| Literature DB >> 35336884 |
Pavlo Petakh1,2, Iryna Kamyshna3, Andriy Nykyforuk1, Rouan Yao4, John F Imbery5, Valentyn Oksenych5, Mykhaylo Korda6, Aleksandr Kamyshnyi2.
Abstract
Coronavirus disease 2019, or COVID-19, is a major challenge facing scientists worldwide. Alongside the lungs, the system of organs comprising the GI tract is commonly targeted by COVID-19. The dysbiotic modulations in the intestine influence the disease severity, potentially due to the ability of the intestinal microbiota to modulate T lymphocyte functions, i.e., to suppress or activate T cell subpopulations. The interplay between the lungs and intestinal microbiota is named the gut-lung axis. One of the most usual comorbidities in COVID-19 patients is type 2 diabetes, which induces changes in intestinal microbiota, resulting in a pro-inflammatory immune response, and consequently, a more severe course of COVID-19. However, changes in the microbiota in this comorbid pathology remain unclear. Metformin is used as a medication to treat type 2 diabetes. The use of the type 2 diabetes drug metformin is a promising treatment for this comorbidity because, in addition to its hypoglycemic action, it can increase amount of intestinal bacteria that induce regulatory T cell response. This dual activity of metformin can reduce lung damage and improve the course of the COVID-19 disease.Entities:
Keywords: COVID-19; SARS-CoV-2; immunoregulation; intestinal microbiota; metformin; type 2 diabetes
Mesh:
Year: 2022 PMID: 35336884 PMCID: PMC8955861 DOI: 10.3390/v14030477
Source DB: PubMed Journal: Viruses ISSN: 1999-4915 Impact factor: 5.818
Figure 1Intestinal bacteria and immune cell homeostasis regulation. The main bacterial inducers of intestinal CD4+ T cells are shown.
Figure 2Induction of T-lymphocytes by microbial metabolites. Shown here are the main mechanisms of intestinal CD4+ T cell induction by major microbial metabolites.
COVID-19 and gut microbiota changes.
| Research | Study Design | Number of Participants | Research Methods | Microbiota Changes |
|---|---|---|---|---|
| Zuo et al. [ | Single-center, prospective | 15 COVID-19 patients compared against 6 subjects with community-acquired pneumonia and 15 healthy individuals | Metagenomic sequencing | Significant changes in the microbiota of the GI tract (dysbiosis) in patients with COVID-19. Positive correlation between the severity of COVID-19 and dysbiosis. |
| Gu et al. [ | Single-center, cross-sectional | 30 COVID-19 patients compared against 24 H1N1 patients and 30 matched healthy controls | 16S rRNA sequencing | Significantly reduced diversity of bacteria (dysbiosis), significantly lower relative number of beneficial symbionts, and higher relative number of opportunistic pathogens in COVID-19. |
| Yeoh et al. [ | Prospective cohort | 100 COVID-19 patients compared against matched healthy controls | Sequencing of fecal DNA. Assessment of levels of inflammatory markers. | Significant changes in the microbiota of the GI tract (dysbiosis) in COVID-19 patients. Dysbiosis continued even after 30 days post-illness. Significant correlation of dysbiosis with COVID-19 severity and numerous pro-inflammatory markers in serum. |
| Prasad et al. [ | Prospective cohort study from one center | 30 hospitalized patients with COVID-19 and 16 healthy subjects. | 16S rRNA sequencing and markers of intestinal permeability | Abnormal signs of microorganisms were observed in plasma samples from approximately 65% of COVID-19 patients. Compared with the uninfected control group, plasma levels of intestinal permeability markers (such as FABP2, PGN, and LPS) were significantly higher in COVID-19 patients. |
| Newsome et al. [ | Prospective cohort study from one center | 50 hospitalized COVID-19 patients, 9 recovered patients, and 34 uninfected subjects. | 16S rRNA sequencing | The microbial composition of feces differed significantly in COVID-19 patients. Patients with COVID-19 had an increased relative amount of |
| Lv et al. [ | Prospective cohort study from one center | 56 hospitalized COVID-19 patients and 47 healthy subjects. | Metabolomics, gas chromatography | There were differences in the metabolomes of COVID-19 patients compared with uninfected members of the control group. |
| Tanget et al. [ | Cohort study | Total: 57 | qPCR | Intestinal dysbiosis progressed depending on the severity of the disease. Significant reduction in the number of probiotic bacteria |
| Chen et al. [ | Cohort study | 30 hospitalized COVID-19 patients | 16S rRNA sequencing | At the beginning of the disease, dysbiosis was observed, and it continued throughout the disease course. |
| Mazzarelliet et al. [ | Cohort study | Total: 23 | qPCR | Decreased microbial diversity in ICU-treated COVID-19 patients compared with those treated in the infectious department. Significant increase in opportunistic pathogens |
| Lv et al. [ | Prospective cohort study from one center | Total: 150 | qPCR with primers ITS1f and ITS2r | |
| Yu et al. [ | Cohort study | Total: 3 hospitalized COVID-19 patients | Sequencing | Intestinal dysbiosis may be an important factor in severe COVID-19 infection. Significant increase in |
Figure 3The gut–lung axis in COVID-19.
Type 2 diabetes and gut microbiota changes.
| Research | Study Design | Number of Participants | Research Methods | Changes in the Intestinal Microbiota | |
|---|---|---|---|---|---|
| Increase | Decrease | ||||
| Candela et al. [ | Open-label trial | 40 patients with T2D and 13 healthy controls | 16S rRNA sequencing | ||
| Sedighi et al. [ | Case–control study | 18 patients with T2D and 18 healthy controls | 16S rRNA sequencing |
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| Wu et al. [ | Double-blind study | 16 patients with T2D and 12 healthy controls | 16S rRNA sequencing | No data | |
| Larsen et al. [ | Open-label trial | 18 patients with T2D and 18 healthy controls | 16S rRNA sequencing |
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Gut microbiota in patients with T2D receiving metformin.
| Research | Research Methods | Number of Participants | Dosage of Metformin | Changes in the Intestinal Microbiota | ||
|---|---|---|---|---|---|---|
| Metformin-untreated T2D | Metformin-treated | Increase | Decrease | |||
| Forslund et al. [ | Metagenomics | 106 | 93 | No data |
| No data |
| Cuesta-Zuluaga et al. [ | 16sRNA | 14 | 14 | No data | ||
| Wu et al. [ | Metagenomics | 22 | 22 | 1700 mg/d | ||
| Hung et al. [ | qPCR | 23 | 23 | No data |
| No data |
| Sun et al. [ | Metagenomics | 22 | 22 | 1000 mg/d | No data |
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| Barengolts et al. [ | 16sRNA | 11 | 21 | No data | No data | |
| Ejtahed et al. [ | 16sRNA | 20 | 20 | 1000 mg/d |
| No data |
| Zhang et al. [ | 16sRNA | 26 | 51 | No data | ||
| Hiel et al. [ | 16sRNA | 53 | 42 | No data | ||
| Chavez-Carbajal et al. [ | 16sRNA | 14 | 14 | No data | No data | |