Evidence map›Paper›PMID 37325660›Full record

Observational studyFrontiers in immunology2023

A plasmatic score using a miRNA signature and CXCL-10 for accurate prediction and diagnosis of liver allograft rejection.

Olga Millán, Pablo Ruiz, Judit Julian, Ana Lizana, Yiliam Fundora, Gonzalo Crespo, Jordi Colmenero, Miquel Navasa, Mercè Brunet

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
5.1field-weighted citation impact, top 4% of its field
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

12 citing papers in PubMed, 16 citations in OpenAlex.

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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

9 authors at 2 institutions in 1 country.

Olga MillánBiomedical Research Center in Hepatic and Digestive Diseases (CIBEREHD), Instituto de Salud Carlos III (ISCII), Madrid, Spain.
Pablo RuizLiver Unit, Hospital Clinic of Barcelona, Instituto de Investigaciones Biomédicas August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain.
Judit JulianPharmacology and Toxicology, Biochemistry and Molecular Genetics, Biomedical Diagnostic Center (CDB), Hospital Clinic of Barcelona, Instituto de Investigaciones Biomédicas August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain.
Ana LizanaPharmacology and Toxicology, Biochemistry and Molecular Genetics, Biomedical Diagnostic Center (CDB), Hospital Clinic of Barcelona, Instituto de Investigaciones Biomédicas August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain.
Yiliam FundoraBiomedical Research Center in Hepatic and Digestive Diseases (CIBEREHD), Instituto de Salud Carlos III (ISCII), Madrid, Spain.
Gonzalo CrespoBiomedical Research Center in Hepatic and Digestive Diseases (CIBEREHD), Instituto de Salud Carlos III (ISCII), Madrid, Spain.
Jordi ColmeneroBiomedical Research Center in Hepatic and Digestive Diseases (CIBEREHD), Instituto de Salud Carlos III (ISCII), Madrid, Spain.
Miquel NavasaBiomedical Research Center in Hepatic and Digestive Diseases (CIBEREHD), Instituto de Salud Carlos III (ISCII), Madrid, Spain.
Mercè BrunetBiomedical Research Center in Hepatic and Digestive Diseases (CIBEREHD), Instituto de Salud Carlos III (ISCII), Madrid, Spain.
Universitat de Barcelona · ESConsorci Institut D'Investigacions Biomediques August Pi I Sunyer · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The use of noninvasive biomarkers may avoid the need for liver biopsy (LB) and could guide immunosuppression adjustment in liver transplantation (LT). The aims of this study were: to confirm the predictive and diagnostic capacity of plasmatic expression of miR-155-5p, miR-181a-5p, miR-122-5p and CXCL-10 for assessing T-cell mediated rejection (TCMR) risk; to develop a score based on a panel of noninvasive biomarkers to predict graft rejection risk and to validate this score in a separate cohort. Methods: A prospective, observational study was conducted with a cohort of 79 patients followed during the first year after LT. Plasma samples were collected at predetermined time points for the analysis of miRNAs and the CXCL-10. Patients with LFTs abnormalities were submitted to a LB to rule out rejection, assessing previous and concurrent expression of the biomarkers to evaluate their predictive and diagnostic ability. Information from 86 patients included in a previous study was collected and used as a validation cohort. Results: Twenty-four rejection episodes were diagnosed in 22 patients. Plasmatic CXCL-10 concentration and the expression of the three miRNAs were significantly elevated prior to and at the moment of the diagnosis of rejection. We developed a logistic model for rejection prediction and diagnosis, which included CXCL-10, miR-155-5p and miR-181a-5p. The area under the ROC curve (AUROC) for rejection prediction was 0.975 (79.6% sensitivity, 99.1% specificity, 90,7% PPV; 97.7% NPV; 97.1% correctly classified) and 0.99 for diagnosis (87.5% sensitivity, 99.5% specificity, 91.3% PPV; 99.3% NPV; 98.9% correctly classified). In the validation cohort (n=86; 14 rejections), the same cut-off points were used obtaining AUROCs for rejection prediction and diagnosis of 0.89 and 0.92 respectively. In patients with graft dysfunction in both cohorts the score could discriminate those with rejection regarding other causes with an AUROC of 0.98 (97.3% sensitivity, 94.1%specificity). Conclusion: These results suggest that the clinical implementation of the monitoring of this noninvasive plasmatic score may allow the prediction and diagnosis of rejection and identify patients with graft dysfunction due to rejection, helping with a more efficient guide for immunosuppressive therapy adjustment. This finding warrants the development of prospective biomarker-guided clinical trials.

Indexed as

MicroRNAsAllograftsBiomarkersHumansLiverTransplantation, HomologousBiomarkersMicroRNAsCXCL-10diagnosisliver transplant (LT)miRNAsnoninvasive biomarkerspredictionrejectionscore

Identifiers

PMID37325660
PMCPMC10265684
OpenAlexW4378907125

What OpenQuestion holds

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LicenceCC BY
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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 OpenQuestion graph.