<scp>MskAge</scp> —An Epigenetic Biomarker of Musculoskeletal Age Derived From a Genetic Algorithm Islands Model

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.

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Publication Details

Journal
Aging Cell
Published
2025-06-19
DOI
https://doi.org/10.1111/acel.70149
Primary Topic
Epigenetics and DNA Methylation
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Peter Clegg, Mandy J. Peffers, Louise N. Reynard, James R. Henstock et al.
Aging Cell
Epigenetics and DNA Methylation
article

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

Peter Clegg, Mandy J. Peffers, Louise N. Reynard, James R. Henstock, Daryl P. Shanley, Sjur Reppe, Kaare M. Gautvik, Daniel C. Green, Elizabeth G. Canty‐Laird
article en

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.

Aging CellVol. 24(9)
Oslo University Hospital (NO), University of Liverpool (GB), Arthritis UK (GB), Lovisenberg Diakonale Sykehus (NO), Newcastle University (GB), Medical Research Council (GB)
University of Liverpool, Versus Arthritis, Medical Research Council
Life below water
Openalex Percentile: Top 87%
Epigenetics and DNA Methylation
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