Negative conversion, lymphocyte/monocyte ratio, and bilirubinemia in COVID-19 with mental disorders (preprint)

This retrospective study explored the changes in biomarkers indicators and prognosis in COVID-19 patients with mental disorders (n = 60) from the author’ Hospital between 2/13/2020 and 4/15/2020. Significant differences before and after negative conversion were observed in lymphocytes, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, aspartate aminotransferase, albumin, albumin/globulin ratio, direct bilirubin, alkaline phosphatase, uric acid, high-density lipoprotein cholesterol, and ApoA1 (all P < 0.05). Compared with the patients who had a negative conversion within 3 weeks, those who did not turn negative within 3 weeks had a higher frequency of cardiovascular diseases (27.3% vs. 4.2%, P = 0.040), a higher lymphocyte-to-monocyte ratio (median, 4.72 vs. 3.35, P = 0.003), and higher total bilirubin levels (median, 12.0 vs. 8.6 µmol/L, P = 0.031). The results present the changes in laboratory parameters in COVID-19 patients with a mental disorder. Cardiovascular diseases and higher lymphocyte-to-monocyte ratio, and total bilirubin levels could be associated with the amount of time required for negative conversion.

Guild-level microbiome signature associated with COVID-19 severity and prognosis (preprint)

COVID-19 severity has been associated with alterations of the gut microbiota. However, the relationship between gut microbiome alterations and COVID-19 prognosis remains elusive. Here, we performed a genome-resolved metagenomic analysis on fecal samples collected from 300 in-hospital COVID-19 patients at time of admission. Among the 2,568 high quality metagenome-assembled genomes (HQMAGs), Redundancy Analysis identified 33 HQMAGs which showed differential distribution among mild, moderate, and severe/critical severity groups. Random Forest model based on these 33 HQMAGs classified patients from different severity groups (average AUC = 0.79). Co-abundance network analysis found that the 33 HQMAGs were organized as two competing guilds. Guild 1 harbored more genes for short-chain fatty acid biosynthesis, and fewer genes for virulence and antibiotic resistance, compared with Guild 2. Random Forest regression showed that these 33 HQMAGs at admission had the capacity to predict 8 clinical parameters, which are predictors for COVID-19 prognosis, at Day 7 in hospital. Moreover, the dominance of Guild 1 over Guild 2 at admission predicted the death/discharge outcome of the critical patients (AUC = 0.92). Random Forest models based on these 33 HQMAGs classified patients with different COVID-19 symptom severity, and differentiated COVID-19 patients from healthy subjects, non-COVID-19, and pneumonia controls in three independent datasets. Thus, this genome-based guild-level signature may facilitate early identification of hospitalized COVID-19 patients with high risk of more severe outcomes at time of admission.

Feasibility for SARS-CoV-2 Tests in the Hospital: An Exposure Analysis of Critical Control Points Approach (preprint)

This work aims to assess the feasibility of performing COVID-19 RNA tests in hospitals and communities experiencing SARS-CoV-2 virus outbreaks, to ultimately provide recommendations for hospitals with so-called fever clinics. In China, these specialized clinics within a hospital specifically receive outpatients with fever symptoms. A team with expertise in the Exposure Analysis and Critical Control Points (EACCP) framework identified potential infection routes during the testing for SARS-CoV-2, then constructed and tested flow diagrams, which were confirmed under actual conditions, demonstrating the feasibility to carry out in hospitals with fever clinics. The team determined critical control points to mitigate the exposure risks at each control point. The sampling and inactivation steps of clinical samples in fever clinics appeared to be associated with particularly high-risk levels of exposure to SARS-CoV-2. Moderate exposure levels were associated with storage and transportation of samples for inactivation; Low-risk levels associated with the transportation, storage, and detection steps after inactivation. To minimize infection risks for personnel, we proposed optimized processes to carry out SARS-CoV-2 RNA tests in hospitals with fever clinics in China. The high risk of SARS-CoV-2 exposure during procedures preceding testing is the sampling and biological inactivation; Simultaneously, full personal protective equipment and BSL2 laboratories in fever clinics or mobile BSL2 laboratories could reduce the risk. Implementing the EACCP framework could facilitate rapid responses to outbreaks of emerging infectious diseases.

Transcriptional Difference between SARS-COV-2 and other Human Coronaviruses Revealed by Sub-genomic RNA Profiling (preprint)

SARS-COV-2 and all other coronaviruses express its 3 prime genes by forming sub-genomic RNA. As the genome of these virus exist in RNA form, only by profiling the relative abundance of these sgRNAs, can the viral transcriptome be revealed. Utilizing publically available meta-transcriptomic data generated from patient samples, we were able to infer the viral transcriptome in vivo, which is distinct from the in vitro one derived from cell culture. Inter-sample diversity was also observed and a sample specific transcript was identified. By doing the same analysis to MERS and SARS data, we were able to compare the three in terms of transcription. Among the differences, SARS-COV-2 has significantly elevated expression of the Spike gene, which may contribute to its high transmissibility. HighlightsO_LIThe in vivo transcriptome of SARS-CoV-2 revealed by sgRNA profiling, for 25 patient samples around the globe. C_LIO_LIThe Spike protein expression is an order of magnitude higher in SARS-CoV-2 than MERS-CoV or SARS-CoV, possibly contributing to the virus elevated transmissibility. C_LIO_LIThe in vivo SARS-CoV-2 transcriptomes, as inferred from human patient data was distinct from the in vitro one derived from cell line culture, all the accessory genes were up-regulated in vivo, suggesting intricate expression regulation mechanism for the small viral genome. C_LI