Evidence map›Paper›PMID 40595564›Full record

ArticleNature communications2025

Enrichment of extracellular vesicles using Mag-Net for the analysis of the plasma proteome.

Christine C Wu, Kristine A Tsantilas, Jea Park, Deanna Plubell, Justin A Sanders, Previn Naicker, Ireshyn Govender, Sindisiwe Buthelezi, Stoyan Stoychev, Justin Jordaan and 9 more

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing 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

40 citing papers in PubMed.

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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

19 authors.

Christine C WuDepartment of Genome Sciences, University of Washington, Seattle, WA, USA. chriscwu@uw.edu.ORCID http://orcid.org/0009-0000-6518-8487
Kristine A TsantilasDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0002-4274-6930
Jea ParkDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0003-1050-9321
Deanna PlubellDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0002-6580-8073
Justin A SandersDepartment of Computer Science, University of Washington, Seattle, WA, USA.
Previn NaickerCSIR, Pretoria, South Africa.
Ireshyn GovenderReSyn Biosciences, Gauteng, South Africa.
Sindisiwe ButheleziCSIR, Pretoria, South Africa.
Stoyan StoychevReSyn Biosciences, Gauteng, South Africa.
Justin JordaanReSyn Biosciences, Gauteng, South Africa.
Gennifer MerrihewDepartment of Computer Science, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0003-4903-0318
Eric HuangDepartment of Computer Science, University of Washington, Seattle, WA, USA.
Edward D ParkerVision Core Lab, Department of Ophthalmology, University of Washington, Seattle, WA, USA.
Michael RiffleDepartment of Biochemistry, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0003-1633-8607
Andrew N HoofnagleDepartment of Lab Medicine and Pathology, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0002-6449-0243
William S NobleDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0001-7283-4715
Kathleen L PostonDepartment of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA, USA.ORCID http://orcid.org/0000-0003-3424-7143
Thomas J MontineDepartment of Pathology, Stanford University, Palo Alto, CA, USA.ORCID http://orcid.org/0000-0002-1346-2728
Michael J MacCossDepartment of Genome Sciences, University of Washington, Seattle, WA, USA. maccoss@uw.edu.ORCID http://orcid.org/0000-0003-1853-0256

Funding

Vector and Transgenic Mouse CoreP30DK017047 · NIDDK · UNIVERSITY OF WASHINGTON · PI Sakeneh Zraika · 1986 to 2026
$41.4M
Stanford Alzheimer's Disease Research CenterAdmin Supp: Developing iPSC models for AD and PDP30AG066515 · NIA · STANFORD UNIVERSITY · PI Lisa Goldman Rosas · 2020 to 2026
$29.0M
University of Washington Nathan Shock Center of Excellence in the Basic Biology of AgingP30AG013280 · NIA · UNIVERSITY OF WASHINGTON · PI Maitreya J Dunham · 1995 to 2026
$27.1M
Project 4: Novel reagent development to enable molecular characterizationU19AG065156 · NIA · UNIVERSITY OF WASHINGTON · PI TIAN, LU · 2020 to 2024
$15.9M
Biological Mechanisms of Healthy Aging Training GrantT32AG066574 · NIA · UNIVERSITY OF WASHINGTON · PI David J. Marcinek, Jessica E Young · 2020 to 2026
$5.3M
The impact of early Tau pathology on cognitive progression and neuropsychiatric symptoms in Parkinson's diseaseR01NS115114 · NINDS · STANFORD UNIVERSITY · PI ANDREASSON, KATRIN I., POSTON, KATHLEEN LOMBARD · 2019 to 2023
$4.2M
Quantifying proteins in plasma do democratize personalized medicine for patients with type 1 diabetesU01DK137097 · NIDDK · UNIVERSITY OF WASHINGTON · PI ANDREW N HOOFNAGLE, Michael MacCoss · 2023 to 2026
$3.4M
Proteolytic activity profiling of Alzheimer's dementiaF31AG069420 · NIA · UNIVERSITY OF WASHINGTON · PI PLUBELL, DEANNA LISA · 2020 to 2021
$81k
NIA NIH HHS F31 AG069420NIA NIH HHS P30 AG013280NIA NIH HHS P30 AG066515NIA NIH HHS T32 AG066574NIA NIH HHS U19 AG065156NIDDK NIH HHS P30 DK017047NIDDK NIH HHS U01 DK137097NINDS NIH HHS R01 NS115114
6 · The paper itself

Abstract

Extracellular vesicles (EVs) in plasma are composed of exosomes, microvesicles, and apoptotic bodies. We report a plasma EV enrichment strategy using magnetic beads called Mag-Net. Proteomic interrogation of this plasma EV fraction enables the detection of proteins that are beyond the dynamic range of liquid chromatography-mass spectrometry of unfractionated plasma. Mag-Net is robust, reproducible, inexpensive, and requires <100 μL plasma input. Coupled to data-independent mass spectrometry, we demonstrate the measurement of >37,000 peptides from >4,000 proteins. Using Mag-Net on a pilot cohort of patients with neurodegenerative disease and healthy controls, we find 204 proteins that differentiate (q-value < 0.05) patients with Alzheimer's disease dementia (ADD) from those without ADD. There are also 310 proteins that differ between individuals with Parkinson's disease and without. Using machine learning we distinguish between individuals with ADD and not ADD with an area under the receiver operating characteristic curve (AUROC) = 0.98 ± 0.06.

Indexed as

Blood ProteinsExtracellular VesiclesProteomeProteomicsAgedAlzheimer DiseaseBiomarkersCase-Control StudiesChromatography, LiquidFemaleHumansMachine LearningMaleMass SpectrometryMiddle AgedParkinson DiseaseBiomarkersBlood ProteinsProteome

Identifiers

PMID40595564
PMCPMC12219689

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.