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Comprehensive longitudinal non-invasive quantification of healthspan and frailty in a large cohort (n = 546) of geriatric C57BL/6 J mice

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Abstract

Frailty is an age-related condition characterized by a multisystem functional decline, increased vulnerability to stressors, and adverse health outcomes. Quantifying the degree of frailty in humans and animals is a health measure useful for translational geroscience research. Two frailty measurements, namely the frailty phenotype (FP) and the clinical frailty index (CFI), have been validated in mice and are frequently applied in preclinical research. However, these two tools are based on different concepts and do not necessarily identify the same mice as frail. In particular, the FP is based on a dichotomous classification that suffers from high sample size requirements and misclassification problems. Based on the monthly longitudinal non-invasive assessment of frailty in a large cohort of mice, here we develop an alternative scoring method, which we called physical function score (PFS), proposed as a continuous variable that resumes into a unique function, the five criteria included in the FP. This score would not only reduce misclassification of frailty but it also makes the two tools, PFS and CFI, integrable to provide an overall measurement of health, named vitality score (VS) in aging mice. VS displays a higher association with mortality than PFS or CFI and correlates with biomarkers related to the accumulation of senescent cells and the epigenetic clock. This longitudinal non-invasive assessment strategy and the VS may help to overcome the different sensitivity in frailty identification, reduce the sample size in longitudinal experiments, and establish the effectiveness of therapeutic/preventive interventions for frailty or other age-related diseases in geriatric animals.

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Data availability

The data that support the findings of this study are available from the corresponding author (MM), upon reasonable request.

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Acknowledgements

The authors would like to acknowledge the Centro Piattaforme Tecnologiche (CPT) of Verona University for the IVIS Spectrum usage. The authors wish also to acknowledge Andrea Amoroso, Daniele Pierelli and Huillca Quispe Doctor Ambrosio from Charles River Laboratory Italia, as well as Beatrice Bartozzi and Gianni Bernardini for their precious technical support.

Funding

This work was supported by The Network IRCCS AGING “Rete Nazionale di Ricerca sull’invecchiamento e la longevità attiva – Implementazione della RoadMap nella ricerca sull’Aging (IRMA)” to FL; by Fondazione Cariplo (grant 2016–1006) “Multicomponent Analysis of Physical Frailty Biomarkers” to EN, MP, and AV; and by Ricerca Corrente funding from Italian Ministry of Health to IRCCS-INRCA (MM and MP) and to IRCCS MultiMedica (AP).

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Authors and Affiliations

  1. Advanced Technology Center for Aging Research, IRCCS INRCA, 60121, Ancona, Italy

    Serena Marcozzi, Giorgia Bigossi, Maria Elisa Giuliani, Robertina Giacconi, Maurizio Cardelli, Francesco Piacenza, Mauro Provinciali & Marco Malavolta

  2. Scientific Direction, IRCCS INRCA, 60124, Ancona, Italy

    Serena Marcozzi & Fabrizia Lattanzio

  3. Experimental Animal Models for Aging Unit, Scientific Technological Area, IRCCS INRCA, 60015, Falconara Marittima (AN), Italy

    Fiorenza Orlando

  4. Department of Molecular and Translational Medicine, University of Brescia, Viale Europa, 11, 25123, Brescia, Italy

    Agnese Segala & Alessandra Valerio

  5. Center for Study and Research On Obesity, Department of Medical Biotechnology and Translational Medicine, University of Milan, Via Vanvitelli, 32, 20129, Milan, Italy

    Enzo Nisoli

  6. Medical Genetics and Neurogenetics Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20126, Milan, Italy

    Dario Brunetti

  7. Department of Medical Biotechnology and Translational Medicine, University of Milan, 20129, Milan, Italy

    Dario Brunetti

  8. Department of Medicine, Surgery and Dentistry “Scuola Medica Salernitana”, University of Salerno, Via Salvatore Allende, 84081, Baronissi, Salerno, Italy

    Annibale Puca

  9. Cardiovascular Research Unit, IRCCS MultiMedica, 20138, Milan, Italy

    Annibale Puca

  10. Department of Computer Science, University of Verona, Strada Le Grazie 15, 37134, Verona, Italy

    Federico Boschi

  11. Laboratory of Epigenetics, Istituti Clinici Scientifici Maugeri IRCCS, Via Maugeri 10, 27100, Pavia, Italy

    Carlo Gaetano & Alessia Mongelli

Authors
  1. Serena Marcozzi
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  2. Giorgia Bigossi
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  3. Maria Elisa Giuliani
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  4. Robertina Giacconi
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  5. Maurizio Cardelli
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  17. Mauro Provinciali
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  18. Marco Malavolta
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Contributions

Conceptualization: MM EN, AV. Data curation: MM, SM. Formal analysis: SM. Funding acquisition: AP, MM, AV, MP, EN, FL. Investigation: MM, GB, AS, MEG, RG. Methodology: MM, FB. Project administration: FL, MP. Supervision: AP, MP, FL. Visualization: SM. Writing—original draft: SM, MM. Writing—review and editing: MP, FP, RG, EN, AV.

Corresponding author

Correspondence to Marco Malavolta.

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Marcozzi, S., Bigossi, G., Giuliani, M.E. et al. Comprehensive longitudinal non-invasive quantification of healthspan and frailty in a large cohort (n = 546) of geriatric C57BL/6 J mice. GeroScience 45, 2195–2211 (2023). https://doi.org/10.1007/s11357-023-00737-1

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