Meta-analysis of Transcriptomic Data from Lung Autopsy and Cellular Models of SARS-CoV-2 Infection

Area of Science:

• Genomics and Molecular Biology
• Infectious Diseases
• Pathology

Background:

• Severe COVID-19 presents as a systemic disorder with inflammation, metabolic issues, and multi-organ damage.
• Understanding the molecular underpinnings of COVID-19 severity is crucial for developing effective treatments.

Approach:

• Performed transcriptome meta-analyses on cellular models of SARS-CoV-2 infection and lung autopsy tissues from deceased patients.
• Conducted functional enrichment, gene-phenotype association, and biological network analyses to identify key genes and pathways.
• Investigated central genes within biological networks for their association with severe COVID-19 clinical features.

Key Points:

• Cellular models revealed genes involved in cytokine signaling and pathogen response.
• Lung autopsy data highlighted genes associated with coagulopathy, fibrosis, multi-organ damage, and long COVID-19.
• DNAH9 and FAM216B were the only genes perturbed in both analyses; several other genes were identified as central to severe COVID-19 pathology.

Conclusions:

• Identified central genes (e.g., BLNK, FOS, JUNB, PPARG) associated with severe COVID-19 manifestations like coagulopathy and fibrosis.
• These central genes represent potential targets for further research into managing COVID-19 severity.
• The study provides molecular insights into systemic damage and clinical outcomes in severe COVID-19.