Evidence map›Paper›PMID 24279768›Full record

ArticleBMC research notes2013

Identifying common and specific microRNAs expressed in peripheral blood mononuclear cell of type 1, type 2, and gestational diabetes mellitus patients.

Cristhianna V A Collares, Adriane F Evangelista, Danilo J Xavier, Diane M Rassi, Thais Arns, Maria C Foss-Freitas, Milton C Foss, Denis Puthier, Elza T Sakamoto-Hojo, Geraldo A Passos and 1 more

Open access · goldAbstract read
In one paragraph

Article in BMC research notes, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 82 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
82citing papers in PubMed, 2 pooled it
4.5field-weighted citation impact, top 5% 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

82 citing papers in PubMed, 2 syntheses or guidelines pooled it, 158 citations in OpenAlex.

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  14. First Trimester Placental Biomarkers for Pregnancy Outcomes.International journal of molecular sciences · 2024
    Review
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  16. Increased intracellular miR-142 in adults with Type 1 diabetes.Journal of diabetes and its complications · 2023
    Article
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  18. Article
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22 more citing papers are in PubMed but not listed here.

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 at 3 institutions in 2 countries.

Cristhianna V A CollaresDepartment of Medicine, Division of Clinical Immunology, Faculty of Medicine of Ribeirao Preto, University of São Paulo, 14048-900 Ribeirao Preto, SP, Brazil. eadonadi@fmrp.usp.br.
Adriane F Evangelista
Danilo J Xavier
Diane M Rassi
Thais Arns
Maria C Foss-Freitas
Milton C Foss
Denis Puthier
Elza T Sakamoto-Hojo
Geraldo A Passos
Eduardo A Donadi
Universidade de São Paulo · BRAix-Marseille Université · FRUniversidade de Ribeirão Preto · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRegardless the regulatory function of microRNAs (miRNA), their differential expression pattern has been used to define miRNA signatures and to disclose disease biomarkers. To address the question of whether patients presenting the different types of diabetes mellitus could be distinguished on the basis of their miRNA and mRNA expression profiling, we obtained peripheral blood mononuclear cell (PBMC) RNAs from 7 type 1 (T1D), 7 type 2 (T2D), and 6 gestational diabetes (GDM) patients, which were hybridized to Agilent miRNA and mRNA microarrays. Data quantification and quality control were obtained using the Feature Extraction software, and data distribution was normalized using quantile function implemented in the Aroma light package. Differentially expressed miRNAs/mRNAs were identified using Rank products, comparing T1DxGDM, T2DxGDM and T1DxT2D. Hierarchical clustering was performed using the average linkage criterion with Pearson uncentered distance as metrics.

resultsThe use of the same microarrays platform permitted the identification of sets of shared or specific miRNAs/mRNA interaction for each type of diabetes. Nine miRNAs (hsa-miR-126, hsa-miR-1307, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-144, hsa-miR-199a-5p, hsa-miR-27a, hsa-miR-29b, and hsa-miR-342-3p) were shared among T1D, T2D and GDM, and additional specific miRNAs were identified for T1D (20 miRNAs), T2D (14) and GDM (19) patients. ROC curves allowed the identification of specific and relevant (greater AUC values) miRNAs for each type of diabetes, including: i) hsa-miR-1274a, hsa-miR-1274b and hsa-let-7f for T1D; ii) hsa-miR-222, hsa-miR-30e and hsa-miR-140-3p for T2D, and iii) hsa-miR-181a and hsa-miR-1268 for GDM. Many of these miRNAs targeted mRNAs associated with diabetes pathogenesis.

conclusionsThese results indicate that PBMC can be used as reporter cells to characterize the miRNA expression profiling disclosed by the different diabetes mellitus manifestations. Shared miRNAs may characterize diabetes as a metabolic and inflammatory disorder, whereas specific miRNAs may represent biological markers for each type of diabetes, deserving further attention.

Indexed as

Diabetes, GestationalDiabetes Mellitus, Type 1Diabetes Mellitus, Type 2FemaleHumansMicroRNAsMonocytesPregnancyMicroRNAs

Identifiers

PMID24279768
PMCPMC4222092
OpenAlexW2051740071

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.