, S., Tanaka, T., Schmitz, L. L., Smith, J. A., Ferrucci, L., & Levine, M. E. (2020) · Aging Cell · doi:10.1111/acel.13229 · Cited by 227
Self-citationPhysiological regulatory networks: ecological roles and evolutionary constraints
Cohen, A. A., Martin, L. B., Wingfield, J. C., McWilliams, S. R., & Dunne, J. A. (2012) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2012.04.008 · Cited by 225
Self-citationFocus on the emerging new fields of network physiology and network medicine
Ivanov, P. C., Liu, K. K. L., & Bartsch, R. P. (2016) · New Journal of Physics · doi:10.1088/1367-2630/18/10/100201 · Cited by 223
Kowald, A., & Kirkwood, T. B. L. (1996) · Mutation Research/DNAging · doi:10.1016/s0921-8734(96)90005-3 · Cited by 221
Manu, Surkova, S. Y., Spirov, A. V., Gursky, V. V., Janssens, H., Kim, A.-R., Radulescu, O., Vanario‐Alonso, C. E., Sharp, D. H., Samsonova, M. G., et al. (2009) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000303 · Cited by 218
Endogenous oxidative stress: relationship to aging, longevity and caloric restriction
Barja, G. (2002) · Ageing Research Reviews · doi:10.1016/s1568-1637(02)00008-9 · Cited by 215
Stability and complexity in model meta-ecosystems
Gravel, D., Massol, F., & Leibold, M. A. (2016) · Nature Communications · doi:10.1038/ncomms12457 · Cited by 213
Self-citationProtein biogenesis machinery is a driver of replicative aging in yeast
Janssens, G. E., Meinema, A. C., González, J., Wolters, J. C., Schmidt, A., Guryev, V., Bischoff, R., Wit, E. C., Veenhoff, L. M., & Heinemann, M. (2015) · eLife · doi:10.7554/elife.08527 · Cited by 199
The temporal scaling of Caenorhabditis elegans ageing
Stroustrup, N., Anthony, W. E., Nash, Z. M., Gowda, V., Gomez, A., López-Moyado, I. F., Apfeld, J., & Fontana, W. (2016) · Nature · doi:10.1038/nature16550 · Cited by 196
Self-citationThe rise of computational biology
Noble, D. (2002) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm810 · Cited by 192
Spatial and Temporal Control of Senescence
Ito, Y., Hoare, M., & Narita, M. (2017) · Trends in Cell Biology · doi:10.1016/j.tcb.2017.07.004 · Cited by 178
The DrugAge Database of Aging-Related Drugs
Barardo, D., Thornton, D., Thoppil, H., Walsh, M., Sharifi, S., Ferreira, S., Anžič, A., Fernandes, M., Monteiro, P., Grum, T., et al. (2017) · Aging Cell · doi:10.1111/acel.12585 · Cited by 173
Report: NIA Workshop on Measures of Physiologic Resiliencies in Human Aging
Hadley, E. C., Kuchel, G. A., Newman, A. B., Allore, H. G., Bartley, J. M., Bergeman, C. S., Blinov, M. L., Colon-Emeric, C. S., Dabhar, F. S., Dugan, L. L., et al. (2017) · The Journals of Gerontology: Series A · doi:10.1093/gerona/glx015 · Cited by 173
Self-citationMcLaughlin, J. M., Jiang, Q. L., Istúriz, R., Sings, H. L., Swerdlow, D. L., Gessner, B. D., Carrico, R., Peyrani, P., Wiemken, T. L., Mattingly, W. A., et al. (2018) · Clinical Infectious Diseases · doi:10.1093/cid/ciy312 · Cited by 161
Inflammatory signaling and cellular senescence
Ren, J., Pan, J., Lu, Y.-P., Sun, P., & Han, J. (2008) · Cellular Signalling · doi:10.1016/j.cellsig.2008.10.011 · Cited by 153
Varadhan, R., Seplaki, C. L., Xue, Q., Bandeen‐Roche, K., & Fried, L. P. (2008) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2008.09.013 · Cited by 150
Self-citationLipsitz, L. A., Lough, M., Niemi, J. B., Travison, T. G., Howlett, H., & Manor, B. D. (2014) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2014.10.004 · Cited by 144
Self-citationComplex systems dynamics in aging: new evidence, continuing questions
Cohen, A. A. (2015) · Biogerontology · doi:10.1007/s10522-015-9584-x · Cited by 144
Self-citationCohen, A. A., Kennedy, B. K., Anglas, U., Bronikowski, A. M., Deelen, J., Dufour, F., Ferbeyre, G., Ferrucci, L., Franceschi, C., Frasca, D., et al. (2020) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2020.111316 · Cited by 141
Self-citationKuo, P.-L., Schrack, J. A., Shardell, M. D., Levine, M. E., Moore, A. Z., An, Y., Elango, P., Karikkineth, A. C., Tanaka, T., de Cabo, R., et al. (2020) · Journal of Internal Medicine · doi:10.1111/joim.13024 · Cited by 140
Self-citationFrailty Status and Altered Glucose-Insulin Dynamics
Kalyani, R. R., Varadhan, R., Weiss, C. O., Fried, L. P., & Cappola, A. R. (2011) · The Journals of Gerontology Series A · doi:10.1093/gerona/glr141 · Cited by 139
Self-citationLeveille, S. G., Kiel, D. P., Jones, R. N., Roman, A., Hannan, M. T., Sorond, F. A., Kang, H. G., Samelson, E. J., Gagnon, M. M., Freeman, M., et al. (2008) · BMC Geriatrics · doi:10.1186/1471-2318-8-16 · Cited by 138
Self-citationA programmable fate decision landscape underlies single-cell aging in yeast
Li, Y., Jiang, Y., Paxman, J., O’Laughlin, R., Klepin, S., Zhu, Y., Pillus, L., Tsimring, L. S., Hasty, J., & Hao, N. (2020) · Science · doi:10.1126/science.aax9552 · Cited by 137
Self-citationGenome-environment interactions that modulate aging: powerful targets for drug discovery
de Magalhães, J. P., Wuttke, D., Wood, S. H., Plank, M., & Vora, C. (2012) · Pharmacological Reviews · doi:10.1124/pr.110.004499 · Cited by 136
The hoverfly and the wasp: A critique of the hallmarks of aging as a paradigm
Gems, D., & de Magalhães, J. P. (2021) · Ageing Research Reviews · doi:10.1016/j.arr.2021.101407 · Cited by 134
The Hoverfly and the Wasp: A Critique of the Hallmarks of Aging as a Paradigm
Gems, D., & de Magalhães, J. P. (2021) · doi:10.20944/preprints202105.0310.v1 · Cited by 134
Biochemical Genetic Pathways that Modulate Aging in Multiple Species: Figure 1.Preprint
Bitto, A., Wang, A. M., Bennett, C. F., & Kaeberlein, M. R. (2015) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a025114 · Cited by 122
Evolution of Bow-Tie Architectures in Biology
Friedlander, T., Mayo, A., Tlusty, T., & Alon, U. S. (2015) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004055 · Cited by 117
Feed-forward activation and feed-back inhibition of pyruvate kinase type L of rat liver
Tanaka, T., Sue, F., & Morimura, H. (1967) · Biochemical and Biophysical Research Communications · doi:10.1016/0006-291x(67)90477-9 · Cited by 115
Cells discover fire: Employing reactive oxygen species in developmentand consequences for aging
de Magalhães, J. P., & Church, G. M. (2005) · Experimental Gerontology · doi:10.1016/j.exger.2005.09.002 · Cited by 109
Zhou, J., Habtemariam, D. A., Iloputaife, I., Lipsitz, L. A., & Manor, B. D. (2017) · Scientific Reports · doi:10.1038/s41598-017-03422-4 · Cited by 108
Self-citationUkraintseva, S. V., Arbeev, K. G., Duan, M., Akushevich, I. V., Kulminski, A. M., Stallard, E., & Yashin, A. I. (2020) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2020.111418 · Cited by 100
Unifying aging and frailty through complex dynamical networks
Rutenberg, A. D., Mitnitski, A., Farrell, S. G., & Rockwood, K. J. (2017) · Experimental Gerontology · doi:10.1016/j.exger.2017.08.027 · Cited by 97
Self-citationWagner, A. (1999) · Biology & Philosophy · doi:10.1023/a:1006580900476 · Cited by 91
Tieri, P., Grignolio, A., Zaikin, A. A., Mishto, M., Remondini, D., Castellani, G., & Franceschi, C. (2010) · Theoretical Biology and Medical Modelling · doi:10.1186/1742-4682-7-32 · Cited by 91
Gijzel, S. M. W., van de Leemput, I. A., Scheffer, M., Roppolo, M., Rikkert, M. G. M. O., & Melis, R. J. F. (2017) · The Journals of Gerontology Series A · doi:10.1093/gerona/glx065 · Cited by 90
Bartlett, D. W., & O’Toole, S. (2019) · Australian Dental Journal · doi:10.1111/adj.12681 · Cited by 90
Robustness and aging—A systems-level perspective
Kriete, A. (2013) · Biosystems · doi:10.1016/j.biosystems.2013.03.014 · Cited by 83
Self-citationEvidence for the hallmarks of human aging in replicatively aging yeast
Janssens, G. E., & Veenhoff, L. M. (2016) · Microbial Cell · doi:10.15698/mic2016.07.510 · Cited by 80
Multigenerational silencing dynamics control cell aging
Li, Y., Jin, M., O’Laughlin, R., Bittihn, P., Tsimring, L. S., Pillus, L., Hasty, J., & Hao, N. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1703379114 · Cited by 80
Self-citationLemoine, M. (2020) · Biology & Philosophy · doi:10.1007/s10539-020-09765-z · Cited by 80
Temiz-Resitoglu, M., Kucukkavruk, S. P., Guden, D. S., Cecen, P., Sari, A. N., Tunctan, B., Gorur, A., Tamer-Gumus, L., Buharalioglu, C. K., Malik, K. U., et al. (2017) · European Journal of Pharmacology · doi:10.1016/j.ejphar.2017.02.034 · Cited by 77
Detection of a Novel, Integrative Aging Process Suggests Complex Physiological Integration
Cohen, A. A., Milot, E., Li, Q., Bergeron, P., Poirier, R., Dusseault-Bélanger, F., Fülöp, T., Leroux, M., Legault, V., Metter, E. J., et al. (2015) · PLOS ONE · doi:10.1371/journal.pone.0116489 · Cited by 75
Self-citationSystems Biology of Phenotypic Robustness and Plasticity
Nijhout, H. F., Sadre‐Marandi, F., Best, J. A., & Reed, M. C. (2017) · Integrative and Comparative Biology · doi:10.1093/icb/icx076 · Cited by 71
mTOR Senses Environmental Cues to Shape the Fibroblast-like Synoviocyte Response to Inflammation
Karonitsch, T., Kandasamy, R. K., Kartnig, F., Herdy, B., von Dalwigk, K., Niederreiter, B., Holinka, J., Sevelda, F., Windhager, R. H., Bilban, M., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.04.044 · Cited by 69
Resilience Versus Robustness in Aging
Ukraintseva, S. V., Yashin, A. I., & Arbeev, K. G. (2016) · The Journals of Gerontology Series A · doi:10.1093/gerona/glw083 · Cited by 68
Inflammation, Telomere Length, and Grip Strength: A 10-year Longitudinal Study
Baylis, D., Ntani, G., Edwards, M. H., Syddall, H. E., Bartlett, D. B., Dennison, E. M., Martin-Ruiz, C. M., von Zglinicki, T., Kuh, D. J., Lord, J. M., et al. (2014) · Calcified Tissue International · doi:10.1007/s00223-014-9862-7 · Cited by 63
Divergent Aging of Isogenic Yeast Cells Revealed through Single-Cell Phenotypic Dynamics
Jin, M., Li, Y., O’Laughlin, R., Bittihn, P., Pillus, L., Tsimring, L. S., Hasty, J., & Hao, N. (2019) · Cell Systems · doi:10.1016/j.cels.2019.02.002 · Cited by 61
Self-citationManor, B. D., Lipsitz, L. A., Wayne, P. M., Peng, C., & Li, L. (2013) · BMC Complementary and Alternative Medicine · doi:10.1186/1472-6882-13-87 · Cited by 58
Self-citationImmunosenescence and Altered Vaccine Efficiency in Older Subjects: A Myth Difficult to Change
Fülöp, T., Larbi, A., Pawelec, G., Cohen, A. A., Provost, G., Khalil, A., Lacombe, G., Rodrigues, S., Desroches, M., Hirokawa, K., et al. (2022) · Vaccines · doi:10.3390/vaccines10040607 · Cited by 58
Self-citationRule-Based Cell Systems Model of Aging using Feedback Loop Motifs Mediated by Stress Responses
Kriete, A., Bosl, W. J., & Booker, G. (2010) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000820 · Cited by 56
Self-citationWhat if there’s no such thing as “aging”?
Cohen, A. A., Legault, V., & Fülöp, T. (2020) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2020.111344 · Cited by 55
Self-citationThe importance of quantitative systemic thinking in medicine
West, G. B. (2012) · The Lancet · doi:10.1016/s0140-6736(12)60281-5 · Cited by 53
Conventional calpains and programmed cell death.
Łopatniuk, P., & Witkowski, J. M. (2011) · Acta Biochimica Polonica · doi:10.18388/abp.2011_2238 · Cited by 53
Javorka, M., Czippelová, B., Turianiková, Z., Lazarova, Z., Tonhajzerová, I., & Faes, L. (2016) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-016-1492-y · Cited by 50
NAKAZATO, Y., Sugiyama, T., Ohno, R., Shimoyama, H., Leung, D. L., Cohen, A. A., KURANE, R., Hirose, S., Watanabe, A., & Shimoyama, H. (2020) · Scientific Reports · doi:10.1038/s41598-020-66861-6 · Cited by 49
Self-citationNetwork model of human aging: Frailty limits and information measures
Farrell, S. G., Mitnitski, A., Rockwood, K. J., & Rutenberg, A. D. (2016) · Physical review. E · doi:10.1103/physreve.94.052409 · Cited by 48
Self-citationEffects of NAD+ precursor supplementation on glucose and lipid metabolism in humans: a meta-analysis
Zhong, O., Wang, J., Tan, Y., Lei, X., & Tang, Z. (2022) · Nutrition & Metabolism · doi:10.1186/s12986-022-00653-9 · Cited by 46
Aging in complex interdependency networks
Vural, D. C., Morrison, G., & Mahadevan, L. (2014) · Physical Review E · doi:10.1103/physreve.89.022811 · Cited by 45
Galatzer‐Levy, R. M. (2002) · Psychoanalytic Inquiry · doi:10.1080/07351692209349014 · Cited by 45
Gijzel, S. M. W., van de Leemput, I. A., Scheffer, M., van Bon, G. E. A., Weerdesteyn, V., Eijsvogels, T. M. H., Hopman, M. T. E., Rikkert, M. G. M. O., & Melis, R. J. F. (2018) · The Journals of Gerontology Series A · doi:10.1093/gerona/gly170 · Cited by 43
Conservation of physiological dysregulation signatures of aging across primates
Dansereau, G., Wey, T. W., Legault, V., Brunet, M. A., Kemnitz, J. W., Ferrucci, L., & Cohen, A. A. (2019) · Aging Cell · doi:10.1111/acel.12925 · Cited by 42
Self-citationXie, K., Fuchs, H., Scifo, E., Liu, D., Aziz, N. A., Aguilar‐Pimentel, J. A., Amarie, O. V., Becker, L., da Silva‐Buttkus, P., Calzada‐Wack, J., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-34515-y · Cited by 42
Witten, M. (1984) · Mechanisms of Ageing and Development · doi:10.1016/0047-6374(84)90056-3 · Cited by 39
Predator control may not increase ungulate populations in the future: A formal meta‐analysis
Clark, T. J., & Hebblewhite, M. (2020) · Journal of Applied Ecology · doi:10.1111/1365-2664.13810 · Cited by 39
Rapamycin, anti-aging, and avoiding the fate of Tithonus
Richardson, A. (2013) · Journal of Clinical Investigation · doi:10.1172/jci70800 · Cited by 35
Toward a Systems Biology Framework for Understanding Aging and Health Span
West, G. B., & Bergman, A. (2009) · The Journals of Gerontology Series A · doi:10.1093/gerona/gln066 · Cited by 34
The Systems Biology of Single-Cell Aging
Song, R., Sarnoski, E. A., & Açar, M. (2018) · iScience · doi:10.1016/j.isci.2018.08.023 · Cited by 31
Multiscale Dynamics of Spontaneous Brain Activity Is Associated With Walking Speed in Older Adults
Zhou, J., Poole, V. N., Wooten, T., Lo, O., Iloputaife, I., Manor, B. D., Esterman, M. S., & Lipsitz, L. A. (2019) · The Journals of Gerontology Series A · doi:10.1093/gerona/glz231 · Cited by 24
Self-citationMa, Y., Zhou, J., Kavousi, M., Lipsitz, L. A., Mattace-Raso, F. U. S., Westerhof, B. E., Wolters, F. J., Wu, J. W., Manor, B. D., Ikram, M. K., et al. (2021) · Alzheimer s & Dementia · doi:10.1002/alz.12288 · Cited by 24
Self-citationA computational exploration of resilience and evolvability of protein–protein interaction networks
Klein, B., Holmér, L., Smith, K., Johnson, M. M., Swain, A., Stolp, L., Teufel, A., & Kleppe, A. S. (2021) · Communications Biology · doi:10.1038/s42003-021-02867-8 · Cited by 23
Interpretable machine learning for high-dimensional trajectories of aging health
Farrell, S., Mitnitski, A., Rockwood, K., & Rutenberg, A. D. (2022) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1009746 · Cited by 22
Self-citationModelling physical resilience in ageing mice
Schosserer, M., Banks, G. T., Doğan, S., Dungel, P., Fernandes, A. M. A., Marolt, D., Matheu, A., Osuchowski, M. F., Potter, P. K., Sanfeliu, C., et al. (2018) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2018.10.001 · Cited by 21
Le, N. P., Varadhan, R., Fried, L. P., & Cappola, A. R. (2020) · The Journals of Gerontology Series A · doi:10.1093/gerona/glaa134 · Cited by 19
Self-citationCohen, A. A., Leung, D. L., Legault, V., Gravel, D., Blanchet, F. G., Côté, A., Fülöp, T., Lee, J., Dufour, F., Liu, M., et al. (2022) · iScience · doi:10.1016/j.isci.2022.104385 · Cited by 19
Self-citationGenerating synthetic aging trajectories with a weighted network model using cross-sectional data
Farrell, S., Mitnitski, A., Rockwood, K. J., & Rutenberg, A. D. (2020) · Scientific Reports · doi:10.1038/s41598-020-76827-3 · Cited by 15
Self-citationKnee extension rate of velocity development affects walking performance differently in men and women
Osawa, Y., Studenski, S. A., & Ferrucci, L. (2018) · Experimental Gerontology · doi:10.1016/j.exger.2018.09.005 · Cited by 13
Self-citationRobust Physiological Metrics From Sparsely Sampled Networks
Cohen, A. A., Leblanc, S., & Roucou, X. (2021) · Frontiers in Physiology · doi:10.3389/fphys.2021.624097 · Cited by 12
Self-citationPrediction of Mortality in Hemodialysis Patients Using Moving Multivariate Distance
Liu, M., Legault, V., Fülöp, T., Côté, A., Gravel, D., Blanchet, F. G., Leung, D. L., Lee, S. J., NAKAZATO, Y., & Cohen, A. A. (2021) · Frontiers in Physiology · doi:10.3389/fphys.2021.612494 · Cited by 12
Self-citationXie, K., Fuchs, H., Scifo, E., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.03.25.485824 · Cited by 6
Simulation of Cellular Energy Restriction in Quiescence (ERiQ)—A Theoretical Model for Aging
Alfego, D., & Kriete, A. (2017) · Biology · doi:10.3390/biology6040044 · Cited by 3
Self-citationPREDICTING AGING PATTERNS WITH PROFILES OF BIOMARKERS IN LONG LIFE FAMILY STUDY PARTICIPANTS
(2015) · The Gerontologist · doi:10.1093/geront/gnv490.01 · Cited by 1
Research works printed but not linked: 3
- May, R. M. Stability in model ecosystems. Proc. Ecol. Soc. Aust. 6, 18–56 (1971).
- Van Der Maaten, L. & Hinton, G. Visualizing data using t-SNE. J. Mach. Learn. Res. 9, 2579–2605 (2008).
- Barabási, A. -L. Network Science (Cambridge Univ. Press, 2016).
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Metadata
- Authors
- Cohen, A. A., Ferrucci, L., Fülöp, T., Gravel, D., Hao, N., Kriete, A., Levine, M. E., Lipsitz, L. A., Olde Rikkert, M. G. M., Rutenberg, A., Stroustrup, N., & Varadhan, R.
- Affiliations
- Université de Sherbrooke (CA)
- National Institute on Aging (US)
- University of California San Diego (US)
- Drexel University (US)
- Yale University (US)
- Beth Israel Deaconess Medical Center (US)
- Dalhousie University (CA)
- Universitat Pompeu Fabra (ES)
- Johns Hopkins University (US)
- Corresponding author
- Cohen, Alan A.
- ORCID
- Venue
- Nature Aging
- Published
- 2022-07-20
- Volume
- 2
- Issue
- 7
- Pages
- 580-591
- ISSN
- 2662-8465 (ISSN-L)
- PMC
- PMC12007111
- OpenAlex
- W4286008101
- Cited by
- 221
- References
- 140
- Citations by year
- 2026: 53 · 2025: 61 · 2024: 60 · 2023: 44 · 2022: 3
- FWCI
- 3.57
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Nature Aging (publishedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Radboud Repository (Radboud University) (submittedVersion)
- Funders
- Drexel University
- ZonMw (09120012010063)
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (645.003.002, COMPL.21COV.001)
- National Institutes of Health
- Canadian Institutes of Health Research (153011)
- National Institute on Aging (R01AG056440, R01AG068112)
- National Institute of General Medical Sciences (R01GM111458)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Philosophy of Biology and Scientific Explanation
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Systems and Dynamics
- Keywords
- biological aging, complex systems, emergence, interaction networks, resilience, homeostasis, hierarchical regulation, network theory, evolutionary theory, multiscale integration, geriatrics
- MeSH terms
- Biology, Geriatrics, Homeostasis, Systems Analysis
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