Evidence map›Paper›PMID 41226804›Full record

ReviewInternational journal of molecular sciences2025

MicroRNA Signatures in Cardiometabolic Disorders as a Next-Generation Diagnostic Approach: Current Insight.

Concetta Iside, Francesca Picone, Paola Di Pietro, Angela Carmelita Abate, Valeria Prete, Antonio Damato, Eleonora Venturini, Saad Akeel, Salvatore Petralia, Carmine Vecchione and 1 more

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Review
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  6. Review
  7. Review
  8. Biomarkers of Cardiac Metabolic Flexibility in Health, HFrEF and HFpEF.International journal of molecular sciences · 2026
    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

11 authors.

Concetta IsideDepartment of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, 84081 Baronissi, Italy.
Francesca PiconeDepartment of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, 84081 Baronissi, Italy.ORCID 0009-0009-6509-9789
Paola Di PietroDepartment of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, 84081 Baronissi, Italy.ORCID 0000-0003-1327-1961
Angela Carmelita AbateDepartment of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, 84081 Baronissi, Italy.ORCID 0009-0007-2811-8018
Valeria PreteDepartment of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, 84081 Baronissi, Italy.ORCID 0009-0006-2380-1611
Antonio DamatoVascular Physiopathology Unit, IRCCS Neuromed, 86077 Pozzilli, Italy.ORCID 0000-0003-0258-5324
Eleonora VenturiniVascular Physiopathology Unit, IRCCS Neuromed, 86077 Pozzilli, Italy.
Saad AkeelDepartment of Drug and Health Sciences, University of Catania, Via Santa Sofia 64, 95125 Catania, Italy.ORCID 0009-0005-8854-5594
Salvatore PetraliaDepartment of Drug and Health Sciences, University of Catania, Via Santa Sofia 64, 95125 Catania, Italy.ORCID 0000-0001-5692-1130
Carmine VecchioneDepartment of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, 84081 Baronissi, Italy.
Albino CarrizzoDepartment of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, 84081 Baronissi, Italy.ORCID 0000-0003-2689-0008

Funding

MASE_regione campania CUP_ B21I22000180001
6 · The paper itself

Abstract

Cardiometabolic diseases, including cardiovascular disorders and type 2 diabetes mellitus, are the leading cause of morbidity and mortality worldwide, placing a significant burden on healthcare systems. Although advances in imaging and risk stratification have improved disease management, conventional diagnostic and prognostic tools often lack the requisite sensitivity and specificity for early and precise risk stratification. This limitation stems from their poor ability to capture the full molecular complexity of these conditions, underscoring an urgent need for innovative biomarkers to bridge these gaps. MicroRNAs, small non-coding RNAs that regulate gene expression post-transcriptionally, have emerged as promising candidates. Their characteristics offer several advantages over traditional methods, including exceptional stability in biological fluids, strong tissue and disease specificity, and the ability to reflect dynamic pathological changes. These unique features enable miRNAs to detect subtle molecular alterations that may precede clinical symptoms, thereby overcoming key limitations of current diagnostic approaches. Altered circulating miRNA profiles have been linked to pathological processes such as endothelial dysfunction, inflammation, oxidative stress, and maladaptive cardiac remodeling. This review provides a comprehensive overview of the current evidence supporting the diagnostic and prognostic role of circulating miRNAs in cardiometabolic disease. We highlight their potential as early detection biomarkers, tools for patient stratification, and indicators of therapeutic response. Furthermore, we discuss key limitations to clinical translation, including methodological variability, challenges in sample handling, differences in normalization strategies, and platform-dependent quantification inconsistencies. Overcoming these obstacles and achieving robust large-scale clinical validation will be essential to fully harness the potential of miRNAs as next-generation molecular signatures in precision medicine.

Indexed as

Cardiovascular DiseasesDiabetes Mellitus, Type 2MicroRNAsAnimalsBiomarkersHumansPrognosisBiomarkersMicroRNAsbiomarkerscardiovascular diseasediabetesdiagnostic discoverymiRNA

Identifiers

PMID41226804
PMCPMC12609130

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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.