Evidence map›Paper›PMID 41469432›Full record

ArticleScientific reports2025

Utility of plasma MicroRNA profiling as diagnostic biomarker in immune system activation and inflammation and early predictor of severity in patients with COVID-19.

Martina Schiavello, Barbara Vizio, Tiziana Sanavia, Ornella Bosco, Chiara Dini, Paolo Cagna Vallino, Emanuele Pivetta, Fulvio Morello, Piero Fariselli, Giuseppe Montrucchio and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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. Article
  2. Article
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.

Martina Schiavello *Department of Medical Sciences, University of Turin, Via Genova 3, Turin, 10126, Italy.
Barbara Vizio *Department of Medical Sciences, University of Turin, Via Genova 3, Turin, 10126, Italy.
Tiziana SanaviaAI and Computational Biomedicine Unit, Department of Medical Sciences, University of Turin, via Santena 19, Turin, 10126, Italy.
Ornella BoscoDepartment of Medical Sciences, University of Turin, Via Genova 3, Turin, 10126, Italy.
Chiara DiniDepartment of Medical Sciences, University of Turin, Via Genova 3, Turin, 10126, Italy.
Paolo Cagna VallinoDepartment of Medical Sciences, University of Turin, Via Genova 3, Turin, 10126, Italy.
Emanuele PivettaDepartment of Medical Sciences, University of Turin, Via Genova 3, Turin, 10126, Italy.
Fulvio MorelloDepartment of Medical Sciences, University of Turin, Via Genova 3, Turin, 10126, Italy.
Piero FariselliAI and Computational Biomedicine Unit, Department of Medical Sciences, University of Turin, via Santena 19, Turin, 10126, Italy.
Giuseppe MontrucchioDepartment of Medical Sciences, University of Turin, Via Genova 3, Turin, 10126, Italy.
Enrico LupiaDepartment of Medical Sciences, University of Turin, Via Genova 3, Turin, 10126, Italy. enrico.lupia@unito.it.

Funding

Project of National Relevence (PRIN) 2022BPNY3E
6 · The paper itself

Abstract

The clinical course of Coronavirus disease 2019 (COVID-19) ranges from mild symptoms to severe complications, including respiratory failure and thromboembolic events. MicroRNAs (miRNAs) are small non-coding RNAs involved in gene regulation and may serve as biomarkers. This study aimed to identify plasma miRNAs that could serve as biomarkers for diagnosing immune system disorders and inflammation, and for prognostic stratification of patients with COVID-19. We enrolled 40 patients with suspected COVID-19 at Emergency Room admission; infection was confirmed in 30 of them. Ten non-COVID-19 patients and 10 healthy subjects were included for comparison. Among the COVID-19 group, 26 hospitalized patients were followed and stratified by disease severity (good vs. poor prognosis). Plasma miRNA profiling and single-tube validation were performed using qRT-PCR, supported by in silico miRNA-mRNA prediction and pathway enrichment analysis. Expressions of miR-199a-5p, miR-142-3p, miR-133a-3p and miR-545-3p were higher in COVID-19 patients vs. healthy subjects. Moreover, miR-133a-3p and miR-545-3p were increased in COVID-19 vs. non-COVID-19 patients. miR-423-3p, miR-106b-5p, miR-142-3p and miR-369-3p were significantly elevated in patients who later developed respiratory failure. Bioinformatics analysis suggested that these miRNAs are involved in immune and inflammation pathways. Plasma miRNA profiling may be a promising non-invasive tool for COVID-19 diagnosis and prediction of severity.

Indexed as

COVID-19InflammationMicroRNAsAdultAgedBiomarkersCase-Control StudiesFemaleGene Expression ProfilingHumansMaleMiddle AgedPrognosisSARS-CoV-2Severity of Illness IndexBiomarkersMicroRNAsBioinformaticsBiomarkersCOVID-19MiRNA profiling

Identifiers

PMID41469432
PMCPMC12770467

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.