Proteomic ageing clocks: methods, mechanisms and the muscle connection
- 1Australian Regenerative Medicine Institute, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, VIC 3800 Australia
- 2Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115 USA
Abstract
Proteomic ageing clocks are emerging tools that estimate biological age from protein abundance patterns. Most models are developed using blood capturing inflammatory, metabolic, and extracellular proteins, including secreted signalling factors. Large-scale plasma studies now predict chronological age, disease risk and mortality, but muscle-related models remain indirect, relying on organ-enriched circulating proteins rather than biopsy-derived skeletal muscle clocks. We review current proteomic clock frameworks, computational approaches, platform considerations and validation strategies, highlighting the potential of muscle-based clocks to capture tissue and subcellular-specific ageing processes. We discuss future integration of spatial, single-cell, and multi-omic data to enhance mechanistic insight and translational relevance.
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BibTeX
@article{reisman2026proteomic,
title = {{Proteomic ageing clocks: methods, mechanisms and the muscle connection}},
author = {Elizabeth G. Reisman and Macsue Jacques and Robin Grolaux and Vadim N. Gladyshev and Nir Eynon},
journal = {Genome Biology},
year = {2026},
month = jul,
doi = {10.1186/s13059-026-04220-w},
url = {https://doi.org/10.1186/s13059-026-04220-w},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Proteomic ageing clocks: methods, mechanisms and the muscle connection
AU - Elizabeth G. Reisman
AU - Macsue Jacques
AU - Robin Grolaux
AU - Vadim N. Gladyshev
AU - Nir Eynon
PY - 2026
DA - 2026/07/30
JO - Genome Biology
DO - 10.1186/s13059-026-04220-w
UR - https://doi.org/10.1186/s13059-026-04220-w
AB - Proteomic ageing clocks are emerging tools that estimate biological age from protein abundance patterns. Most models are developed using blood capturing inflammatory, metabolic, and extracellular proteins, including secreted signalling factors. Large-scale plasma studies now predict chronological age, disease risk and mortality, but muscle-related models remain indirect, relying on organ-enriched circulating proteins rather than biopsy-derived skeletal muscle clocks. We review current proteomic clock frameworks, computational approaches, platform considerations and validation strategies, highlighting the potential of muscle-based clocks to capture tissue and subcellular-specific ageing processes. We discuss future integration of spatial, single-cell, and multi-omic data to enhance mechanistic insight and translational relevance.
SN - 1474-7596
SN - 1474-760X
ER -