The interplay between the compositional changes in the gastrointestinal microbiome, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) susceptibility and severity, and host functions is complex and yet to be fully understood. This study performed 16S rRNA gene-based microbial profiling of 143 subjects. We observed structural and compositional alterations in the gut microbiota of the SARS-CoV-2-infected group in comparison to non-infected controls. The gut microbiota composition of the SARS-CoV-2-infected individuals showed an increase in anti-inflammatory bacteria such as Faecalibacterium (p-value = 1.72 × 10–6) and Bacteroides (p-value = 5.67 × 10–8). We also revealed a higher relative abundance of the highly beneficial butyrate producers such as Anaerostipes (p-value = 1.75 × 10–230), Lachnospiraceae (p-value = 7.14 × 10–65), and Blautia (p-value = 9.22 × 10–18) in the SARS-CoV-2-infected group in comparison to the control group. Moreover, phylogenetic investigation of communities by reconstructing unobserved state (PICRUSt) functional prediction analysis of the 16S rRNA gene abundance data showed substantial differences in the enrichment of metabolic pathways such as lipid, amino acid, carbohydrate, and xenobiotic metabolism, in comparison between both groups. We discovered an enrichment of linoleic acid, ether lipid, glycerolipid, and glycerophospholipid metabolism in the SARS-CoV-2-infected group, suggesting a link to SARS-CoV-2 entry and replication in host cells. We estimate the major contributing genera to the four pathways to be Parabacteroides, Streptococcus, Dorea, and Blautia, respectively. The identified differences provide a new insight to enrich our understanding of SARS-CoV-2-related changes in gut microbiota, their metabolic capabilities, and potential screening biomarkers linked to COVID-19 disease severity.

Coronavirus disease 2019 (COVID-19) was first identified in respiratory samples and was found to commonly cause cough and pneumonia. However, non-respiratory symptoms including gastrointestinal disorders are also present and a big proportion of patients test positive for the virus in stools for a prolonged period. In this cross-sectional study, we investigated viral load trends in stools and nasopharyngeal swabs and their correlation with multiple demographic and clinical factors. The study included 211 laboratory-confirmed cases suffering from a mild form of the disease and completing their isolation period at a non-hospital center in the United Arab Emirates. Demographic and clinical information was collected by standardized questionnaire and from the medical records of the patient. Of the 211 participants, 25% tested negative in both sample types at the time of this study and 53% of the remaining patients had detectable viral RNA in their stools. A positive fecal viral test was associated with male gender, diarrhea as a symptom, and hospitalization during infection. A positive correlation was also observed between a delayed onset of symptoms and a positive stool test. Viral load in stools positively correlated with, being overweight, exercising, taking antibiotics in the last 3 months and blood type O. The viral load in nasopharyngeal swabs, on the other hand, was higher for blood type A, and rhesus positive (Rh factor). Regression analysis showed no correlation between the viral loads measured in stool and nasopharyngeal samples in any given patient. The results of this work highlight the factors associated with a higher viral count in each sample. It also shows the importance of stool sample analysis for the follow-up and diagnosis of recovering COVID-19 patients.

Background: Patients with severe coronavirus disease 2019 (COVID-19) are at an increased risk of acute respiratory distress syndrome and mortality. This is due to the increased levels of pro-inflammatory cytokines that amplify downstream pathways that are controlled by immune regulators. Objective: This study aimed to investigate the association between cytokine genetic variants, cytokine serum levels/profiles, and disease severity in critically and noncritically ill COVID-19 patients. Methods: This cross-sectional study recruited 646 participants who tested positive for severe acute respiratory syndrome coronavirus 2 from six collection sites across the United Arab Emirates. Medical files were accessed to retrieve clinical data. Blood samples were collected from all participants. Patients were divided into two clinical groups, noncritical (n = 453) and critical (n = 193), according to World Health Organization classification guidelines for COVID-19 patients. Cytokine analyses were conducted on serum of a subset of the cohort, specifically on 426 participants (noncritical, 264; critical, 162). Candidate gene analyses of 33 cytokine-related genes (2,836 variants) were extracted from a genome-wide association study to identify genetic variants with pleiotropic effects on a specific cytokine and the severity of COVID-19 disease. Results: Age, body mass index (BMI), and pre-existing medical conditions were found to be significant risk factors that contribute to COVID-19 disease severity. After correcting for age, sex, and BMI, IP-10 (P < 0.001), IFN (P = 0.001), IL-6 (P < 0.001), and CXCL-16 (P < 0.001) serum levels were significantly higher among critical COVID-19 cases, when compared with noncritically ill patients. To investigate if the genetic variants involved in the serum cytokine levels are associated with COVID-19 severity, we studied several genes. Single nucleotide polymorphisms in IL6 (rs1554606; odd ratio (OR)G = 0.67 [0.66, 0.68]; P = 0.017), IFNG (rs2069718; ORG = 0.63 [0.62, 0.64]; P = 0.001), MIP (rs799187; ORA = 1.69 [1.66, 1.72]; P = 0.034), and CXCL16 (rs8071286; ORA = 1.42 [1.41, 1.44]; P = 0.018) were found to be associated with critically ill patients. Polymorphisms in the CXCL10, CCL2, IL1, CCL7, and TNF genes were not associated with the COVID-19 critical phenotype. The genotypes of IL-6 (gene, IL6 [7p15.3]) and CXCL-16 (gene, CXCL16 [17p13.2]) were significantly associated with the serum levels of the respective cytokine in critical cases of COVID-19. Conclusion: Data obtained from measuring cytokine levels and genetic variant analyses suggest that IL-6 and CXCL-16 could potentially be used as potential biomarkers for monitoring disease progression of COVID-19 patients. The findings in this study suggest that specific cytokine gene variants correlate with serum levels of the specific cytokine. These genetic variants could be of assistance in the early identification of high-risk patients on admission to the clinic to improve the management of COVID-19 patients and other infectious dise...