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Human Gut Microbiota and Its Metabolites Impact Immune Responses in COVID-19 and Its Complications
Gastroenterology ( IF 29.4 ) Pub Date : 2022-09-23 , DOI: 10.1053/j.gastro.2022.09.024
Naoyoshi Nagata 1 , Tadashi Takeuchi 2 , Hiroaki Masuoka 3 , Ryo Aoki 4 , Masahiro Ishikane 5 , Noriko Iwamoto 5 , Masaya Sugiyama 6 , Wataru Suda 3 , Yumiko Nakanishi 2 , Junko Terada-Hirashima 7 , Moto Kimura 8 , Tomohiko Nishijima 4 , Hiroshi Inooka 4 , Tohru Miyoshi-Akiyama 9 , Yasushi Kojima 10 , Chikako Shimokawa 11 , Hajime Hisaeda 11 , Fen Zhang 12 , Yun Kit Yeoh 12 , Siew C Ng 12 , Naomi Uemura 13 , Takao Itoi 14 , Masashi Mizokami 15 , Takashi Kawai 16 , Haruhito Sugiyama 7 , Norio Ohmagari 5 , Hiroshi Ohno 17
Affiliation  

Background & Aims

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.

Methods

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.

Results

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.

Conclusions

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.

更新日期:2022-09-23
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