Evidence mapPaperPMID 41369156Full record

ArticleJournal of the American Heart Association2026

Circulating Extracellular Vesicle MicroRNAs as Predictive Biomarkers for Kidney and Cardiovascular Events.

Shunsuke Inaba, Takanori Hasegawa, Yuta Nakano, Shotaro Naito, Rena Suzukawa, Takaaki Koide, Hisateru Sekiya, Hisazumi Matsuki, Tamami Fujiki, Hiroaki Kikuchi and 9 more

Abstract read
In one paragraph

Article in Journal of the American Heart Association, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

19 authors.

Shunsuke Inaba *Department of Nephrology, Graduate School of Medical and Dental Sciences Institute of Science Tokyo Tokyo Japan.ORCID 0009-0007-7901-1659
Takanori Hasegawa *M&D Data Science Center, Institute of Integrated Research Institute of Science Tokyo Tokyo Japan.ORCID 0000-0001-7251-9950
Yuta NakanoDepartment of Nephrology, Graduate School of Medical and Dental Sciences Institute of Science Tokyo Tokyo Japan.ORCID 0000-0002-6069-066X
Shotaro NaitoDepartment of Nephrology, Graduate School of Medical and Dental Sciences Institute of Science Tokyo Tokyo Japan.ORCID 0000-0001-9774-1638
Rena SuzukawaDepartment of Nephrology, Graduate School of Medical and Dental Sciences Institute of Science Tokyo Tokyo Japan.ORCID 0009-0005-4455-9193
Takaaki KoideDepartment of Nephrology, Graduate School of Medical and Dental Sciences Institute of Science Tokyo Tokyo Japan.
Hisateru SekiyaDepartment of Nephrology, Graduate School of Medical and Dental Sciences Institute of Science Tokyo Tokyo Japan.
Hisazumi MatsukiDepartment of Nephrology, Graduate School of Medical and Dental Sciences Institute of Science Tokyo Tokyo Japan.
Tamami FujikiDepartment of Nephrology, Graduate School of Medical and Dental Sciences Institute of Science Tokyo Tokyo Japan.
Hiroaki KikuchiDepartment of Nephrology, Graduate School of Medical and Dental Sciences Institute of Science Tokyo Tokyo Japan.ORCID 0000-0001-7722-4131
Yohei AraiDepartment of Nephrology, Graduate School of Medical and Dental Sciences Institute of Science Tokyo Tokyo Japan.ORCID 0009-0002-7458-0266
Yutaro MoriDepartment of Nephrology, Graduate School of Medical and Dental Sciences Institute of Science Tokyo Tokyo Japan.ORCID 0000-0002-8499-5636
Fumiaki AndoDepartment of Nephrology, Graduate School of Medical and Dental Sciences Institute of Science Tokyo Tokyo Japan.ORCID 0000-0002-8401-1705
Takayasu MoriDepartment of Nephrology, Graduate School of Medical and Dental Sciences Institute of Science Tokyo Tokyo Japan.ORCID 0000-0002-9308-7787
Koichiro SusaDepartment of Nephrology, Graduate School of Medical and Dental Sciences Institute of Science Tokyo Tokyo Japan.ORCID 0000-0002-0100-4527
Soichiro IimoriDepartment of Nephrology, Graduate School of Medical and Dental Sciences Institute of Science Tokyo Tokyo Japan.
Eisei SoharaDepartment of Nephrology, Graduate School of Medical and Dental Sciences Institute of Science Tokyo Tokyo Japan.ORCID 0000-0003-1668-8308
Shinichi UchidaDepartment of Nephrology, Graduate School of Medical and Dental Sciences Institute of Science Tokyo Tokyo Japan.
Shintaro MandaiDepartment of Nephrology, Graduate School of Medical and Dental Sciences Institute of Science Tokyo Tokyo Japan.ORCID 0000-0001-6709-306X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChronic kidney disease (CKD) leads to premature mortality from cardiovascular events before kidney replacement therapy. Despite recognition of syndromes like cardiorenal anemia and cardiovascular-kidney-metabolic, predictive models for kidney and cardiovascular outcomes remain inadequate. This study aimed to develop a minimally invasive, risk model using circulating small extracellular vesicle-derived miRNAs among patients with CKD.

methodsA derivation cohort (n=36) underwent microarray-based miRNA profiling, and a least absolute shrinkage and selection operator-penalized Cox proportional hazards model was constructed. Validation was performed using TaqMan quantitative polymerase chain reaction in a cohort of 234 patients with CKD without kidney replacement therapy. The primary outcome was a ≥30% reduction in estimated glomerular filtration rate or progression to kidney replacement therapy. The secondary outcome included all-cause mortality, kidney replacement therapy initiation, and major adverse cardiovascular events.

resultsIn the derivation cohort, 36% of patients had hypertensive glomerulosclerosis as the underlying CKD cause, increasing to 48% in the validation cohort. Twenty-three miRNAs were significantly downregulated in advanced CKD, associated with cellular senescence, FOXO (forkhead box, class O) signaling, and cell cycle pathways. From these, 3 miRNAs-

conclusionsCirculating small extracellular vesicle-derived miRNA profiles enable a noninvasive, longitudinally predictive model for adverse kidney and cardiovascular outcomes in CKD. This approach may improve early risk identification and clinical decision-making.

Indexed as

Cardiovascular DiseasesCirculating MicroRNAExtracellular VesiclesMicroRNAsRenal Insufficiency, ChronicAgedBiomarkersDisease ProgressionFemaleGene Expression ProfilingGlomerular Filtration RateHumansMaleMiddle AgedPredictive Value of TestsPrognosisBiomarkersCirculating MicroRNAMicroRNAsbiomarkercardiovascular‐kidney‐metabolic syndromechronic kidney diseaseextracellular vesiclesmicroRNA

Identifiers

PMID41369156
PMCPMC12909002

What Socratic holds

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LicenceCC BY-NC-ND
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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.