Hidden in plain sight: The effects of BCG vaccination in the COVID-19 pandemic.
To investigate the relationship between Bacille Calmette-Guérin (BCG) vaccination and SARS-CoV-2 by a bioinformatics approach, two datasets for the SARS-CoV-2 infection group and BCG-vaccinated group were downloaded. Differentially Expressed Genes were identified. Gene ontology and pathways were functionally enriched, and networking was constructed in NetworkAnalyst. Lastly, the correlation between post-BCG vaccination and COVID-19 transcriptome signatures was established. A total of 161 DEGs (113 upregulated DEGs and 48 downregulated genes) were identified in the SARS-CoV-2 group. In the pathway enrichment analysis, a cross-reference of upregulated Kyoto Encyclopedia of Genes and Genomes pathways in SARS-CoV-2 with downregulated counterparts in the BCG-vaccinated group, resulted in the intersection of 45 common pathways, accounting for 86.5% of SARS-CoV-2 upregulated pathways. Of these intersecting pathways, a vast majority were immune and inflammatory pathways with top significance in interleukin-17, tumor necrosis factor, NOD-like receptors, and nuclear factor-κB signaling pathways. Given the inverse relationship of the specific differentially expressed gene pathways highlighted in our results, the BCG-vaccine may play a protective role against COVID-19 by mounting a nonspecific immunological response and further investigation of this relationship is warranted.
['Toraih|Eman A|EA|', 'Sedhom|Jessica A|JA|', 'Dokunmu|Titilope M|TM|', 'Hussein|Mohammad H|MH|', 'Ruiz|Emmanuelle M L|EML|', 'Muthusamy|Kunnimalaiyaan|K|', 'Zerfaoui|Mourad|M|', 'Kandil|Emad|E|']
D001500:BCG Vaccine D000086382:COVID-19 D019295:Computational Biology D066264:Datasets as Topic D063990:Gene Ontology D006801:Humans D015398:Signal Transduction D059467:Transcriptome D014611:Vaccination
BCG vaccine COVID-19 differentially expressed genes pathways networking in silico analysis