ArticleJournal of clinical laboratory analysis2022
Screening the hub genes and analyzing the mechanisms in discharged COVID-19 patients retesting positive through bioinformatics analysis.
Article in Journal of clinical laboratory analysis, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed, 16 citations in OpenAlex.
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- Bioinformatics and molecular biology tools for diagnosis, prevention, treatment and prognosis of COVID-19.Heliyon · 2024Review
- MMPred: a tool to predict peptide mimicry events in MHC class II recognition.Frontiers in genetics · 2024Article
- Review
- Parkinson's Disease Gene Biomarkers Screened by the LASSO and SVM Algorithms.Brain sciences · 2023Article
- Classification of tuberculosis-related programmed cell death-related patient subgroups and associated immune cell profiling.Frontiers in immunology · 2023Article
- Exploring the diagnostic markers of essential tremor: A study based on machine learning algorithms.Open life sciences · 2023Article
- Classification and severity progression measure of COVID-19 patients using pairs of multi-omic factors.Journal of applied statistics · 2023Article
- Transcriptional Profiles Analysis of COVID-19 and Malaria Patients Reveals Potential Biomarkers in Children.bioRxiv : the preprint server for biology · 2022Article
- Screening the hub genes and analyzing the mechanisms in discharged COVID-19 patients retesting positive through bioinformatics analysis.Journal of clinical laboratory analysis · 2022Article
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAfter encountering COVID-19 patients who test positive again after discharge, our study analyzed the pathogenesis to further assess the risk and possibility of virus reactivation.
methodsA separate microarray was acquired from the Gene Expression Omnibus (GEO), and its samples were divided into two groups: a "convalescent-RTP" group consisting of convalescent and "retesting positive" (RTP) patients (group CR) and a "healthy-RTP" group consisting of healthy control and RTP patients (group HR). The enrichment analysis was performed with R software, obtaining the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, the protein-protein interaction (PPI) networks of each group were established, and the hub genes were discovered using the cytoHubba plugin.
resultsIn this study, 6622 differentially expressed genes were identified in the group CR, among which RAB11B-AS1, DISP1, MICAL3, PSMG1, and DOCK4 were up-regulated genes, and ANAPC1, IGLV1-40, SORT1, PLPPR2, and ATP1A1-AS1 were down-regulated. 7335 genes were screened in the group HR, including the top 5 up-regulated genes ALKBH6, AMBRA1, MIR1249, TRAV18, and LRRC69, and the top 5 down-regulated genes FAM241B, AC018529.3, AL031963.3, AC006946.1, and FAM149B1. The GO and KEGG analysis of the two groups revealed a significant enrichment in immune response and apoptosis. In the PPI network constructed, group CR and group HR identified 10 genes, respectively, and TP53BP1, SNRPD1, and SNRPD2 were selected as hub genes.
conclusionsUsing the messenger ribonucleic acid (mRNA) expression data from GSE166253, we found TP53BP1, SNRPD1, and SNRPD2 as hub genes in RTP patients, which is vital to the management and prognostic prediction of RTP patients.
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