Evidence map›Paper›PMID 39471136›Full record

ArticlePloS one2024

Profiling of five urinary exosomal miRNAs for the differential diagnosis of patients with diabetic kidney disease and focal segmental glomerulosclerosis.

Sinan Trabulus, Mehmet Seyit Zor, Selma Alagoz, Mevlut Tamer Dincer, Meral Meşe, Erkan Yilmaz, Eda Tahir Turanli, Nurhan Seyahi

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

8 authors.

Sinan TrabulusDivision of Nephrology, Department of Internal Medicine, Cerrahpasa Medical Faculty, Istanbul University-Cerrahpasa, Istanbul, Turkey.ORCID 0000-0003-3843-5950
Mehmet Seyit ZorDepartment of Molecular Biology and Genetics, Faculty of Science and Letters, Istanbul Technical University, Istanbul, Turkey.
Selma AlagozDivision of Nephrology, Bagcilar Training and Research Hospital, University of Health Sciences, Istanbul, Turkey.
Mevlut Tamer DincerDivision of Nephrology, Department of Internal Medicine, Cerrahpasa Medical Faculty, Istanbul University-Cerrahpasa, Istanbul, Turkey.
Meral MeşeDivision of Nephrology, Kartal Lutfi Kirdar Training and Research Hospital, University of Health Sciences, Istanbul, Turkey.
Erkan YilmazTissue Typing Laboratory, Cerrahpasa Medical Faculty, Istanbul University-Cerrahpasa, Istanbul, Turkey.
Eda Tahir TuranliDepartment of Molecular Biology and Genetics, Faculty of Engineering and Natural Sciences, Acibadem University, Istanbul, Turkey.
Nurhan SeyahiDivision of Nephrology, Department of Internal Medicine, Cerrahpasa Medical Faculty, Istanbul University-Cerrahpasa, Istanbul, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe objective of this study is to investigate the diagnostic utility of microRNAs (miRNAs) for distinguishing between urine samples from patients with Diabetic Kidney Disease (DKD) and those with Focal Segmental Glomerulosclerosis (FSGS).

methodsIn this multicentric, cross-sectional investigation, we enrolled patients diagnosed with DKD, individuals with primary biopsy-proven FSGS, and healthy controls. The top 5 miRNAs (hsa-mir-21, hsa-mir-30a, hsa-mir-193a, hsa-mir-196a, hsa-mir-200a) were selected to quantify miRNAs in urine samples. Isolation of targeted miRNAs was performed from urinary exosomes, and the quantitative profile of the isolated miRNAs was measured by RT-qPCR. The ΔΔCt method was implemented to calculate the fold differences between disease and control samples.

resultsThirteen DKD patients, 11 FSGS patients, and 14 healthy controls were included in this study. Hsa-mir-21 and hsa-mir-30a exhibited distinct regulation in both groups, with upregulation observed in FSGS and downregulation in DKD (hsa-mir-21 in DKD (0.668 ± 0.25, p < 0.0005) and FSGS (2.267 ± 1.138, p < 0.0077); hsa-mir-30a in DKD (0.874 ± 0.254, p = 0.079) and FSGS (1.378 ± 0.312, p < 0.0006)). Hsa-mir-193a exhibited significant dysregulation in DKD (1.017 ± 0.413, p < 0.029) but not in FSGS (4.18 ± 1.528, p = 0.058). Hsa-mir-196a and hsa-mir-200a showed upregulation in patient groups (hsa-mir-196a in DKD (1.278 ± 0.527, p = 0.074) and FSGS (2.47 ± 0.911, p < 0.0003); hsa-mir-200a in DKD (1.909 ± 0.825, p = 0.082) and FSGS (1.301 ± 0.358, p < 0.008)).

conclusionSpecific miRNAs, particularly miR-21, miR-30a, miR-196a, and miR-200a, might play a role in the pathogenesis of kidney diseases and could potentially serve as biomarkers to distinguish between FSGS and DKD patients.

Indexed as

Diabetic NephropathiesExosomesGlomerulosclerosis, Focal SegmentalMicroRNAsAdultBiomarkersCase-Control StudiesCross-Sectional StudiesDiagnosis, DifferentialFemaleGene Expression ProfilingHumansMaleMiddle AgedBiomarkersMicroRNAsMIRN193 microRNA, humanMIRN196 microRNA, humanMIRN200 microRNA, humanMIRN21 microRNA, humanMIRN30a microRNA, human

Identifiers

PMID39471136
PMCPMC11521285

What Socratic holds

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LicenceCC BY
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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 Socratic graph.