Human Gut Microbiota and Its Metabolites Impact Immune Responses in COVID-19 and Its Complications.
Level 4 - case-series / case-control
Case-control multi-omics association study with matched non-COVID-19 controls
PubMed 36155191 · doi:10.1053/j.gastro.2022.09.024
What was done
The authors performed shotgun metagenomic sequencing and metabolomic profiling on stool samples alongside plasma cytokine measurements in 112 hospitalized patients with SARS-CoV-2 infection and 112 matched non-COVID-19 controls. They evaluated multi-omic correlations across disease severity groups, tracked changes in a follow-up dataset, and compared findings against external datasets (including the Japanese 4D microbiome cohort) and other disease cohorts (diabetes, inflammatory bowel disease, rheumatoid arthritis, and proton-pump inhibitor use). Random forest classifiers were constructed to predict infection and severe disease.
What was found
The abstract reports no exact numerical values, effect sizes, p-values, or model accuracy metrics. It reports qualitative correlations between gut microbes (oral taxa and short-chain fatty acid producers) and metabolites (branched-chain and aromatic amino acids, short-chain fatty acids, carbohydrates, neurotransmitters, and vitamin B6), which in turn correlated with inflammatory cytokines (IFN-γ, IFN-λ3, IL-6, CXCL-9, and CXCL-10). These correlations were strong in severe disease and pneumonia, moderate in high D-dimer and renal/hepatic dysfunction groups, and rare in patients with diarrhea. Random forest models using microbiome profiles predicted COVID-19 and severe disease with moderate concordance between Hong Kong and Japanese cohorts.
Why it matters
This study provides comprehensive multi-omic mapping linking gut microbial and metabolic profiles to systemic inflammatory responses and extraintestinal organ dysfunction in COVID-19, supporting the relevance of a gut-lung axis.
Limits
The abstract reports zero quantitative figures, confidence intervals, or performance metrics. As a case-control observational study, it cannot determine whether microbiome alterations cause severe immune responses or reflect systemic illness and hospital interventions. The primary sample size is moderate (112 cases and 112 controls).
Cited by
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