Evidence map›Paper›PMID 37749569›Full record

ArticleCardiovascular diabetology2023

Microvesicle-associated and circulating microRNAs in diabetic dyslipidemia: miR-218, miR-132, miR-143, and miR-21, miR-122, miR-155 have biomarker potential.

Miruna Nemecz, Diana Simona Stefan, Ioana Karla Comarița, Alina Constantin, Gabriela Tanko, Cristian Guja, Adriana Georgescu

Open access · goldAbstract read
In one paragraph

Article in Cardiovascular diabetology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
3.7field-weighted citation impact, top 6% 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

27 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.

  1. Pooled it
  2. Biochemical and Molecular Markers Among Prediabetic and Type 2 Diabetes Mellitus Patients.International journal of endocrinology and metabolism · 2026
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  20. Cholesterol promotesLife science alliance · 2024
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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

7 authors at 1 institution in 1 country.

Miruna NemeczInstitute of Cellular Biology and Pathology 'Nicolae Simionescu' of the Romanian Academy, Bucharest, Romania. miruna.nemecz@icbp.ro.
Diana Simona StefanNational Institute of Diabetes, Nutrition and Metabolic Disease 'Prof. Dr. Nicolae Constantin Paulescu', Bucharest, Romania.
Ioana Karla ComarițaInstitute of Cellular Biology and Pathology 'Nicolae Simionescu' of the Romanian Academy, Bucharest, Romania.
Alina ConstantinInstitute of Cellular Biology and Pathology 'Nicolae Simionescu' of the Romanian Academy, Bucharest, Romania.
Gabriela TankoInstitute of Cellular Biology and Pathology 'Nicolae Simionescu' of the Romanian Academy, Bucharest, Romania.
Cristian GujaNational Institute of Diabetes, Nutrition and Metabolic Disease 'Prof. Dr. Nicolae Constantin Paulescu', Bucharest, Romania.
Adriana GeorgescuInstitute of Cellular Biology and Pathology 'Nicolae Simionescu' of the Romanian Academy, Bucharest, Romania. adriana.georgescu@icbp.ro.
Romanian Academy · RO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCirculating MicroRNAs (miRNAs) carried by microvesicles (MVs) have various physiological and pathological functions by post-transcriptional regulation of gene expression being considered markers for many diseases including diabetes and dyslipidemia. We aimed to identify new common miRNAs both in MVs and plasma that could be predictive biomarkers for diabetic dyslipidemia evolution.

methodsFor this purpose, plasma from 63 participants in the study (17 type 2 diabetic patients, 17 patients with type 2 diabetes and dyslipidemia, 14 patients with dyslipidemia alone and 15 clinically healthy persons without diabetes or dyslipidemia) was used for the analysis of circulating cytokines, MVs, miRNAs and MV-associated miRNAs.

resultsThe results uncovered three miRNAs, miR-218, miR-132 and miR-143, whose expression was found to be significantly up-regulated in both circulating MVs and plasma from diabetic patients with dyslipidemia. These miRNAs showed significant correlations with important plasma markers, representative of this pathology. Thus, MV/plasma miR-218 was negatively correlated with the levels of erythrocyte MVs, plasma miR-132 was positively connected with MV miR-132 and negatively with uric acid and erythrocyte plasma levels, and plasma miR-143 was negatively related with creatinine levels and diastolic blood pressure. Also, three miRNAs common to MV and plasma, namely miR-21, miR-122, and miR-155, were identified to be down-regulated and up-regulated, respectively, in diabetic dyslipidemia. In addition, MV miR-21 was positively linked with cholesterol plasma levels and plasma miR-21 with TNFα plasma levels, MV miR-122 was negatively correlated with LDL-c levels and plasma miR-122 with creatinine and diastolic blood pressure and positively with MV miR-126 levels, MV miR-155 was positively associated with cholesterol and total MV levels and negatively with HDL-c levels, whereas plasma miR-155 was positively correlated with Il-1β plasma levels and total MV levels and negatively with MV miR-223 levels.

conclusionsIn conclusion, miR-218, miR-132, miR-143, and miR-21, miR-122, miR-155 show potential as biomarkers for diabetic dyslipidemia, but there is a need for more in-depth studies. These findings bring new information regarding the molecular biomarkers specific to diabetic dyslipidemia and could have important implications for the treatment of patients affected by this pathology.

Indexed as

Circulating MicroRNADiabetes Mellitus, Type 2DyslipidemiasMicroRNAsBiomarkersCreatinineHumansBiomarkersCirculating MicroRNACreatinineMicroRNAsMIRN122 microRNA, humanMIRN132 microRNA, humanMIRN143 microRNA, humanMIRN155 microRNA, humanMIRN218 microRNA, humanMIRN21 microRNA, humanDiabetic dyslipidemiamicroRNAsMicrovesicles

Identifiers

PMID37749569
PMCPMC10521428
OpenAlexW4387013000

What Socratic holds

Textmetadata
LicenceCC BY
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.