Evidence map›Paper›PMID 42251203›Full record

ArticleDiabetologia2026

Plasma small RNA profiling reveals a three-miRNA signature associated with early beta cell dysfunction across glucose tolerance stages.

Elena Aiello, Giuseppina Emanuela Grieco, Michela Brunetti, Giulia Gliozzo, Daniela Fignani, Giuseppe Quero, Sergio Alfieri, Gianfranco Di Giuseppe, Gea Ciccarelli, Angela Dardano and 8 more

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Article in Diabetologia, 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

18 authors.

Elena AielloDiabetes Unit, Department of Medicine, Surgery and Neurosciences, University of Siena, Siena, Italy.ORCID http://orcid.org/0000-0002-2054-4369
Giuseppina Emanuela GriecoDiabetes Unit, Department of Medicine, Surgery and Neurosciences, University of Siena, Siena, Italy.ORCID http://orcid.org/0000-0001-7325-6128
Michela BrunettiDipartimento di Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, Rome, Italy.ORCID http://orcid.org/0009-0008-0139-4749
Giulia GliozzoDipartimento di Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, Rome, Italy.ORCID http://orcid.org/0009-0002-1065-6030
Daniela FignaniDiabetes Unit, Department of Medicine, Surgery and Neurosciences, University of Siena, Siena, Italy.ORCID http://orcid.org/0000-0001-8803-5846
Giuseppe QueroDipartimento di Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, Rome, Italy.ORCID http://orcid.org/0000-0002-0001-9479
Sergio AlfieriDipartimento di Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, Rome, Italy.ORCID http://orcid.org/0000-0002-7813-4426
Gianfranco Di GiuseppeDipartimento di Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, Rome, Italy.ORCID http://orcid.org/0000-0003-4506-5193
Gea CiccarelliDipartimento di Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, Rome, Italy.ORCID http://orcid.org/0009-0001-3621-6298
Angela DardanoDepartment of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy.ORCID http://orcid.org/0000-0001-6176-4379
Martina ParentiDepartment of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy.
Andrea MariInstitute of Neuroscience, National Research Council, Padova, Italy.ORCID http://orcid.org/0000-0002-1436-5591
Roberto BizzottoInstitute of Neuroscience, National Research Council, Padova, Italy.ORCID http://orcid.org/0000-0002-8251-1730
Giuseppe DanieleDepartment of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy.ORCID http://orcid.org/0000-0001-6301-9161
Andrea GiaccariDipartimento di Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, Rome, Italy.ORCID http://orcid.org/0000-0002-7462-7792
Francesco DottaDiabetes Unit, Department of Medicine, Surgery and Neurosciences, University of Siena, Siena, Italy. francesco.dotta@unisi.it.ORCID http://orcid.org/0000-0003-4947-7478
Guido SebastianiDiabetes Unit, Department of Medicine, Surgery and Neurosciences, University of Siena, Siena, Italy.ORCID http://orcid.org/0000-0003-4374-8564
Teresa MezzaDipartimento di Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, Rome, Italy.ORCID http://orcid.org/0000-0001-5407-9576

Funding

Ministero della Salute GR-2018-12365577Ministero della Salute T4-AN-07Ministero dell'Università e della Ricerca 2022FRBXHYMinistero dell'Università e della Ricerca 2022TJWNLLMinistero dell'Università e della Ricerca CN00000041Ministero dell'Università e della Ricerca P2022445ESMinistero dell'Università e della Ricerca P2022EB5B8Ministero dell'Università e della Ricerca PNC 0000001 D3 4 Health
6 · The paper itself

Abstract

aims/hypothesisType 2 diabetes mellitus is a multifactorial disease marked by progressive beta cell dysfunction; however, no reliable, easily measurable circulating biomarkers are currently available to track this decline. As microRNAs (miRNAs) tightly regulate beta cell physiology and are secreted and found in blood, we investigated whether specific circulating miRNAs reflect in vivo beta cell function in living donors.

methodsWe conducted a cross-sectional study on two independent cohorts: a discovery cohort comprising 78 individuals with different levels of glucose tolerance [23 with normal glucose tolerance (NGT), 22 with impaired glucose tolerance (IGT) and 33 with type 2 diabetes] and a validation cohort comprising 158 individuals (71 non-diabetic individuals and 87 with type 2 diabetes) who were administered an oral glucose tolerance test (OGTT) and/or a mixed meal test (MMT) with measurement of glucose, insulin and C-peptide. We profiled plasma RNA by small RNA sequencing, and analysed differences between glucose tolerance groups using DESeq2. We used linear regression analyses to determine the association between miRNA abundance and clinical and metabolic measures. We validated selected miRNAs using droplet digital PCR (ddPCR). Finally, we specified a set of features that were used as an input for a LASSO model to select a biomarker signature that was able to estimate beta cell rate sensitivity (RS) values as a measure of beta cell function.

resultsWe identified 11 miRNAs that were differentially expressed across the three glucose tolerance groups of the discovery cohort. Integrated analyses pinpointed a three-miRNA signature (miR-34a-5p, miR-1306-5p and miR-335-5p) that correlated with beta cell RS, which is an early indicator of insulin secretory impairment. We incorporated this panel of selected miRNAs with age and 1 h post-load glucose into a LASSO regression model that enabled discrimination of RS values (Spearman's ρ=0.43, p<0.05). We also confirmed model performance in an additional cohort of 71 non-diabetic individuals and 87 individuals with type 2 diabetes (Spearman's ρ=0.23, p<0.05). To provide proof of concept for potential clinical use, we substituted basal glucose for 1 h post-load glucose while retaining miRNA levels and age; this adaptation preserved the significance of the model in the discovery cohort (Spearman's ρ=0.46, p<0.05), and showed an interesting, but not significant, association in the validation cohort (Spearman's ρ=0.15, p=0.061). CONCLUSIONS/

interpretationThis three-miRNA signature combined with simple clinical parameters constitutes a promising biomarker for early beta cell dysfunction and type 2 diabetes progression that deserves further validation in additional cohorts.

Indexed as

Diabetes Mellitus, Type 2Glucose IntoleranceInsulin-Secreting CellsMicroRNAsAdultBiomarkersBlood GlucoseCross-Sectional StudiesFemaleGlucose Tolerance TestHumansInsulinMaleMiddle AgedBiomarkersBlood GlucoseInsulinMicroRNAsBeta cell functionBiomarkerMicroRNARate sensitivityType 2 diabetes

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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.