Characterization of Genetic and Chemical Drivers in the Pathogenesis of DRESS Syndrome: In Silico Study

Fuente: Wiley Open Access
Saved in:
Bibliographic Details
Main Authors: Ahmed I. AbdElneam, Mohammed S. Al‐Dhubaibi, Saleh S. Bahaj, Ghada F. Mohammed, Lina M. Atef, Walaa A. Siam, Amany A. E. Elshemally, Ali I. A. Abdel Rhaim, Sameh S. Aziz
Format: Artículo Open Access
Published: Wiley 2025
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1867006309155471360
author Ahmed I. AbdElneam
Mohammed S. Al‐Dhubaibi
Saleh S. Bahaj
Ghada F. Mohammed
Lina M. Atef
Walaa A. Siam
Amany A. E. Elshemally
Ali I. A. Abdel Rhaim
Sameh S. Aziz
author_facet Ahmed I. AbdElneam
Mohammed S. Al‐Dhubaibi
Saleh S. Bahaj
Ghada F. Mohammed
Lina M. Atef
Walaa A. Siam
Amany A. E. Elshemally
Ali I. A. Abdel Rhaim
Sameh S. Aziz
Ahmed I. AbdElneam
Mohammed S. Al‐Dhubaibi
Saleh S. Bahaj
Ghada F. Mohammed
Lina M. Atef
Walaa A. Siam
Amany A. E. Elshemally
Ali I. A. Abdel Rhaim
Sameh S. Aziz
collection Wiley Open Access
contents Characterization of Genetic and Chemical Drivers in the Pathogenesis of DRESS Syndrome: In Silico Study Ahmed I. AbdElneam Mohammed S. Al‐Dhubaibi Saleh S. Bahaj Ghada F. Mohammed Lina M. Atef Walaa A. Siam Amany A. E. Elshemally Ali I. A. Abdel Rhaim Sameh S. Aziz Health Science Reports ABSTRACT Background and Aims The pathophysiology of drug rash with eosinophilia and systemic symptoms (DRESS) syndrome is complex and poorly understood. Genetic predispositions play a significant role. We aimed to explore the genetic factors and molecular mechanisms driving DRESS, focusing on gene expression, transcription factors (TFs), microRNAs (miRNAs), and chemical interactions. Methods We utilized RNA‐seq data from the GSE160369 data set in the gene expression omnibus (GEO) database to identify differentially expressed genes (DEGs) related to DRESS. The analysis was conducted using GEO2R for identifying upregulated and downregulated genes. Protein–protein interaction (PPI) networks were constructed using STRING and further analyzed with Cytoscape and CytoHubba. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to identify biological pathways. miRNAs and TFs were predicted using bioinformatics tools like TargetScan, miRDB, and ChEA3, while chemical interactions with key genes were explored using CTDbase. Results A total of 336 DEGs were identified, including 239 upregulated and 97 downregulated genes. The PPI network highlighted TNF, IL2, and CD40 as central genes involved in immune‐related pathways. Functional enrichment analyses revealed significant pathways related to immune activation, such as leukocyte‐mediated immunity. We predicted 15 miRNAs, including hsa‐miR‐1296‐5p, and identified 10 TFs, such as MTF1 and NFKB2, which regulate the expression of key genes. Chemical interaction analysis revealed decitabine and tetradecanoylphorbol acetate as prominent agents modulating gene expression. Conclusion miRNAs, TFs, and chemical modulators, which play a key role in the development of DRESS syndrome. Knowledge of the molecular underpinnings of DRESS, imperative for therapeutic targets. 10.1002/hsr2.71283 http://creativecommons.org/licenses/by-nc-nd/4.0/
doi_str_mv 10.1002/hsr2.71283
format Artículo Open Access
id wiley_oa_10_1002_hsr2_71283
institution Wiley Open Access
license_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
publishDate 2025
publisher Wiley
record_format wiley_oa
spellingShingle Characterization of Genetic and Chemical Drivers in the Pathogenesis of DRESS Syndrome: In Silico Study
Ahmed I. AbdElneam
Mohammed S. Al‐Dhubaibi
Saleh S. Bahaj
Ghada F. Mohammed
Lina M. Atef
Walaa A. Siam
Amany A. E. Elshemally
Ali I. A. Abdel Rhaim
Sameh S. Aziz
Health Science Reports
Characterization of Genetic and Chemical Drivers in the Pathogenesis of DRESS Syndrome: In Silico Study Ahmed I. AbdElneam Mohammed S. Al‐Dhubaibi Saleh S. Bahaj Ghada F. Mohammed Lina M. Atef Walaa A. Siam Amany A. E. Elshemally Ali I. A. Abdel Rhaim Sameh S. Aziz Health Science Reports ABSTRACT Background and Aims The pathophysiology of drug rash with eosinophilia and systemic symptoms (DRESS) syndrome is complex and poorly understood. Genetic predispositions play a significant role. We aimed to explore the genetic factors and molecular mechanisms driving DRESS, focusing on gene expression, transcription factors (TFs), microRNAs (miRNAs), and chemical interactions. Methods We utilized RNA‐seq data from the GSE160369 data set in the gene expression omnibus (GEO) database to identify differentially expressed genes (DEGs) related to DRESS. The analysis was conducted using GEO2R for identifying upregulated and downregulated genes. Protein–protein interaction (PPI) networks were constructed using STRING and further analyzed with Cytoscape and CytoHubba. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to identify biological pathways. miRNAs and TFs were predicted using bioinformatics tools like TargetScan, miRDB, and ChEA3, while chemical interactions with key genes were explored using CTDbase. Results A total of 336 DEGs were identified, including 239 upregulated and 97 downregulated genes. The PPI network highlighted TNF, IL2, and CD40 as central genes involved in immune‐related pathways. Functional enrichment analyses revealed significant pathways related to immune activation, such as leukocyte‐mediated immunity. We predicted 15 miRNAs, including hsa‐miR‐1296‐5p, and identified 10 TFs, such as MTF1 and NFKB2, which regulate the expression of key genes. Chemical interaction analysis revealed decitabine and tetradecanoylphorbol acetate as prominent agents modulating gene expression. Conclusion miRNAs, TFs, and chemical modulators, which play a key role in the development of DRESS syndrome. Knowledge of the molecular underpinnings of DRESS, imperative for therapeutic targets. 10.1002/hsr2.71283 http://creativecommons.org/licenses/by-nc-nd/4.0/
title Characterization of Genetic and Chemical Drivers in the Pathogenesis of DRESS Syndrome: In Silico Study
topic Health Science Reports
url https://onlinelibrary.wiley.com/doi/10.1002/hsr2.71283