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Identification of Key Genes and Pathways in Persistent Hyperplastic Primary Vitreous of the Eye Using Bioinformatic Analysis

Overview of attention for article published in Frontiers in Medicine, August 2021
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (61st percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

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1 Wikipedia page

Citations

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14 Dimensions

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20 Mendeley
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Title
Identification of Key Genes and Pathways in Persistent Hyperplastic Primary Vitreous of the Eye Using Bioinformatic Analysis
Published in
Frontiers in Medicine, August 2021
DOI 10.3389/fmed.2021.690594
Pubmed ID
Authors

Derin M. Thomas, Chitra Kannabiran, D. Balasubramanian

Abstract

Background: The failure of the embryonic hyaloid vascular system to regress naturally causes persistent hyperplastic primary vitreous (PHPV), a congenital eye disease. PHPVs molecular pathway, candidate genes, and drug targets are unknown. The current paper describes a comprehensive analysis using bioinformatics to identify the key genes and molecular pathways associated with PHPV, and to evaluate potential therapeutic agents for disease management. Methods: The genes associated with PHPV were identified using the pubmed2ensembl text mining platform. GeneCodis was employed to evaluate the Gene Ontology (GO) biological process terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Search Tool for the Retrieval of Interacting Genes (STRING) constructed a protein-protein interaction (PPI) network from the text mining genes (TMGs) in Cytoscape. The significant modules were clustered using Molecular Complex Detection (MCODE), and the GO and KEGG analysis for the hub genes were analyzed with the Database of Annotation, Visualization and Integrated Discovery (DAVID) tool. ClueGO, CluePedia, and ShinyGo were used to illustrate the functions and pathways of the clustered hub genes in a significant module. The Drug-Gene Interaction database (DGIdb) was used to evaluate drug-gene interactions of the hub genes to identify potential PHPV drug candidates. Results: A total of 50 genes associated with PHPV were identified. Overall, 35 enriched GO terms and 15 KEGG pathways were discovered by the gene functional enrichment analysis. Two gene modules were obtained from the PPI network constructed with 31 nodes with 42 edges using MCODE. We selected 14 hub genes as core candidate genes: TP53, VEGFA, SMAD2, CDKN2A, FOXC, FZD4, LRP5, KDR, FZD5, PAX6, MYCN, NDP, PITX2, and PAX2, primarily associated with camera-type eye morphogenesis, pancreatic cancer, the apoptotic process involved in morphogenesis, and the VEGF receptor signaling pathway. We discovered that 26 Food and Drug Administration (FDA)-approved drugs could target 7 of the 14 hub genes. Conclusions: In conclusion, the results revealed a total of 14 potential genes, 4 major pathways, 7 drug gene targets, and 26 candidate drugs that could provide the basis of novel targeted therapies for targeted treatment and management of PHPV.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 10%
Researcher 2 10%
Student > Master 1 5%
Unknown 15 75%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 15%
Medicine and Dentistry 2 10%
Unknown 15 75%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 January 2023.
All research outputs
#7,717,448
of 23,467,261 outputs
Outputs from Frontiers in Medicine
#1,850
of 6,028 outputs
Outputs of similar age
#156,323
of 431,691 outputs
Outputs of similar age from Frontiers in Medicine
#137
of 422 outputs
Altmetric has tracked 23,467,261 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,028 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.5. This one has gotten more attention than average, scoring higher than 68% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 431,691 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.
We're also able to compare this research output to 422 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.