ArticleScientific reports2024
Exploration of common pathogenesis and candidate hub genes between HIV and monkeypox co-infection using bioinformatics and machine learning.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- A hybrid machine learning framework with two-step feature selection for identifying key biomarkers and drug targets in monkeypox.Biochemistry and biophysics reports · 2026Article
- Decoding cross-talk between Mpox and HIV: insights from transcriptomics and network-based analyses.Virology journal · 2025Article
- Urogenital Manifestations in Mpox (Monkeypox) Infection: A Comprehensive Review of Epidemiology, Pathogenesis, and Therapeutic Approaches.Infection and drug resistance · 2025Review
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Authors and funding
16 authors.
Funding
Abstract
This study explored the pathogenesis of human immunodeficiency virus (HIV) and monkeypox co-infection, identifying candidate hub genes and potential drugs using bioinformatics and machine learning. Datasets for HIV (GSE 37250) and monkeypox (GSE 24125) were obtained from the GEO database. Common differentially expressed genes (DEGs) in co-infection were identified by intersecting DEGs from monkeypox datasets with genes from key HIV modules screened using Weighted Gene Co-Expression Network Analysis (WGCNA). After gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and construction of protein-protein interaction (PPI) network, candidate hub genes were further screened based on machine learning algorithms. Transcriptional factors (TFs) and miRNA-candidate hub gene networks were constructed to understand regulatory mechanisms and protein-drug interactions to identify potential therapeutic drugs. Seven candidate hub genes-MX2, ADAR, POLR2H, RPL5, IFI16, IFIT2, and RPS5-were identified. TFs and miRNAs associated with these hub genes, playing a key role in regulating viral infection and inflammation due to the activation of antiviral innate immunity, were also identified through network analysis. Potential therapeutic drugs were screened based on these hub genes: AZT, a nucleotide reverse transcriptase inhibitor, suppressed viral replication in HIV and monkeypox co-infection, while mefloquine inhibited inflammation due to the activation of antiviral innate immunity. In conclusion, the study identified candidate hub genes, their transcriptional regulation, signaling pathways, and small-molecule drugs in HIV and monkeypox co-infection, contributing to understanding the pathogenesis of HIV and monkeypox co-infection and informing precise therapeutic strategies.
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