Evidence mapPaperPMID 42465266Full record

ArticlebioRxiv : the preprint server for biology2026

Circulating extracellular vesicles in plasma carry accessible molecular signatures of aging in mice.

Kristine A Tsantilas, Michael Riffle, Gennifer E Merrihew, Christine C Wu, Gregory R Keele, Aaron Maurais, Richard S Johnson, Alison Luciano, Laura Robinson, Gary A Churchill and 1 more

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In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Kristine A TsantilasDepartment of Genome Sciences, University of Washington, 1705 NE Pacific Street, Seattle, Washington 98195, United States.ORCID 0000-0002-4274-6930
Michael RiffleDepartment of Genome Sciences, University of Washington, 1705 NE Pacific Street, Seattle, Washington 98195, United States.ORCID 0000-0003-1633-8607
Gennifer E MerrihewDepartment of Genome Sciences, University of Washington, 1705 NE Pacific Street, Seattle, Washington 98195, United States.ORCID 0000-0003-4903-0318
Christine C WuDepartment of Genome Sciences, University of Washington, 1705 NE Pacific Street, Seattle, Washington 98195, United States.
Gregory R KeeleThe Jackson Laboratory, 600 Main Street, Bar Harbor, Maine, 04609, United States.
Aaron MauraisDepartment of Genome Sciences, University of Washington, 1705 NE Pacific Street, Seattle, Washington 98195, United States.
Richard S JohnsonDepartment of Genome Sciences, University of Washington, 1705 NE Pacific Street, Seattle, Washington 98195, United States.
Alison LucianoThe Jackson Laboratory, 600 Main Street, Bar Harbor, Maine, 04609, United States.
Laura RobinsonThe Jackson Laboratory, 600 Main Street, Bar Harbor, Maine, 04609, United States.
Gary A ChurchillThe Jackson Laboratory, 600 Main Street, Bar Harbor, Maine, 04609, United States.ORCID 0000-0001-9190-9284
Michael J MacCossDepartment of Genome Sciences, University of Washington, 1705 NE Pacific Street, Seattle, Washington 98195, United States.ORCID 0000-0003-1853-0256

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cells release membrane-bound extracellular vesicles into the bloodstream laden with proteins that may reflect their physiological state. How this circulating EV proteome changes across life remains poorly understood. Identifying molecular signatures of aging in accessible biofluids could facilitate earlier intervention and monitoring of age-related disease. Many circulating aging proteome studies rely on affinity-based platforms which suffer from poor cross-species translation, ambiguous signal attribution, and inconsistent agreement between platforms. Here, we present a characterization of the aging plasma EV proteome from a cross-sectional cohort of 86 male and female C57BL/6J mice (5-31 months). We leveraged a species-agnostic EV enrichment (Mag-Net) and mass spectrometry to detect 2,575 protein groups from 15,969 peptides. Protein abundance heterogeneity increased with age and the abundance of 272 proteins were significantly correlated with chronological age including established senescence and frailty markers. Proteins increasing with age were enriched in genome maintenance pathways, while those decreasing were associated with the extracellular matrix organization and lipid metabolism. Notably, several of the strongest age-increased proteins converged on Alzheimer's and Parkinson's disease pathology. We observed sexual divergence in the aging EV proteome not previously characterized at this resolution. A proteomic clock built from this data accurately predicts chronological age, and peptide-level analysis reveals aging signals invisible at protein-level. These findings demonstrate that EV-enriched plasma proteomics can identify known aging markers, reveal novel sex-specific age-related changes, and generate predictive models of chronological age. This study provides a species-agnostic foundation for proteomic clocks that complement epigenetic approaches to monitor aging and evaluate healthspan.

Indexed as

agingextracellular vesiclesmass spectrometrymouseplasma proteomicsproteomic clock

Identifiers

PMID42465266
PMCPMC13370508

What Socratic holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.