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Meta-analysis of Transcriptomic Data from Lung Autopsy and Cellular Models of SARS-CoV-2 Infection.
Cadore, Nathan Araujo; Lord, Vinicius Oliveira; Recamonde-Mendoza, Mariana; Kowalski, Thayne Woycinck; Vianna, Fernanda Sales Luiz.
Afiliación
  • Cadore NA; Laboratory of Genomic Medicine, Center of Experimental Research, Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, Brazil.
  • Lord VO; Laboratory of Immunobiology and Immunogenetics, Department of Genetics, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
  • Recamonde-Mendoza M; Post-Graduation Program in Genetics and Molecular Biology, Department of Genetics, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
  • Kowalski TW; Laboratory of Genomic Medicine, Center of Experimental Research, Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, Brazil.
  • Vianna FSL; Centro Universitário CESUCA, Cachoeirinha, Brazil.
Biochem Genet ; 62(2): 892-914, 2024 Apr.
Article en En | MEDLINE | ID: mdl-37486510
Severe COVID-19 is a systemic disorder involving excessive inflammatory response, metabolic dysfunction, multi-organ damage, and several clinical features. Here, we performed a transcriptome meta-analysis investigating genes and molecular mechanisms related to COVID-19 severity and outcomes. First, transcriptomic data of cellular models of SARS-CoV-2 infection were compiled to understand the first response to the infection. Then, transcriptomic data from lung autopsies of patients deceased due to COVID-19 were compiled to analyze altered genes of damaged lung tissue. These analyses were followed by functional enrichment analyses and gene-phenotype association. A biological network was constructed using the disturbed genes in the lung autopsy meta-analysis. Central genes were defined considering closeness and betweenness centrality degrees. A sub-network phenotype-gene interaction analysis was performed. The meta-analysis of cellular models found genes mainly associated with cytokine signaling and other pathogen response pathways. The meta-analysis of lung autopsy tissue found genes associated with coagulopathy, lung fibrosis, multi-organ damage, and long COVID-19. Only genes DNAH9 and FAM216B were found perturbed in both meta-analyses. BLNK, FABP4, GRIA1, ATF3, TREM2, TPPP, TPPP3, FOS, ALB, JUNB, LMNA, ADRB2, PPARG, TNNC1, and EGR1 were identified as central elements among perturbed genes in lung autopsy and were found associated with several clinical features of severe COVID-19. Central elements were suggested as interesting targets to investigate the relation with features of COVID-19 severity, such as coagulopathy, lung fibrosis, and organ damage.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Systematic_reviews Idioma: En Revista: Biochem Genet Año: 2024 Tipo del documento: Article País de afiliación: Brasil Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Systematic_reviews Idioma: En Revista: Biochem Genet Año: 2024 Tipo del documento: Article País de afiliación: Brasil Pais de publicación: Estados Unidos