Evidence map›Paper›PMID 41239829›Full record

ReviewEuropean journal of clinical investigation2026

Integrated biomarker landscape for the early detection and management of calcific aortic valve disease.

Alberto Cook-Calvete, Silvia Moreta, Maria Delgado-Marin, Blanca Fernandez-Rodriguez, Carlos Zaragoza, Marta Saura

Abstract readReview
In one paragraph

Review in European journal of clinical investigation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

6 authors.

Alberto Cook-CalveteDepartamento de Biología de Sistemas Facultad de Medicina, Universidad de Alcalá, Alcalá de Henares, Spain.
Silvia MoretaDepartamento de Biología de Sistemas Facultad de Medicina, Universidad de Alcalá, Alcalá de Henares, Spain.ORCID https://orcid.org/0009-0002-1197-8330
Maria Delgado-MarinDepartamento de Biología de Sistemas Facultad de Medicina, Universidad de Alcalá, Alcalá de Henares, Spain.
Blanca Fernandez-RodriguezDepartamento de Biología de Sistemas Facultad de Medicina, Universidad de Alcalá, Alcalá de Henares, Spain.
Carlos ZaragozaUnidad Mixta de Investigación Cardiovascular Universidad Francisco de Vitoria Hospital Ramón y Cajal (IRYCIS), Madrid, Spain.ORCID https://orcid.org/0000-0002-1706-8592
Marta SauraDepartamento de Biología de Sistemas Facultad de Medicina, Universidad de Alcalá, Alcalá de Henares, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCalcific aortic valve disease (CAVD) is the predominant valvular pathology in older adults, advancing from aortic sclerosis to life-threatening stenosis. Without effective medical therapies, intervention mainly relies on timely valve replacement, although silent myocardial and valvular damage may progress before symptoms arise. Early, non-invasive detection of disease activity is a crucial unmet need.

aimsTo review circulating and mechanistic biomarkers reflecting the core pathogenic pathways of CAVD and asses their potential for early detection and patient-specific risk stratification.

methodsNarrative review of literature focusing on traditional protein biomarkers, emerging non-coding RNAs, and extracellular vesicles (EVs) associated with lipid oxidation and inflammation, bone and mineral metabolism, extracellular matrix (ECM) remodelling, endothelial dysfunction and non-coding RNA regulation.

resultsTraditional protein biomarkers-such as lipoprotein(a), osteopontin, fetuin-A, galectin-3 and matrix metalloproteinases-offer insights into the disease and correlate with disease burden but lack sensitivity for detecting early-stage CAVD. Emerging non-coding RNA markers, including long non-coding RNAs (lncRNAs) and microRNAs (like miR-30b and miR-125b), show promise as predictive and diagnostic tools by mediating key molecular pathways involved in calcification and inflammation. EVs, which carry proteins, lipids and nucleic acids across all pathogenic pathways, provide stable and comprehensive signatures that enhance risk stratification compared to conventional markers. Notably, no single biomarker has demonstrated sufficient sensitivity or specificity across all stages of the disease. Combining proteins, RNAs and EV cargo into integrative, multimodal panels-supported by proteomics and transcriptomics-provides the greatest potential for early detection and patient-specific management. However, further validation in prospective cohorts and standardization of assays are necessary before clinical implementation.

conclusionBiomarker-guided approaches could revolutionize CAVD management by enabling early detection and patient stratification before irreversible valvular damage occurs.

Indexed as

Aortic ValveAortic Valve DiseaseAortic Valve StenosisCalcinosisBiomarkersEarly DiagnosisExtracellular VesiclesGalectin 3HumansMicroRNAsOsteopontinRNA, Long NoncodingBiomarkersGalectin 3MicroRNAsOsteopontinRNA, Long Noncodingagingbiomarkerscalcific aortic valve diseasecardiovascular disease

Identifiers

PMID41239829
PMCPMC12820923

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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.