Integration of human organoids single-cell transcriptomic profiles and human genetics repurposes critical cell type-specific drug targets for severe COVID-19 (preprint)

Human organoids recapitulate the cell type diversity and function of their primary organs holding tremendous potentials for basic and translational research. Advances in single-cell RNA sequencing (scRNA-seq) technology and genome-wide association study (GWAS) have accelerated the biological and therapeutic interpretation of trait-relevant cell types or states. Here, we constructed a computational framework to integrate atlas-level organoid scRNA-seq data, GWAS summary statistics, expression quantitative trait loci, and gene-drug interaction data for distinguishing critical cell populations and drug targets relevant to COVID-19 severity. We found that 39 cell types across eight kinds of organoids were significantly associated with COVID-19 outcomes. Notably, subset of lung mesenchymal stem cells (MSCs) increased proximity with fibroblasts predisposed to repair COVID-19-damaged lung tissue. Brain endothelial cell subset exhibited significant associations with severe COVID-19, and this cell subset showed a notable increase in cell-to-cell interactions with other brain cell types, including microglia. We repurposed 33 druggable genes, including IFNAR2, TYK2, and VIPR2, and their interacting drugs for COVID-19 in a cell-type-specific manner. Overall, our results showcase that host genetic determinants have cellular specific contribution to COVID-19 severity, and identification of cell type-specific drug targets may facilitate to develop effective therapeutics for treating severe COVID-19 and its complications.

Disaster Preparedness Among Nurses in China: A Cross-Sectional Study.

BACKGROUND: Increasingly frequent global disasters such as coronavirus disease 2019 pose a threat to human health and life. The World Health Organization has called on countries to formulate detailed plans to prepare for disasters. It is critical to investigate and evaluate the disaster preparedness of nurses. PURPOSE: This study was designed to investigate the disaster preparedness and psychological condition of nurses in China and analyze the significant factors influencing their disaster preparedness. METHODS: A cross-sectional survey was conducted in 2020, and 1,313 nurses were enrolled using convenience sampling. The study questionnaires were distributed and collected via a networking platform equivalent to Amazon Mechanical Turk. The disaster preparedness of the respondents was measured using the Disaster Preparedness Evaluation Tool, the Hospital Anxiety and Depression Scale was used to evaluate anxiety and depression status, and a self-designed questionnaire developed based on a review of the literature was used to explore the potential factors of influence on disaster preparedness. RESULTS: The average score for disaster preparedness among the participants was 186.34 (SD = 40.80), which corresponded with a moderate level, especially in skill (mean score = 42.01, SD = 12.39). Items with higher scores included support for the government, personal protection, and health education, whereas items with lower scores included nursing leadership in the community, capacity to cope with chemical or biological attacks, and assessment of posttraumatic stress disorder. Disaster preparedness was negatively related with mental health, including depression and anxiety. The main factors affecting disaster preparedness included educational background, nursing specialty, prior disaster training, prior disaster rescue experience, and depression level. CONCLUSIONS/IMPLICATIONS FOR PRACTICE: The disaster preparedness of Chinese nurses must be improved. More attention should be paid to disaster preparedness in nurses, and future tailored interventions are urgently needed to promote nursing leadership in the community, the ability to cope with chemical or biological attacks, and posttraumatic stress disorder assessments. Moreover, relieving negative emotions to promote the mental health of nurses should receive greater attention.

Secondary PM2.5 decreases significantly less than NO2 emission reductions during COVID lockdown in Germany

This study estimates the influence of anthropogenic emission reductions on the concentration of particulate matter with a diameter smaller than 2.5 µm (PM2.5) during the 2020 lockdown period in German metropolitan areas. After accounting for meteorological effects, PM2.5 concentrations during the spring 2020 lockdown period were 5 % lower compared to the same time period in 2019. However, during the 2020 pre-lockdown period (winter), PM2.5 concentrations with meteorology accounted for were 19 % lower than in 2019. Meanwhile, NO2 concentrations with meteorology accounted for dropped by 23 % during the 2020 lockdown period compared to an only 9 % drop for the 2020 pre-lockdown period, both compared to 2019. SO2 and CO concentrations with meteorology accounted for show no significant changes during the 2020 lockdown period compared to 2019. GEOS-Chem (GC) simulations with a COVID-19 emission reduction scenario based on the observations (23 % reduction in anthropogenic NOx emission with unchanged anthropogenic volatile organic compounds (VOCs) and SO2) are consistent with the small reductions of PM2.5 during the lockdown and are used to identify the underlying drivers for this. Due to being in a NOx-saturated ozone production regime, GC OH radical and O3 concentrations increased (15 % and 9 %, respectively) during the lockdown compared to a business-as-usual (BAU, no lockdown) scenario. Ox (equal to NO2+O3) analysis implies that the increase in ozone at nighttime is solely due to reduced NO titration. The increased O3 results in increased NO3 radical concentrations, primarily during the night, despite the large reductions in NO2. Thus, the oxidative capacity of the atmosphere is increased in all three important oxidants, OH, O3, and NO3. PM nitrate formation from gas-phase nitric acid (HNO3) is decreased during the lockdown as the increased OH concentration cannot compensate for the strong reductions in NO2, resulting in decreased daytime HNO3 formation from the OH + NO2 reaction. However, nighttime formation of PM nitrate from N2O5 hydrolysis is relatively unchanged. This results from the fact that increased nighttime O3 results in significantly increased NO3, which roughly balances the effect of the strong NO2 reductions on N2O5 formation. Ultimately, the only small observed decrease in lockdown PM2.5 concentrations can be explained by the large contribution of nighttime PM nitrate formation, generally enhanced sulfate formation, and slightly decreased ammonium. This study also suggests that high PM2.5 episodes in early spring are linked to high atmospheric ammonia concentrations combined with favorable meteorological conditions of low temperature and low boundary layer height. Northwest Germany is a hot-spot of NH3 emissions, primarily emitted from livestock farming and intensive agricultural activities (fertilizer application), with high NH3 concentrations in the early spring and summer months. Based on our findings, we suggest that appropriate NOx and VOC emission controls are required to limit ozone, and that should also help reduce PM2.5. Regulation of NH3 emissions, primarily from agricultural sectors, could result in significant reductions in PM2.5 pollution.

Neighborhood-based Inference and Restricted Boltzmann Machine for microbe and drug associations prediction (preprint)

Efficient identification of microbe-drug associations is critical for drug development and solving problem of antimicrobial resistance. Traditional wet-lab method requires a lot of money and labor in identifying potential microbe-drug associations. With development of machine learning and large amounts of biological data, computational methods become feasible. In this paper, we proposed a computational model of Neighborhood-based Inference (NI) and Restricted Boltzmann Machine (RBM) to predict potential Microbe-Drug Association (NIRBMMDA) by using multisource data. First, NI was used to predict potential microbe-drug associations by using different thresholds to find similar neighbors for drug or microbe. Then, RBM was also employed to predict potential microbe-drug associations based on contrastive divergence algorithm and sigmoid function. Because generalization ability of individual method is poor, we used an ensemble learning to integrate the two predicted microbe-drug associations. Especially, NI can fully utilize similar (neighbor) information of drug or microbe and RBM can learn potential probability distribution hid in known microbe-drug associations. Finally, ensemble learning was used to integrate individual predictor for obtaining a stronger predictor. To evaluate the performance of NIRBMMDA, global leave-one-out cross validation (LOOCV), local LOOCV and five-fold cross validations were implemented to evaluate the performance of NIRBMMDA based on three datasets of DrugVirus, MDAD and aBiofilm. In global LOOCV, NIRBMMDA gained the area under the receiver operating characteristics curve (AUC) of 0.8666, 0.9413 and 0.9557 for datasets of DrugVirus, MDAD and aBiofilm, respectively. In local LOOCV, AUCs of 0.8512, 0.9204 and 0.9414 were obtained for NIRBMMDA based on datasets of DrugVirus, MDAD and aBiofilm, respectively. For five-fold cross validation, NIRBMMDA acquired AUC and standard deviation of 0.8569 0.0027, 0.9248 0.0014 and 0.9369 0.0020 on the basis of datasets of DrugVirus, MDAD and aBiofilm, respectively. Moreover, case study for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) showed that 13 out of the top 20 predicted drugs were verified by searching literature. The other two case studies indicated that 17 and 15 out of the top 20 predicted microbes for the drug of ciprofloxacin and minocycline were confirmed by published literature, respectively. The results demonstrated NIRBMMDA is an effective model in predicting microbe-drug associations.

Single cell sequencing analysis uncovers genetics-influenced CD16+monocytes and memory CD8+T cells involved in severe COVID-19 (preprint)

Background: Understanding the host genetic architecture and viral immunity contributes to the development of effective vaccines and therapeutics for controlling the COVID-19 pandemic. Alterations of immune responses in peripheral blood mononuclear cells play a crucial role in the detrimental progression of COVID-19. However, the effects of host genetic factors on immune responses for severe COVID-19 remain largely unknown. Methods: We constructed a powerful computational framework to characterize the host genetics-influenced immune cell subpopulations for severe COVID-19 by integrating GWAS summary statistics (N = 969,689 samples) with four independent scRNA-seq datasets (N = 606,534 cells). Results: We found that 34 risk genes were significantly associated with severe COVID-19, and the number of highly-expressed genetics-risk genes increased with the severity of COVID-19. Three cell-subtypes that are CD16+monocytes, megakaryocytes, and memory CD8+T cells were significantly enriched by COVID-19-related genetic association signals. Notably, three causal risk genes of CCR1, CXCR6, and ABO were specifically expressed in these three cell types, respectively. CCR1+CD16+monocytes and ABO+ megakaryocytes with significant up-regulated genes including S100A12, S100A8, S100A9, and IFITM1 confer higher risk to the cytokine storms among severe patients. CXCR6+ memory CD8+ T cells exhibit a notable polyfunctionality of multiple immunologic features, including elevation of proliferation, migration, and chemotaxis. Moreover, we observed a prominent increase in cell-cell interactions of both CCR1+ CD16+monocytes and CXCR6+ memory CD8+T cells in severe patients compared to normal controls among both PBMCs and lung tissues, and elevated interactions with epithelial cells could contribute to enhance the resident to lung airway for against COVID-19 infection. Conclusions: We uncover a major genetics-modulated immunological shift between mild and severe infection, including an increase in up-regulated genetic-risk genes, excessive secreted inflammatory cytokines, and functional immune cell subsets contributing high risk to severity, which provides novel insights in parsing the host genetics-influenced immune cells for severe COVID-19.

Viral Drug prediction with Matrix Decomposition and Two-layer Heterogeneous Graph Inference (preprint)

Recently, the association prediction between viruses and drugs has drawn more and more attention. A growing number of studies have shown that the problem of antiviral drug resistance is increasing and has become a major problem plaguing the medical community. Moreover, the development cycle of new drugs is long and requires a lot of funds. If new viruses emerge, effective antiviral drugs are urgently needed. Therefore, effective calculation methods are required to predict potential antiviral drugs. In this paper, we developed a computational model of Matrix Decomposition and Heterogeneous Graph based Inference for Drug-Virus Association (MDHGIVDA) to predict potential drug-virus associations. MDHGIVDA integrated virus sequence similarity, drug chemical structure similarity, drug side effect similarity, Gaussian interaction profile kernel similarity for drugs and viruses, new drug-virus associations matrix obtained by matrix decomposition to discover new drug-virus associations. Due to the use of matrix factorization and heterogeneous graphs, our model has a high prediction accuracy compared with the previous four models. In the global and local leave-one-out cross validation (LOOCV), MDHGIVDA obtained area under the receiver operating characteristics curve (AUC) of 0.8528 and AUC of 0.8532, respectively. In addition, in the five-fold cross validation, the AUC and the standard deviation is 0.8299 0.0037, which shows that MDHGIVDA has stability and high prediction accuracy. In the case studies of three important viruses, 18, 14, and 16 out of the top 20 predicted drugs for Zika virus (ZIKV), Severe Acute Respiratory Syndrome Coronavirus 2 ( SARS-COV-2 ), Human Immunodeficiency Virus-1 (HIV-1) were verified respectively by searching the literature on PubMed. These results showed that MDHGIVDA is effective in predicting potential drug-virus associations.

Tropospheric and response to COVID-19 lockdown restrictions at the national and urban scales in Germany

Abstract This study estimates the influence of anthropogenic emission reductions on nitrogen dioxide () and ozone () concentration changes in Germany during the COVID-19 pandemic period using in-situ surface and Sentinel-5p (TROPOMI) satellite column measurements and GEOS-Chem model simulations. We show that reductions in anthropogenic emissions in eight German metropolitan areas reduced mean in-situ (& column) concentrations by 23 (& 16 ) between March 21 and June 30, 2020 after accounting for meteorology, whereas the corresponding mean in-situ concentration increased by 4 between March 21 and May 31, 2020, and decreased by 3 in June 2020, compared to 2019. In the winter and spring, the degree of saturation of ozone production is stronger than in the summer. This implies that future reductions in emissions in these metropolitan areas are likely to increase ozone pollution during winter and spring if appropriate mitigation measures are not implemented. TROPOMI concentrations decreased nationwide during the stricter lockdown period after accounting for meteorology with the exception of North-West Germany which can be attributed to enhanced emissions from agricultural soils.

COVID-19 Quarantine Reveals Grade-specific Behavioral Modification of Myopia: One-Million Chinese Schoolchildren Study (preprint)

BackgroundHigh prevalence of myopia of adolescent has been a global public health concern. Their risk factors and effective prevention methods for myopia across schoolchildren developmental stages are critically needed but remain uncertain due to the difficulty in implementing intervention measurements under normal life situation. We aimed to study the impact of the COVID-19 quarantine on myopia development among over one-million schoolchildren. MethodsWe designed the ongoing longitudinal project of Myopic Epidemiology and Intervention Study (MEIS) to biannually examine myopia among millions of schoolchildren for ten years in Wenzhou City, Zhejiang Province, China. In the present study, we performed three examinations of myopia in 1,305 elementary and high schools for schoolchildren in June 2019, December 2019 and June 2020. We used the normal period (June-December 2019) and COVID-19 quarantine period (January-June 2020) for comparisons. Myopia was defined as an uncorrected visual acuity of 20/25 or less and a spherical equivalent refraction (SER) of -0.5 diopters (D) or less. High myopia was defined as an SER of -6.0 D or less. FindingsIn June 2019, 1,001,749 students aged 7-18 were eligible for examinations. In the 6-month and 12-month follow-up studies, there were 813,755 eligible students (81.2%) and 768,492 eligible students (76.7%), respectively. Among all students, we found that half-year myopia progression increased approximate 1.5 times from -0.263 D (95% CI, -0.262 to -0.264) during normal period to -0.39 D (95% CI, -0.389 to -0.391) during COVID-19 quarantine (P < 0.001). Multivariate Cox regression analysis identified grade rather than age was significantly associated with myopia (Hazard ratio [HR]: 1.10, 95% CI, 1.08 to 1.13; P < 0.001) and high myopia (HR: 1.40, 95% CI, 1.35 to 1.46; P < 0.001) after adjustment for other factors. The prevalence, progression, and incidence of myopia and high myopia could be categorized into two grade groups: I (grades 1-6) and II (grades 7-12). Specifically, COVID-19 quarantine for 6 months sufficiently increased risk of developing myopia (OR: 1.36, 95% CI, 1.33 to 1.40) or high myopia (OR: 1.30, 95% CI, 1.22 to 1.39) in Grade Group I, but decreased risk of developing myopia (OR: 0.45, 95% CI, 0.43 to 0.48) or high myopia (OR: 0.57, 95% CI, 0.54 to 0.59) in Grade Group II. InterpretationThe finding that behavioral modifications for six months during COVID-19 quarantine sufficiently and grade-specifically modify myopia development offers the largest human behavioral intervention data at the one million scale to identify the grade-specific causal factors and effective prevention methods for guiding the formulation of myopia prevention and control policies. FundingKey Program of National Natural Science Foundation of China; the National Natural Science Foundation of China; Scientific Research Foundation for Talents of Wenzhou Medical University; Key Research and Development Program of Zhejiang Province. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSMyopia is the most-common refractive error worldwide. Myopia with younger onset may result in developing high myopia, which is associated with sight-threatening ocular diseases such as maculopathy, retinal detachment, opticneuropathy, glaucoma, retinal atrophy, choroidal neovascularization. In light of the increasing prevalence of myopia and high myopia has been a global public health concern, the impact of COVID-19 lockdown on myopia development has gained substantial attention. We searched PubMed, Google Scholar, and MEDLINE databases for original articles reported between database inception and November 10, 2020, using the following search terms: (coronavirus OR COVID* OR SARS-COV-2 OR lockdown OR quarantine) AND (myopia OR short-sightedness OR refractive error). To date, there was no original study reported to uncover the influence of COVID-19 quarantine on myopia progression. Added value of this studyThis study provides the largest longitudinal intervention data on myopia progression in Chinese schoolchildren covering all grades of schoolchildren at one-million scale. COVID-19 quarantine model uncovers that behavioral modifications for six months may lead to significant increase of overall prevalence of myopia associated with their increased screen times and decreased outdoor activity times. Importantly, their effects on developing myopia or high myopia of students are grade-dependent, which were risk factors for elementary schools period but protective factors for high schools period partly due to reduced school education burden. Implications of all the available evidenceThis one-million schoolchildren myopia survey offers evidence that six months behavioral modifications sufficiently and grade-specifically change the progression of myopia and high myopia. In view of the increased use of electronic devices is an unavoidable trend, effective myopia prevention strategy according to grade among students is urgently needed. Since COVID-19 outbreak is still ongoing and spreading, international collaborate efforts are warranted to uncover the influence of COVID-19 on myopia progression to further substantiate these findings.

Integrative Genomics Analysis Reveals a Novel 21q22.11 Locus Contributing to Susceptibility of COVID-19 (preprint)

The systematic identification of host genetic risk factors is essential for the understanding and treatment of COVID-19. By performing a meta-analysis of two independent genome-wide association (GWAS) summary datasets (N = 680,128), a novel locus at 21q22.11 was identified to be associated with COVID-19 infection (rs9976829 in IFNAR2 and upstream of IL10RB, OR = 1.16, 95% CI = 1.09 - 1.23, P = 2.57x10-6). The rs9976829 represents a strong splicing quantitative trait locus (sQTL) for both IFNAR2 and IL10RB genes, especially in lung tissue (P 1.8x10-24). Gene-based association analysis also found IFNAR2 was significantly associated with COVID-19 infection (P = 2.58x10-7). Integrative genomics analysis of combining GWAS with eQTL data showed the expression variations of IFNAR2 and IL10RB have prominent effects on COVID-19 in various types of tissues, especially in lung tissue. The majority of IFNAR2-expressing cells were dendritic cells (40%) and plasmacytoid dendritic cells (38.5%), and IL10RB-expressing cells were mainly nonclassical monocytes (29.6%). IFNAR2 and IL10RB are targeted by several interferons-related drugs. Together, our results uncover 21q22.11 as a novel susceptibility locus for COVID-19, in which individuals with G alleles of rs9976829 have a higher probability of COVID-19 susceptibility than those with non-G alleles.

Co-expression of Mitochondrial Genes and ACE2 in Cornea Involved in COVID-19 Infection (preprint)

The Coronavirus disease 2019 (COVID-19) pandemic severely challenges public health and necessitates the need for increasing our understanding of COVID-19 pathogenesis, especially host factors facilitating virus infection and propagation. Here, the co-expression network was constructed by mapping the well-known ACE2, TMPRSS2 and host susceptibility genes implicated in COVID-19 GWAS onto a cornea, retinal pigment epithelium and lung. We found a significant co-expression module of these genes in the cornea, revealing that cornea is potential extra-respiratory entry portal of SARS-CoV-2. Strikingly, both co-expression and interaction networks show a significant enrichment in mitochondrial function, which are the hub of cellular oxidative homeostasis, inflammation and innate immune response. We identified a corneal mitochondrial susceptibility module (CMSM) of 14 mitochondrial genes by integrating ACE2 co-expression cluster and SARS-CoV-2 interactome. Gene ECSIT, as a cytosolic adaptor protein involved in inflammatory responses, exhibits the strongest correlation with ACE2 in CMSM, which has shown to be an important risk factor for SARS-CoV-2 infection and prognosis. Our co-expression and protein interaction network analysis uncover that the mitochondrial function related genes in cornea contribute to the dissection of COVID-19 susceptibility and potential therapeutic interventions.

Necessity and feasibility of viral RNA detection in specialist ophthalmic institute during the COVID-19 epidemic / 中华实验眼科杂志

The prevention and treatment of COVID-19 in China is now at a key stage. The tasks faced by the medical organs are fighting against the COVID-19 while providing the medical services orderly. As a Specialist medical institution nationwide, ophthalmic hospitals are resuming receiving patients and performing operations gradually, including precision interruption of the epidemic, prevention of the secondary virus transmission, and avoidance of nosocomial cross infection among health care providers are required. We explored a multifaceted management for the prevention and control of epidemic, with a special focus on the individual protection for patients and medical staffs. A preliminary positive effect can be observed as a result. The main measures taken cover two aspects. On the one hand, 2019-nCoV ribonucleic acid (RNA) detection and hematological indices inspection including C-reactive protein (CRP) and serum amyloid A (SAA) are listed as routine tests of preoperative screening for ocular surgical patients. These tests are required to be completed upon the admission to avoid the possibility of accepting any asymptomatic infected individual and to reduce the risk of nosocomial cross infection. On the other hand, the 2019-nCoV RNA detection is also provided to high-risk employees who visited affected area recently. This assists in obtaining guarantee in both safety and quality of medical services provided, but also helps in lessening the mental and spiritual stress for medical staffs. It is expected that these measures can contribute to the work of our peers of ophthalmology in the prevention and control of COVID-19 and to the safe environment where the medical services are provided, and provide a reference for other outbreak of virus-causing disease.

Highland of COVID-19 outside Hubei: epidemic characteristics, control and projections of Wenzhou, China (preprint)

In late December 2019, Chinese authorities reported a cluster of pneumonia cases of unknown aetiology in Wuhan, China. Wenzhou, as a southeast coastal city with the most cases outside Hubei Province, its policy control and epidemic projections have certain references for national and worldwide epidemic prevention and control. The maximum number of illness onset in Wenzhou appeared on January 26 (38 cases). Since January 27, the incidence per day in Wenzhou has continued to decline is likely to be due to isolation of people return to Wenzhou, implementation of region quarantine and suspension of public transportation system. Under the current control efforts, we estimate that the daily incidence by March 3-9, 2020 will drop to 0 in Wenzhou using SEIR model. The total number of affected people is 538.