MskAge—An Epigenetic Biomarker of Musculoskeletal Age Derived From a Genetic Algorithm Islands Model

Daniel C. Green, Louise N. Reynard, James R. Henstock, Sjur Reppe, Kaare Gautvik, Mandy J. Peffers, Daryl P. Shanley, Peter D. Clegg, Elizabeth G. Canty-Laird*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

Age is a significant risk factor for functional decline and disease of the musculoskeletal system, yet few biomarkers exist to facilitate ageing research in musculoskeletal tissues. Multivariate models based on DNA methylation, termed epigenetic clocks, have shown promise as markers of biological age. However, the accuracy of existing epigenetic clocks in musculoskeletal tissues are no more, and often less accurate than a randomly sampled baseline model. We developed a highly accurate epigenetic clock, MskAge, that is specific to tissues and cells of the musculoskeletal system. MskAge was built using a penalised genetic algorithm islands model that addresses multi-tissue clock bias. The final model was trained on the transformed principal components of CpGs selected by the genetic algorithm. We show that MskAge tracks epigenetic ageing ex vivo and in vitro. Epigenetic age estimates are rejuvenated with cellular reprogramming and are accelerated at a rate of 0.45 years per population doubling. MskAge explains more variance associated with in vitro ageing of fibroblasts than the purpose-developed skin and blood clock. The precision of MskAge and its ability to capture perturbations in biological ageing make it a promising research tool for musculoskeletal and ageing biologists.

Original languageEnglish
Article numbere70149
Number of pages14
JournalAging Cell
Volume24
Issue number9
Early online date19 Jun 2025
DOIs
Publication statusPublished - 1 Sept 2025
Externally publishedYes

Keywords

  • ageing
  • biomarker
  • epigenetics
  • genetic algorithm
  • musculoskeletal system

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