Evidence map›Paper›PMID 41621130›Full record

ArticleBiomaterials2026

"Comprehensive multi-omics of age-respective plasma and matrix-bound extracellular vesicles identifies anti-fibrotic miRNAs validated on a heart-on-a-chip".

George Ronan, Lauren Hawthorne, Jun Yang, Ruyu Zhou, Frank Ketchum, Nicole Kowalczyk, Fang Liu, Pinar Zorlutuna

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biomaterials, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
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

8 authors.

George RonanDepartment of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA.
Lauren HawthorneDepartment of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA; Bioengineering Graduate Program, University of Notre Dame, Notre Dame, IN, 46556, USA.
Jun YangDepartment of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA.
Ruyu ZhouDepartment of Applied and Computational Mathematics and Statistics, University of Notre Dame, IN, 46556, USA.
Frank KetchumDepartment of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA; Bioengineering Graduate Program, University of Notre Dame, Notre Dame, IN, 46556, USA.
Nicole KowalczykDepartment of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA.
Fang LiuDepartment of Applied and Computational Mathematics and Statistics, University of Notre Dame, IN, 46556, USA.
Pinar ZorlutunaDepartment of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA; Bioengineering Graduate Program, University of Notre Dame, Notre Dame, IN, 46556, USA; Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA; Harper Cancer Research Institute, University of Notre Dame, Notre Dame, 46556, USA. Electronic address: pzorlutu@nd.edu.

Funding

An integrated human organ-on-chip ultrasensitive miRNA detection platform for novel biomarker discoveryR01HL141909 · NHLBI · UNIVERSITY OF NOTRE DAME · PI ZORLUTUNA, PINAR · 2018 to 2022
$1.9M
NHLBI NIH HHS R01 HL141909
6 · The paper itself

Abstract

Aging is a major risk factor for cardiovascular disease, the leading cause of death worldwide, and numerous other diseases, but the mechanisms of these aging-related effects remain elusive. Recent evidence suggests that chronic changes in the microenvironment and local paracrine signaling are major drivers of these effects, but the precise effect of aging on these factors remains understudied. Here, for the first time, we directly compare extracellular vesicles obtained from young and aged patients to identify therapeutic or disease-associated agents, and directly compare vesicles isolated from heart tissue matrix (TEVs) or plasma (PEVs). While young TEVs and PEVs showed notable overlap of miRNA cargo, aged EVs differed substantially, indicating differential aging-related changes between TEVs and PEVs. TEVs overall were uniquely enriched in miRNAs which directly or indirectly demonstrate cardioprotective effects, with 45 potential therapeutic agents identified in our analysis. Both populations also showed increased predisposition to disease with aging, though through different mechanisms. Changes in PEV cargo were largely correlated with chronic systemic inflammation, while those in TEVs were more related to cardiac homeostasis and local inflammation. From this, 17 protein targets were identified which were unique to TEVs and highly correlated with aging and the onset of cardiovascular disease. Further analysis via machine learning techniques implicated several new miRNA and protein targets, independently suggesting several of the targets identified by non-machine learning analysis, which correlated with aging-related changes in TEVs. With further study, this biomarker set may serve as a powerful, potential indicator of cardiac health and age which can be measured from PEVs. Additionally, several proposed "young-enriched" therapeutic agents were validated and, when tested, could successfully prevent cell death and cardiac fibrosis in disease-like conditions using a microfluidic heart-on-a-chip to model of acute and chronic fibrosis, making this study the first in literature to test the efficacy of a miRNA-based therapeutic encapsulated in lipid nanoparticles in an organ-on-a-chip device.

Indexed as

AgingExtracellular MatrixExtracellular VesiclesLab-On-A-Chip DevicesMicroRNAsMyocardiumFibrosisHumansMultiomicsMicroRNAs

Identifiers

PMID41621130
PMCPMC13405247

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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 OpenQuestion graph.