Evidence map›Paper›PMID 33251083›Full record

Article3 Biotech2020

Identification of potential mRNA panels for severe acute respiratory syndrome coronavirus 2 (COVID-19) diagnosis and treatment using microarray dataset and bioinformatics methods.

Basavaraj Vastrad, Chanabasayya Vastrad, Anandkumar Tengli

Open access · hybridAbstract read
In one paragraph

Article in 3 Biotech, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 14% 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

28 citing papers in PubMed, 1 synthesis or guideline pooled it, 46 citations in OpenAlex.

  1. The role of microRNAs in modulating SARS-CoV-2 infection in human cells: a systematic review.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2021
    Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. miRNAs: The Key Regulator of COVID-19 Disease.International journal of cell biology · 2022
    Review
  18. Review
  19. Article
  20. Frontiers in cellular and infection microbiology · 2022
    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

3 authors at 3 institutions in 1 country.

Basavaraj VastradDepartment of Pharmaceutics, SET`S College of Pharmacy, Dharwad, Karnataka 580002 India.ORCID 0000-0003-2202-7637
Chanabasayya VastradBiostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad, Karnataka 580001 India.ORCID 0000-0003-3615-4450
Anandkumar TengliDepartment of Pharmaceutical Chemistry, JSS College of Pharmacy, Mysuru and JSS Academy of Higher Education & Research, Mysuru, Karnataka 570015 India.ORCID 0000-0001-8076-928X
JSS Academy of Higher Education and Research · INNational Institute of Pharmaceutical Education and Research · INSri Dharmasthala Manjunatheshwara College of Dental Sciences & Hospital · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The goal of the present investigation is to identify the differentially expressed genes (DEGs) between SARS-CoV-2 infected and normal control samples to investigate the molecular mechanisms of infection with SARS-CoV-2. The microarray data of the dataset E-MTAB-8871 were retrieved from the ArrayExpress database. Pathway and Gene Ontology (GO) enrichment study, protein-protein interaction (PPI) network, modules, target gene-miRNA regulatory network, and target gene-TF regulatory network have been performed. Subsequently, the key genes were validated using an analysis of the receiver operating characteristic (ROC) curve. In SARS-CoV-2 infection, a total of 324 DEGs (76 up- and 248 down-regulated genes) were identified and enriched in a number of associated SARS-CoV-2 infection pathways and GO terms. Hub and target genes such as TP53, HRAS, MAPK11, RELA, IKZF3, IFNAR2, SKI, TNFRSF13C, JAK1, TRAF6, KLRF2, CD1A were identified from PPI network, target gene-miRNA regulatory network, and target gene-TF regulatory network. Study of the ROC showed that ten genes (CCL5, IFNAR2, JAK2, MX1, STAT1, BID, CD55, CD80, HAL-B, and HLA-DMA) were substantially involved in SARS-CoV-2 patients. The present investigation identified key genes and pathways that deepen our understanding of the molecular mechanisms of SARS-CoV-2 infection, and could be used for SARS-CoV-2 infection as diagnostic and therapeutic biomarkers.

Indexed as

Bioinformatics analysisBiomarkersDifferentially expressed genesProtein–protein interaction (PPI) networkSARS-CoV-2 infection

Identifiers

PMID33251083
PMCPMC7679428
OpenAlexW3085545636

What OpenQuestion holds

Textmetadata
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.