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A toolbox for the longitudinal assessment of healthspan in aging mice

Nature Protocols volume 15, pages 540–574 (2020)Cite this article

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Abstract

The number of people aged over 65 is expected to double in the next 30 years. For many, living longer will mean spending more years with the burdens of chronic diseases such as Alzheimer’s disease, cardiovascular disease, and diabetes. Although researchers have made rapid progress in developing geroprotective interventions that target mechanisms of aging and delay or prevent the onset of multiple concurrent age-related diseases, a lack of standardized techniques to assess healthspan in preclinical murine studies has resulted in reduced reproducibility and slow progress. To overcome this, major centers in Europe and the United States skilled in healthspan analysis came together to agree on a toolbox of techniques that can be used to consistently assess the healthspan of mice. Here, we describe the agreed toolbox, which contains protocols for echocardiography, novel object recognition, grip strength, rotarod, glucose tolerance test (GTT) and insulin tolerance test (ITT), body composition, and energy expenditure. The protocols can be performed longitudinally in the same mouse over a period of 4–6 weeks to test how candidate geroprotectors affect cardiac, cognitive, neuromuscular, and metabolic health.

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Fig. 1: A graphic representation of the experimental design for healthspan assessment in response to a geroprotector of choice in C57BL6/J using the recommended toolbox.
Fig. 2: Representative images from high-resolution echocardiography systems.
Fig. 3: Novel object recognition (NOR) memory enhancement in exercised male mice.
Fig. 4: Assessment of muscle strength and neuromuscular function.
Fig. 5: Effects of dietary protein level on energy balance.
Fig. 6: Glucose and insulin tolerance tests.

Data availability

All data shown in this paper are available from the authors upon reasonable request.

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Acknowledgements

We thank K. R. McGreevy from the Cajal Institute for her assistance with Fig. 3, and D. E. Cohen for enabling D.W.L. to attend the 2017 MouseAGE annual meeting. This article is based on work from COST Action (BM1402: MouseAGE), supported by COST (European Cooperation in Science and Technology; I.B., P.K.P., D.E., L.J.T.). Part of this work has been funded by the European Union Research and Innovation Program Horizon 2020 (grant agreement number 730879; I.B.). The Lamming laboratory is supported in part by the NIH (AG051974, AG056771 and AG062328) and by the US Department of Veterans Affairs (I01-BX004031), and this work was supported using facilities and resources from the William S. Middleton Memorial Veterans Hospital. D.E. was supported by a grant from the Helmholtz-Future Topic ‘Aging and Metabolic Programming’ (AMPro), the Mayo clinic is funded by Robert and Arlene Kogod, the Connor Group, and partially by NIA grant AG13925. R.dC., C.D.G., and I.N. are supported by the Intramural Research Program of the NIA/NIH. This work does not necessarily represent the official views of the NIH, the Department of Veterans Affairs or the United States Government.

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Authors and Affiliations

  1. Department of Oncology and Metabolism, Healthy Lifespan Institute and MRC–Arthritis Research UK Centre for Integrated research into Musculoskeletal Ageing, University of Sheffield, Sheffield, UK

    I. Bellantuono

  2. Translational Gerontology Branch, National Institutes of Health, Baltimore, MD, USA

    R. de Cabo, C. Di Germanio & I. Navas-Enamorado

  3. German Center for Neurodegenerative Diseases (DZNE), Venusberg Campus 1, Bonn, Germany

    D. Ehninger

  4. Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, UK

    A. Lawrie

  5. Robert and Arlene KogodCenter on Aging, Mayo Clinic, Rochester, MN, USA

    J. Miller & T. Tchkonia

  6. Department of Molecular Medicine, Harvard T. H. Chan School of Public Health, Boston, MA, USA

    S. J. Mitchell

  7. Department of Biological and Life Sciences, Faculty of Health and Life Sciences, Oxford Brookes University, Oxfordshire, UK

    P. K. Potter

  8. Department of Translational Neuroscience, Cajal Institute (CSIC), Madrid, Spain

    J. L. Trejo

  9. William S. Middleton Memorial Veterans Hospital, Madison, WI, USA

    D. W. Lamming

  10. Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA

    D. W. Lamming

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  1. I. Bellantuono
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Contributions

I.B., R.d.C., D.E., C.D.G., I.N.-E., S.M., P.K.P., T.T., J.L.T., A.L. and D.W.L. contributed equally to the development of the protocols. I.B. and D.L. wrote the manuscript. All other authors edited and approved the final manuscript.

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Correspondence to I. Bellantuono or D. W. Lamming.

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The authors declare no competing interests.

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Peer review information Nature Protocols thanks Erin R. Hascup, Susan Howlett and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Key references using this protocol

Martin-Montalvo, A. et al. Nat. Commun. 4, 2192 (2013): https://doi.org/10.1038/ncomms3192.

Neff, F. et al. J. Clin. Invest. 123, 3272–3291 (2013): https://doi.org/10.1172/JCI67674.

Zhu, Y. et al. Aging Cell 14, 644–658 (2015): https://doi.org/10.1111/acel.12344.

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Bellantuono, I., de Cabo, R., Ehninger, D. et al. A toolbox for the longitudinal assessment of healthspan in aging mice. Nat Protoc 15, 540–574 (2020). https://doi.org/10.1038/s41596-019-0256-1

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