BACKGROUND & AIMS: Although severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infects gastrointestinal tissues, little is known about the roles of gut commensal microbes in susceptibility to and severity of infection. We investigated changes in fecal microbiomes of patients with SARS-CoV-2 infection during hospitalization and associations with severity and fecal shedding of virus. METHODS: We performed shotgun metagenomic sequencing analyses of fecal samples from 15 patients with Coronavirus Disease 2019 (COVID-19) in Hong Kong, from February 5 through March 17, 2020. Fecal samples were collected 2 or 3 times per week from time of hospitalization until discharge; disease was categorized as mild (no radiographic evidence of pneumonia), moderate (pneumonia was present), severe (respiratory rate !30/min, or oxygen saturation 93% when breathing ambient air), or critical (respiratory failure requiring mechanical ventilation, shock, or organ failure requiring intensive care). We compared microbiome data with those from 6 subjects with communityacquired pneumonia and 15 healthy individuals (controls). We assessed gut microbiome profiles in association with disease severity and changes in fecal shedding of SARS-CoV-2. RESULTS: Patients with COVID-19 had significant alterations in fecal microbiomes compared with controls, characterized by enrichment of opportunistic pathogens and depletion of beneficial commensals, at time of hospitalization and at all timepoints during hospitalization. Depleted symbionts and gut dysbiosis persisted even after clearance of SARS-CoV-2 (determined from throat swabs) and resolution of respiratory Gastroenterology 2020;159:944-955 BASIC AND TRANSLATIONAL AT symptoms. The baseline abundance of Coprobacillus, Clostridium ramosum, and Clostridium hathewayi correlated with COVID-19 severity; there was an inverse correlation between abundance of Faecalibacterium prausnitzii (an antiinflammatory bacterium) and disease severity. Over the course of hospitalization, Bacteroides dorei, Bacteroides thetaiotaomicron, Bacteroides massiliensis, and Bacteroides ovatus, which downregulate expression of angiotensin-converting enzyme 2 (ACE2) in murine gut, correlated inversely with SARS-CoV-2 load in fecal samples from patients. CONCLUSIONS: In a pilot study of 15 patients with COVID-19, we found persistent alterations in the fecal microbiome during the time of hospitalization, compared with controls. Fecal microbiota alterations were associated with fecal levels of SARS-CoV-2 and COVID-19 severity. Strategies to alter the intestinal microbiota might reduce disease severity.

Significance There is growing evidence that preexisting autoantibodies neutralizing type I interferons (IFNs) are strong determinants of life-threatening COVID-19 pneumonia. It is important to estimate their quantitative impact on COVID-19 mortality upon SARS-CoV-2 infection, by age and sex, as both the prevalence of these autoantibodies and the risk of COVID-19 death increase with age and are higher in men. Using an unvaccinated sample of 1,261 deceased patients and 34,159 individuals from the general population, we found that autoantibodies against type I IFNs strongly increased the SARS-CoV-2 infection fatality rate at all ages, in both men and women. Autoantibodies against type I IFNs are strong and common predictors of life-threatening COVID-19. Testing for these autoantibodies should be considered in the general population.

Baricitinib therapy in COVID-19: A pilot study on safety and clinical impactDear Editor , 38.1 (37.7-38.7) 0.356 Breath rate N/min, median (IQR), 23 (19.5-24.2) 22 (19.7-24) 0.665 SpO2 (%),median (IQR) 91 (90-92.5) 92 (91.2-93) 0.157 PaO2/FiO2, median (IQR) 290 (199.2-292.2) 268.6 (264.4-295) 0.603 Pulse rate, median (IQR) 82 (73-88.3) 90 (87.2-94.5) 0.069 SBP mm/Hg, median (IQR) 120 (110-131.2) 105 (100-111.25) 0.003 DBP mm/Hg, median (IQR) 70 (60-80) 62.5 (60-66.25) 0.094 WBC (x10 9 /L), median (IQR) 7.8 (5.8-10.8) 8.2 (7.3-8.8) 0.908 Neutrophils (x10 9 /L), median (IQR) 6,5 (4.5-7.7) 6.9 (6.4-7.6) 0.707 Lymphocytes (x10 9 /L), median (IQR) 0.7 (0.7-1.2) 0.89 (0.7-0.9) 1.0 0 0 Hemoglobin (g/L), median (IQR) 118 (102-134.2) 125 (108-134) 0.568 Platelets (x10 9 /L), median (IQR) 203 (174-227) 366 (340-407) 0.0 0 0 ALT (U/L), median (IQR) 28.5 (23.5-52) 44 (37-50) 0.157 AST (U/L), median (IQR) 34 (26.2-48) 44 (34.7-47) 0.525 Creatinine (mg/dl), median (IQR)1.0 (0.9-1.1) 1.00 (0.9-1) 0.583 CRP (mg/dl), median (IQR) 8.2 (5.8-14.5) 3 (1.5-3.2) 0.002 Procalcitonin ng/ml, median (IQR) 0.7 (0.4-1.1) 1.2 (0.8-2.1) 0.902 MEWS, median (IQR) 3 ( 2-3.25) 3 (3-4) 0.544 Abbreviations and symbols: N = number;% = percentage; °C: grade Celsius; min = minute; SpO2 = peripheral capillary oxygen saturation; PaO2/FiO2 = ratio of arterial oxygen partial pressure to fractional inspired oxygen; SBP = systolic blood pressure; DBP = diastolic blood pressure; WBC = white blood cells; AST = serum glutamic oxaloacetic transaminase; ALT = serum alanine aminotransferase; MEWS = Modified Early Warning Score; IQR: Interquartile range.

Objectives/Hypothesis: This study investigated olfactory and gustatory dysfunction in the 2020 novel coronavirus disease (COVID-19) patients, and their correlations with viral load evaluation. Study Design: Prospective cross-sectional cohort study. Methods: One hundred forty-three symptomatic patients being screened for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were invited to participate. The clinical data of 83 confirmed COVID-19 subjects were collected, with 60 patients who were symptomatic but negative for COVID-19 recruited as controls. The prevalence and severity of and recovery time for olfactory and gustatory dysfunction, and cycle threshold (Ct) values from a SARS-CoV-2 polymerase chain reaction assay of nasopharyngeal and deep throat swabs were collected. Their correlations with Ct values were reported. Results: Thirty-nine (47.0%) and 36 (43.4%) COVID-19 patients reported olfactory and gustatory dysfunction, respectively. The results of one-way analysis of variance did not show statistically significant relationships between the Ct values and severity of olfactory and gustatory dysfunction (P = .780 and P = .121, respectively). Among the COVID-19 patients who reported smell and taste loss, 28/39 (71.8%) and 30/36 (83.3%) experienced complete recovery, respectively. The mean recovery time was 10.3 ± 8.1 days for olfactory dysfunction and 9.5 ± 6.8 days for gustatory dysfunction. The recovery time was not correlated with the Ct values (Pearson correlation coefficient, smell: −0.008, P = .968; taste: −0.015, P = .940). Conclusions: There is a high prevalence of olfactory and gustatory dysfunction in COVID-19. However, the severity of and recovery from these symptoms have no correlations with the viral load of SARS-CoV-2.

The cytokine release syndrome has been proposed as the driver of inflammation in coronavirus disease 2019 (COVID-19). However, studies on longitudinal cytokine profiles in patients across the whole severity spectrum of COVID-19 are lacking. In this prospective observational study on adult COVID-19 patients admitted to two Hong Kong public hospitals, cytokine profiling was performed on blood samples taken during early phase (within 7 days of symptom onset) and late phase (8 to 12 days of symptom onset). The primary objective was to evaluate the difference in early and late cytokine profiles among patient groups with different disease severity. The secondary objective was to assess the associations between cytokines and clinical endpoints in critically ill patients. A total of 40 adult patients (mild = 8, moderate = 15, severe/critical = 17) hospitalized with COVID-19 were included in this study. We found 22 cytokines which were correlated with disease severity, as proinflammatory Th1-related cytokines (interleukin (IL)-18, interferon-induced protein-10 (IP-10), monokine-induced by gamma interferon (MIG), and IL-10) and ARDS-associated cytokines (IL-6, monocyte chemoattractant protein-1 (MCP-1), interleukin-1 receptor antagonist (IL-1RA), and IL-8) were progressively elevated with increasing disease severity. Furthermore, 11 cytokines were consistently different in both early and late phases, including seven (growth-regulated oncogene-alpha (GRO-α), IL-1RA, IL-6, IL-8, IL-10, IP-10, and MIG) that increased and four (FGF-2, IL-5, macrophage-derived chemokine (MDC), and MIP-1α) that decreased from mild to severe/critical patients. IL-8, followed by IP-10 and MDC were the best performing early biomarkers to predict disease severity. Among critically ill patients, MCP-1 predicted the duration of mechanical ventilation, highest norepinephrine dose administered, and length of intensive care stay.