Single cell sequencing reveals cellular landscape alterations in the airway mucosa of patients with pulmonary long COVID (preprint)

To elucidate the important cellular and molecular drivers of pulmonary long COVID, we generated a single-cell transcriptomic map of the airway mucosa using bronchial brushings from patients with long COVID who reported persistent pulmonary symptoms. Adults with and without long COVID were recruited from the general community in greater Vancouver, Canada. The cohort was divided into those with pulmonary long COVID (PLC), which was defined as persons with new or worsening respiratory symptoms following at least one year from their initial acute SARS-CoV-2 infection (N=9); and control subjects defined as SARS-CoV-2 infected persons whose acute respiratory symptoms had fully resolved or individuals who had not experienced acute COVID-19 (N=9). These participants underwent bronchoscopy from which a single cell suspension was created from bronchial brush samples and then sequenced. A total of 56,906 cells were recovered for the downstream analysis, with 34,840 cells belonging to the PLC group. A dimensionality reduction plot shows a unique cluster of neutrophils in the PLC group (p<.05). Ingenuity Pathway Analysis revealed that neutrophil degranulation pathway was enriched across epithelial cells. Differential gene expression analysis between the PLC and control groups demonstrated upregulation of mucin genes in secretory cell clusters. A single-cell transcriptomic landscape of the small airways shows that the PLC airways harbors a dominant neutrophil cluster and an upregulation in the neutrophil-associated activation signature with increased expression of MUC genes in the secretory cells. Together, they suggest that pulmonary symptoms of long COVID may be driven by chronic small airway inflammation.

Challenges for COVID-19 surveillance through wastewater-based epidemiology in post-pandemic era: A retrospective study in 222 USA counties (preprint)

The post-pandemic world still faces ongoing COVID-19 infections, where wastewater-based epidemiology (WBE) is recognized as an efficient tool for the population-wide surveillance of COVID-19 infections. Utilizing weekly county-level wastewater-surveillance data during pandemic across 222 counties from 49 states in United States of America (USA) from June 2021-November 2022 and covering 104 M populations, we retrospectively evaluated the correlation between SARS-CoV-2 RNA concentrations in wastewater (CRNA) and reported cases as well as the impacts of demographics, socioeconomical, test accessibility, epidemiological, environmental factors and international air travelling on reported cases under the corresponding CRNA. The lift of travel restrictions in June 2022, a milestone for the post-pandemic era, shifted the correlation between CRNA and COVID-19 incidence in following 7-day and 14-day from 0.70 (IQR: 0.30-0.88) and 0.74 (IQR: 0.31-0.90) to 0.01 (IQR: -0.31-0.36) and -0.01 (IQR: -0.38-0.45), respectively. In post-pandemic period, under the same CRNA, the reported case numbers were impacted by international passengers, test accessibility, Omicron prevalence, ratio of population aged between 18-65, minority vulnerability, and healthcare system. These factors bring new challenges in post-pandemic era, which needs additional attention while using WBE surveillance for COVID-19 infections. This study facilitates public health authorities to dynamically adjust their WBE to the local context to achieve optimal community surveillance.

A swarm-optimizer-assisted simulation and prediction model for emerging infectious diseases based on SEIR.

Mechanism-driven models based on transmission dynamics and statistic models driven by public health data are two main methods for simulating and predicting emerging infectious diseases. In this paper, we intend to combine these two methods to develop a more comprehensive model for the simulation and prediction of emerging infectious diseases. First, we combine a standard epidemic dynamic, the susceptible-exposed-infected-recovered (SEIR) model with population migration. This model can provide a biological spread process for emerging infectious diseases. Second, to determine suitable parameters for the model, we propose a data-driven approach, in which the public health data and population migration data are assembled. Moreover, an objective function is defined to minimize the error based on these data. Third, based on the proposed model, we further develop a swarm-optimizer-assisted simulation and prediction method, which contains two modules. In the first module, we use a level-based learning swarm optimizer to optimize the parameters required in the epidemic mechanism. In the second module, the optimized parameters are used to predicate the spread of emerging infectious diseases. Finally, various experiments are conducted to validate the effectiveness of the proposed model and method.

Wastewater-based epidemiology predicts COVID-19-induced hospital and ICU admission numbers in over 100 USA counties (preprint)

With the ease of coronavirus disease (COVID-19) emergency status globally, a population-wide low-cost prediction for COVID-19-induced hospitalization and intensive care unit (ICU) admission numbers is essential for healthcare systems. For the first time, we evaluated the feasibility of using wastewater-based epidemiology (WBE) to predict COVID-19-induced hospitalization and ICU admission numbers in 102 counties across 42 states in the United States of America (USA), covering a population of nearly 60 million, through random forest models using the county-level weekly wastewater surveillance data (over 15 months). WBE-based models accurately predicted the admission numbers, allowing a preparation window of 5-28 days. In real applications, periodically updated WBE-based models showed good accuracy and transferability, with mean absolute error within 20 and 2 patients/100k population for upcoming hospitalization and ICU admission numbers in 28 days, respectively. Our study demonstrated the potential of using WBE as a cost-effective method to provide early warnings for healthcare systems.

Financial Stability and Economic Activity in China: Based on Mixed-Frequency Spillover Method

To improve financial sustainability and promote economic stability, it is important to understand the intricate relationship between finance and macroeconomy. Thus, focusing on financial stress and macroeconomic sectors, this paper investigates macro-financial spillovers in China. First, we develop a high-frequency financial stress index based on eight daily financial indicators to measure the stability of China’s financial markets. Through event identification, we find that China’s Financial Stress Index can effectively reflect the stress situation of China’s financial market. Then, given that the traditional co-frequency method fails to deal with financial stress index and macroeconomic data with different frequencies, we employ the mixed-frequency spillover method to evaluate macro-financial spillovers to examine the connectedness between China’s financial market and the real side of the economy. We find that financial stress is the leading net risk output and primarily affects the loan sector;deterioration of economic conditions can lead to more apparent fluctuations in spillover effects, with spillovers from financial stress to others being the most susceptible;within the sample, the 2015 stock crash, U.S.–China trade friction, and COVID-19 have the most impact on macro-financial spillover effects. In addition, we track the results of different risk events on spillover effects across sectors.

2D Zn‐Porphyrin‐Based Co(II)‐MOF with 2‐Methylimidazole Sitting Axially on the Paddle–Wheel Units: An Efficient Electrochemiluminescence Bioassay for SARS‐CoV‐2

High electrocatalytic activity with tunable luminescence is crucial for the development of electrochemiluminescence (ECL) luminophores. In this study, a porphyrin‐based heterobimetallic 2D metal organic framework (MOF), [(ZnTCPP)Co2(MeIm)] (1), is successfully self‐assembled from the zinc(II) tetrakis(4‐carboxyphenyl)porphine (ZnTCPP) linker and cobalt(II) ions in the presence of 2‐methylimidazole (MeIm) by a facile one‐pot reaction in methanol at room temperature. On the basis of the experimental results and the theoretical calculations, the MOF 1 contains paddle–wheel [Co2(‐CO2)4] secondary building units (SBUs) axially coordinated by a MeIm ligand, which is very beneficial to the electron transfer between the Co(II) ions and oxygen. Combining the photosensitizers ZnTCPP and the electroactive [Co2(‐CO2)4] SBUs, the 2D MOF 1 possesses an excellent ECL performance, and can be used as a novel ECL probe for rapid nonamplified detection of the RdRp gene of SARS‐CoV‐2 with an extremely low limit of detection (≈30 aM). A novel porphyrin‐based heterobimetallic 2D MOF, [(ZnTCPP)Co2(MeIm)] (1) is constructed to act as an excellent electrochemiluminescence probe for rapid nonamplified detection of SARS‐CoV‐2.

Causal influence of lung function on risk of fatality of COVID-19: a two-sample Mendelian randomization study

Objective: To investigate whether lung function was causally associated with risk of fatality of COVID-19 based on a two-sample Mendelian randomization study.

Successful Application of Wastewater-Based Epidemiology in Prediction and Monitoring of the Second Wave of COVID-19 in India with Fragmented Sewerage Systems- A Case Study of Jaipur (India) (preprint)

The present study tracked the city-wide dynamics of severe acute respiratory syndrome-corona virus 2 (SARS-CoV-2) RNA in the wastewater from nine different wastewater treatment plants (WWTPs) in Jaipur during second wave of COVID-19 out-break in India. A total of 164 samples were collected weekly between February 19th and June 8th, 2021. SARS-CoV-2 was detected in 47.2% (52/110) influent samples and 37% (20/54) effluent samples. The increasing percentage of positive influent samples correlated with the citys increasing active clinical cases during the second wave of COVID-19 in Jaipur. Furthermore, WBE based evidence clearly showed early detection of about 20 days (9/9 samples reported positive on April 20th, 2021) prior to the maximum cases & maximum deaths reported in the city on May 8th, 2021. The present study further observed the presence of SARS-CoV-2 RNA in treated effluents at the time window of maximum active cases in the city even after tertiary disinfection treatments of UV & Chlorine. The average genome concentration in the effluents and removal efficacy of six commonly used treatments; Activated Sludge Treatment + Chlorine disinfection (ASP + Cl2), Moving Bed Biofilm Reactor (MBBR) with Ultraviolet radiations disinfection (MBBR + UV), MBBR + Chlorine (Cl2), Sequencing Batch Reactor (SBR) and SBR + Cl2 were compared with removal efficacy of SBR + Cl2 (81.2%)> MBBR + UV (68.8%) > SBR (57.1%) > ASP (50%) > MBBR + Cl2(36.4%). The study observed the trends & prevalence of four genes (E, RdRp, N, and ORF1ab gene) based on two different kits and found that prevalence of N> ORF1ab >RdRp> E gene, suggested that the effective genome concentration should be calculated based on the presence/absence of multiple genes. Hence, it is imperative to say that using a combination of different detection genes (E, N, RdRp & ORF1ab genes) reduce false positives in WBE. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=131 SRC="FIGDIR/small/21263417v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@156126corg.highwire.dtl.DTLVardef@1d39404org.highwire.dtl.DTLVardef@19a9dcdorg.highwire.dtl.DTLVardef@1ee3a0c_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LISuccessful application of WBE with prediction of 14-20 days for COVID-19 in Jaipur C_LIO_LIA comparison of SARS-CoV-2 RNA removal efficacy of 9 WWTPs was investigated C_LIO_LISBR showed better performance than MBBR with SARS-CoV-2 RNA removal from wastewater C_LIO_LIPresence of SARS-CoV-2 in effluents even after UV and Chlorine disinfection C_LIO_LIUsing a combination of different detection genes reduce false positives in WBE C_LI

Multi-omics highlights ABO plasma protein as a causal risk factor for COVID-19 (preprint)

SARS-CoV-2 is responsible for the coronavirus disease 2019 (COVID-19) and the current health crisis. Despite intensive research efforts, the genes and pathways that contribute to COVID-19 remain poorly understood. We therefore used an integrative genomics (IG) approach to identify candidate genes responsible for COVID-19 and its severity. We used Bayesian colocalization (COLOC) and summary-based Mendelian randomization to combine gene expression quantitative trait loci (eQTLs) from the Lung eQTL (n=1,038) and eQTLGen (n=31,784) studies with published COVID-19 genome-wide association study (GWAS) data from the COVID-19 Host Genetics Initiative. Additionally, we used COLOC to integrate plasma protein quantitative trait loci (pQTL) from the INTERVAL study (n=3,301) with COVID-19-associated loci. Finally, we determined any causal associations between plasma proteins and COVID-19 using multi-variable two-sample Mendelian randomization (MR). We found that the expression of 20 genes in lung and 31 genes in blood was associated with COVID-19. Of these genes, only three (LZTFL1, SLC6A20 and ABO) had been previously linked with COVID-19 in GWAS. The novel loci included genes involved in interferon pathways (IL10RB, IFNAR2 and OAS1). Plasma ABO protein, which is associated with blood type in humans, demonstrated a significant causal relationship with COVID-19 in MR analysis; increased plasma levels were associated with an increased risk of having COVID-19 and risk of severe COVID-19. In summary, our study identified genes associated with COVID-19 that may be prioritized for future investigation. Importantly, this is the first study to demonstrate a causal association between plasma ABO protein and COVID-19.

The Impact of COVID-19 on Gastric Cancer Surgery: A Single-Center Retrospective Study (preprint)

Background: The coronavirus disease 2019 (COVID-19) has been declared a global pandemic by the World Health Organization. Patients with cancer are more likely to incur poor clinical outcomes. Due to the prevailing pandemic, we propose some surgical strategies for gastric cancer patients. Methods: : The ‘COVID-19’ period was defined as occurring between 2020-01-20 and 2020-03-20. The enrolled patients were divided into two groups, pre-COVID-19 group (PCG) and COVID-19 group (CG). A total of 109 patients with gastric cancer were enrolled in this study. Results: : The waiting time before admission increased by 4 days in the CG (PCG: 4.5 [IQR: 2, 7.8] vs. CG: 8.0 [IQR: 2,20]; p=0.006). More patients had performed chest CT scans besides abdominal CT before admission during the COVID-19 period (PCG: 22 [32%] vs. CG: 30 [73%], p=0.001). After admission during the COVID period, the waiting time before surgery was longer (PCG: 3[IQR: 2,5] vs. CG: 7[IQR: 5,9]; p<0.001), more laparoscopic surgeries were performed (PCG: 51[75%] vs. CG: 38[92%], p=0.021), and hospital stay period after surgery was longer (7[IQR: 6,8] vs.9[IQR:7,11]; p<0.001). In addition, the total cost of hospitalization increased during this period, (PCG: 9.22[IQR:7.82,10.97] vs. CG: 10.42[IQR:8.99,12.57]; p=0.006). Conclusion: This study provides an opportunity for our surgical colleagues to reflect on their own services and any contingency plans they may have to tackle the COVID-19 crisis.

How Do Investors React to Investment-Opportunity Shock? Evidence from the COVID-19 Pandemic and Taiwan Bio-Tech Firms (preprint)

While the stock market crashed in the first quarter after the outbreak of COVID-19, this paper finds that bio-tech firms and their investors could take advantage of the COVID-19 investment opportunity and earn positive abnormal returns. Bio-tech firms earn abnormal returns of 1.63% per day—which can be translated into average capital gains of about 86.7 million NT dollars per day— around the event day on which the WHO declared COVID-19 a global emergency. Positive returns continue after the event day. Moreover, small firms and firms that enjoy greater patent originality and receiving government R&D subsidies earn higher abnormal returns.

Inhaled corticosteroids downregulate SARS-CoV-2-related gene expression in COPD: results from a RCT (preprint)

RationaleChronic obstructive pulmonary disease (COPD) is a risk factor for severe COVID-19. Inhaled corticosteroids (ICS) are commonly prescribed for the prevention of acute exacerbations in people with COPD, but their use is associated with increased risk of respiratory infections. The effects of ICS on SARS-CoV-2 susceptibility or COVID-19 severity are currently unknown. ObjectivesTo determine the effects of ICS treatment on the bronchial epithelial cell expression of key SARS-CoV-2-related genes in volunteers with COPD. MethodsWe performed a randomized, open-label, parallel treatment trial of 12 weeks treatment with ICS in combination with long-acting beta-agonist (formoterol/budesonide 12/400 {micro}g twice daily or salmeterol/fluticasone propionate 25/250 {micro}g twice daily), or treatment with LABA only (formoterol 12 {micro}g twice daily), in volunteers with mild to very severe COPD. We obtained bronchial epithelial cell samples via bronchoscopy before and after treatment, and determined transcriptome-wide gene expression by RNA sequencing. Main Results63 volunteers were randomized to receive treatment. Compared to formoterol alone, formoterol/budesonide treatment decreased the expression of the SARS-CoV-2 receptor gene ACE2 and the host cell protease gene ADAM17. These genes were highly co-expressed with innate immune response genes, particularly those of the type I interferon and anti-viral response pathways, which also tended to decrease following ICS treatment. ConclusionsThis is the first randomized controlled trial to show that ICS affect the expression of key SARS-CoV-2-related genes in COPD. Their relation to important anti-viral response genes may have critical implications for SARS-CoV-2 susceptibility or COVID-19 severity in this vulnerable population.

Gene Expression Network Analysis Provides Potential Targets Against SARS-CoV-2 (preprint)

ABSTRACTBACKGROUND Cell entry of SARS-CoV-2, the novel coronavirus causing COVID-19, is facilitated by host cell angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2). We aimed to identify and characterize genes that are co-expressed with ACE2 and TMPRSS2, and to further explore their biological functions and potential as druggable targets.METHODS Using the gene expression profiles of 1,038 lung tissue samples, we performed a weighted gene correlation network analysis (WGCNA) to identify modules of co-expressed genes. We explored the biology of co-expressed genes using bioinformatics databases, and identified known drug-gene interactions.RESULTS ACE2 was in a module of 681 co-expressed genes; 12 genes with moderate-high correlation with ACE2 (r>0.3, FDR<0.05) had known interactions with existing drug compounds. TMPRSS2 was in a module of 1,086 co-expressed genes; 15 of these genes were enriched in the gene ontology biologic process ‘Entry into host cell’, and 53 TMPRSS2-correlated genes had known interactions with drug compounds.CONCLUSION Dozens of genes are co-expressed with ACE2 and TMPRSS2, many of which have plausible links to COVID-19 pathophysiology. Many of the co-expressed genes are potentially targetable with existing drugs, which may help to fast-track the development of COVID-19 therapeutics.Competing Interest StatementS.M. reports personal fees from Novartis and Boehringer-Ingelheim, outside the submitted work. W.T. reports fees to Institution from Roche-Ventana, AbbVie, Merck-Sharp-Dohme and Bristol-Myers-Squibb, outside the submitted work. M.B. reports research grants paid to University from Astra Zeneca, Novartis, outside the submitted work. D.D.S. reports research funding from AstraZeneca and received honoraria for speaking engagements from Boehringer Ingelheim and AstraZeneca over the past 36 months, outside of the submitted work.View Full Text

Initial Study of Human Genetic Contribution to COVID-19 Severity and Susceptibility (preprint)

The COVID-19 pandemic has accounted for more than five million infections and hundreds of thousand deaths worldwide in the past six months. The patients demonstrate a great diversity in clinical and laboratory manifestations and disease severity. Nonetheless, little is known about the host genetic contribution to the observed inter-individual phenotypic variability. Here, we report the first host genetic study in China by deeply sequencing and analyzing 332 COVID-19 patients categorized by varying levels of severity from the Shenzhen Third Peoples Hospital. Upon a total of 22.2 million genetic variants, we conducted both single-variant and gene-based association tests among five severity groups including asymptomatic, mild, moderate, severe and critical ill patients after the correction of potential confounding factors. The most significant gene locus associated with severity is located in TMEM189-UBE2V1 involved in the IL-1 signaling pathway. The p.Val197Met missense variant that affects the stability of the TMPRSS2 protein displays a decreasing allele frequency among the severe patients compared to the mild and the general population. We also identified that the HLA-A*11:01, B*51:01 and C*14:02 alleles significantly predispose the worst outcome of the patients. This initial study of Chinese patients provides a comprehensive view of the genetic difference among the COVID-19 patient groups and highlighted genes and variants that may help guide targeted efforts in containing the outbreak. Limitations and advantages of the study were also reviewed to guide future international efforts on elucidating the genetic architecture of host-pathogen interaction for COVID-19 and other infectious and complex diseases.

Influencing factors of virus duration and virus clearance in COVID-19 patients in Shenzhen: A retrospective study. (preprint)

Abstract Background. We aimed to analyze the influencing factors of virus duration and virus clearance in coronavirus disease 2019 (COVID-19) in Shenzhen, China, and to provide our experience in the treatment and management of COVID-19. Methods. The clinical data and laboratory test results of COVID-19 inpatients admitted to the Third People's Hospital of Shenzhen, Guangdong Province from January 2020 to March 2020 were retrospectively collected. In COVID-19 rehabilitation patients, two consecutive negative RT-PCR results on nasopharyngeal swabs were defined as virus clearance. The time from onset of the disease to virus clearance was defined as the virus duration. We analyzed the virus clearance rate at different time points and the impact of clinical features and treatments on virus clearance. Results. A total of 201 patients with COVID-19, including 89 women (44.3%) and 112 men (55.7%), were included in our study. According to the severity of the disease, the patients were divided into no severe patients and severe patients. The overall median virus duration for all patients was 17 days. The overall virus clearance rates within 1, 2, 3, 4, 5, and 6 weeks after onset were 1.5%, 36.6%, 73.4%, 90.2%, 97.3%, and 100%, respectively. A multiple linear regression model was performed to analyze the factors influencing virus clearanc.The factors influencing virus clearance within 2 weeks were treatment timing and glucocorticoid usage. The influencing factors for virus clearance within 4 weeks were treatment timing, glucocorticoid usage and age. Conclusion. Treatment timing was related to virus clearance. The earlier the treatment was initiated, the faster the virus clearance. For COVID-19 patients, early detection and early treatment strategies should be adopted. Glucocorticoid usage may be detrimental to virus clearance and should be more restricted. Age > 60 years may also be a detrimental factor for virus clearance.

The timeline and risk factors of clinical progression of COVID-19 in Shenzhen, China (preprint)

Background: The novel coronavirus disease 2019(COVID-19) broke out globally. Early prediction of the clinical progression was essential but still unclear. We aimed to evaluate the timeline of COVID-19 development and analyze risk factors of disease progression.Methods In this retrospective study, we included 333 patients with laboratory-confirmed COVID-19 infection hospitalized in the Third People's Hospital of Shenzhen from 10 January to 10 February 2020. Epidemiological feature, clinical records, laboratory and radiology manifestations were collected and analyzed. 323 patients with mild-moderate symptoms on admission were observed to determine whether they exacerbated to severe-critically ill conditions (progressive group) or not (stable group). We used logistic regression to identify the risk factors associated with clinical progression.Results Of all the 333 patients, 70(21.0%) patients progressed into severe-critically ill conditions during hospitalization and assigned to the progressive group, 253(76.0%) patients belonged to the stable group, another 10 patients were severe before admission. we found that the clinical features of aged over 40 (3.80[1.72, 8.52]), males (2.21[1.20, 4.07]), with comorbidities (1.78[1.13, 2.81]) certain exposure history (0.38[0.20, 0.71]), abnormal radiology manifestations (3.56[1.13, 11.40]), low level of T lymphocytes (0.99[0.997, 0.999]), high level of NLR (0.99[0.97, 1.01]), IL-6 (1.05[1.03, 1.07]) and CRP (1.67[1.12, 2.47]) were the risk factors of disease progression by logistic regression.Conclusions the potential risk factors of males, older age, with comorbidities, low T lymphocyte level and high level of NLR, CRP, IL-6 can help to predict clinical progression of COVID-19 at an early stage.

ACE inhibition and cardiometabolic risk factors, lung ACE2 and TMPRSS2 gene expression, and plasma ACE2 levels: a Mendelian randomization study (preprint)

ObjectivesTo use human genetic variants that proxy angiotensin-converting enzyme (ACE) inhibitor drug effects and cardiovascular risk factors to provide insight into how these exposures affect lung ACE2 and TMPRSS2 gene expression and circulating ACE2 levels. DesignTwo-sample Mendelian randomization (MR) analysis. SettingSummary-level genetic association data. ParticipantsParticipants were predominantly of European ancestry. Variants that proxy ACE inhibitor drug effects and cardiometabolic risk factors (body mass index, chronic obstructive pulmonary disease, lifetime smoking index, low-density lipoprotein cholesterol, systolic blood pressure and type 2 diabetes mellitus) were selected from publicly available genome-wide association study data (sample sizes ranging from 188,577 to 898,130 participants). Genetic association estimates for lung expression of ACE2 and TMPRSS2 were obtained from the Gene-Tissue Expression (GTEx) project (515 participants) and the Lung eQTL Consortium (1,038 participants). Genetic association estimates for circulating plasma ACE2 levels were obtained from the INTERVAL study (4,947 participants). Main outcomes and measuresLung ACE2 and TMPRSS2 expression and plasma ACE2 levels. ResultsThere were no association of genetically proxied ACE inhibition with any of the outcomes considered here. There was evidence of a positive association of genetic liability to type 2 diabetes mellitus with lung ACE2 gene expression in GTEx (p = 4x10-4) and with circulating plasma ACE2 levels in INTERVAL (p = 0.03), but not with lung ACE2 expression in the Lung eQTL Consortium study (p = 0.68). There were no associations between genetically predicted levels of the other cardiometabolic traits with the outcomes. ConclusionsThis study does not provide evidence to support that ACE inhibitor antihypertensive drugs affect lung ACE2 and TMPRSS2 expression or plasma ACE2 levels. In the current COVID-19 pandemic, our findings do not support a change in ACE inhibitor medication use without clinical justification. Summary boxesO_ST_ABSWhat is already known on this topicC_ST_ABSO_LISevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the current coronavirus disease 2019 (COVID-19) pandemic. C_LIO_LISerine protease TMPRSS2 is involved in priming the SARS-CoV-2 spike protein for cellular entry through the angiotensin-converting enzyme 2 (ACE2) receptor. C_LIO_LIExpression of ACE2 and TMPRSS2 in the lung epithelium might have implications for risk of SARS-CoV-2 infection and severity of COVID-19. C_LI What this study addsO_LIWe used human genetic variants that proxy ACE inhibitor drug effects and cardiometabolic risk factors to provide insight into how these exposures affect lung ACE2 and TMPRSS2 expression and circulating ACE2 levels. C_LIO_LIOur findings do not support the hypothesis that ACE inhibitors have effects on ACE2 expression. C_LIO_LIWe found some support for an association of genetic liability to type 2 diabetes mellitus with higher lung ACE2 expression and plasma ACE2 levels, but evidence was inconsistent across studies. C_LI

The Impact of COVID-19 on Gastric Cancer Surgery: A Single-center Retrospective Study Based on Real-world Data (preprint)

Background ： A respiratory epidemic defined as coronavirus disease 2019 ( COVID-19 ) is becoming unstoppable and has been declared a pandemic. Patients with cancer are more likely to develop COVID-19. Based on our experience during the pandemic period, we propose some surgery strategies for gastric cancer patients under the COVID-19 situation. Methods ： We defined the ‘COVID-19’ period as occurring between 2020-01-20 and 2020-03-20. All the enrolled patients were divided into two groups, pre-COVID-19 group (PCG) and COVID-19 group (CG). A total of 109 patients with gastric cancer were enrolled in this study. Results ： The waiting times before admission increased by 4 days in CG(PCG:4.5 [IQR: 2, 7.8] vs. CG:8.0 [IQR: 2,20]; P = 0.006). More patients had performed chest CT scan besides abdominal CT before admission during COVID-19 period(PCG:22[32%]vs. CG:30[73%], p=0.001). After admission, during COVID period, the waiting time before surgery was longer(3[IQR: 2,5] vs. 7[IQR: 5,9]; P < 0.001),more laparoscopic surgery were performed(PCG: 51[75%] vs. CG: 38[92%],p=0.021), and hospital stay after surgery was longer (7[IQR: 6,8] vs.9[IQR:7,11] ; P < 0.001). The total cost of hospitalization increased during COVID period, (9.22[IQR:7.82,10.97] vs. 10.42[IQR:8.99,12.57]; p=0.006). Conclusion ： Since no data is available yet on the impact of COVID-19 on gastric cancer patients,our own experience with COVID-19 in gastric cancer surgery has hopefully provided an opportunity for colleagues to reflect on their own service and any contingency plans they have to tackle the crisis.  Keywords:  gastric cancer; coronavirus disease 2019; COVID-19; retrospective analysis; real-world data.