Abstract

Systemic inflammation and innate immune activation are associated with COVID-19 disease severity. Knowledge gaps remain in the relationships between microbiome, inflammation and COVID-19 disease severity. To better characterise these associations, we performed 16SrDNA analysis of stool samples in COVID-19 subjects to explore diversity and taxanomic composition. We correlated these to host inflammatory profiles, derived from soluble plasma biomarkers measured by bead-based fluorescence and electrochemiluminescence immunoassays. Associations of microbial diversity and inflammatory biomarkers on maximal COVID-19 severity (mild, moderate v severe/critical) was explored using logistic regression and weighted gene correlation network analysis (WGCNA). Of 79 subjects, 58% were male and 88% were Caucasian with 36% experiencing mild disease, 22% moderate disease and 40% critical/severe COVID-19. Hierarchical clustering and principal component analysis (PCo) revealed distinct inflammatory clusters that were found to correlate with 4 modules of microbiome profiles. Modules 3 and 4 were associated with both older age and severe/critical disease outcomes. These modules were enriched in pathogenic and inflammatory bacteria that mapped to a pro-inflammatory biomarker cluster. In contrast, module 1 exhibited enrichment of anti-inflammatory bacteria, was associated with younger age and mild/moderate disease outcomes and mapped to a less-inflamed biomarker cluster. This study provides further insights into links between host microbiome, inflammatory responses to SARS-CoV-2 infection and clinical COVID-19 disease severity, suggesting a role for the microbiome in shaping distinct host inflammatory responses to infection.

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