Evidence map›Paper›PMID 39500909›Full record

ArticleScientific reports2024

Data normalization of plasma miRNA profiling from patients with COVID-19.

Julia Tiemi Siguemoto, Carolini Motta Neri, Nadine de Godoy Torso, Aline de Souza Nicoletti, Marília Berlofa Visacri, Carla Regina da Silva Correa da Ronda, Mauricio Wesley Perroud, Leonardo Oliveira Reis, Luiz Augusto Dos Santos, Nelson Durán and 3 more

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
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

13 authors.

Julia Tiemi Siguemoto *Faculty of Pharmaceutical Sciences, Universidade Estadual de Campinas, Campinas, 13083970, Brazil.
Carolini Motta Neri *Faculty of Pharmaceutical Sciences, Universidade Estadual de Campinas, Campinas, 13083970, Brazil.
Nadine de Godoy TorsoSchool of Medical Sciences, Universidade Estadual de Campinas, Campinas , 13083894, Brazil.
Aline de Souza NicolettiSchool of Medical Sciences, Universidade Estadual de Campinas, Campinas , 13083894, Brazil.
Marília Berlofa VisacriFaculty of Pharmaceutical Sciences, University of São Paulo, São Paulo, 05508-000, Brazil.
Carla Regina da Silva Correa da RondaFaculty of Pharmaceutical Sciences, Universidade Estadual de Campinas, Campinas, 13083970, Brazil.
Mauricio Wesley PerroudSchool of Medical Sciences, Universidade Estadual de Campinas, Campinas , 13083894, Brazil.
Leonardo Oliveira ReisSchool of Medical Sciences, Universidade Estadual de Campinas, Campinas , 13083894, Brazil.
Luiz Augusto Dos SantosHospital Municipal de Paulínia, Paulínia, SP, Brazil.
Nelson DuránSchool of Medical Sciences, Universidade Estadual de Campinas, Campinas , 13083894, Brazil.
Wagner José FávaroSchool of Medical Sciences, Universidade Estadual de Campinas, Campinas , 13083894, Brazil.
Eder de Carvalho PincinatoSchool of Medical Sciences, Universidade Estadual de Campinas, Campinas , 13083894, Brazil.
Patricia MorielFaculty of Pharmaceutical Sciences, Universidade Estadual de Campinas, Campinas, 13083970, Brazil. patricia.moriel@fcf.unicamp.br.

Funding

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior 88887.513100/2020-00Fundação de Amparo à Pesquisa do Estado de São Paulo 2021/04669-9Fundação de Amparo à Pesquisa do Estado de São Paulo 2021/12359-0Fundação de Amparo à Pesquisa do Estado de São Paulo 2021/12387-3
6 · The paper itself

Abstract

When using the reverse-transcription quantitative polymerase chain reaction (RT-qPCR) technique for quantitative assessment of microRNA (miRNA) expression, normalizing data using a stable endogenous gene is essential; however, no universally adequate reference gene exists. Therefore, in this study, we aimed to determine, via the RNA-Seq technique, the most adequate endogenous normalizer for the expression assessment of plasma miRNAs in patients with coronavirus disease 2019 (COVID-19). Two massive sequencing procedures were performed (a) to identify differentially expressed miRNAs between patients with COVID-19 and healthy volunteers (n = 12), and (b) to identify differentially expressed miRNAs between patients with severe COVID-19 and those with mild COVID-19 (n = 8). The endogenous normalizer candidates were selected according to the following criteria: (1) the miRNA must have a fold regulation = 1; (2) the miRNA must have a p-value > 0.990; and (3) the miRNAs that were discovered the longest ago should be selected. Four miRNAs (hsa-miR-34a-3p, hsa-miR-194-3p, hsa-miR-17-3p, and hsa-miR-205-3p) met all criteria and were selected for validation by RT-qPCR in a cohort of 125 patients. Of these, only hsa-miR-205-3p was eligible endogenous normalizers in the context of COVID-19 because their expression was stable between the compared groups.

Indexed as

COVID-19MicroRNAsSARS-CoV-2AdultAgedCase-Control StudiesFemaleGene Expression ProfilingHumansMaleMiddle AgedRNA-SeqMicroRNAsMIRN17 microRNA, humanMIRN194 microRNA, humanMIRN34 microRNA, humanCOVID-19Endogenous normalizerMicroRNAReference gene

Identifiers

PMID39500909
PMCPMC11538513

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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.