Evidence map›Paper›PMID 38511065›Full record

ArticleNon-coding RNA research2024

Plasma miRNAs as potential biomarkers for schizophrenia in a Jordanian cohort.

Mohammad Shboul, Amal Bani Domi, Abdulmalek Abu Zahra, Aws G Khasawneh, Reem Darweesh

Open access · goldAbstract read
In one paragraph

Article in Non-coding RNA research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.9field-weighted citation impact, top 9% 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

6 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. MicroRNAs as biomarkers and molecular mediators of cognitive dysfunction in schizophrenia.Journal of neural transmission (Vienna, Austria : 1996) · 2026
    Review
  3. Article
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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

5 authors at 1 institution in 1 country.

Mohammad ShboulDepartment of Medical Laboratory Sciences, Faculty of Medical Sciences, Jordan University of Science and Technology, P.O. Box 3030, Irbid, 22110, Jordan.
Amal Bani DomiDepartment of Medical Laboratory Sciences, Faculty of Medical Sciences, Jordan University of Science and Technology, P.O. Box 3030, Irbid, 22110, Jordan.
Abdulmalek Abu ZahraDepartment of Medical Laboratory Sciences, Faculty of Medical Sciences, Jordan University of Science and Technology, P.O. Box 3030, Irbid, 22110, Jordan.
Aws G KhasawnehDepartment of Neurosciences, Faculty of Medicine, Jordan University of Science and Technology, P.O. Box 3030, Irbid, 22110, Jordan.
Reem DarweeshDepartment of Medical Laboratory Sciences, Faculty of Medical Sciences, Jordan University of Science and Technology, P.O. Box 3030, Irbid, 22110, Jordan.
Jordan University of Science and Technology · JO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Schizophrenia (SZ), a complex and chronic neuropsychiatric disorder affecting approximately 1 % of the general population, presents diagnostic challenges due to the absence of reliable biomarkers, and relying mainly on clinical observations. MicroRNAs (miRNAs) signatures in a wide range of diseases, including psychiatric disorders, hold immense potential for serving as biomarkers. This study aimed to analyze the expression levels of specific microRNAs (miRNAs) namely miR-29b-3p, miR-106b-5p, and miR-199a-3p and explore their diagnostic potential for SZ in Jordanian patients. Methods: Small RNAs (miRNAs) were extracted from plasma samples of 30 SZ patients and 35 healthy controls. RNA was reverse transcribed and quantified by real-time polymerase chain reaction (qRT-PCR). The expression levels of three miRNAs (miR-29b-3p, miR-106b-5p and miR-199a-3p) were analyzed. Receiver operating characteristic (ROC) curves analysis was performed to evaluate diagnostic value of these miRNAs. Target genes prediction, functional enrichment and pathway analyses were done using miRWalk and Metascape. STRING database was used to construct protein-protein network and identify hub genes. Results: Notably, miR-106b-5p and miR-199a-3p were significantly upregulated (p < 0.0001), while miRNA-29b-3p was downregulated (p < 0.0001) in SZ patients compared to controls. The diagnostic potential was assessed through ROC curves, revealing substantial diagnostic value for miR-199a-3p (AUC: 0.979) followed by miR-106b-5p (AUC: 0.774), with limited diagnostic efficacy for miR-29b-3p. Additionally, bioinformatic analyses for the predicted target genes of the diagnostically significant miRNAs uncovered Gene Ontology (GO) terms related to neurological development, including morphogenesis, which is involved in neuron differentiation, brain development, head development, and neuron projection morphogenesis. These findings highlight a potential connection between the identified miRNAs and SZ pathophysiology in the studied Jordanian population. Furthermore, a protein-protein interaction network from the target genes identified in association with neurological development in the Gene Ontology (GO) terms deepens our comprehension of the molecular landscape of the regulated target genes. Conclusions: This comprehensive exploration highlights the promising role of miRNAs in unraveling intricate molecular pathways associated with SZ in the Jordanian cohort and suggests that plasma miRNAs could serve as reliable biomarkers for SZ diagnosis and disease progression. Remarkably, this study represents the first investigation into the role of circulating miRNA expression among Jordanian patients with SZ, providing valuable insights into the diagnostic landscape of this disorder.

Indexed as

BiomarkersMicroRNAsPlasmaSchizophreniaTarget genes

Identifiers

PMID38511065
PMCPMC10950580
OpenAlexW4391345384

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.