Human Gut Microbiota and Its Metabolites Impact Immune Responses in COVID-19 and Its Complications

• Published in: Gastroenterology (New York, N.Y. 1943) Vol. 164; no. 2; pp. 272 - 288
• Main Authors: Nagata, Naoyoshi, Takeuchi, Tadashi, Masuoka, Hiroaki, Aoki, Ryo, Ishikane, Masahiro, Iwamoto, Noriko, Sugiyama, Masaya, Suda, Wataru, Nakanishi, Yumiko, Terada-Hirashima, Junko, Kimura, Moto, Nishijima, Tomohiko, Inooka, Hiroshi, Miyoshi-Akiyama, Tohru, Kojima, Yasushi, Shimokawa, Chikako, Hisaeda, Hajime, Zhang, Fen, Yeoh, Yun Kit, Ng, Siew C., Uemura, Naomi, Itoi, Takao, Mizokami, Masashi, Kawai, Takashi, Sugiyama, Haruhito, Ohmagari, Norio, Ohno, Hiroshi
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.02.2023; by the AGA Institute
• Subjects: COVID-19; Cross-Sectional Studies; Cytokine Storm; Cytokines; Fecal Metabolome; Feces - chemistry; Gastrointestinal Microbiome - genetics; Gut Microbiome; Gut-Lung Axis; Humans; Immunity; SARS-CoV-2; Vitamin B 6 - analysis; IL; KO; Gut-Lung Axis; Spo2; PPI; DM; IBD; Gut Microbiome; SCFA; bp; AUC; RA; Cytokine Storm; 4D; Fecal Metabolome; FDR; KEGG; WBC; BCAA; BMI; COPD; NCGM
• ISSN: 0016-5085; 1528-0012; 1528-0012
• DOI: 10.1053/j.gastro.2022.09.024

We investigate interrelationships between gut microbes, metabolites, and cytokines that characterize COVID-19 and its complications, and we validate the results with follow-up, the Japanese 4D (Disease, Drug, Diet, Daily Life) microbiome cohort, and non-Japanese data sets. We performed shotgun metagenomic sequencing and metabolomics on stools and cytokine measurements on plasma from 112 hospitalized patients with SARS-CoV-2 infection and 112 non–COVID-19 control individuals matched by important confounders. Multiple correlations were found between COVID-19–related microbes (eg, oral microbes and short-chain fatty acid producers) and gut metabolites (eg, branched-chain and aromatic amino acids, short-chain fatty acids, carbohydrates, neurotransmitters, and vitamin B6). Both were also linked to inflammatory cytokine dynamics (eg, interferon γ, interferon λ3, interleukin 6, CXCL-9, and CXCL-10). Such interrelationships were detected highly in severe disease and pneumonia; moderately in the high D-dimer level, kidney dysfunction, and liver dysfunction groups; but rarely in the diarrhea group. We confirmed concordances of altered metabolites (eg, branched-chain amino acids, spermidine, putrescine, and vitamin B6) in COVID-19 with their corresponding microbial functional genes. Results in microbial and metabolomic alterations with severe disease from the cross-sectional data set were partly concordant with those from the follow-up data set. Microbial signatures for COVID-19 were distinct from diabetes, inflammatory bowel disease, and proton-pump inhibitors but overlapping for rheumatoid arthritis. Random forest classifier models using microbiomes can highly predict COVID-19 and severe disease. The microbial signatures for COVID-19 showed moderate concordance between Hong Kong and Japan. Multiomics analysis revealed multiple gut microbe-metabolite-cytokine interrelationships in COVID-19 and COVID-19related complications but few in gastrointestinal complications, suggesting microbiota-mediated immune responses distinct between the organ sites. Our results underscore the existence of a gut-lung axis in COVID-19. [Display omitted]