PXD080860

PXD080860 is an original dataset announced via ProteomeXchange.

Title	Circulating extracellular vesicles in plasma carry accessible molecular signatures of aging in mice
Description	Cells continuously release membrane-bound extracellular vesicles (EVs) into the bloodstream laden with proteins that may reflect their physiological state, yet how this circulating EV proteome changes across the lifespan remains poorly understood. Identifying molecular signatures of aging in accessible biofluids could enable earlier intervention and monitoring of age-related disease. Many studies of the circulating aging proteome have relied on affinity-based platforms that suffer from poor cross-species translation, ambiguous signal attribution, and inconsistent agreement between platforms. Here, we present a mass spectrometry (MS)-based characterization of the aging plasma EV proteome from a cross-sectional cohort of 86 male and female C57BL/6J mice from 5 to 31 months old. Using a species-agnostic EV enrichment method (Mag-Net) coupled with data-independent acquisition MS, we detected 2,575 protein groups from 15,969 peptides, a depth of coverage is not achievable across model organisms with current affinity-based approaches. Protein abundance variability increased with age, consistent with the established heterogeneity of aging. We identified 272 proteins whose abundance 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 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 which had not previously characterized at this resolution. A proteomic clock built from these data accurately predicts chronological age, with peptide-level analysis revealing aging signal invisible at the 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 complements epigenetic approaches to monitoring aging and evaluating healthspan.
HostingRepository	PanoramaPublic
AnnounceDate	2026-07-10
AnnouncementXML	Submission_2026-07-10_11:38:34.702.xml
DigitalObjectIdentifier
ReviewLevel	Non peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Supported dataset by repository
PrimarySubmitter	Kristine Tsantilas
SpeciesList	scientific name: Mus musculus; NCBI TaxID: 10090;
ModificationList	Carbamidomethyl; Label:13C(6)15N(2); Label:13C(6)15N(4)
Instrument	Orbitrap Astral; Orbitrap Exploris 480

Revision	Datetime	Status	ChangeLog Entry
0	2026-07-10 11:07:24	ID requested
⏵ 1	2026-07-10 11:38:35	announced

no publication

submitter keyword: aging, DIA mass spectrometry, extracellular vesicles, proteomic clock, plasma proteomics, mouse

Michael MacCoss
contact affiliation	University of Washington
contact email	maccoss@uw.edu
lab head
Kristine Tsantilas
contact affiliation	University of Washington
contact email	ktsantil@uw.edu
dataset submitter

Panorama Public dataset URI