| Literature DB >> 35978881 |
Chiranjib Chakraborty1, Ashish Ranjan Sharma2, Manojit Bhattacharya3, Kuldeep Dhama4, Sang-Soo Lee5.
Abstract
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection leads to a severe respiratory illness and alters the gut microbiota, which dynamically interacts with the human immune system. Microbiota alterations include decreased levels of beneficial bacteria and augmentation of opportunistic pathogens. Here, we describe critical factors affecting the microbiota in coronavirus disease 2019 (COVID-19) patients. These include, such as gut microbiota imbalance and gastrointestinal symptoms, the pattern of altered gut microbiota composition in COVID-19 patients, and crosstalk between the microbiome and the gut-lung axis/gut-brain-lung axis. Moreover, we have illustrated the hypoxia state in COVID-19 associated gut microbiota alteration. The role of ACE2 in the digestive system, and control of its expression using the gut microbiota is discussed, highlighting the interactions between the lungs, the gut, and the brain during COVID-19 infection. Similarly, we address the gut microbiota in elderly or co-morbid patients as well as gut microbiota dysbiosis of in severe COVID-19. Several clinical trials to understand the role of probiotics in COVID-19 patients are listed in this review. Augmented inflammation is one of the major driving forces for COVID-19 symptoms and gut microbiome disruption and is associated with disease severity. However, understanding the role of the gut microbiota in immune modulation during SARS-CoV-2 infection may help improve therapeutic strategies for COVID-19 treatment. ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.Entities:
Keywords: COVID-19; Gut microbiota; Inflammation; Therapeutic
Mesh:
Year: 2022 PMID: 35978881 PMCID: PMC9280735 DOI: 10.3748/wjg.v28.i25.2802
Source DB: PubMed Journal: World J Gastroenterol ISSN: 1007-9327 Impact factor: 5.374
Figure 1The schematic diagram shows normal healthy gut and the incidence in gut microbiota and gut virome in coronavirus disease 2019 patients. COVID-19: Coronavirus disease 2019.
Different gastrointestinal symptoms in coronavirus disease 2019 patients
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| 1 | 191 | Adults (46-67 years) hospitalised, Chinese peoples, 91 patients having comorbidity | 7 (3.7%) | 9 (4.7%) | 7 (3.7%) | Identification of several risk factors and a detailed clinical course of illness for mortality of COVID-19 patients | [ |
| 2 | 171 | Minor aged (1 d-15 years, hospitalised, Chinese children, no such comorbidity | 11 (6.4%) | 15 (8.8%) | NA | Report of a spectrum of illness from children infected with SARS-CoV-2 virus | [ |
| 3 | 1099 | Median age group (35-58 years), hospitalised, Chinese patients without any comorbidity | 55 (5.0%) | 42 (3.8%) | 55 (5.0%) | Identification and definition of clinical characteristics and disease severity of hospitalized COVID-19 patients | [ |
| 4 | 140 | Adults (25-87 year), hospitalised Chinese patients with high comorbidity | 7 (5.0%) | 18 (12.9%) | 24 (17.3%) | Report on hospitalized patients having COVID-19 with abnormal clinical manifestations (fever, fatigue, gastrointestinal symptoms, allergy) | [ |
| 5 | 73 | Adults hospitalised Chinese patients, comorbidity reported | NA | 26 (35.6%) | NA | Clinical significance of SARS-CoV-2 by examining viral RNA in feces of COVID-19 patients during hospitalizations | [ |
| 6 | 52 | Adults (mean age 59.7 year), critically ill ICU- admitted Chinese patients, comorbidity reported | 2 (3.8%) | NA | NA | Retrospective, single-centered, observational study on critically ill, ICU-admitted adult COVID-19 patients | [ |
| 7 | 138 | Adult (median age 56 years), hospitalised Chinese patients with comorbidities | 5 (3.6%) | 14 (10.1%) | 14 (10.1%) | Clinical characteristics of COVID-19 patients in hospitalized conditions | [ |
| 8 | 41 | Middle age group (41-58 years) hospitalised Chinese patients with comorbidities | NA | 1 (2.6%) | NA | Epidemiological, laboratory, clinical, and radiological features and treatment with clinical outcomes of hospitalized COVID-19 patients | [ |
| 9 | 62 | Studied patients (median age 41 years) were hospitalised, Chinese ethnicity and comorbidity reported | NA | 3 (4.8%) | NA | Most common symptoms at onset of illness with clinical data in confirmed COVID-19 patients | [ |
| 10 | 137 | Studied patients ( mean age 57-55) ware Chinese and hospitalised, comorbidity was also noted | NA | 11 (8%) | NA | Investigation of epidemiological history, clinical characteristics, treatment, and prognosis of COVID-19 patients | [ |
| 11 | 81 | Chinese patients (mean age was 49.5 years), hospitalised with high comorbidities | 4 (4.9%) | 3 (3.7%) | NA | Report of confirmed COVID-19 patients with chest computer tomography imaging anomalies | [ |
| 12 | 99 | Hospitalised, Chinese patients (average age of the patients was 55.5 years), comorbidity was reported | 1 (1%) | 2 (2.0%) | 1 (1%) | Inclusive exploration of epidemiology and clinical features of COVID-19 patients | [ |
NA: Not available; ICU: Intensive care unit; COVID-19: Coronavirus disease 2019; SARS-CoV-2: Severe acute respiratory syndrome coronavirus 2.
Figure 2The schematic diagram illustrates the severe acute respiratory syndrome coronavirus 2 entry in the body, causes of gut microbiota imbalance which assists in manifesting the gastrointestinal symptoms in coronavirus disease 2019 patients. GI: Gastrointestinal; SARS-CoV-2: Severe acute respiratory syndrome coronavirus 2.
Fecal viral shedding in coronavirus disease 2019 patients
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| 1 | 205 | Patients (mean age of 44 years) were hospitalised, Chinese without any comorbidities | No symptoms | 44 | Evidence-based study for gastrointestinal infection of SARS-CoV-2 virus and its possible fecal-oral transmission route in humans | [ |
| 2 | 73 | Different age group (10 mo to 78 years old), hospitalised Chinese patients without report any comorbidities | Gastrointestinal bleeding, diarrhea | 39 | Description of epidemiological and clinical characteristics of COVID-19 patients | [ |
| 3 | 10 | Chinese patients have aged 19-40 years, hospitalised and no such comorbidity was reported | Hemoptysis, diarrhea, cough | 8 | Report of median aged COVID-19 confirmed patients in ICU | [ |
| 4 | 14 | Patients (18-87 years) were hospitalized, Chinese individuals without any comorbidities | No symptoms | 5 | Retrospective analysis of laboratory-confirmed COVID-19 cases in hospitalized conditions | [ |
| 5 | 66 | Chinese patients (median age of 44 years) were hospitalised, comorbidity was not reported | No symptoms | 11 | Viral RNA detection was performed from throat swabs, stool, urine, and serum samples in different clinical conditions in COVID-19 patients | [ |
| 6 | 18 | Adults patients (median age, 47 years) from Singapore were hospitalised and comorbidities was noted | No symptoms | 4 | COVID-19 patient case series using clinical, laboratory, and radiological data | [ |
| 7 | 74 | Studied paients belonged from China and were hospitalised with comorbidities | No symptoms | 41 | Analysis of respiratory and fecal samples to determine clinical symptoms and medical treatments of COVID-19 patients | [ |
| 8 | 9 | Adults Chinese patients were hospitalised without any comorbidities | Diarrhea and urinary irritation | 2 | Detection of SARS-CoV-2 RNA in urine and blood samples, and anal, oropharyngeal swabs of confirmed COVID-19 patients | [ |
ICU: Intensive care unit; COVID-19: Coronavirus disease 2019; SARS-CoV-2: Severe acute respiratory syndrome coronavirus 2.
Analysis of gut microbiota in coronavirus disease 2019 patients in different cohorts
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| 1 | A pilot study with 15 healthy individuals (controls) and 15 patients with COVID-19 | 15 | Study performed with hospitalised patients (median age 55 years), Chinese ethnicity and comorbidities were reported | Hong Kong | Abundance of | Change in the fecal microbiome of COVID-19 patients during hospitalization, compared to healthy individuals (controls) | [ |
| 2 | The two-hospitals cohort, serial stool samples collected from 27 COVID-19 patients among 100 | 27 | Adults hospitalised Chinese patients, comorbidities were noted | Hong Kong |
| Gut microbiome involved in COVID-19 severity | [ |
| 3 | United States cohort (majority African American) | 50 | Studied patients (mean age 62.3 years) were hospitalised with comorbidities, American ethnicity | United States | Some of the significant genera ( | No significant associations found between the composition microbiome and disease severity from COVID-19 patient gut microbiota | [ |
| 4 | The study used 53 COVID-19 patients and 76 healthy individuals. 81 fecal samples collected during hospitalization | 53 | Adults Chinase hospitalised patients, no such comorbidities were noted | China | Elevated gut microbes such as | COVID-19 infection linked with change of the microbiome in COVID-19 patients | [ |
| 5 | 15 patients Cohort | 15 | Study performed adults hospitalised patients with comorbidities, Chinese ethnicity | Hong Kong | Elevated bacterial species | The study found fecal viral (SARS-CoV-2) activity | [ |
| 6 | Two-hospital cohort with a total of 100 patients. Stool samples collected from 27 patients | 27 | Hospitalised adults patients were from China, comorbidities were noted | Hong Kong | Several gut microbiota such as | Gut microbiota associated disease severity and inflammation in COVID-19 patients | [ |
| 7 | 98 COVID-19 patients (3 asymptomatic, 34 moderate, 53 mild, 3 critical, 5 severe), serial fecal samples collected from 37 COVID-19 patients | 37 | Adults (mean age 37 years) patients, hospitalised condition from Chinese ethnicity, comorbidities were reported | Hong Kong | A total of 10 virus species in fecal matter (9 DNA virus species and 1 RNA virus, pepper chlorotic spot virus) | Analysis of gut virome (RNA and DNA virome) in COVID-19 patients | [ |
| 8 | Study of fecal samples from 30 COVID-19 patients | 30 | Patients (mean age 46 years) were hospitalised from Chinese groups, comorbidities were noted | Hong Kong | Increased proportions of fungal pathogens ( | Analysis of fecal fungal microbiome of COVID-19 patients | [ |
COVID-19: Coronavirus disease 2019.
Figure 3The diagram illustrates increased or decreased gut microbiota in coronavirus disease 2019 patients, including bacterial, viral, and fungal populations. COVID-19: Coronavirus disease 2019.
Figure 4The diagram illustrates different types of mapped gut microbiota in coronavirus disease 2019 patients. Pro-inflammatory microbiota, opportunistic microbiota, the microbiome in severe coronavirus disease 2019 (COVID-19) patients, and the microbiome in low to moderate COVID-19 patients, anti-inflammatory microbiota, and beneficial microbiota. COVID-19: Coronavirus disease 2019.
Figure 5The diagram points out the normal gut and its microbial association. The figure also illustrates the crosstalk between the microbiome and gut-lung axis. SARS-CoV-2: Severe acute respiratory syndrome coronavirus 2.
Figure 6The diagram describes the normal gut and its microbial association. The figure also illustrates the crosstalk between the microbiome and gut-brain-lung axis. BDNF: Brain-derived neurotrophic factor; HPA: Hypothalamic-pituitary-adrenal; SARS-CoV-2: Severe acute respiratory syndrome coronavirus 2.
Figure 7The figure illustrates an association between gut microbiota and hypoxia in coronavirus disease 2019 patients, and it is connected with central nervous system. SARS-CoV-2: Severe acute respiratory syndrome coronavirus 2.
Figure 8The figure illustrates normal gut microbiota and immunological consequences, and coronavirus disease 2019 related altered gut microbiota associated inflammation. A: Normal gut microbiota and immunological consequences for healthy gut; B: Coronavirus disease 2019 (COVID-19) related altered gut microbiota associated inflammation. The inflammatory condition in COVID-19 patients causes the abnormal release of different cytokines, such as interleukin-1 beta (IL-1β), IL-6, IL-8, IL-10, IL-12, granulocyte-macrophage colony-stimulating factor, tumor necrosis factor-alpha, and interferon-gamma. PSA: Polysaccharide A; SCFA: Short-chain fatty acid; IL-1β: Interleukin-1 beta; IL-6: Interleukin-6; GMCSF: Granulocyte-macrophage colony-stimulating factor; TNF-α: Tumor necrosis factor-alpha; IFN-γ: Interferon-gamma.
List of clinical trials initiated to understand the role of gut microbiota in coronavirus disease 2019 and its therapeutic implications
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| 1 | Evaluate the combination of probiotics ( | NCT04517422 | It was a randomized controlled trial, 300 participants, treatment by dietary supplement (probiotics) | Observational study of adult and older adult, trial completed |
| 2 | To explore the natural history of mild-to-moderate COVID-19 illness and safety of a novel glycan (KB109) and self-supportive care | NCT04414124 | It was a randomized, prospective, open-label, parallel-group controlled clinical study of 350 participants | Observational study of adults (both male and female), trial completed |
| 3 | Investigate the physiologic effects of the novel glycan (KB109) on patients with COVID-19 illness on gut microbiota structure and function in the outpatient | NCT04486482 | It was a randomized, open-label clinical study of 49 participants | Observational study of adults patients with mild-to-moderate COVID-19 infections, trial completed |
| 4 | Evaluate the clinical contribution of the gut microbiota and its diversity on the COVID-19 disease severity and the viral load | NCT05107245 | It was case-control, diagnostic study of 143 participants | Observational study on the diagnostic evaluation of the human intestinal microbiota, trial completed |
| 5 | Studied the effects of | NCT04366180 | A randomized, interventional study of 314 participants | Investigation of probiotic effects to healthcare personnel exposed to COVID-19 infection |
| 6 | Investigate to exploring the role of nutritional support by probiotics to COVID-19 outpatients (adult) | NCT04907877 | Randomized, evidence based study of 300 participants | Used of probiotics as dietary supplement that enhance specific immune response of patients having COVID-19 respiratory infection |
| 7 | Use of dietary supplement (Omni-Biotic® 10 AAD) can decrease the intestinal inflammation and improves dysbiosis for COVID-19 patients | NCT04420676 | It was a randomized Interventional study of 30 participants | This study performed as double blind, placebo-controlled study |
| 8 | Evaluate the probiotics efficacy to decrease the COVID-19 infection symptoms and duration of COVID-19 positive patients | NCT04621071 | The double-blind, randomized, controlled trial of 17 participants | This study performed to explored the effects of dietary supplement: Probiotics (2 strains 10 × 109 UFC), trial completed |
| 9 | Impact analysis of probiotic strain | NCT04734886 | It was control, randomized trial of 161 participants | To assess the upon and after COVID-19 infection in healthy adults, trial completed |
| 10 | To evaluate the primary efficacy of live microbials (probiotics) for boosting up the immunity of SARS-CoV-2 infected persons (unvaccinated) | NCT04847349 | It was double-blind, randomized, controlled trial of 54 participants | Efficacy analysis of dietary supplement (combination of live microbials) as anti COVID-19 infection, trial completed |
| 11 | Evaluate the follow -up of Symprove (probiotic) to COVID-19 positive patients | NCT04877704 | The randomized clinical trial was performed with 60 patients | Observational study to supervision of hospitalized COVID-19 patients |
| 12 | Study was performed to evaluate the possible effect of a probiotic mixtures in the improvement of COVID-19 infection symptoms | NCT04390477 | It was randomized case control, clinical trial of 41 participants | Observational study of dietary supplement: Probiotic to COVID-19 patients |
| 13 | The probiotic ( Omni-Biotic Pro Vi 5) use for investigate the side effect of post-COVID syndrome | NCT04813718 | It was a randomized trial of 20 participants | It was a therapeutic target study of probiotic for treatment of acute COVID-19 and prevention of post COVID infections |
| 14 | To evaluate the effect of a probiotic strain on the occurrence and severity of COVID-19 in hospitalised elderly population | NCT04756466 | Randomized control trial of 201 participants | It was observational study, probiotic sued for improve the immune response of elderly patients |
| 15 | This study assesses the beneficial effects of the nutritional supplementation (ABBC1) to individuals taken the COVID-10 vaccine | NCT04798677 | It was a double-blinded, placebo-controlled, randomized clinical study of 90 participants | Used as knowing the microbiome modulating properties, observational study |
| 16 | To investigate the consequence of | NCT04922918 | Non-randomised study of 25 participants | Observational study of aged patients having highly affected by COVID-19 |
| 17 | Study was performed to explored the effect of the probiotic | NCT04399252 | It was a randomized double-blind, placebo-controlled trail of 182 participants | Observational study of individuals microbiome of household contacts exposed to COVID-19 |
| 18 | Treatment approaches by probiotics to human gut microbiome and growing the anti-inflammatory response for COVID-19 infected patients | NCT04854941 | It was a randomized controlled open-label study of 200 participants | The optimizing treatment approaches based observational study, trial completed |
| 19 | To evaluate the capability of the novel nutritional supplement (probiotics and other vitamins) to COVID-19 infected and hospitalised patients | NCT04666116 | Randomized, single blind clinical trial of 96 participants | Used of dietary supplementation with probiotics aims to reduce the viral load |
| 20 | Using of probiotics for COVID 19 transmission reduction to health care professionals | NCT04462627 | It was a non-randomized trial of 500 participants | Analysis and reduction of COVID-19 viral load to health care professionals |
P. acidilactici: Pediococcus acidilactici; L. plantarum: Lactobacillus plantarum; COVID-19: Coronavirus disease 2019; SARS-CoV-2: Severe acute respiratory syndrome coronavirus 2.