Evidence map›Paper›PMID 34696164›Full record

ArticleVaccines2021

SnoRNAs and miRNAs Networks Underlying COVID-19 Disease Severity.

Aijaz Parray, Fayaz Ahmad Mir, Asmma Doudin, Ahmad Iskandarani, Ibn Mohammed Masud Danjuma, Rahim Ayadathil Thazhhe Kuni, Alaaedin Abdelmajid, Ibrahim Abdelhafez, Rida Arif, Mohammad Mulhim and 7 more

Open access · goldAbstract read
In one paragraph

Article in Vaccines, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 2 pooled it
2.9field-weighted citation impact, top 7% 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

29 citing papers in PubMed, 2 syntheses or guidelines pooled it, 40 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Article
  5. Review
  6. Review
  7. Article
  8. Review
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Review
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. Review
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

17 authors at 5 institutions in 3 countries.

Aijaz ParrayThe Neuroscience Institute, Academic Health System, Hamad Medical Corporation, Doha 3050, Qatar.
Fayaz Ahmad MirQatar Metabolic Institute, Academic Health System, Hamad Medical Corporation, Doha 3050, Qatar.ORCID 0000-0003-1104-0852
Asmma DoudinDepartment of Math and Science, Community College of Qatar, Doha 7344, Qatar.
Ahmad IskandaraniQatar Metabolic Institute, Academic Health System, Hamad Medical Corporation, Doha 3050, Qatar.
Ibn Mohammed Masud DanjumaCollege of Medicine, QU Health, Qatar University, Doha 2713, Qatar.ORCID 0000-0003-2198-5278
Rahim Ayadathil Thazhhe KuniThe Neuroscience Institute, Academic Health System, Hamad Medical Corporation, Doha 3050, Qatar.
Alaaedin AbdelmajidCommunicable Diseases Center, Hamad Medical Corporation, Doha 3050, Qatar.
Ibrahim AbdelhafezCollege of Medicine, QU Health, Qatar University, Doha 2713, Qatar.ORCID 0000-0002-3050-9057
Rida ArifCollege of Medicine, QU Health, Qatar University, Doha 2713, Qatar.
Mohammad MulhimCommunicable Diseases Center, Hamad Medical Corporation, Doha 3050, Qatar.
Mohammad AbukhattabCommunicable Diseases Center, Hamad Medical Corporation, Doha 3050, Qatar.
Shoukat Rashhid DarDepartment of Emergency, Hamad Medical Corporation, Doha 3050, Qatar.
Ala-Eddin Al MoustafaCollege of Medicine, QU Health, Qatar University, Doha 2713, Qatar.ORCID 0000-0003-4452-3439
Eyad ElkordNatural and Medical Sciences Research Centre, University of Nizwa, Nizwa 208, Oman.ORCID 0000-0002-3868-0318
Abdul Latif Al KhalCommunicable Diseases Center, Hamad Medical Corporation, Doha 3050, Qatar.
Abdel-Naser ElzoukiCollege of Medicine, QU Health, Qatar University, Doha 2713, Qatar.
Farhan CyprianCollege of Medicine, QU Health, Qatar University, Doha 2713, Qatar.
Hamad Medical Corporation · QAQatar University · QAHamad General Hospital · QACommunity College of Qatar · QAUniversity of Nizwa · OM

Funding

Qatar University QUST-1-CMED-2021-2
6 · The paper itself

Abstract

There is a lack of predictive markers for early and rapid identification of disease progression in COVID-19 patients. Our study aims at identifying microRNAs (miRNAs)/small nucleolar RNAs (snoRNAs) as potential biomarkers of COVID-19 severity. Using differential expression analysis of microarray data (n = 29), we identified hsa-miR-1246, ACA40, hsa-miR-4532, hsa-miR-145-5p, and ACA18 as the top five differentially expressed transcripts in severe versus asymptomatic, and ACA40, hsa-miR-3609, ENSG00000212378 (SNORD78), hsa-miR-1231, hsa-miR-885-3p as the most significant five in severe versus mild cases. Moreover, we found that white blood cell (WBC) count, absolute neutrophil count (ANC), neutrophil (%), lymphocyte (%), red blood cell (RBC) count, hemoglobin, hematocrit, D-Dimer, and albumin are significantly correlated with the identified differentially expressed miRNAs and snoRNAs. We report a unique miRNA and snoRNA profile that is associated with a higher risk of severity in a cohort of SARS-CoV-2 infected patients. Altogether, we present a differential expression analysis of COVID-19-associated microRNA (miRNA)/small nucleolar RNA (snoRNA) signature, highlighting their importance in SARS-CoV-2 infection.

Indexed as

biomarkersCOVID-19miRNASARS-CoV-2snoRNA

Identifiers

PMID34696164
PMCPMC8538251
OpenAlexW3199742077

What OpenQuestion 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 OpenQuestion graph.