Evidence map›Paper›PMID 38332929›Full record

ArticleHealth science reports2024

Analyzing the expression pattern of the noncoding RNAs (HOTAIR, PVT-1, XIST, H19, and miRNA-34a) in PBMC samples of patients with COVID-19, according to the disease severity in Iran during 2022-2023: A cross-sectional study.

Khadijeh Khanaliha, Javid Sadri Nahand, AliReza Khatami, Hamed Mirzaei, Sara Chavoshpour, Mohammad Taghizadieh, Mohammad Karimzadeh, Tahereh Donyavi, Farah Bokharaei-Salim

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Article in Health science reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

4 citing papers in PubMed, 11 citations in OpenAlex.

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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

9 authors at 4 institutions in 1 country.

Khadijeh KhanalihaResearch Center of Pediatric Infectious Diseases, Institute of Immunology and Infectious Diseases Iran University of Medical Sciences Tehran Iran.
Javid Sadri NahandInfectious and Tropical Diseases Research Center Tabriz University of Medical Sciences Tabriz Iran.ORCID https://orcid.org/0000-0002-5808-6869
AliReza KhatamiDepartment of Virology Iran University of Medical Sciences Tehran Iran.
Hamed MirzaeiResearch Center for Biochemistry and Nutrition in Metabolic Diseases Kashan University of Medical Sciences Kashan Iran.
Sara ChavoshpourDepartment of Virology Tehran University of Medical Sciences Tehran Iran.
Mohammad TaghizadiehDepartment of Pathology, Faculty of Medicine Tabriz University of Medical Sciences Tabriz Iran.
Mohammad KarimzadehCore Research Facilities (CRF) Isfahan University of Medical Science Isfahan Iran.
Tahereh DonyaviDepartment of Medical Biotechnology, Faculty of Allied Medicine Iran University of Medical Sciences Tehran Iran.
Farah Bokharaei-SalimDepartment of Virology Iran University of Medical Sciences Tehran Iran.ORCID 0000-0002-5367-0847
Iran University of Medical Sciences · IRTabriz University of Medical Sciences · IRIsfahan University of Medical Sciences · IRKashan University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and aims: MicroRNAs (miRNAs) and long noncoding RNAs (lncRNAs) are well-known types of noncoding RNAs (ncRNAs), which have been known as the key regulators of gene expression. They can play critical roles in viral infection by regulating the host immune response and interacting with genes in the viral genome. In this regard, ncRNAs can be employed as biomarkers for viral diseases. The current study aimed to evaluate peripheral blood mononuclear cell (PBMC) ncRNAs (lncRNAs-homeobox C antisense intergenic RNA [HOTAIR], -H19, X-inactive-specific transcript [XIST], plasmacytoma variant translocation 1 [PVT-1], and miR-34a) as diagnostic biomarkers to differentiate severe COVID-19 cases from mild ones. Methods: Candidate ncRNAs were selected according to previous studies and assessed by real-time polymerase chain reaction in the PBMC samples of patients with severe coronavirus disease 2019 (COVID-19) ( Results: The results demonstrated that the expression pattern of the selected ncRNAs was significantly different between the studied groups. The levels of HOTAIR, XIST, and miR-34a were remarkably overexpressed in the severe COVID-19 group in comparison with the mild COVID-19 group, and in return, the PVT-1 levels were lower than in the mild COVID-19 group. Interestingly, the XIST expression level in men with severe COVID-19 was higher compared to women with mild COVID-19. ROC results suggested that HOTAIR and PVT-1 could serve as useful biomarkers for screening mild COVID-19 from severe COVID-19. Conclusions: Overall, different expression patterns of the selected ncRNAs and ROC curve results revealed that these factors can contribute to COVID-19 pathogenicity and can be considered diagnostic markers of COVID-19 severe outcomes.

Indexed as

biomarkerlong noncoding RNAsmiR‐34aSARS‐CoV‐2severe COVID‐19

Identifiers

PMID38332929
PMCPMC10850438
OpenAlexW4391649720

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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.