Evidence map›Paper›PMID 38804362›Full record

ReviewNon-coding RNA2024

A Systematic Review and Meta-Analysis of microRNA Profiling Studies in Chronic Kidney Diseases.

Gantsetseg Garmaa, Stefania Bunduc, Tamás Kói, Péter Hegyi, Dezső Csupor, Dariimaa Ganbat, Fanni Dembrovszky, Fanni Adél Meznerics, Ailar Nasirzadeh, Cristina Barbagallo and 1 more

Erratum issuedAbstract readReview
In one paragraph

Review in Non-coding RNA, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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  12. PeerJ · 2024
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Gantsetseg GarmaaInstitute of Translational Medicine, Semmelweis University, Nagyvárad tér 4, 1089 Budapest, Hungary.ORCID 0000-0001-9631-8635
Stefania BunducCenter for Translational Medicine, Semmelweis University, Üllői út 26, 1085 Budapest, Hungary.ORCID 0000-0001-6978-4526
Tamás KóiCenter for Translational Medicine, Semmelweis University, Üllői út 26, 1085 Budapest, Hungary.
Péter HegyiCenter for Translational Medicine, Semmelweis University, Üllői út 26, 1085 Budapest, Hungary.
Dezső CsuporCenter for Translational Medicine, Semmelweis University, Üllői út 26, 1085 Budapest, Hungary.ORCID 0000-0002-4088-3333
Dariimaa GanbatDepartment of Pathology, School of Medicine, Mongolian National University of Medical Sciences, Ulan-Bator 14210, Mongolia.ORCID 0000-0003-2929-8392
Fanni DembrovszkyCenter for Translational Medicine, Semmelweis University, Üllői út 26, 1085 Budapest, Hungary.ORCID 0000-0001-6953-3591
Fanni Adél MeznericsCenter for Translational Medicine, Semmelweis University, Üllői út 26, 1085 Budapest, Hungary.
Ailar NasirzadehInstitute of Translational Medicine, Semmelweis University, Nagyvárad tér 4, 1089 Budapest, Hungary.
Cristina BarbagalloSection of Biology and Genetics "G. Sichel", Department of Biomedical and Biotechnological Sciences, University of Catania, 95123 Catania, Italy.ORCID 0000-0002-6769-4516
Gábor KökényInstitute of Translational Medicine, Semmelweis University, Nagyvárad tér 4, 1089 Budapest, Hungary.ORCID 0000-0002-0345-6914

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic kidney disease (CKD) represents an increasing health burden. Evidence suggests the importance of miRNA in diagnosing CKD, yet the reports are inconsistent. This study aimed to determine novel miRNA biomarkers and potential therapeutic targets from hypothesis-free miRNA profiling studies in human and murine CKDs. Comprehensive literature searches were conducted on five databases. Subgroup analyses of kidney diseases, sample types, disease stages, and species were conducted. A total of 38 human and 12 murine eligible studies were analyzed using Robust Rank Aggregation (RRA) and vote-counting analyses. Gene set enrichment analyses of miRNA signatures in each kidney disease were conducted using DIANA-miRPath v4.0 and MIENTURNET. As a result, top target genes, Gene Ontology terms, the interaction network between miRNA and target genes, and molecular pathways in each kidney disease were identified. According to vote-counting analysis, 145 miRNAs were dysregulated in human kidney diseases, and 32 were dysregulated in murine CKD models. By RRA, miR-26a-5p was significantly reduced in the kidney tissue of Lupus nephritis (LN), while miR-107 was decreased in LN patients' blood samples. In both species, epithelial-mesenchymal transition, Notch, mTOR signaling, apoptosis, G2/M checkpoint, and hypoxia were the most enriched pathways. These miRNA signatures and their target genes must be validated in large patient cohort studies.

Indexed as

bloodchronic kidney diseasemeta-analysismicroRNAurine

Identifiers

PMID38804362
PMCPMC11130806

What OpenQuestion holds

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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.