Gut microbiota, inflammation, and molecular signatures of host response to infection.

Gut microbial dysbiosis has been linked to many noncommunicable diseases. However, little is known about specific gut microbiota composition and its correlated metabolites associated with molecular signatures underlying host response to infection. Here, we describe the construction of a proteomic risk score based on 20 blood proteomic biomarkers, which have recently been identified as molecular signatures predicting the progression of the COVID-19. We demonstrate that in our cohort of 990 healthy individuals without infection, this proteomic risk score is positively associated with proinflammatory cytokines mainly among older, but not younger, individuals. We further discover that a core set of gut microbiota can accurately predict the above proteomic biomarkers among 301 individuals using a machine learning model and that these gut microbiota features are highly correlated with proinflammatory cytokines in another independent set of 366 individuals. Fecal metabolomics analysis suggests potential amino acid-related pathways linking gut microbiota to host metabolism and inflammation. Overall, our multi-omics analyses suggest that gut microbiota composition and function are closely related to inflammation and molecular signatures of host response to infection among healthy individuals. These results may provide novel insights into the cross-talk between gut microbiota and host immune system.

Proteomic and metabolomic profiling of urine uncovers immune responses in patients with COVID-19.

The utility of the urinary proteome in infectious diseases remains unclear. Here, we analyzed the proteome and metabolome of urine and serum samples from patients with COVID-19 and healthy controls. Our data show that urinary proteins effectively classify COVID-19 by severity. We detect 197 cytokines and their receptors in urine, but only 124 in serum using TMT-based proteomics. The decrease in urinary ESCRT complex proteins correlates with active SARS-CoV-2 replication. The downregulation of urinary CXCL14 in severe COVID-19 cases positively correlates with blood lymphocyte counts. Integrative multiomics analysis suggests that innate immune activation and inflammation triggered renal injuries in patients with COVID-19. COVID-19-associated modulation of the urinary proteome offers unique insights into the pathogenesis of this disease. This study demonstrates the added value of including the urinary proteome in a suite of multiomics analytes in evaluating the immune pathobiology and clinical course of COVID-19 and, potentially, other infectious diseases.

Eleven routine clinical features predict COVID-19 severity uncovered by machine learning of longitudinal measurements.

Severity prediction of COVID-19 remains one of the major clinical challenges for the ongoing pandemic. Here, we have recruited a 144 COVID-19 patient cohort, resulting in a data matrix containing 3,065 readings for 124 types of measurements over 52 days. A machine learning model was established to predict the disease progression based on the cohort consisting of training, validation, and internal test sets. A panel of eleven routine clinical factors constructed a classifier for COVID-19 severity prediction, achieving accuracy of over 98% in the discovery set. Validation of the model in an independent cohort containing 25 patients achieved accuracy of 80%. The overall sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 0.70, 0.99, 0.93, and 0.93, respectively. Our model captured predictive dynamics of lactate dehydrogenase (LDH) and creatine kinase (CK) while their levels were in the normal range. This model is accessible at https://www.guomics.com/covidAI/ for research purpose.

Clinical evaluation of a rapid colloidal gold immunochromatography assay for SARS-Cov-2 IgM/IgG.

BACKGROUND: Since December 2019, there had been an outbreak of COVID-19 in Wuhan, China. At present, diagnosis COVID-19 were based on real-time RT-PCR, which have to be performed in biosafe laboratory and is unsatisfactory for suspect case screening. Therefore, there is an urgent need for rapid diagnostic test for COVID-19. OBJECTIVE: To evaluate the diagnostic performance and clinical utility of the colloidal gold immunochromatography assay for SARS-Cov-2 specific IgM/IgG anti-body detection in suspected COVID-19 cases. METHODS: In the prospective cohort, 150 patients with fever or respiratory symptoms were enrolled in Taizhou Public Health Medical Center, Taizhou Hospital, Zhejiang province, China, between January 20 to February 2, 2020. All patients were tested by the colloidal gold immunochromatography assay for COVID-19. At least two samples of each patient were collected for RT-PCR assay analysis, and the PCR results were performed as the reference standard of diagnosis. Meanwhile 26 heathy blood donor were recruited. The sensitivity and specificity of the immunochromatography assay test were evaluated. Subgroup analysis were performed with respect to age, sex, period from symptom onset and clinical severity. RESULTS: The immunochromatography assay test had 69 positive result in the 97 PCR-positive cases, achieving sensitivity 71.1% [95% CI 0.609-0.797], and had 2 positive result in the 53 PCR-negative cases, achieving specificity 96.2% [95% CI 0.859-0.993]. In 26 healthy donor blood samples, the immunochromatography assay had 0 positive result. In subgroup analysis, the sensitivity was significantly higher in patients with symptoms more than 14 days 95.2% [95% CI 0.741-0.998] and patients with severe clinical condition 86.0% [95% CI 0.640-0.970]. CONCLUSIONS: The colloidal gold immunochromatography assay for SARS-Cov-2 specific IgM/IgG anti-body had 71.1% sensitivity and 96.2% specificity in this population, showing the potential for a useful rapid diagnosis test for COVID-19. Further investigations should be done to evaluate this assay in variety of clinical settings and populations.

Mask wearing in pre-symptomatic patients prevents SARS-CoV-2 transmission: An epidemiological analysis.

OBJECTIVES: Pandemic COVID-19 has become a seriously public health priority worldwide. Comprehensive strategies including travel restrictions and mask-wearing have been implemented to mitigate the virus circulation. However, detail information on community transmission is unavailable yet. METHODS: From January 23 to March 1, 2020, 127 patients (median age: 46 years; range: 11-80) with 71 male and 56 female, were confirmed to be infected with the SARS-CoV-2 in Taizhou, Zhejiang, China. Epidemiological trajectory and clinical features of these COVID-19 cases were retrospectively retrieved from electronic medical records and valid individual questionnaire. RESULTS: The disease onset was between January 9 to February 14, 2020. Among them, 64 patients are local residents, and 63 patients were back home from Wuhan from January 10 to 24, 2020 before travel restriction. 197 local residents had definite close-contact with 41 pre-symptomatic patients back from Wuhan. 123 and 74 of them contact with mask-wearing or with no mask-wearing pre-symptomatic patients back from Wuhan, respectively. Data showed that incidence of COVID-19 was significantly higher for local residents close-contact with no mask-wearing Wuhan returned pre-symptomatic patients (19.0% vs. 8.1%, p < 0.001). Among 57 close-contact individuals, 21 sequential local COVID-19 patients originated from a pre-symptomatic Wuhan returned couple, indicated dense gathering in congested spaces is a high risk for SARS-CoV-2 transmission. CONCLUSIONS: Our findings provided valuable details of pre-symptomatic patient mask-wearing and restriction of mass gathering in congested spaces particularly, are important interventions to mitigate the SARS-CoV-2 transmission.