MassIVE MSV000086782

Partial Public PXD023897

Comprehensive Profiling of Plasma Exosomes Using Data Independent Acquisitions New Tools for Aging Cohort Studies

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Description

Aging is a complex biological process associated with progressive loss of physiological function and susceptibility to several diseases, such as cancer and neurodegeneration. Exosomes are involved in many cellular signaling pathways, and their cargo may serve as promising disease or aging biomarkers. These membrane-bound extracellular vesicles facilitate the transport of intracellular contents to proximal and distal cells in the body. Here, we investigated two omics approaches for exosome analysis. To overcome the challenges of plasma exosome contamination with abundant soluble plasma proteins, we developed a high throughput method to isolate highly purified exosomes from human plasma by sequential size exclusion chromatography and ultrafiltration. First, we used data-dependent acquisitions from offline high-pH reversed-phase fractions of exosome lysate to generate a deep spectral library comprising ~2,300 exosome proteins. Second, in a pilot aging study, we used comprehensive data-independent acquisitions to compare plasma exosomes from young (20 to 26 yrs) and old (60 to 66 yrs) individuals. We quantified 1,318 exosome proteins, and levels of 144 proteins were significantly different in young and old plasma groups (Q<0.05 and >1.5-fold change). We also analyzed exosome miRNA cargo and detected 331 miRNAs. Levels of several were significantly different in young and old individuals. In addition, 88 and 17 miRNAs were unique to old and young individuals, respectively. Plasma exosome biomarkers have great potential for translational studies investigating biomarkers of aging and age-related diseases and to monitor therapeutic aging interventions. [doi:10.25345/C5X79Q] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: exosomes ; data-independent acquisition ; plasma ; biomarker ; directDIA ; aging

Contact

Principal Investigators:
(in alphabetical order) 		Birgit Schilling, Buck Institute for Research on Aging, United States
Submitting User: bschilling
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Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

"N/A" means no results of this type were submitted.
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