The Genetic Interface of Immunity and COVID-19: Insights from a Two-Sample Mendelian Randomization Approach (preprint)

Introduction Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has emerged as a global public health emergency since late 2019. Immune cells are crucial for host defense against viral infection and disease progression. However, the specific immune cell characteristics that influence susceptibility to COVID-19 remain unclear. This study aimed to investigate the causal relationship between immune cell signatures and COVID-19 using MR analysis.Materials and Methods This study utilized publicly available genetic datasets from the COVID-19 Host Genetics Initiative and the Blueprint Consortium and applied a two-sample Mendelian randomization approach to examine the association between 731 immune cell signatures and the risk of COVID-19. We included four types of immune signatures: median fluorescence intensity (MFI), relative cell count (RC), absolute cell count (AC), and morphological parameter (MP) data. We used the inverse-variance weighted (IVW) method as the primary analysis and performed several sensitivity analyses to test the robustness of the results.Results Our analysis revealed 30 distinct immune cell characteristics that were directly associated with the risk of COVID-19, including CD4 + regulatory T cells (CD4 + Treg cells), CCR2 + CD14- CD16 + monocytes, CD86 + plasmacytoid DC AC, CCR2 + plasmacytoid DC (CCR2 + pDC), CCR2 + CD62L + plasmacytoid DC (CCR2 + CD62L + pDC), and CD80 + CD62L + plasmacytoid DC (CD80 + pDC). However, among these findings, only the expression of CCR2 on CD14-CD16 + monocytes had a significant impact (P = 0.0249, OR = 1.0427, 95% CI=[1.0053, 1.0814]) on immune cell attributes in the context of COVID-19. Sensitivity analyses confirmed the validity of the IVW results and ruled out the possibility of horizontal pleiotropy.Conclusion Through two-sample Mendelian randomization analysis, we demonstrated a significant causal relationship between specific immune cell characteristics and the risk of COVID-19. These findings provide important genetic evidence for the development of future vaccines and treatment strategies.

#COVIDisAirborne: AI-Enabled Multiscale Computational Microscopy of Delta SARS-CoV-2 in a Respiratory Aerosol (preprint)

We seek to completely revise current models of airborne transmission of respiratory viruses by providing never-before-seen atomic- level views of the SARS-CoV-2 virus within a respiratory aerosol. Our work dramatically extends the capabilities of multiscale computational microscopy to address the significant gaps that exist in current experimental methods, which are limited in their ability to interrogate aerosols at the atomic/molecular level and thus obscure our understanding of airborne transmission. We demonstrate how our integrated data-driven platform provides a new way of exploring the composition, structure, and dynamics of aerosols and aerosolized viruses, while driving simulation method development along several important axes. We present a series of initial scientific discoveries for the SARS-CoV-2 Delta variant, noting that the full scientific impact of this work has yet to be realized.

Intelligent Resolution: Integrating Cryo-EM with AI-driven Multi-resolution Simulations to Observe the SARS-CoV-2 Replication-Transcription Machinery in Action (preprint)

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) replication transcription complex (RTC) is a multi-domain protein responsible for replicating and transcribing the viral mRNA inside a human cell. Attacking RTC function with pharmaceutical compounds is a pathway to treating COVID-19. Conventional tools, e.g., cryo-electron microscopy and all-atom molecular dynamics (AAMD), do not provide sufficiently high resolution or timescale to capture important dynamics of this molecular machine. Consequently, we develop an innovative workflow that bridges the gap between these resolutions, using mesoscale fluctuating finite element analysis (FFEA) continuum simulations and a hierarchy of AI-methods that continually learn and infer features for maintaining consistency between AAMD and FFEA simulations. We leverage a multi-site distributed workflow manager to orchestrate AI, FFEA, and AAMD jobs, providing optimal resource utilization across HPC centers. Our study provides unprecedented access to study the SARS-CoV-2 RTC machinery, while providing general capability for AI-enabled multi-resolution simulations at scale.

Multimorbidity and adverse events of special interest associated with CoronaVac (Sinovac) and Comirnaty (Pfizer-BioNTech) (preprint)

We examined the potential additional risk of adverse events of special interest (AESI) within 28 days post-Covid-19 vaccination with CoronaVac or Comirnaty (Pfizer-BioNTech) imposed by multimorbidity (2 + chronic conditions). Using a territory-wide public healthcare database with linkage to population-based vaccination records in Hong Kong, we conducted a retrospective cohort study of patients with chronic diseases. Thirty AESI according to World Health Organization’s Global Advisory Committee on Vaccine Safety were examined. In total, 883,416 patients were included. During follow-up, 2,807 (0.3%) patients had AESI. Weighted Cox models suggested that vaccinated patients had lower risks of any AESI than those unvaccinated, that multimorbidity was associated with an increased risk regardless of vaccination status, and there was no significant effect modification of the association of vaccination with AESI by multimorbidity status. To conclude, we found no evidence that multimorbidity imposes extra risks of AESI within 28 days following Covid-19 vaccination.

Human Mesenchymal Stem Cells Treatment for Severe COVID-19: 1-Year Follow-Up Results of a Randomized, Double-Blind, Placebo-Controlled Trial (preprint)

Background The long-term consequences of human umbilical cord-derived mesenchymal stem cell (UC-MSC) treatment for COVID-19 patients are yet to be reported. This study assessed the 1-year outcomes in patients with severe COVID-19, who were recruited in our previous UC-MSC clinical trial.Methods: In this prospective, longitudinal, cohort study, 100 patients enrolled in our phase 2 trial were prospectively followed up at 3-month intervals for 1 year to evaluate the long-term safety and effectiveness of UC-MSC treatment. The primary endpoint was an altered proportion of whole-lung lesion volumes measured by high-resolution CT. Other imaging outcomes, 6-minute walking distance (6-MWD), lung function, plasma biomarkers, and adverse events were also recorded and analyzed. This trial was registered with ClinicalTrials.gov (NCT04288102).Findings: Within 3 months, MSC administration exerted numerical improvement in whole-lung lesion volume compared with the placebo, leading to a significant difference of −10.82% (95% CI: −20.69%, −1.46%, P=0.030) on day 10. MSC also reduced the proportion of solid component lesion volume compared with the placebo at each follow-up point, with a significant difference of − 9.02% (95%CI: − 17.44%, − 0.10%, P=0.045) at month 9. More interestingly, 17.86% (10/56) of patients in the MSC group had normal CT images at month 12 ( P= 0.013), but none in the placebo group. The incidence of symptoms was lower in the MSC group than in the placebo group at each follow-up time, particularly sleep difficulties at month 3 (OR 0.19, 95% CI 0.07,0.50; P=0.001), and usual activity at month 12 (OR 0.15, 95% CI 0.03,0.79; P=0.018). Neutralizing antibodies were all positive, with a similar median inhibition rate (61.6% vs. 67.55%) in both groups at month 12. No difference in adverse events at the 1-year follow-up and tumor markers at month 12 were observed between the two groups.Interpretation: UC-MSC administration achieves a long-term benefit in the recovery of lung lesions and symptoms in COVID-19 patients.Trial Registration: This trial was registered with ClinicalTrials.gov (NCT04288102).Funding The National Key R&D Program of China, the Innovation Groups of the National Natural Science Foundation of China, and the National Science and Technology Major Project.Declaration of Interest: None to declare. Ethical Approval: This study was approved by the Ethics Committee of the Fifth Medical Center, Chinese PLA General Hospital (2020-013-D).

Heterologous vaccination strategy for containing COVID-19 pandemic (preprint)

An unequitable vaccine allocation and continuously emerging SARS-CoV-2 variants pose challenges to contain the pandemic, which underscores the need for licensing more vaccine candidates, increasing manufacturing capacity and implementing better immunization strategy. Here, we report data from a proof-of-concept investigation in two healthy individuals who received two doses of inactivated whole-virus COVID-19 vaccines, followed by a single heterologous boost vaccination after 7 months with an mRNA vaccine candidate (LPP-Spike-mRNA) developed by Stemirna Therapeutics. Following the boost, Spike-specific antibody (Ab), memory B cell and T cell responses were significantly increased. These findings indicate that a heterologous immunization strategy combining inactivated and mRNA vaccines can generate robust vaccine responses and therefore provide a rational and effective vaccination regimen.

AI-Driven Multiscale Simulations Illuminate Mechanisms of SARS-CoV-2 Spike Dynamics (preprint)

We develop a generalizable AI-driven workflow that leverages heterogeneous HPC resources to explore the time-dependent dynamics of molecular systems. We use this workflow to investigate the mechanisms of infectivity of the SARS-CoV-2 spike protein, the main viral infection machinery. Our workflow enables more efficient investigation of spike dynamics in a variety of complex environments, including within a complete SARS-CoV-2 viral envelope simulation, which contains 305 million atoms and shows strong scaling on ORNL Summit using NAMD. We present several novel scientific discoveries, including the elucidation of the spikes full glycan shield, the role of spike glycans in modulating the infectivity of the virus, and the characterization of the flexible interactions between the spike and the human ACE2 receptor. We also demonstrate how AI can accelerate conformational sampling across different systems and pave the way for the future application of such methods to additional studies in SARS-CoV-2 and other molecular systems. ACM Reference FormatLorenzo Casalino1{dagger}, Abigail Dommer1{dagger}, Zied Gaieb1{dagger}, Emilia P. Barros1, Terra Sztain1, Surl-Hee Ahn1, Anda Trifan2,3, Alexander Brace2, Anthony Bogetti4, Heng Ma2, Hyungro Lee5, Matteo Turilli5, Syma Khalid6, Lillian Chong4, Carlos Simmerling7, David J. Hardy3, Julio D. C. Maia3, James C. Phillips3, Thorsten Kurth8, Abraham Stern8, Lei Huang9, John McCalpin9, Mahidhar Tatineni10, Tom Gibbs8, John E. Stone3, Shantenu Jha5, Arvind Ramanathan2*, Rommie E. Amaro1*. 2020. AI-Driven Multiscale Simulations Illuminate Mechanisms of SARS-CoV-2 Spike Dynamics. In Supercomputing 20: International Conference for High Performance Computing, Networking, Storage, and Analysis. ACM, New York, NY, USA, 14 pages. https://doi.org/finalDOI

Treatment with human umbilical cord-derived mesenchymal stem cells for COVID-19 patients with lung damage: a randomised, double-blind, placebo controlled phase 2 trial (preprint)

Objective To assess the safety and efficacy of human umbilical cord-derived MSCs (UC-MSCs) for severe COVID-19 patients with lung damage. Design, Multicentre , randomised, double-blind, placebo-controlled trial. Setting Two hospitals in Wuhan, China, 5 March 2020 to 28 March 2020. Participants 101 severe COVID-19 patients with lung damage aged between 18-74 years. Intervention Patients were randomly assigned at a 2:1 ratio to receive either UC-MSCs (40 million cells per infusion) or placebo on days 0, 3, and 6. Main outcome measures The primary endpoints were safety and an altered proportion of whole lung lesion size from baseline to day 28, measured by chest computed tomography. Secondary outcomes were reduction of consolidation lesion sizeand lung function improvement (6-minute walk test, maximum vital capacity, diffusing capacity). Primary analysis was done in the modified intention-to-treat (mITT) population and safety analysis was done in all patients who started their assigned treatment. Results 100 patients were finally recruited to receive either UC-MSCs (n = 65) or placebo (n = 35). The patients receiving UC-MSCs exhibited a trend of numerical improvement in whole lung lesion size from baseline to day 28 compared with the placebo cases (the median difference was -13.31%, 95%CI -29.14%, 2.13%, P=0.080). UC-MSCs administration significantly reduced the proportions of consolidation lesion size from baseline to day 28 compared with the placebo (median difference: -15.45%, 95% CI -30.82%, -0.39%, P=0.043). The 6-minute walk test showed an increased distance in patients treated with UC-MSCs (difference: 27.00 m, 95% CI 0.00, 57.00, P=0.057). The incidence of adverse events was similar, and no serious adverse events were observed in the two groups. Conclusions UC-MSCs treatment is a safe and potentially effective therapeutic approach for COVID-19 patients with lung damage. A phase 3 trial is required to evaluate effects on reducing mortality and preventing long-term pulmonary disability.

Treatment with Human Umbilical Cord-Derived Mesenchymal Stem Cells for Severe COVID-19 Patients with Lung Damage: A Randomised, Double-Blind, Placebo‑Controlled Phase 2 Trial (preprint)

Background: Treatment of severe Corona Virus Disease 2019 (COVID-19) is challenging. We performed a phase 2 trial to assess the efficacy and safety of human umbilical cord-mesenchymal stem cells (UC‑MSCs) to treat patients with severe COVID-19 with lung damage, based on our phase 1 data.Methods: In this randomised, double-blind, and placebo-controlled trial, we recruited 101 eligible patients with severe COVID-19 with lung damage aged between 18–74 years from two hospitals. Enrolled patients were randomly assigned at a 2:1 ratio to receive either UC-MSCs (4 × 107 cells per infusion) or placebo on day 0, 3, and 6. We excluded patients with malignant tumours, shock, or other organ failure. The primary endpoint was an altered proportion of whole lung lesion areas from baseline to day 28, measured by chest computed tomography. Other imaging outcomes, 6-minute walk test, maximum vital capacity, diffusing capacity, plasma biomarkers, and adverse events were recorded and analysed. Primary analysis was done in the modified intention-to-treat (mITT) population and safety analysis was done in all patients who started their assigned treatment. Findings: From March 5, 2020, to March 28, 2020, 100 patients were finally enrolled and received either UC-MSCs (n = 65) or placebo (n = 35). During follow-up, the patients receiving UC-MSCs exhibited a trend of numerical improvement in whole lung lesions from baseline to day 28 compared with the placebo cases. UC-MSCs administration significantly reduced the proportions of consolidation lesions from baseline to day 28 in the treated patients compared with the placebo subjects. The 6-minute walk test showed an increased distance in patients treated with UC-MSCs. Notably, UC-MSCs delivery was well tolerated, with no serious adverse events.Interpretation: UC-MSCs treatment is a safe and potentially effective therapeutic approach for patients with severe COVID‑19. The trial suggests that UC-MSCs administration might benefit patients with COVID-19 with lung damage at the convalescent stage as well as the progression stage.Trial Registration: This trial is registered with ClinicalTrials.gov, number NCT04288102.Funding Statement: This trial was supported by The National Key R&D Program of China (2020YFC0841900, 2020YFC0844000, 2020YFC08860900); The Innovation Groups of the National Natural Science Foundation of China (81721002); The National Science and Technology Major Project (2017YFA0105703).Declaration of Interests: All authors declare no competing interests.Ethics Approval Statement: Ethical approval was obtained from the institutional review boards of each participating hospital. Written informed consent was obtained from all the enrolled patients or their legal representatives if they were unable to provide consent.

The Impact of COVID-19 Pandemic on Gig Economy Labor Supply (preprint)

Using data from a large online education platform with more than 100,000 gig workers, we investigate the causal impact of the COVID-19 pandemic on gig economy labor supply and quantify how much of the impact can be attributed to lockdown policies. The average labor supply on the gig economy platform increases by 25% during the pandemic. The impact is nationwide and is stronger in states with more confirmed cases of COVID-19. The impact of state-level shelter-in-place or stay-at-home orders accounts for only 7%~16% of the overall impact of the pandemic, suggesting that simply lifting the lockdown policies without controlling the disease well is unlikely to get the economy back on track. We also evaluate how female and male workers respond differently. Although both female and male workers increase their labor supply, female workers' increase in labor supply is smaller than male workers', and consequently, the already existing gender gap in labor supply increases by 31%. The increase in gender gap is primarily driven by workers in their age of 30-50, implying that the increase in gender gap is likely to be caused by the school closures during the pandemic and the disproportionate allocation of housework and childcare responsibility across gender.

Coronavirus disease 2019 in pregnancy.

OBJECTIVES: This study aimed to compare clinical courses and outcomes between pregnant and reproductive-aged non-pregnant women with COVID-19, and to assess the vertical transmission potential of COVID-19 in pregnancy. METHODS: Medical records of pregnant and reproductive-aged non-pregnant women hospitalized with COVID-19 from January 15 to March 15, 2020 were retrospectively reviewed. The severity of disease, virus clearance time, and length of hospital stay were measured as the primary objective, while the vertical transmission potential of COVID-19 was also assessed. RESULTS: Eighty-two patients (28 pregnant women, 54 reproductive-aged non-pregnant women) with laboratory-confirmed COVID-19 were enrolled in this study. Univariate regression indicated no association between pregnancy and severity of disease (OR 0.73, 95% CI 0.08-5.15; p=0.76), virus clearance time (HR 1.16, 95% CI 0.65-2.01; p=0.62), and length of hospital stay (HR 1.10, 95% CI 0.66-1.84; p=0.71). Of the pregnant women, 22 delivered 23 live births, either by cesarean section (17, 60.7%) or vaginal delivery (5, 17.9%), and no neonate was infected with SARS-CoV-2. CONCLUSIONS: Pregnant women have comparable clinical courses and outcomes with reproductive-aged non-pregnant women when infected with SARS-CoV-2. No evidence supported vertical transmission of COVID-19 in the late stage of pregnancy, including vaginal delivery.

Single-cell landscape of immunological responses in COVID-19 patients (preprint)

In COVID-19 caused by SARS-CoV-2 infection, the relationship between disease severity and the host immune response is not fully understood. Here we performed single-cell RNA sequencing in peripheral blood samples of five healthy donors and 13 COVID-19 patients including moderate, severe and convalescent cases. Through determining the transcriptional profiles of immune cells, coupled with assembled T cell receptor and B cell receptor sequences, we analyzed the functional properties of immune cells. Most cell types in COVID-19 patients showed a strong interferon-alpha response, and an overall acute inflammatory response. Moreover, intensive expansion of highly cytotoxic effector T cell subsets, such as CD4+ Effector-GNLY (Granulysin), CD8+ Effector-GNLY and NKT CD160, was associated with convalescence in moderate patients. In severe patients, the immune landscape featured a deranged interferon response, profound immune exhaustion with skewed T cell receptor repertoire and broad T cell expansion. These findings illustrate the dynamic nature of immune responses during the disease progression.

Spatial-temporal distribution of coronavirus disease 2019 in Jingzhou City

Objective • To explore the spatial distribution and spatial-temporal clustering of coronavirus disease 2019(COVID-19) in Jingzhou City. Methods • Data of COVID-19 cases in Jingzhou City from January 1 to March 12, 2020 were collected. Trend surface analysis, spatial autocorrelation and spatial-temporal scanning analysis were conducted to understand the spatial-temporal distribution of COVID-19 at town (street) level in Jingzhou City, and the spatial-temporal clustering characteristics of local cases and imported cases were compared. Results • Trend surface analysis showed that the incidence rate of COVID-19 in Jingzhou City was slightly "U" from west to east, slightly higher in the east, and inverted "U" from south to north, slightly higher in the south. Global autocorrelation showed that the incidence rate of COVID-19 in Jingzhou City was positively correlated (Moran's I=0.410, P=0.000). Local spatial autocorrelation analysis showed that the highly clustered areas and hot spot areas were mainly in Shashi District, Jingzhou District and the main urban area of Honghu City (Xindi Street) (P<0.05). Five clusters were found by spatial-temporal scanning of imported cases. The cluster time of the main cluster was from January 18 to February 3, 2020, and it was centered on Lianhe Street, covering 15 towns (streets) in Shashi District and Jingzhou District (LLR=174.944, RR=7.395, P=0.000). Five clusters were found by spatial-temporal scanning of local cases. The cluster time of the main cluster was from January 20 to February 24, 2020, which was located in Xindi Street, Honghu City (LLR=224.434, RR=16.133, P=0.000). Conclusion • Obvious spatialtemporal clustering of COVID-19 was found in Jingzhou City, and Shashi District, Jingzhou District and Honghu City were the most prevalent areas.

Protocol for a retrospective cohort study for evaluating the early antibiotics use in non-severe COVID-19 patients (preprint)

The use of antibiotics is common in the treatment of COVID-19, but adequate evaluation is lacking. We aimed to evaluate the efficacy of antibiotic use in non-severe COVID-19 patients, particularly in patients admitted with low risk of bacterial infection. This is a multi-center retrospective cohort study. Patients are screened strictly according to the inclusion/exclusion criteria and are divided into two groups based on antibiotics exposure. The exposure is defined as the treatment of antibiotics prescribed within 48 hours after admission, with a course of treatment≥3 days; and patients in this group are classified as early antibiotic use group. Otherwise, patients are classified as the non early antibiotic use group. The primary end point of the study is progressing from non-severe type COVID-19 into severe type. This is the first protocol to put a focus on the transformation of the severity of the disease, based on a multi-center retrospective cohort design.

Evaluation of early antibiotics use in non-severe COVID-19 patients admitted with low risk of bacterial infection (preprint)

The use of antibiotics is common in the treatment of COVID-19, but adequate evaluation is lacking. This study aimed to evaluate the effect of early antibiotic use in non-severe COVID-19 patients admitted with low risk of bacterial infection. The multi-center retrospective cohort study included 1613 non-severe COVID-19 inpatients admitted with low risk of bacterial infection. During the follow-up of 30 days, the proportion of patients progressed into severe type COVID-19 in the early antibiotics use group was almost 1.5 times than that of the comparision group. In the mixed-effect model, the early use of antibiotics was associated with higher probability of developing severe type, staying in the hospital for over 15 days, and secondary infection. However, it was not significant association with mortality rate. Analysis with propensity score-matched cohort displayed similar results. It is suggested that antibiotic use should be avoided unless absolutely necessary in non-severe COVID-19 patients, particularly in the early stages.

The effectiveness of antiviral treatment in severe COVID-19 patients in Wuhan: a retrospective cohort study (preprint)

Background Since the outbreak of COVID-19, the application of appropriate treatment strategy for COVID-19 patients, notably for the severe patients, was a huge challenge in case management. Therefore, we aimed to evaluate the effectiveness of antiviral treatment in severe COVID-19 patients.Methods A retrospective cohort study was conducted from January 8, 2020 to March 9, 2020 in four designated hospitals of COVID-19 in Wuhan, China. 138 severe COVID-19patients with above 18 years were included in this study. 109 patients receiving the antiviral treatment were selected in antiviral group. The remaining 29 patients were in control group. The primary outcome of the study was in-hospital death and length of hospitalization. Secondary outcomes included ICU admission, length of stays in ICU, use of mechanical ventilation, length of mechanical ventilation, and the development of complications. Univariate analysis and Kaplan-Meier curves were used to examined the association between antiviral treatment and the clinical outcomes of the COVID-19 patients.Results 48 (44.0%) and 15 (51.7%) deaths were occurred in antiviral and control groups, respectively. Antiviral treatment was not associated with the rate of fatal outcome in COVID-19 patients (P > 0.05). Among the survival patients, the median length of hospitalization was 11.0 days (IQR: 6.5–18.0) and 16.0 days (IQR: 8.5–26.0) in antiviral and control groups, respectively. No significant association was identified between the antiviral treatment and the length of hospitalization in survival patients (P > 0.05). Moreover, the antiviral treatment was not statistically associated with ICU admission, mechanical ventilation and length of mechanical ventilation (P > 0.05, respectively). However, the length of ICU stays in deaths was different both groups (P < 0.05). The median length of ICU stays in deaths was 7.0 days (IQR: 3.0-14.3) and 15.5 days (IQR: 8.3–21.8) in antiviral and control groups, respectively. The occurrence of majority of complications were similar both groups. Sepsis was the single complication in which the occurrence rates were statistical different between the antiviral group and control group (40.4% vs 13.8%, P < 0.01).Conclusion No benefit of antiviral treatment in severe COVID-19 patients was observed in our study. Clinical physicians should cautiously prescribe the antiviral drugs in severe COVID-19 patients.

Clinical features of 162 fatal cases of COVID-19: a multi-center, retrospective study (preprint)

Understanding the epidemiological and clinical characteristics of fatal cases infected with SARS-CoV-2 is import to develop appropriate preventable intervention programs in hospitals. Demographic data, clinical symptoms, clinical course, co-morbidities, laboratory findings, CT scans, treatments and complications of 162 fatal cases were retrieved from electric medical records in 5 hospitals of Wuhan, China. The median age was 69.5 years old (IQR: 63.0-77.25; range: 29-96). 112 (69.1%) cases were men. Hypertension (45.1%) was the most common co-morbidity, but 59 (36.4%) cases had no co-morbidity. At admission, 131 (81.9%) cases were assessed as severe or critical. However, 39 (18.1%) were assessed as moderate. Moderate cases had a higher prevalence of hypertension and chronic lung disease comparing with severe or critical cases (P<0.05, respectively). 126 (77.8%) and 132 (81.5%) cases received antiviral treatment and glucocorticoids, respectively. 116 (71.6%) cases were admitted to ICU and 137 (85.1%) cases received mechanical ventilation. Respiratory failure or acute respiratory distress syndrome (93.2%) was the most common complication. The young cases of COVID-19, without co-morbidity and in a moderate condition at admission could develop fatal outcome. We need to be more cautious in case management of COVID-19 for preventing the fatal outcomes.

ACE2 and TMPRSS2 expression by clinical, HLA, immune, and microbial correlates across 34 human cancers and matched normal tissues: implications for SARS-COV-2 COVID-19 (preprint)

Background: Pandemic COVID-19 by SARS-COV-2 infection is facilitated by the ACE2 receptor and protease TMPRSS2. Modestly sized case series have described clinical factors associated with COVID-19, while ACE2 and TMPRSS2 expression analyses have been described in some cell types. Cancer patients may have worse outcomes to COVID-19. Methods: We performed an integrated study of ACE2 and TMPRSS2 gene expression across and within organ systems, by normal versus tumor, across several existing databases (The Cancer Genome Atlas, Census of Immune Single Cell Expression Atlas, The Human Cell Landscape, and more). We correlated gene expression with clinical factors (including but not limited to age, gender, race, BMI and smoking history), HLA genotype, immune gene expression patterns, cell subsets, and single-cell sequencing as well as commensal microbiome. Results: Matched normal tissues generally display higher ACE2 and TMPRSS2 expression compared with cancer, with normal and tumor from digestive organs expressing the highest levels. No clinical factors were consistently identified to be significantly associated with gene expression levels though outlier organ systems were observed for some factors. Similarly, no HLA genotypes were consistently associated with gene expression levels. Strong correlations were observed between ACE2 expression levels and multiple immune gene signatures including interferon-stimulated genes and the T cell-inflamed phenotype as well as inverse associations with angiogenesis and transforming growth factor-{beta} signatures. ACE2 positively correlated with macrophage subsets across tumor types. TMPRSS2 was less associated with immune gene expression but was strongly associated with epithelial cell abundance. Single-cell sequencing analysis across nine independent studies demonstrated little to no ACE2 or TMPRSS2 expression in lymphocytes or macrophages. ACE2 and TMPRSS2 gene expression associated with commensal microbiota in matched normal tissues particularly from colorectal cancers, with distinct bacterial populations showing strong associations. Conclusions: We performed a large-scale integration of ACE2 and TMPRSS2 gene expression across clinical, genetic, and microbiome domains. We identify novel associations with the microbiota and confirm host immunity associations with gene expression. We suggest caution in interpretation regarding genetic associations with ACE2 expression suggested from smaller case series.

Epidemiological and clinical features of COVID-19 patients with and without pneumonia in Beijing, China (preprint)

Background:SARS-CoV-2-caused coronavirus disease (COVID-19) is posinga large casualty. The features of COVID-19patients withand without pneumonia,SARS-CoV-2 transmissibility in asymptomatic carriers, and factors predicting disease progression remain unknown. Methods: We collected information on clinical characteristics, exposure history, andlaboratory examinations of all laboratory-confirmed COVID-19 patients admitted to PLA General Hospital. Cox regression analysis was applied to identify prognostic factors. The last follow-up was February 18, 2020. Results:We characterized 55 consecutive COVID-19 patients. The mean incubation was 8.42(95% confidence interval [CI], 6.55-10.29) days. The mean SARS-CoV-2-positive duration from first positive test to clearance was 9.71(95%CI, 8.21-11.22) days. COVID-19 course was approximately 2 weeks. Asymptomatic carriers might transmit SARS-CoV-2. Compared with patients without pneumonia, those with pneumonia were 15 years older and had a higher rate of hypertension, higher frequencies of having a fever and cough, and higher levels of interleukin-6 (14.61 vs. 8.06pg/mL, P=0.040), B lymphocyte proportion (13.0% vs.10.0%, P=0.024), low account (<190/L) of CD8+ T cells (33.3% vs. 0, P=0.019). Multivariate Cox regression analysis indicated that circulating interleukin-6 andlactate independently predicted COVID-19 progression, with a hazard ratio (95%CI) of 1.052 (1.000-1.107) and 1.082 (1.013-1.155), respectively. During disease course,T lymphocytes were generally lower,neutrophils higher, in pneumonia patients than in pneumonia-free patients. CD8+ lymphocytes did not increase at the 20th days after illness onset. Conclusion: The epidemiological features areimportant for COVID-19 prophylaxis. Circulating interleukin-6 and lactateare independent prognostic factors. CD8+ T cell exhaustion might be critical in the development of COVID-19.