Nature Communications (Sep 2020)

Age and life expectancy clocks based on machine learning analysis of mouse frailty

  • Michael B. Schultz,
  • Alice E. Kane,
  • Sarah J. Mitchell,
  • Michael R. MacArthur,
  • Elisa Warner,
  • David S. Vogel,
  • James R. Mitchell,
  • Susan E. Howlett,
  • Michael S. Bonkowski,
  • David A. Sinclair

DOI
https://doi.org/10.1038/s41467-020-18446-0
Journal volume & issue
Vol. 11, no. 1
pp. 1 – 12

Abstract

Read online

The discovery of interventions that slow aging could be accelerated by employing non-invasive biometrics that predict biological age or life expectancy. Here the authors use longitudinal frailty data from naturally aging mice to develop two such tools, that are responsive to interventions.