Proteomic clocks reveal organ-specific signatures of aging in mice

Aging alters protein abundance throughout the body, but whether proteomic aging signatures are shared across organs, and how they are represented in RNA, remains unclear. Plasma proteomics does not measure protein abundance directly within individual organs. Here, we developed organ-specific proteomic aging clocks for eight mouse organs. The clocks retained age associations across independent cohorts but transferred poorly between organs of the same mice, indicating predominantly organ-specific aging signatures. This organ specificity extended to RNA. Applied to the transcriptomes of the genes encoding each clock's protein features, with protein-derived weights unchanged, the scores retained age associations in independent transcriptomic cohorts, with stronger associations in the corresponding organs. The strength of age associations across molecular layers also differed by organ: in paired analysis, protein scores tracked age more strongly than RNA scores in brain and skeletal muscle, with no statistically detectable difference in kidney, liver or lung, suggesting a greater post-transcriptional contribution to proteomic aging in brain and muscle. In spatial transcriptomes, protein-derived RNA scores rose with age within tissue niches, usually without detectable changes in relative niche abundance. In the brain, white matter and glia-enriched microdomains showed elevated proteomic scores compared to other regions since young age. Together, these findings support organ-specific regulation of proteomic aging and identify molecular remodeling within persistent tissue compartments.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-10-29
DOI
https://doi.org/10.64898/2026.10.27.762011
Primary Topic
Genetics, Aging, and Longevity in Model Organisms
Type
preprint

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preprint

Proteomic clocks reveal organ-specific signatures of aging in mice

Andrew M. Pickering, Sean Lim
5 links
bioRxiv (Cold Spring Harbor Laboratory)
Genetics, Aging, and Longevity in Model Organisms
preprint

Proteomic clocks reveal organ-specific signatures of aging in mice

Andrew M. Pickering, Sean Lim
preprint en

Abstract

Aging alters protein abundance throughout the body, but whether proteomic aging signatures are shared across organs, and how they are represented in RNA, remains unclear. Plasma proteomics does not measure protein abundance directly within individual organs. Here, we developed organ-specific proteomic aging clocks for eight mouse organs. The clocks retained age associations across independent cohorts but transferred poorly between organs of the same mice, indicating predominantly organ-specific aging signatures. This organ specificity extended to RNA. Applied to the transcriptomes of the genes encoding each clock's protein features, with protein-derived weights unchanged, the scores retained age associations in independent transcriptomic cohorts, with stronger associations in the corresponding organs. The strength of age associations across molecular layers also differed by organ: in paired analysis, protein scores tracked age more strongly than RNA scores in brain and skeletal muscle, with no statistically detectable difference in kidney, liver or lung, suggesting a greater post-transcriptional contribution to proteomic aging in brain and muscle. In spatial transcriptomes, protein-derived RNA scores rose with age within tissue niches, usually without detectable changes in relative niche abundance. In the brain, white matter and glia-enriched microdomains showed elevated proteomic scores compared to other regions since young age. Together, these findings support organ-specific regulation of proteomic aging and identify molecular remodeling within persistent tissue compartments.

bioRxiv (Cold Spring Harbor Laboratory)
Rice University (US), The University of Texas Health Science Center at Houston (US)
National Institutes of Health
Genetics, Aging, and Longevity in Model Organisms
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Proteomic clocks reveal organ-specific signatures of aging in mice — Andrew M. Pickering, Sean Lim · bioRxiv (Cold Spring Harbor Laboratory) (2026) | TGRS Research Map | TGRS