ArticleAnnals of transplantation2022
Bioinformatics Identification of Candidate Biomarkers in Endomyocardial Biopsy and Peripheral Blood for Cardiac Allograft Rejection.
Article in Annals of transplantation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 authors at 2 institutions in 1 country.
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Abstract
BACKGROUND Cardiac allograft rejection is still a crucial barrier to achieving satisfactory outcomes after surgery. In this study, we propose to find candidate biomarkers from endomyocardial biopsy (EMB) and peripheral blood (PB) samples for efficient diagnosis and treatment of cardiac allograft rejection. MATERIAL AND METHODS Microarray datasets were obtained from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) of cardiac allograft rejection patients and control subjects from EMB and PB samples were screened using the online tool GEO2R. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of all samples' DEGs were performed with the DAVID online tool. Protein-protein interaction (PPI) networks were constructed and visualized using Cytoscape and the top 10 hub genes were selected. Finally, the most highly enriched GO and KEGG pathways of the top 10 hub genes were determined. RESULTS A total of 57 502 genes from EMB samples and 131 624 genes from PB samples were identified. Gene characteristics and enrichment analysis indicated that both EMB and PB samples contained DEGs involved in antigen presentation, immune cells activation, inflammatory process, and cellular injuries. In EMB samples, there were some DEGs related to heart tissue injury and cardiac malfunction. Moreover, DEGs that regulates hypoxia-induced factors and erythrocyte function in response of ischemia and hypoxia stress were present in PB samples but were absent in EMB samples. CONCLUSIONS The screened differentially expressed genes (DEGs) from EMB and PB samples of patients with cardiac graft rejection are potential candidate biomarkers of diagnosis and treatment.
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