Skip to main content Accessibility help
×
Hostname: page-component-78c5997874-lj6df Total loading time: 0 Render date: 2024-11-15T02:34:11.806Z Has data issue: false hasContentIssue false

7 - Perspectives in Comparative Biology of Ageing

Published online by Cambridge University Press:  14 November 2024

Jean-François Lemaître
Affiliation:
Centre National de la Recherche Scientifique (CNRS)
Samuel Pavard
Affiliation:
National Museum of Natural History, Paris
Get access

Summary

The dream of eternal youth and immortality has always fascinated human societies. Even today, this quest is the source of major financial investments, particularly for the development of anti-ageing drugs. To unravel the mysteries of longevity, scientists have long been observing and quantifying the lifespan of animals. These decades of extensive comparative biology research have documented the extreme diversity of lifespan on Earth and identified key ecological and life history factors driving this diversity and, more recently, molecular pathways that might modulate it. However, the maximum lifespan of a species is far from being an accurate representation of a species’ ageing trajectory, both biologically and demographically. For a given species, the changes in mortality risk over the life course can be complex, and the ageing process is much more accurately described by ageing parameters, such as the age of onset of actuarial senescence and the rate of actuarial senescence. This chapter argues that current research in the comparative biology of ageing should now focus on the diversity of actuarial senescence patterns documented across the tree of life, as well as the species-specific causes of death, to identify key genetic and physiological determinants associated with delayed actuarial senescence or low actuarial senescence rate. Just a few years ago, such research projects would have seemed unrealistic, but the recent development of omics tools, coupled with the increased availability of demographic data for a wide range of species with contrasting life histories, lifestyles and habitats make such exciting comparative analyses now achievable and full of promise.

Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2024

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Carey, J., Judge, D. 2000. Longevity Records: Life Spans of Mammals, Birds, Reptiles, Amphibians and Fish. University Odense Press.Google Scholar
Aristotle, . 2001. On Longevity and Shortness of Life (trans. G.R.T. Ross). Internet Classics Archive. https://classics.mit.edu/Aristotle/longev_short.html.Google Scholar
Huxley, J.S. 1932. Problems of Relative Growth. Methuen.Google Scholar
Thompson, D.A.W. 1942. On Growth and Form. Cambridge University Press.Google Scholar
Lemaître, J.-F. et al. 2020. Sex differences in adult lifespan and aging rates of mortality across wild mammals. Proc. Natl. Acad. Sci. 117, 85468553.CrossRefGoogle ScholarPubMed
Peters, R.H. 1983. The Ecological Implications of Body Size. Cambridge University Press (doi:10.1017/CBO9780511608551).CrossRefGoogle Scholar
Calder, W.A. 1984. Size, Function, and Life History. Courier Corporation.Google Scholar
West, G.B., Brown, J.H. 2004. Life’s universal scaling laws. Phys. Today 57, 3643.CrossRefGoogle Scholar
Hofman, M.A. 1983. Energy metabolism, brain size and longevity in mammals. Q. Rev. Biol. 58, 495512.CrossRefGoogle ScholarPubMed
Piper, M.D., Skorupa, D., Partridge, L. 2005. Diet, metabolism and lifespan in Drosophila. Exp. Gerontol. 40, 857862.CrossRefGoogle ScholarPubMed
Healy, K. et al. 2014. Ecology and mode-of-life explain lifespan variation in birds and mammals. Proc. R. Soc. Lond. B Biol. Sci. 281, 20140298.Google ScholarPubMed
Gaillard, J.-M., Viallefont, A., Loison, A., Festa-Bianchet, M. 2004. Assessing senescence patterns in populations of large mammals. Anim. Biodivers. Conserv. 27, 4758.CrossRefGoogle Scholar
Fushan, A.A. et al. 2015. Gene expression defines natural changes in mammalian lifespan. Aging Cell 14, 352365.CrossRefGoogle ScholarPubMed
Haghani, A. et al. 2023. DNA methylation networks underlying mammalian traits. Science 381, eabq5693 (doi: 10.1126/science.abq5693).CrossRefGoogle ScholarPubMed
Aledo, J.C., Li, Y., de Magalhães, J.P., Ruíz-Camacho, M., Pérez-Claros, J.A. 2011. Mitochondrially encoded methionine is inversely related to longevity in mammals. Aging Cell 10, 198207.CrossRefGoogle ScholarPubMed
Lindstedt, S.L., Calder III, W.A. 1981. Body size, physiological time, and longevity of homeothermic animals. Q. Rev. Biol. 56, 116.CrossRefGoogle Scholar
West, G.B. 2017. Scale: The Universal Laws of Growth, Innovation, Sustainability, and the Pace of Life in Organisms, Cities, Economies, and Companies. Penguin Press.Google Scholar
Stearns, S.C. 1983. The influence of size and phylogeny on patterns of covariation among life-history traits in the mammals. Oikos 41, 173187.CrossRefGoogle Scholar
Gaillard, J.-M., Lemaître, J.-F., Berger, V., Bonenfant, C., Devillard, S., Douhard, M., Gamelon, M., Plard, F., Lebreton, J.-D. 2016. Life histories, axes of variation. In Encyclopedia of Evolutionary Biology (ed. Kilman, R.M.), pp. 312323. Elsevier.CrossRefGoogle Scholar
Dupoué, A., Blaimont, P., Angelier, F., Ribout, C., Rozen-Rechels, D., Richard, M., Le Galliard, J.F. 2022. Lizards from warm and declining populations are born with extremely short telomeres. Proc. Natl. Acad. Sci. 119, 2201371119.CrossRefGoogle ScholarPubMed
Shattuck, M.R., Williams, S.A. 2010. Arboreality has allowed for the evolution of increased longevity in mammals. Proc. Natl. Acad. Sci. 107, 46354639 (doi:10.1073/pnas.0911439107).CrossRefGoogle ScholarPubMed
Krementz, D.G., Sauer, J.R., Nichols, J.D. 1989. Model-based estimates of annual survival rate are preferable to observed maximum lifespan statistics for use in comparative life-history studies. Oikos 70, 203208.CrossRefGoogle Scholar
Vaupel, J.W. 2003. Post-Darwinian longevity. Popul. Dev. Rev. 29, 258269.Google Scholar
Moorad, J.A., Promislow, D.E., Flesness, N., Miller, R.A. 2012. A comparative assessment of univariate longevity measures using zoological animal records. Aging Cell 11, 940948.CrossRefGoogle ScholarPubMed
Ronget, V., Gaillard, J.-M. 2020. Assessing ageing patterns for comparative analyses of mortality curves: going beyond the use of maximum longevity. Funct. Ecol. 34, 6575.CrossRefGoogle Scholar
Péron, G., Lemaître, J.-F., Ronget, V., Tidière, M., Gaillard, J.-M. 2019. Variation in actuarial senescence does not reflect life span variation across mammals. PLoS Biol. 17, e3000432.CrossRefGoogle Scholar
de Magalhaes, J.P., Costa, J. 2009. A database of vertebrate longevity records and their relation to other life-history traits. J. Evol. Biol. 22, 17701774.CrossRefGoogle ScholarPubMed
Deevey Jr, E.S. 1947. Life tables for natural populations of animals. Q. Rev. Biol. 22, 283314.CrossRefGoogle ScholarPubMed
Caughley, G. 1966. Mortality patterns in mammals. Ecology 47, 906918.CrossRefGoogle Scholar
Spinage, C.A. 1973. A review of the age determination of mammals by means of teeth, with especial reference to Africa. Afr. J. Ecol. 11, 165187.CrossRefGoogle Scholar
Clutton-Brock, T., Sheldon, B.C. 2010. Individuals and populations: the role of long-term, individual-based studies of animals in ecology and evolutionary biology. Trends Ecol. Evol. 25, 562573.CrossRefGoogle ScholarPubMed
Gimenez, O. et al. 2008. The risk of flawed inference in evolutionary studies when detectability is less than one. Am. Nat. 172, 441448.CrossRefGoogle ScholarPubMed
Gaillard, J.-M., Ronget, V., Lemaître, J.-F., Bonenfant, C., Péron, G., Capdevila, P., Gamelon, M., Salguero-Gómez, R. 2021. Applying comparative methods to different databases: lessons from demographic analyses across mammal species. In Demographic Methods across the Tree of Life (eds Salguero-Gómez, R. and Gamelon, M.), pp. 299312. Oxford University Press.CrossRefGoogle Scholar
Nussey, D.H., Froy, H., Lemaitre, J.-F., Gaillard, J.-M., Austad, S.N. 2013. Senescence in natural populations of animals: widespread evidence and its implications for bio-gerontology. Ageing Res. Rev. 12, 214225.CrossRefGoogle ScholarPubMed
Reinke, B.A. et al. 2022. Diverse aging rates in ectothermic tetrapods provide insights for the evolution of aging and longevity. Science 376, 14591466.CrossRefGoogle ScholarPubMed
Jones, O.R. et al. 2014. Diversity of ageing across the tree of life. Nature 505, 169173.CrossRefGoogle ScholarPubMed
Ricklefs, R.E. 1998. Evolutionary theories of aging: confirmation of a fundamental prediction, with implications for the genetic basis and evolution of life span. Am. Nat. 152, 2444.CrossRefGoogle ScholarPubMed
Ricklefs, R.E., Scheuerlein, A. 2001. Comparison of aging-related mortality among birds and mammals. Exp. Gerontol. 36, 845857.CrossRefGoogle ScholarPubMed
Ricklefs, R.E. 2010. Insights from comparative analyses of aging in birds and mammals. Aging Cell 9, 273284.CrossRefGoogle ScholarPubMed
Ronget, V., Lemaître, J.-F., Tidière, M., Gaillard, J.-M. 2020. Assessing the diversity of the form of age-specific changes in adult mortality from captive mammalian populations. Diversity 12, 354.CrossRefGoogle Scholar
Kirkwood, T.B. 2015. Deciphering death: a commentary on Gompertz (1825) ‘On the nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies’. Philos. Trans. R. Soc. B Biol. Sci. 370, 20140379.CrossRefGoogle Scholar
Bronikowski, A.M. et al. 2011. Aging in the natural world: comparative data reveal similar mortality patterns across primates. Science 331, 13251328.CrossRefGoogle ScholarPubMed
Colchero, F. et al. 2021. The long lives of primates and the ‘invariant rate of ageing’ hypothesis. Nat. Commun. 12, 110.CrossRefGoogle Scholar
Williams, G.C. 1957. Pleiotropy, natural selection, and the evolution of senescence. Evolution 11, 398411.CrossRefGoogle Scholar
Hamilton, W.D. 1966. The moulding of senescence by natural selection. J. Theor. Biol. 12, 1245.CrossRefGoogle ScholarPubMed
Péron, G., Gimenez, O., Charmantier, A., Gaillard, J.-M., Crochet, P.-A. 2010. Age at the onset of senescence in birds and mammals is predicted by early-life performance. Proc. R. Soc. Lond. B Biol. Sci. 10, rspb20100530 (doi:10.1098/rspb.2010.0530).Google Scholar
Tidière, M., Gaillard, J.-M., Müller, D.W., Lackey, L.B., Gimenez, O., Clauss, M., Lemaître, J.-F. 2015. Does sexual selection shape sex differences in longevity and senescence patterns across vertebrates? A review and new insights from captive ruminants. Evolution 69, 31233140.CrossRefGoogle ScholarPubMed
Lehallier, B. et al. 2019. Undulating changes in human plasma proteome profiles across the lifespan. Nat. Med. 25, 18431850.CrossRefGoogle ScholarPubMed
Richardson, R.B., Allan, D.S., Le, Y. 2014. Greater organ involution in highly proliferative tissues associated with the early onset and acceleration of ageing in humans. Exp. Gerontol. 55, 8091.CrossRefGoogle ScholarPubMed
Ricklefs, R.E. 2000. Intrinsic aging-related mortality in birds. J. Avian Biol. 31, 103111.CrossRefGoogle Scholar
Lemaître, J.-F., Gaillard, J.-M. 2013. Polyandry has no detectable mortality cost in female mammals. PLoS ONE 8, e66670 (doi:10.1371/journal.pone.0066670).CrossRefGoogle Scholar
Ricklefs, R.E. 2010. Life-history connections to rates of aging in terrestrial vertebrates. Proc. Natl. Acad. Sci. 107, 1031410319.CrossRefGoogle ScholarPubMed
Freckleton, R.P. 2009. The seven deadly sins of comparative analysis. J. Evol. Biol. 22, 13671375.CrossRefGoogle ScholarPubMed
Ricklefs, R.E. 2010. Embryo growth rates in birds and mammals. Funct. Ecol. 24, 588596.CrossRefGoogle Scholar
Ricklefs, R.E. 2006. Embryo development and ageing in birds and mammals. Proc. R. Soc. B Biol. Sci. 273, 20772082.CrossRefGoogle ScholarPubMed
Zierer, J., Menni, C., Kastenmuller, G., Spector, T.D. 2015. Integration of ‘omics’ data in aging research: from biomarkers to systems biology. Aging Cell 14, 933944.CrossRefGoogle ScholarPubMed
Rutledge, J., Oh, H., Wyss-Coray, T. 2022. Measuring biological age using omics data. Nat. Rev. Genet. 23, 715727.CrossRefGoogle ScholarPubMed
Hoffman, J.M., Lyu, Y., Pletcher, S.D., Promislow, D.E. 2017. Proteomics and metabolomics in ageing research: from biomarkers to systems biology. Essays Biochem. 61, 379388.Google ScholarPubMed
Kirkwood, T.B.L. 2011. Systems biology of ageing and longevity. Philos. Trans. R. Soc. B 366, 6470.CrossRefGoogle ScholarPubMed
McGuire, A.L. 2020. The road ahead in genetics and genomics. Nat Rev. Genet. 21, 582596.CrossRefGoogle ScholarPubMed
Wang, B., Kumar, V., Olson, A., Ware, D. 2019. Reviving the transcriptome studies: an insight into the emergence of single-molecule transcriptome sequencing. Front. Genet. 10, 384.CrossRefGoogle ScholarPubMed
Hotaling, S., Kelley, J.L., Frandsen, P.B. 2021. Toward a genome sequence for every animal: where are we now? Proc. Natl. Acad. Sci. USA 118, 2109019118.CrossRefGoogle Scholar
Joyce, A.R., Palsson, B.O. 2006. The model organism as a system: integrating ‘omics’ data sets. Nat. Rev. Mol. Cell Biol. 7, 198210.CrossRefGoogle ScholarPubMed
Wang, Z., Gerstein, M., Snyder, M. 2009. RNA-seq: a revolutionary tool for transciptomics. Nat. Rev. Genet. 10, 5763.CrossRefGoogle Scholar
Micheel, J., Safrastyan, A., Wollny, D. 2021. Advances in non-coding RNA sequencing. Non-Coding RNA 7, 70.CrossRefGoogle ScholarPubMed
Messner, C.B., Demichev, V., Wang, Z., Hartl, J., Kustatscher, G., Mülleder, M., Ralser, M. 2023. Mass spectrometry-based high-throughput proteomics and its role in biomedical studies and systems biology. Proteomics 23, e2200013.CrossRefGoogle ScholarPubMed
Aebersold, R., Mann, M. 2016. Mass-spectrometric exploration of proteome structure and function. Nature 537, 347355.CrossRefGoogle ScholarPubMed
Wishart, D.S. 2019. Metabolomics for investigating physiological and pathophysiological processes. Physiol. Rev. 99, 18191875.CrossRefGoogle ScholarPubMed
Subramanian, I., Verma, S., Kumar, S., Jere, A., Anamika, K. 2020. Multi-omics data integration, interpretation, and its application. Bioinform. Biol. Insights 14, 124.CrossRefGoogle ScholarPubMed
Mani, D.R., Krug, K., Zhang, B., Satpathy, S., Clauser, K.R., Ding, L., Ellis, M., Gillette, M.A., Carr, S.A. 2022. Cancer proteogenomics: current impact and future prospects. Nat. Rev. Cancer 22, 298313.CrossRefGoogle ScholarPubMed
Krassowski, M., Das, V., Sahu, S.K., Misra, B.B. 2020. State of the field in multi-omics research: from computational needs to data mining and sharing. Front. Genet. 11, 610798.CrossRefGoogle ScholarPubMed
López-Otín, C., Blasco, M.A., Partridge, L., Serrano, M., Kroemer, G. 2023. Hallmarks of aging: an expanding universe. Cell 186, 243278 (doi:10.1016/j.cell.2022.11.001).CrossRefGoogle ScholarPubMed
Gomes, N.M. et al. 2011. Comparative biology of mammalian telomeres: hypotheses on ancestral states and the roles of telomeres in longevity determination. Aging Cell 10, 761768.CrossRefGoogle ScholarPubMed
Seluanov, A., Chen, Z., Hine, C., Sasahara, T.H., Ribeiro, A.A., Catania, K.C., Presgraves, D.C., Gorbunova, V. 2007. Telomerase activity coevolves with body mass not lifespan. Aging Cell 6, 4552.CrossRefGoogle Scholar
Hulbert, A.J., Pamplona, R., Buffenstein, R., Buttemer, W.A. 2007. Life and death: metabolic rate, membrane composition, and life span of animals. Physiol. Rev. 87, 11751213.CrossRefGoogle ScholarPubMed
Tobler, M., Gómez-Blanco, D., Hegemann, A., Lapa, M., Neto, J.M., Tarka, M., Xiong, Y., Hasselquist, D. 2022. Telomeres in ecology and evolution: a review and classification of hypotheses. Mol. Ecol. 31, 59465965.CrossRefGoogle ScholarPubMed
Haussmann, M.F., Vleck, C.M. 2002. Telomere length provides a new technique for aging animals. Oecologia 130, 325328.CrossRefGoogle ScholarPubMed
Lu, A.T. et al. 2021. Universal DNA methylation age across mammalian tissues. bioRxiv. www.biorxiv.org/content/10.1101/2021.01.18.426733v2.Google Scholar
Lemaître, J. et al. 2021. DNA methylation as a tool to explore ageing in wild roe deer populations. Mol. Ecol. Resour. 22. 10021015.CrossRefGoogle ScholarPubMed
Simpson, D.J., Chandra, T. 2021. Epigenetic age prediction. Aging Cell 20, e13452.CrossRefGoogle ScholarPubMed
Kristic, J. 2014. Glycans are a novel biomarker of chronological and biological ages. J Gerontol. Biol. Sci. Med. Sci. 69, 779789.CrossRefGoogle ScholarPubMed
Hertel, J. et al. 2016. Measuring biological age via metabonomics: the metabolic age score. J. Proteome Res. 15, 400410.CrossRefGoogle ScholarPubMed
van den Akker Erik, B. et al. 2020. Metabolic age based on the BBMRI-NL 1H-NMR metabolomics repository as biomarker of age-related disease. Circ. Genomic Precis. Med. 13, 541547 (doi:10.1161/CIRCGEN.119.002610).CrossRefGoogle ScholarPubMed
Robinson, O. et al. 2020. Determinants of accelerated metabolomic and epigenetic aging in a UK cohort. Aging Cell 19, e13149.CrossRefGoogle Scholar
Gaillard, Lemaître J.-F. 2020. An integrative view of senescence in nature. Funct. Ecol. 34, 416.CrossRefGoogle Scholar
Jylhava, J., Pedersen, N.L., Hagg, S. 2017. Biological age predictors. EBioMedicine 21, 2936.CrossRefGoogle ScholarPubMed
Dato, S., Piras, I.S., eds. 2022. Omics of human aging and longevity in the post genome era: from single biomarkers to systems biology approaches. Front. Genet. 13, 913531.CrossRefGoogle ScholarPubMed
Elsner, D., Meusemann, K., Korb, J. 2018. Longevity and transposon defense, the case of termite reproductives. Proc. Natl. Acad. Sci. USA 115, 55045509.CrossRefGoogle ScholarPubMed
Criscuolo, F., Sorci, G., Behaim-Delarbre, M., Zahn, S., Faivre, B., Bertile, F. 2018. Age-related response to an acute innate immune challenge in mice: proteomics reveals a telomere maintenance-related cost. Proc. R. Soc. B 285, 20181877.CrossRefGoogle Scholar
Frenk, S., Houseley, J. 2018. Gene expression hallmarks of cellular ageing. Biogerontology 19, 547566.CrossRefGoogle ScholarPubMed
Ham, S., Lee, S.V. 2020. Advances in transcriptome analysis of human brain aging. Exp. Mol. Med. 52, 17871797.CrossRefGoogle ScholarPubMed
Palmer, D., Fabris, F., Doherty, A., Freitas, A.A., Magalhaes, J.P. 2021. Ageing transcriptome meta-analysis reveals similarities and differences between key mammalian tissues. Aging 13, 33133341.CrossRefGoogle ScholarPubMed
Saitou, M., Lizardo, D.Y., Taskent, R.O., Millner, A., Gokcumen, O., Atilla-Gokcumen, G.E. 2018. An evolutionary transcriptomics approach links CD36 to membrane remodeling in replicative senescence. Mol. Omics 14, 237246.CrossRefGoogle ScholarPubMed
Srivastava, A., Barth, E., Ermolaeva, M.A., Guenther, M., Frahm, C., Marz, M., Witte, O.W. 2020. Tissue-specific gene expression changes are associated with aging in mice. Genom. Proteom. Bioinform. 18, 430442.CrossRefGoogle ScholarPubMed
Solovev, I., Shaposhnikov, M., Moskalev, A. 2020. Multi-omics approaches to human biological age estimation. Mech. Ageing Dev. 185, 111192.CrossRefGoogle ScholarPubMed
Tyshkovskiy, A. et al. 2023. Distinct longevity mechanisms across and within species and their association with aging. Cell. 186, 29292949.e20.CrossRefGoogle ScholarPubMed
Beheshti, A. 2017. A circulating microRNA signature predicts age-based development of lymphoma. PLoS ONE 12, 0170521.CrossRefGoogle ScholarPubMed
Peffers, M.J. 2016. Age-related changes in mesenchymal stem cells identified using a multi-omics approach. Eur. Cell Mater. 31, 136159.CrossRefGoogle ScholarPubMed
Griffiths, H.R. et al. 2015. Novel ageing-biomarker discovery using data-intensive technologies. Mech. Ageing Dev. 151, 114121.CrossRefGoogle ScholarPubMed
Lemaître, J.-F., Garratt, M., Gaillard, J.-M. 2020. Going beyond lifespan in comparative biology of aging. Adv. Geriatr. Med. Res. 2. e200011.Google Scholar
Gelfi, C. et al. 2006. The human muscle proteome in aging. J. Proteome Res. 5, 13441353.CrossRefGoogle ScholarPubMed
Chakrabarti, A., Mukhopadhyay, D. 2012. Brain senescence-omics. J. Protein Proteomics 3, 1529.Google Scholar
Tanaka, T. et al. 2018. Plasma proteomic signature of age in healthy humans. Aging Cell 17, e12799.CrossRefGoogle ScholarPubMed
Enroth, S., Enroth, S.B., Johansson, A., Gyllensten, U. 2015. Protein profiling reveals consequences of lifestyle choices on predicted biological aging. Sci. Rep. 5, 17282.CrossRefGoogle ScholarPubMed
Menni, C. et al. 2015. Circulating proteomic signatures of chronological age. J. Gerontol. Ser. Biomed. Sci. Med. Sci. 70, 809816.Google ScholarPubMed
Vanhooren, V., Santos, A.N., Voutetakis, K., Petropoulos, I., Libert, C., Simm, A., Gonos, E.S., Friguet, B. 2015. Protein modification and maintenance systems as biomarkers of ageing. Mech. Ageing Dev. 151, 7184.CrossRefGoogle ScholarPubMed
Plumel, M.I., Benhaim-Delarbre, M., Rompais, M., Thiersé, D., Sorci, G., van Dorsselaer, A., Criscuolo, F., Bertile, F. 2016. Differential proteomics reveals age-dependent liver oxidative costs of innate immune activation in mice. J. Proteomics 135, 181190.CrossRefGoogle ScholarPubMed
Walker, K.A., Basisty, N., Wilson III, D.M., Ferrucci, L. 2022. Connecting aging biology and inflammation in the omics era. J. Clin. Invest. 132, e158448.CrossRefGoogle ScholarPubMed
Chan, M. et al. 2022. Novel insights from a multiomics dissection of the Hayflick limit. eLife 11, e70283.CrossRefGoogle ScholarPubMed
Sturm, G. et al. 2022. A multi-omics longitudinal aging dataset in primary human fibroblasts with mitochondrial perturbations. Sci. Data 9, 751.CrossRefGoogle ScholarPubMed
Song, Q. et al. 2022. Integrated multi-omics approach revealed cellular senescence landscape. Nucleic Acids Res. 50, 1094710963.CrossRefGoogle ScholarPubMed
MacRae, S.L. et al. 2015. DNA repair in species with extreme lifespan differences. Aging 7, 1171.CrossRefGoogle ScholarPubMed
Verma, A., Verma, M., Singh, A. 2020. Animal tissue culture principles and applications. In Animal Biotechnology, pp. 269–293. Academic Press.Google Scholar
Bermejo, M., Rodríguez-Teijeiro, J.D., Illera, G., Barroso, A., Vilà, C., Walsh, P.D. 2006. Ebola outbreak killed 5000 gorillas. Science 314, 15641564.CrossRefGoogle ScholarPubMed
Gaillard, J.-M., Lemaître, J.-F. 2017. The Williams’ legacy: a critical reappraisal of his nine predictions about the evolution of senescence. Evolution 71, 27682785 (doi:10.1111/evo.13379).CrossRefGoogle ScholarPubMed
Cohen, A.A., Coste, C.F., Li, X.-Y., Bourg, S., Pavard, S. 2020. Are trade-offs really the key drivers of ageing and life span? Funct. Ecol. 34, 153166.CrossRefGoogle Scholar
Moorad, J.A., Ravindran, S. 2022. Natural selection and the evolution of asynchronous aging. Am. Nat. 199, 551563.CrossRefGoogle ScholarPubMed
Vincze, O. et al. 2022. Cancer risk across mammals. Nature 601, 15.Google ScholarPubMed
Gorbunova, V., Seluanov, A., Kennedy, B.K. 2020. The world goes bats: living longer and tolerating viruses. Cell Metab. 32, 3143.CrossRefGoogle ScholarPubMed
Gorbunova, V., Seluanov, A., Zhang, Z., Gladyshev, V.N., Vijg, J. 2014. Comparative genetics of longevity and cancer: insights from long-lived rodents. Nat. Rev. Genet. 15, 531.CrossRefGoogle ScholarPubMed
Abegglen, L.M. et al. 2015. Potential mechanisms for cancer resistance in elephants and comparative cellular response to DNA damage in humans. JAMA 314, 18501860.CrossRefGoogle ScholarPubMed
Tian, X., Seluanov, A., Gorbunova, V. 2017. Molecular mechanisms determining lifespan in short- and long-lived species. Trends Endocrinol. Metab. 28, 722734 (doi:10.1016/j.tem.2017.07.004).CrossRefGoogle Scholar
Farré, X. et al. 2021. Comparative analysis of mammal genomes unveils key genomic variability for human life span. Mol. Biol. Evol. 38, 49484961.CrossRefGoogle ScholarPubMed
Singh, P.P., Demmitt, B.A., Nath, R.D., Brunet, A. 2019. The genetics of aging: a vertebrate perspective. Cell 177, 200220.CrossRefGoogle ScholarPubMed
Dato, S., Crocco, P., Migliore, N.R., Lescai, F. 2021. Omics in a digital world: the role of bioinformatics in providing new insights into human aging. Front Genet. 12, 689824.CrossRefGoogle Scholar
Ma, S., Gladyshev, V.N. 2017. Molecular signatures of longevity: insights from cross-species comparative studies. Semin Cell Dev Biol 70, 190203.Google Scholar
Seluanov, A., Gladyshev, V.N., Vijg, J., Gorbunova, V. 2018. Mechanisms of cancer resistance in long-lived mammals. Nat. Rev. Cancer 18, 433441.CrossRefGoogle ScholarPubMed
Ujvari, B. et al. 2022. Telomeres, the loop tying cancer to organismal life-histories. Mol. Ecol. 31, 62736285.CrossRefGoogle ScholarPubMed
He, S., Sharpless, N.E. 2017. Senescence in health and disease. Cell 169, 10001011.CrossRefGoogle ScholarPubMed
Bieuville, M., Tissot, T., Robert, A., Henry, P.-Y., Pavard, S. 2023. Modeling of senescent cell dynamics predicts a late-life decrease in cancer incidence. Evol. Appl. 16, 609624.CrossRefGoogle ScholarPubMed
Ma, S. et al. 2015. Organization of the mammalian metabolome according to organ function, lineage specialization, and longevity. Cell Metab. 22, 332343.CrossRefGoogle ScholarPubMed
Prado, N.A. et al. 2021. Epigenetic clock and methylation studies in elephants. Aging Cell 20, e13414.CrossRefGoogle ScholarPubMed
Ruby, J.G., Smith, M., Buffenstein, R. 2018. Naked mole-rat mortality rates defy Gompertzian laws by not increasing with age. eLife 7, e31157.CrossRefGoogle Scholar
Garratt, M., Erturk, I., Alonzo, R., Zufall, F., Leinders-Zufall, T., Pletcher, S.D., Miller, R.A. 2022. Lifespan extension in female mice by early, transient exposure to adult female olfactory cues. eLife 11, e84060.CrossRefGoogle ScholarPubMed
Zhuang, J. 2019. Comparison of multi-tissue aging between human and mouse. Sci. Rep. 9, 6220.CrossRefGoogle ScholarPubMed
Yang, J. et al. 2015. Synchronized age-related gene expression changes across multiple tissues in human and the link to complex diseases. Sci. Rep. 5, 15145.CrossRefGoogle ScholarPubMed
Aramillo Irizar, P. et al. 2018. Transcriptomic alterations during ageing reflect the shift from cancer to degenerative diseases in the elderly. Nat. Commun. 9, 327.CrossRefGoogle ScholarPubMed
Beheshti, A., Vanderburg, C., McDonald, J.T., Ramkumar, C., Kadungure, T., Zhang, H., Gartenhaus, R.B., Evens, A.M. 2017. A circulating microRNA signature predicts age-based development of lymphoma. PloS ONE 12, e0170521.CrossRefGoogle ScholarPubMed
Caliskan, A., Crouch, S.A.W., Giddins, S., Dandekar, T., Dangwal, S. 2022. Progeria and aging-omics based comparative analysis. Biomedicines 10. 2440.CrossRefGoogle ScholarPubMed
Vialle, R.A., Paiva Lopes, K., Bennett, D.A., Crary, J.F., Raj, T. 2022. Integrating whole-genome sequencing with multi-omic data reveals the impact of structural variants on gene regulation in the human brain. Nat. Neurosci. 25, 504514.CrossRefGoogle ScholarPubMed
Lemaître, J.-F., Ronget, V., Gaillard, J.-M. 2020. Female reproductive senescence across mammals: a high diversity of patterns modulated by life history and mating traits. Mech. Ageing Dev. 192, 111377.CrossRefGoogle ScholarPubMed

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×