Voluntary exercise normalizes the proteomic landscape in muscle and brain and improves the phenotype of progeroid mice
Open accessAbstract
The accumulation of mitochondrial DNA (mtDNA) mutations is a suspected driver of aging and age‐related diseases, but forestalling these changes has been a major challenge. One of the best‐studied models is the prematurely aging mtDNA mutator mouse, which carries a homozygous knock‐in of a proofreading deficient version of the catalytic subunit of mtDNA polymerase‐γ (PolgA). We investigated how voluntary exercise affects the progression of aging phenotypes in this mouse, focusing on mitochondrial and protein homeostasis in both brain and peripheral tissues. Voluntary exercise significantly ameliorated several aspects of the premature aging phenotype, including decreased locomotor activity, alopecia, and kyphosis, but did not have major effects on the decreased lifespan of mtDNA mutator mice. Exercise also decreased the mtDNA mutation load. In‐depth tissue proteomics revealed that exercise normalized the levels of about half the proteins, with the majority involved in mitochondrial function and nuclear–mitochondrial crosstalk. There was also a specific increase in the nuclear‐encoded proteins needed for the tricarboxylic acid cycle and complex II, but not in mitochondrial‐encoded oxidative phosphorylation proteins, as well as normalization of enzymes involved in coenzyme Q biosynthesis. Furthermore, we found tissue‐specific alterations, with brain coping better as compared to muscle and with motor cortex being better protected than striatum, in response to mitochondrial dysfunction. We conclude that voluntary exercise counteracts aging in mtDNA mutator mice by counteracting protein dysregulation in muscle and brain, decreasing the mtDNA mutation burden in muscle, and delaying overt aging phenotypes.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
Daily voluntary exercise ameliorates progeroid mouse phenotypes and deregulated proteomic profiles in muscle and brain in mtDNA mutator mice.
“Daily voluntary exercise also ameliorates progeroid mouse phenotypes, such as locomotor activity, alopecia and kyphosis, and the deregulated proteomic profiles in muscle and brain in mtDNA mutator mice216.”
From Mitochondrial and metabolic dysfunction in ageing and age-related diseases (2022) · cites this paper as [216]
Thirty weeks of voluntary wheel running in mtDNA mutator mice from 10 wk of age reduced mtDNA mutations and features of accelerated aging in skeletal muscle, heart, and brain.
“Impressively, 30 wk of voluntary wheel running in mtDNA mutator mice (mice with defective mtDNA polymerase, PolgA) from 10 wk of age reduced mtDNA mutations and features of accelerated aging in skeletal muscle, heart, and brain (24).”
From Exercise Counters the Age-Related Accumulation of Senescent Cells (2022) · cites this paper as [24]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
2 retracted
Safdar, A., Bourgeois, J. M., Ogborn, D. I., Little, J. P., Hettinga, B. P., Akhtar, M., Thompson, J. E., Melov, S., Mocellin, N. J., Kujoth, G. C., et al. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1019581108 · Cited by 358 · see citing works
RetractedRETRACTED ARTICLE:Exercise-induced mitochondrial p53 repairs mtDNA mutations in mutator mice
Safdar, A., Khrapko, K., Flynn, J. M., Saleem, A., Lisio, M. D., Johnston, A. P. W., Kratysberg, Y., Samjoo, I. A., Kitaoka, Y., Ogborn, D. I., et al. (2015) · Skeletal Muscle · doi:10.1186/s13395-016-0075-9 · Cited by 66 · see citing works
RetractedCytoscape: A software Environment for integrated models of biomolecular interaction networks
Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., Amin, N., Schwikowski, B., & Ideker, T. (2003) · Genome Research · doi:10.1101/gr.1239303 · Cited by 51,888 · see citing works
Gene Ontology: tool for the unification of biology
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206 · see citing works
STRING v10: protein–protein interaction networks, integrated over the tree of life
Szklarczyk, D., Franceschini, A., Wyder, S., Forslund, K., Heller, D., Huerta-Cepas, J., Simonovic, M., Roth, A., Santos, A., Tsafou, K. P., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gku1003 · Cited by 10,436 · see citing works
Universal sample preparation method for proteome analysis
Wiśniewski, J. R., Zougman, A., Nagaraj, N., & Mann, M. (2009) · Nature Methods · doi:10.1038/nmeth.1322 · Cited by 8,352 · see citing works
The Gene Ontology Resource: 20 years and still GOing strong
The Gene Ontology Consortium (2019) · Nucleic Acids Research · doi:10.1093/nar/gky1055 · Cited by 4,747 · see citing works
Premature ageing in mice expressing defective mitochondrial DNA polymerase
Trifunovic, A., Wredenberg, A., Falkenberg, M., Spelbrink, J. N., Rovio, A. T., Bruder, C. E., Bohlooly-Y, M., Gidlöf, S., Oldfors, A., Wibom, R., et al. (2004) · Nature · doi:10.1038/nature02517 · Cited by 2,734 · see citing works
Mitochondrial DNA mutations, oxidative stress, and apoptosis in mammalian aging
Kujoth, G. C., Hiona, A., Pugh, T. D., Someya, S., Panzer, K., Wohlgemuth, S. E., Hofer, T., Seo, A. Y., Sullivan, R., Jobling, W. A., et al. (2005) · Science · doi:10.1126/science.1112125 · Cited by 2,165 · see citing works
WEB-based GEne SeT AnaLysis Toolkit (WebGestalt): update 2013
Wang, J., Duncan, D. T., Shi, Z., & Zhang, B. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt439 · Cited by 1,502 · see citing works
Long-term health benefits of physical activity – a systematic review of longitudinal studies
Reiner, M., Niermann, C. Y. N., Jekauc, D., & Wöll, A. (2013) · BMC Public Health · doi:10.1186/1471-2458-13-813 · Cited by 1,475 · see citing works
Mammalian Mitochondria and Aging: An Update
Kauppila, T. E. S., Kauppila, J. H. K., & Larsson, N.-G. (2017) · Cell Metabolism · doi:10.1016/j.cmet.2016.09.017 · Cited by 578 · see citing works
A Scalable Approach for Protein False Discovery Rate Estimation in Large Proteomic Data Sets
Savitski, M. M., Wilhelm, M., Hahne, H., Küster, B., & Bantscheff, M. (2015) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m114.046995 · Cited by 436 · see citing works
The Role of Skeletal Muscle Glycogen Breakdown for Regulation of Insulin Sensitivity by Exercise
Jensen, J., Rustad, P. I., Kolnes, A. J., & Lai, Y.-C. (2011) · Frontiers in Physiology · doi:10.3389/fphys.2011.00112 · Cited by 412 · see citing works
Germline mitochondrial DNA mutations aggravate ageing and can impair brain development
Ross, J. M., Stewart, J. B., Hagström, E., Brené, S., Mourier, A., Coppotelli, G., Freyer, C., Lagouge, M., Hoffer, B. J., Olson, L., et al. (2013) · Nature · doi:10.1038/nature12474 · Cited by 273 · see citing works
Self-citationReduced mitochondrial DNA copy number is a biomarker of Parkinson's disease
Pyle, A., Anugrha, H., Kurzawa‐Akanbi, M., Yarnall, A. J., Burn, D. J., & Hudson, G. (2015) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2015.10.033 · Cited by 258 · see citing works
Kühl, I., Miranda, M., Atanassov, I., Kuznetsova, I., Hinze, Y., Mourier, A., Filipovska, A., & Larsson, N. (2017) · eLife · doi:10.7554/elife.30952 · Cited by 251 · see citing works
Ahlqvist, K. J., Hämäläinen, R. H., Yatsuga, S., Uutela, M., Terzioglu, M., Götz, A., Forsström, S., Salvén, P., Angers‐Loustau, A., Kopra, O., et al. (2012) · Cell Metabolism · doi:10.1016/j.cmet.2011.11.012 · Cited by 240 · see citing works
Synaptic markers of cognitive decline in neurodegenerative diseases: a proteomic approach
Bereczki, E., Branca, R. M., Francis, P. T., Pereira, J. B., Baek, J.-H., Hortobágyi, T., Winblad, B., Ballard, C., Lehtiö, J., & Aarsland, D. (2018) · Brain · doi:10.1093/brain/awx352 · Cited by 220 · see citing works
Self-citationIncreased Susceptibility of Striatal Mitochondria to Calcium-Induced Permeability Transition
Brustovetsky, N., Brustovetsky, T., Purl, K. J., Capano, M., Crompton, M., & Dubinsky, J. M. (2003) · Journal of Neuroscience · doi:10.1523/jneurosci.23-12-04858.2003 · Cited by 176 · see citing works
Increased Total mtDNA Copy Number Cures Male Infertility Despite Unaltered mtDNA Mutation Load
Jiang, M., Kauppila, T. E. S., Motori, E., Li, X., Atanassov, I., Folz‐Donahue, K., Bonekamp, N. A., Albarran-Gutierrez, S., Stewart, J. B., & Larsson, N. (2017) · Cell Metabolism · doi:10.1016/j.cmet.2017.07.003 · Cited by 144 · see citing works
Pickrell, A. M., Pinto, M., Hida, A., & Moraes, C. T. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.4871-11.2011 · Cited by 120 · see citing works
Sasaki, H., Hattori, Y., Ikeda, Y., Kamagata, M., Iwami, S., Yasuda, S., Tahara, Y., & Shibata, S. (2016) · Scientific Reports · doi:10.1038/srep27607 · Cited by 104 · see citing works
Sandberg, A., Lindell, G., Källström, B. N., Branca, R. M., Gemzell‐Danielsson, K., Dahlberg, M., Larson, B., Forshed, J., & Lehtiö, J. (2012) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m112.016998 · Cited by 99 · see citing works
Self-citationIncreased mitochondrial biogenesis in muscle improves aging phenotypes in the mtDNA mutator mouse
Dillon, L. M., Williams, S. L., Hida, A., Peacock, J. D., Prolla, T. A., Lincoln, J., & Moraes, C. T. (2012) · Human Molecular Genetics · doi:10.1093/hmg/dds049 · Cited by 98 · see citing works
Shabalina, I. G., Vyssokikh, M. Y., Gibanova, N. V., Csikasz, R. I., Edgar, D., Waldemarson, A. H., Rozhdestvenskaya, Z., Bakeeva, L. E., Vays, V. B., Pustovidko, A. V., et al. (2017) · Aging · doi:10.18632/aging.101174 · Cited by 96 · see citing works
Ross, J. M. (2011) · Journal of Visualized Experiments · doi:10.3791/3266 · Cited by 81 · see citing works
Self-citationMemon, A. A., Zöller, B., Hedelius, A., Wang, X., Stenman, E., Sundquist, J., & Sundquist, K. (2017) · Biomolecular Detection and Quantification · doi:10.1016/j.bdq.2017.08.001 · Cited by 78 · see citing works
Huang, J., Tan, L., Shen, R., Zhang, L., Zuo, H., & Wang, D. W. (2016) · Medicine · doi:10.1097/md.0000000000003323 · Cited by 68 · see citing works
High-fat diet and FGF21 cooperatively promote aerobic thermogenesis in mtDNA mutator mice
Wall, C. E., Whyte, J., Suh, J. M., Fan, W., Collins, B. L., Liddle, C., Yu, R. T., Atkins, A. R., Naviaux, J. C., Li, K., et al. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1509930112 · Cited by 61 · see citing works
Significance analysis of microarray for relative quantitation of LC/MS data in proteomics
Roxas, B. P., & Li, Q. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-187 · Cited by 58 · see citing works
McMullan, R., Kelly, S. A., Hua, K., Buckley, B. K., Faber, J., de Villena, F. P.-M., & Pomp, D. (2016) · Physiological Reports · doi:10.14814/phy2.13011 · Cited by 54 · see citing works
Maternally transmitted mitochondrial DNA mutations can reduce lifespan
Ross, J. M., Coppotelli, G., Hoffer, B. J., & Olson, L. (2014) · Scientific Reports · doi:10.1038/srep06569 · Cited by 53 · see citing works
Self-citationFox, R. G., Magness, S. T., Kujoth, G. C., Prolla, T. A., & Maeda, N. (2012) · American Journal of Physiology-Gastrointestinal and Liver Physiology · doi:10.1152/ajpgi.00402.2011 · Cited by 49 · see citing works
Oliveira, J. M. A., & Gonçalves, J. (2008) · Journal of Biological Chemistry · doi:10.1074/jbc.m807459200 · Cited by 45 · see citing works
Metabolomic analysis of exercise effects in the POLG mitochondrial DNA mutator mouse brain
Clark, J., Saleem, A., Dai, Y., Shurubor, Y. I., Ma, X., Safdar, A., Beal, M. F., Tarnopolsky, M. A., & Simon, D. K. (2015) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2015.07.020 · Cited by 40 · see citing works
Effects of calorie restriction on the lifespan and healthspan of POLG mitochondrial mutator mice
Someya, S., Kujoth, G. C., Kim, M., Hacker, T. A., Vermulst, M., Weindruch, R. H., & Prolla, T. A. (2017) · PLoS ONE · doi:10.1371/journal.pone.0171159 · Cited by 21 · see citing works
Chen, Y., Hsieh, T.-H., Kuo, T., Kao, J., Ma, K., Huang, E. Y., Chou, Y., Olson, L., & Hoffer, B. J. (2019) · Journal of Neurochemistry · doi:10.1111/jnc.14702 · Cited by 13 · see citing works
Self-citationSuwa, M., Ishioka, T., Kato, J., Komaita, J., Imoto, T., Kida, A., & Yokochi, T. (2016) · International Journal of Sports Medicine · doi:10.1055/s-0042-101412 · Cited by 6 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Mitochondrial and metabolic dysfunction in ageing and age-related diseases
Amorim, J. A., Coppotelli, G., Rolo, A. P., Palmeira, C. M., Ross, J. M., & Sinclair, D. A. (2022) · Nature Reviews Endocrinology · doi:10.1038/s41574-021-00626-7 · Cited by 990 · see citing works
Self-citationRoberts, M. D., McCarthy, J. J., Hornberger, T. A., Phillips, S. M., Mackey, A. L., Nader, G. A., Boppart, M. D., Kavazis, A. N., Reidy, P. T., Ogasawara, R., et al. (2023) · Physiological Reviews · doi:10.1152/physrev.00039.2022 · Cited by 214 · see citing works
Mitochondrial Dysfunction: A Key Player in Brain Aging and Diseases
Bartman, S., Coppotelli, G., & Ross, J. M. (2024) · Current Issues in Molecular Biology · doi:10.3390/cimb46030130 · Cited by 101 · see citing works
Self-citationAgeing in the brain: mechanisms and rejuvenating strategies
Gaspar-Silva, F., Trigo, D., & Magalhães, J. (2023) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-023-04832-6 · Cited by 64 · see citing works
Exercise Counters the Age-Related Accumulation of Senescent Cells
Zhang, X., Englund, D. A., Aversa, Z., Jachim, S. K., White, T. A., & LeBrasseur, N. K. (2022) · Exercise and Sport Sciences Reviews · doi:10.1249/jes.0000000000000302 · Cited by 63 · see citing works
McLaughlin, K., Kew, K. A., McClung, J. M., & Fisher‐Wellman, K. H. (2020) · Scientific Reports · doi:10.1038/s41598-020-60536-y · Cited by 38 · see citing works
PFKFB3-mediated glycolysis rescues myopathic outcomes in the ischemic limb
RYAN, T. E., Schmidt, C. A., Tarpey, M. D., Amorese, A. J., Yamaguchi, D. J., Goldberg, E. J., Iñigo, M. R., Karnekar, R. R., O’Rourke, A. R., Ervasti, J. M., et al. (2020) · JCI Insight · doi:10.1172/jci.insight.139628 · Cited by 37 · see citing works
Secondary CoQ10 deficiency, bioenergetics unbalance in disease and aging
Navas, P., Cascajo, M. V., Alcázar‐Fabra, M., Hernández‐Camacho, J. D., Sánchez‐Cuesta, A., Cortés-Rodríguez, A. B., Ballesteros‐Simarro, M., Arroyo‐Luque, A., Rodríguez‐Aguilera, J. C., Fernández‐Ayala, D. J. M., et al. (2021) · BioFactors · doi:10.1002/biof.1733 · Cited by 37 · see citing works
Yilmaz, D., Mathavan, N., Wehrle, E., Kuhn, G. A., & Müller, R. (2023) · Ageing Research Reviews · doi:10.1016/j.arr.2023.102118 · Cited by 34 · see citing works
Hallmarks of frailty and osteosarcopenia in prematurely aged PolgA (D257A/D257A) mice
Scheuren, A. C., D’Hulst, G., Kuhn, G. A., Masschelein, E., Wehrle, E., Bock, K. D., & Müller, R. (2020) · Journal of Cachexia Sarcopenia and Muscle · doi:10.1002/jcsm.12588 · Cited by 29 · see citing works
SESN1 is a FOXO3 effector that counteracts human skeletal muscle ageing
Jing, Y., Zuo, Y., Sun, L., Yu, Z., Ma, S., Hu, H., Zhao, Q., Huang, D., Zhang, W., Belmonte, J. C. I., et al. (2023) · Cell Proliferation · doi:10.1111/cpr.13455 · Cited by 25 · see citing works
Lim, E. W., Handzlik, M. K., Trefts, E., Gengatharan, J. M., Pondevida, C. M., Shaw, R. J., & Metallo, C. M. (2021) · Science Advances · doi:10.1126/sciadv.abj4077 · Cited by 20 · see citing works
Principles of brain aging: Status and challenges of modeling human molecular changes in mice
Kluever, V., & Fornasiero, E. F. (2021) · Ageing Research Reviews · doi:10.1016/j.arr.2021.101465 · Cited by 18 · see citing works
The impact of COVID-19 on accelerating of immunosenescence and brain aging
Müller, L., & Benedetto, S. D. (2024) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2024.1471192 · Cited by 19 · see citing works
Lee, M. J.-C., Saner, N. J., Ferri, A., García-Domínguez, E., Broatch, J. R., & Bishop, D. J. (2024) · Molecular Aspects of Medicine · doi:10.1016/j.mam.2024.101272 · Cited by 16 · see citing works
Shafqat, A., Masters, M. C., Tripathi, U., Tchkonia, T., Kirkland, J. L., & Hashmi, S. K. (2024) · Ageing Research Reviews · doi:10.1016/j.arr.2024.102400 · Cited by 15 · see citing works
RNA‐Based Therapies for Neurodegenerative Diseases Targeting Pathogenic Proteins
Rabbani, S. A., El‐Tanani, M., Sharma, S., El‐Tanani, Y., Kumar, R., Saini, M., Yadav, M., Khan, M. A., & Parvez, S. (2025) · European Journal of Neuroscience · doi:10.1111/ejn.70110 · Cited by 15 · see citing works
Mitochondrial DNA alterations in precision oncology: Emerging roles in diagnostics and therapeutics
Carrasco, A. G. M., Chammas, R. J., & Furuya, T. K. (2025) · Clinics · doi:10.1016/j.clinsp.2024.100570 · Cited by 13 · see citing works
Strength exercise reduces hepatic pyruvate carboxylase and gluconeogenesis in DIO mice
Pereira, R. M., Rodrigues, K. C. D. C., Sant’Ana, M. R., Peruca, G. F., Morelli, A. P., Simabuco, F. M., da Silva, A. S. R., Cintra, D. E., Ropelle, E. R., Pauli, J. R., et al. (2020) · Journal of Endocrinology · doi:10.1530/joe-20-0193 · Cited by 13 · see citing works
Peng, T., Xiang, J., Tian, Y., Tang, X., Wang, L., Gao, L., Luo, O. J., Huang, L., & Chen, G. (2025) · Experimental Gerontology · doi:10.1016/j.exger.2025.112686 · Cited by 13 · see citing works
Chermside‐Scabbo, C. J., Shuster, J. T., Erdmann-Gilmore, P., Tycksen, E., Zhang, Q., Townsend, R. R., & Silva, M. J. (2024) · Aging · doi:10.18632/aging.206131 · Cited by 10 · see citing works
The mtDNA mutation spectrum in the PolG mutator mouse reveals germline and somatic selection
Maclaine, K. D., Stebbings, K. A., Llano, D. A., & Havird, J. C. (2021) · BMC Genomic Data · doi:10.1186/s12863-021-01005-x · Cited by 10 · see citing works
Maclaine, K. D., Stebbings, K. A., Llano, D. A., & Rhodes, J. S. (2020) · PLoS ONE · doi:10.1371/journal.pone.0226860 · Cited by 10 · see citing works
Exercise attenuates the hallmarks of aging: Novel perspectives
Qiu, Y., Fernández‐Garcia, B., Lehmann, H. I., Li, G., Kroemer, G., López-Otı́n, C., & Xiao, J. (2025) · Journal of sport and health science/Journal of Sport and Health Science · doi:10.1016/j.jshs.2025.101108 · Cited by 15 · see citing works
Vujosevic, S., Limoli, C., & Kozak, I. (2024) · Eye · doi:10.1038/s41433-024-03341-5 · Cited by 9 · see citing works
la Torre, M. F.-D., Fiuza‐Luces, C., Valenzuela, P. L., Laine-Menéndez, S., Arenas, J., Martín, M. A., Turnbull, D. M., Lucía, A., & Morán, M. (2020) · Frontiers in Physiology · doi:10.3389/fphys.2020.594223 · Cited by 9 · see citing works
Modeling aging and retinal degeneration with mitochondrial DNA mutation burden
Sturgis, J., Singh, R., Caron, Q. R., Samuels, I. S., Shiju, T. M., Mukkara, A., Freedman, P., & Bonilha, V. L. (2024) · Aging Cell · doi:10.1111/acel.14282 · Cited by 8 · see citing works
Pinker, S. A., & Ullman, M. T. (2002) · Cited by 8 · see citing works
Mrohs, D., Rybarski, M. O., Andriske, M., Bohne, P., Mark, M. D., Lübbert, H., & Zhu, X. (2023) · Aging Pathobiology and Therapeutics · doi:10.31491/apt.2023.03.106 · Cited by 6 · see citing works
Impacto do tempo de hospitalização na mobilidade e na qualidade de vida de idosos
Miranda, G. B. S., Borges, N. G. S., & Ribeiro, N. M. D. S. (2019) · Revista de Ciências Médicas e Biológicas · doi:10.9771/cmbio.v18i3.34417 · Cited by 5 · see citing works
Chrono-Exercise Medicine: Why Biological Timing Matters for Human Health
Hesketh, S. J. (2026) · Biomedicines · doi:10.3390/biomedicines14071601 · Cited by 2 · see citing works
Tobias-Wallingford, H., Bartman, S., Gaspar, L., Gallagher, B., Bassa, C., Sotirakis, E., Dubus, V., Hemme, C., Olson, L., Coppotelli, G., et al. (2025) · Innovation in Aging · doi:10.1093/geroni/igaf122.534 · Cited by 2 · see citing works
Self-citationLaine-Menéndez, S., la Torre, M. F.-D., Fiuza‐Luces, C., Delmiro, A., Arenas, J., Martín, M. A., Boya, P., Lucía, A., & Morán, M. (2022) · Antioxidants · doi:10.3390/antiox11030510 · Cited by 2 · see citing works
Chen, X., Xie, J., Lu, F.-C., Li, Q., Qiu, G., & Liang, C. (2025) · Lara D. Veeken · doi:10.1093/rheumatology/keaf600 · Cited by 1 · see citing works
Exercise-Mediated Autophagy and Brain Aging
Kou, X., Zhang, H., Guo, Y. L., Kirberger, M., & Chen, N. (2021) · Springer eBooks · doi:10.1007/978-981-16-4525-9_6 · Cited by 1 · see citing works
Multi-omic analysis of the aging mouse brain
Kluever, V. (2021) · doi:10.53846/goediss-9022
Ross, J. M., Kim, A., Berthod, K., Branca, R. M., Olin, M., Pichardo‐Casas, I., Lehtiö, J., Björkhem, I., Sinclair, D. A., Olson, L., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.04.25.650453
Self-citationThe longevity effects of reduced IGF-1 signaling depend on the stability of the mitochondrial genome
Shemtov, S. J., McGann, E. G., Carrillo, L., Lee, S.-M., Anson, H., Hwang, E., Chung, C. S., Weinert, J. L., Anagnostou, M., Lai, G.-J. D., et al. (2026) · Science Advances · doi:10.1126/sciadv.aea4279
Martin, I., Flickinger, J., Rahaman, I., Sarna, T., Ballance, E., Ginelli, N., Peterson, J. T., Uryash, A., Adams, J. A., Xiao, R., et al. (2026) · BMC Medicine · doi:10.1186/s12916-026-04944-3
Bao-Sheng, W. A. N. G., & Ben, Z. H. O. U. (2026) · Shengming kexue · doi:10.3724/cbls.2026103
Exercise-induced mitochondrial remodeling in energy-demanding organs during aging
Zhou, Z., Gao, J., Wang, M., & Zhang, H. (2026) · iScience · doi:10.1016/j.isci.2026.116791
- Authors
- Ross, J. M., Coppotelli, G., Branca, R. M., Kim, K. M., Lehtiö, J., Sinclair, D. A., & Olson, L.
- Affiliations
- Harvard University (US)
- Science for Life Laboratory (SE)
- Karolinska Institutet (SE)
- Corresponding author
- Ross, Jaime M.
- Coppotelli, Giuseppe
- Venue
- Aging Cell
- Publisher
- Wiley
- Published
- 2019-09-06
- Volume
- 18
- Issue
- 6
- Pages
- e13029-e13029
- ISSN
- 1474-9718 (ISSN-L)
- 1474-9726
- PMC
- PMC6826127
- OpenAlex
- W2972213850
- Cited by
- 41
- References
- 39
- Citations by year
- 2026: 5 · 2025: 7 · 2024: 7 · 2023: 5 · 2022: 3 · 2021: 6 · 2020: 6 · 2019: 1
- FWCI
- 1.46
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Aging Cell (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- National Institute on Aging (K99AG055683)
- Radiumhemmets Forskningsfonder
- Stiftelsen för Strategisk Forskning
- Barncancerfonden
- Swedish Brain Power
- Hjärnfonden
- Konung Gustaf V:s och Drottning Victorias Frimurarestiftelse
- Loo och Hans Ostermans Stiftelse för Medicinsk Forskning
- FP7 Ideas: European Research Council (322744)
- Svenska Sällskapet för Medicinsk Forskning
- Karolinska Institutet
- Vetenskapsrådet (537‐2014‐6856, 2015‐04622, K2012‐62X‐03185‐42‐4)
- Cancerfonden
- Lundbeckfonden
- Glenn Foundation for Medical Research
- National Institutes of Health (R37AG028730, R01DK100263)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Mitochondrial Function and Pathology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Muscle Physiology and Disorders
- Keywords
- voluntary exercise, premature aging, mitochondrial DNA mutations, mitochondrial dysfunction, proteostasis, tissue proteomics, nuclear-mitochondrial crosstalk, TCA cycle, coenzyme Q biosynthesis, motor cortex, striatum, brain aging, muscle aging, aging phenotypes
- MeSH terms
- Animals, Brain, DNA, Mitochondrial, Female, Male, Mice, Mutant Strains, Mutation, Phenotype, Physical Conditioning, Animal, Muscle, Skeletal, Proteomics, 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
