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Aging Research Using Mouse Models
Open accessAbstract
Despite the dramatic increase in human lifespan over the past century, there remains pronounced variability in “health‐span,” or the period of time in which one is generally healthy and free of disease. Much of the variability in health‐span and lifespan is thought to be genetic in origin. Understanding the genetic mechanisms of aging and identifying ways to boost longevity is a primary goal in aging research. Here, we describe a pipeline of phenotypic assays for assessing mouse models of aging. This pipeline includes behavior/cognition testing, body composition analysis, and tests of kidney function, hematopoiesis, and immune function, as well as physical parameters. We also describe study design methods for assessing lifespan and health‐span, and other important considerations when conducting aging research in the laboratory mouse. The tools and assays provided can assist researchers with understanding the correlative relationships between age‐associated phenotypes and, ultimately, the role of specific genes in the aging process. © 2015 by John Wiley & Sons, Inc.
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“As mice age, they undergo characteristic physical and physiological changes, including alopecia, hair greying, kyphosis, decreased body weight, motion in dark phase, and a reduced respiratory exchange ratio (RER) (Ackert-Bicknell et al., 2015; Harkema et al., 2016; Houtkooper et al., 2011; Koks et al., 2016).”
From Loss of epigenetic information as a cause of mammalian aging (2023) · cites this paper as Ackert-Bicknell et al., 2015
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“WT C57BL6/J mice have a median lifespan of ∼129 weeks (Yuan et al., 2012), equivalent to ∼80 years in humans (Ackert-Bicknell et al., 2015)”
From Gene Therapy-Mediated Partial Reprogramming Extends Lifespan and Reverses Age-Related Changes in Aged Mice (2024) · cites this paper as Ackert-Bicknell et al., 2015
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Levey, A. S., Eckardt, K., Tsukamoto, Y., Levin, A., Coresh, J., Rossert, J., de Zeeuw, D., Hostetter, T. H., Lameire, N. H., & Eknoyan, G. (2005) · Kidney International · doi:10.1111/j.1523-1755.2005.00365.x · Cited by 4,031
A new one-trial test for neurobiological studies of memory in rats. 1: behavioral data
Ennaceur, A., & Delacour, J. (1988) · Behavioural Brain Research · doi:10.1016/0166-4328(88)90157-x · Cited by 3,223
Broken Limits to Life Expectancy
Oeppen, J., & Vaupel, J. W. (2002) · Science · doi:10.1126/science.1069675 · Cited by 2,819
Kenyon, C. J. (2010) · Nature · doi:10.1038/nature08980 · Cited by 2,739
The open-field test: A critical review.
WALSH, R. N., & Cummins, R. A. (1976) · Psychological Bulletin · doi:10.1037/0033-2909.83.3.482 · Cited by 2,389
Cryan, J. F., Mombereau, C., & Vassout, A. (2005) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2005.03.009 · Cited by 1,674
T-maze alternation in the rodent
Deacon, R. M. J., & Rawlins, J. N. P. (2006) · Nature Protocols · doi:10.1038/nprot.2006.2 · Cited by 903
Fitzmaurice, G. M., Davidian, M., Molenberghs, G., & Molenberghs, G. (2008) · Chapman & Hall/CRC eBooks · doi:10.1201/9781420011579 · Cited by 474
Global Prevalence and Economic Burden of Urgency Urinary Incontinence: A Systematic Review
Milsom, I., Coyne, K. S., Nicholson, S., Kvasz, M., Chen, C.-I., & Wein, A. J. (2013) · European Urology · doi:10.1016/j.eururo.2013.08.031 · Cited by 453
Visual Perception and Memory: A New View of Medial Temporal Lobe Function in Primates and Rodents
Murray, E. A., Bussey, T. J., & Saksida, L. M. (2007) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.29.051605.113046 · Cited by 449
Research works printed but not linked: 2
- Fox J.G., 2006, The Mouse in Biomedical Research 2nd ed, 566
- Jaffe M.Z., 1886, Über den Niederschlag welchen Pikrinsäure in normalen Harn erzeugt und über eine neue Reaction des Kreatinins, Z. Physiol. Chem., 10, 391
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Han, J., Liu, Q., Xu, X., Qin, W., Pan, Y., Qin, R., Zhao, R., Gu, Y., Gu, J., & Ren, S. (2020) · ACS Omega · doi:10.1021/acsomega.9b04412 · Cited by 10
Mecklenburg, J. M., Patil, M. J., Koek, W., & Akopian, A. N. (2017) · PAIN Reports · doi:10.1097/pr9.0000000000000584 · Cited by 10
Zee, R. S., Mbanefo, E. C., Le, L., Pennington, L. F., Odegaard, J. I., Jardetzky, T. S., Alouffi, A., Akinwale, J., Falcone, F. H., & Hsieh, M. H. (2019) · American Journal of Physiology-Renal Physiology · doi:10.1152/ajprenal.00468.2018 · Cited by 9
Rabaglino, M. B., Wakabayashi, M., Pearson, J. T., & Jensen, L. J. (2021) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2021.111594 · Cited by 10
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Li, J., Liu, M., Liang, S., Yu, Y., & Gu, M. (2022) · BioMed Research International · doi:10.1155/2022/1732438 · Cited by 10
Furth, P. A., Wang, W., Kang, K., Rooney, B. L., Keegan, G., Muralidaran, V., Wong, J., Shearer, C. R., Zou, X., & Flaws, J. A. (2022) · American Journal Of Pathology · doi:10.1016/j.ajpath.2022.09.008 · Cited by 8
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Celebi-Birand, D., Erbaba, B., Ozdemir, A. T., Kafalıgönül, H., & Adams, M. M. (2018) · InTech eBooks · doi:10.5772/intechopen.75554 · Cited by 8
Matamoros, J. A., Rubio‐Casado, S., Fernández‐Albarral, J. A., Martínez‐López, M. A., Ramirez, A. I., Salobrar‐García, E., Marco, E. M., Paleo‐García, V., de Hoz, R., López‐Cuenca, I., et al. (2025) · Pharmaceuticals · doi:10.3390/ph18050694 · Cited by 7
Experimental models for ageing research.
Toniolo, L., Sirago, G., & Giacomello, E. (2023) · PubMed · doi:10.14670/hh-18-576 · Cited by 9
Pu, X., & Qu, Y. (2023) · Journal of Cosmetic Dermatology · doi:10.1111/jocd.15835 · Cited by 7
Lin, D., Hu, Q., Yang, L. Y., Zeng, X., Xiao, Y., Wang, D., Dai, W., Lu, H., Fang, J., Tang, Z., et al. (2022) · Microbial Genomics · doi:10.1099/mgen.0.000811 · Cited by 9
Micturition defects and altered bladder function in the klotho mutant mouse model of aging.
Bartolone, S. N., Ward, E. P., Wang, Z., Zwaans, B. M. M., Chancellor, M. B., Bjorling, D. E., & Lamb, L. E. (2020) · PubMed Central · Cited by 7
Malavolta, M. (2024) · GeroScience · doi:10.1007/s11357-024-01309-7 · Cited by 6
ExerGeneDB: A physical exercise-regulated differential gene expression database
Pan, L., Ai, S., Shi, X., Tong, X., Spanos, M., Li, G., Crețoiu, D., Gao, J., Zhou, Q., & Xiao, J. (2025) · Journal of sport and health science/Journal of Sport and Health Science · doi:10.1016/j.jshs.2025.101027 · Cited by 8
Brown, R. E. (2022) · The EuroBiotech Journal · doi:10.2478/ebtj-2022-0008 · Cited by 5
Dowling, P., Zweyer, M., Sabir, H., Henry, M., Meleady, P., Swandulla, D., & Ohlendieck, K. (2023) · European Journal of Translational Myology · doi:10.4081/ejtm.2023.11553 · Cited by 5
Dual-Stream Spatiotemporal Networks with Feature Sharing for Monitoring Animals in the Home Cage
Nwokedi, E. I., Bains, R. S., Bidaut, L. M., Ye, X., Wells, S. E., & Brown, J. M. (2023) · Sensors · doi:10.3390/s23239532 · Cited by 5
Moon, H. S., Mahzarnia, A., Stout, J. A., Anderson, R. J., Strain, M., Tremblay, J. T., Han, Z. Y., Niculescu, A., MacFarlane, A., King, J., et al. (2023) · Brain Structure and Function · doi:10.1007/s00429-023-02731-x · Cited by 4
Utility of the DHFR-based destabilizing domain across mouse models of retinal degeneration and aging
Peng, H., Ramadurgum, P., Woodard, D. R., Daniel, S., Nakahara, E., Renwick, M., Aredo, B., Datta, S., Chen, B., Ufret-Vincenty, R. L., et al. (2022) · iScience · doi:10.1016/j.isci.2022.104206 · Cited by 5
SOX9 in Keratinocytes Regulates Claudin 2 Transcription during Skin Aging
Wang, J., Xie, X.-Y., Deng, Y., Yang, H., Du, X., Liu, P., & Du, Y. (2022) · Contrast Media & Molecular Imaging · doi:10.1155/2022/6884308 · Cited by 5
Research Progress of Senolytic Drugs in the Treatment of Orthopedic Diseases
Zhang, M., Lou, P., Shou, D., Tong, P., & Zhang, Y. (2025) · Gerontology · doi:10.1159/000543386 · Cited by 4
Genetic links between multimorbidity and human aging
Dinh, P.-A., Han, H., Kim, S., Guo, Q., Zhang, Z. D., Vijg, J., & Suh, Y. (2025) · GeroScience · doi:10.1007/s11357-025-02044-3 · Cited by 5
Mutoh, T., Yamamoto, S., & Moriya, T. (2021) · Biomedicines · doi:10.3390/biomedicines9060664 · Cited by 4
Otsuka, H., Nonaka, N., Nakamura, M., & Soeta, S. (2023) · Journal of Oral Biosciences · doi:10.1016/j.job.2023.06.002 · Cited by 4
Verdú, D., Valls, A., Díaz, A., Carretero, A., Dromant, M., Kuligowski, J., Serna, E., & Viña, J. (2023) · Antioxidants · doi:10.3390/antiox12111991 · Cited by 4
Relationship between Hypoxia and Hypercapnia Tolerance and Life Expectancy
Tregub, P. P., Komleva, Y. K., Kulikov, V. P., Chekulaev, P. A., Tregub, O. F., Maltseva, L. D., Manasova, Z. S., Popova, I. A., Andriutsa, N. S., Samburova, N. V., et al. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25126512 · Cited by 4
Dowling, P., Gargan, S., Zweyer, M., Henry, M. A., Meleady, P., Swandulla, D., & Ohlendieck, K. (2024) · European Journal of Translational Myology · doi:10.4081/ejtm.2024.12564 · Cited by 5
McCorrison, J., Girke, T., Goetz, L. H., Miller, R. A., & Schork, N. J. (2019) · The Journals of Gerontology Series A · doi:10.1093/gerona/glz206 · Cited by 4
Ammann, A. M., Wolfe, V., Piraino, G., Ziady, A. G., & Zingarelli, B. (2024) · Biomedicines · doi:10.3390/biomedicines12112615 · Cited by 3
The Converging Roles of Nucleases and Helicases in Genome Maintenance and the Aging Process
Margariti, A., Daniil, P., & Rampias, T. N. (2025) · Life · doi:10.3390/life15111729 · Cited by 3
Establishment of an overactive bladder model in mice
Lv, T., Zhong, S., & Guo, X. (2023) · BMC Urology · doi:10.1186/s12894-023-01181-1 · Cited by 3
Metadata
- Authors
- Ackert‐Bicknell, C. L., Anderson, L. C., Sheehan, S., Hill, W. G., Chang, B., Churchill, G. A., Chesler, E. J., Korstanje, R., & Peters, L. L.
- Affiliations
- University of Rochester Medicine (US)
- Jackson Laboratory (US)
- Beth Israel Deaconess Medical Center (US)
- ORCID
- Venue
- Current Protocols in Mouse Biology
- Publisher
- Wiley
- Published
- 2015-06
- Volume
- 5
- Issue
- 2
- Pages
- 95-133
- ISSN
- 2161-2617 (ISSN-L)
- PMC
- PMC4590775
- OpenAlex
- W1519109490
- Cited by
- 135
- References
- 41
- Citations by year
- 2026: 13 · 2025: 13 · 2024: 19 · 2023: 20 · 2022: 18 · 2021: 23 · 2020: 8 · 2019: 8 · 2018: 6 · 2017: 4 · 2016: 3
- FWCI
- 1.74
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Current Protocols in Mouse Biology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- The Mouseion at the JAXlibrary (Jackson Laboratory) (submittedVersion)
- Funders
- National Institutes of Health (5p20dk097818-02, 5r01ey019943-13)
- National Institute on Aging (AG-038070, P30AG038070)
- National Eye Institute (EY019943, R01-EY019943)
- National Cancer Institute (P30CA034196)
- National Institute of Diabetes and Digestive and Kidney Diseases (DK097818, DK083299, P20-DK-097818, R01DK083299)
- 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 › Neuroscience › Cellular and Molecular Neuroscience › Antioxidants, Aging, Portulaca oleracea
- Keywords
- aging, mouse models of aging, healthspan, lifespan, longevity, phenotypic assays, body composition, renal function, hematopoiesis, immune function, research design
- MeSH terms
- Aging, Animals, Animal Structures, Behavior, Animal, Disease Models, Animal, Humans, Laboratory Animal Science, Longevity, Research Design, Mice
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