ArticleAnnals of medicine2025
Identification and mechanism analysis of biomarkers related to butyrate metabolism in COVID-19 patients.
Article in Annals of medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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26 citing papers in PubMed.
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- Identification of potential biomarkers related to mannose metabolism in keloids: analysis of integrated bulk RNA-seq and scRNA-seq.Frontiers in immunology · 2026Article
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- Identification of AICD-associated transcriptomic markers in major depressive disorder.Frontiers in psychiatry · 2026Article
- Exploring the potential of gut microbiota metabolites in the treatment of endometriosis through network pharmacology and Mendelian randomization.Frontiers in microbiology · 2026Article
- Integrative multi-omics and machine learning analysis identifies candidate biomarkers associated with mitochondrial quality control in major depressive disorder.Frontiers in psychiatry · 2026Article
- Identification and Validation of Mannose Metabolism-Related Biomarkers in COPD Through Integrated Bioinformatics and Machine Learning Analysis: A Pilot Study.International journal of chronic obstructive pulmonary disease · 2026Article
- Revealing the Diagnostic Potential of Three RHO GTPase-Related Genes in Osteoarthritis Based on Single-Cell RNA Sequencing and GEO Dataset Analysis.International journal of genomics · 2026Article
- Prognostic value of neuro-related genes in colorectal cancer and their potential implications for immunotherapy.Journal of Cancer · 2026Article
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12 authors.
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Abstract
backgroundButyrate may inhibit SARS-CoV-2 replication and affect the development of COVID-19. However, there have been no systematic comprehensive analyses of the role of butyrate metabolism-related genes (BMRGs) in COVID-19.
methodsWe performed differential expression analysis of BMRGs in the brain, liver and pancreas of COVID-19 patients and controls in GSE157852 and GSE151803. The differentially expressed genes (DEGs) and module genes between COVID-19 patients and healthy controls in GSE171110 were screened through 'limma' and 'WGANA' R package, respectively, followed by an intersection with BMRGs via 'ggvenn' R package. Six machine learning algorithms were employed to determine the best model for identifying biomarkers, and receiver operating characteristic (ROC) curves were plotted to evaluate the diagnostic value of the biomarkers in COVID-19. Moreover, the differences in immune-infiltrating cells between the COVID-19 and control groups were compared using CIBERSORT. The differences in immune cells and expression levels of biomarkers in immune cells among different tissues were analysed using GSE171668.
resultsThe BMRGs were the most different in the brain between the COVID-19 and control groups, including 21 upregulated and 16 downregulated genes. Five important common BMRGs were screened as biomarkers for COVID-19 using XGBoost, namely CCNB1, CCNA2, BRCA1, HBB and HSPA5, with increased diagnostic performance. Enrichment analysis revealed that these five genes were related to the cell cycle, cell proliferation and cell senescence. The infiltrating abundance of 12 immune cells was different between the COVID-19 and control groups. Finally, the expression levels of HSPA5, BRCA1 and HBB were higher in annotated cells than in CCNB1 and CCNA2, and there were four different types of immune cells in the liver, heart, lungs and kidneys.
conclusionsThese five genes may be potential biomarkers of butyrate metabolism in COVID-19 patients. These findings provide a direction for further studies on the molecular mechanisms underlying COVID-19.
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