Integrating population-level and cell-based signatures for drug repositioning (preprint)

Drug repositioning presents a streamlined and cost-efficient way to expand the range of therapeutic possibilities. Furthermore, drugs with genetic evidence are more likely to progress successfully through clinical trials towards FDA approval. Exploiting these developments, single gene-based drug repositioning methods have been implemented, but approaches leveraging the entire spectrum of molecular signatures are critically underexplored. Most multi-gene-based approaches rely on differential gene expression (DGE) analysis, which is prone to identify the molecular consequence of disease and renders causal inference challenging. We propose a framework TReD (Transcriptome-informed Reversal Distance) that integrates population-level disease signatures robust to reverse causality and cell-based drug-induced transcriptome response profiles. TReD embeds the disease signature and drug profile in a high-dimensional normed space, quantifying the reversal potential of candidate drugs in a disease-related cell screen assay. The robustness is ensured by evaluation in additional cell screens. For an application, we implement the framework to identify potential drugs against COVID-19. Taking transcriptome-wide association study (TWAS) results from four relevant tissues and three DGE results as disease features, we identify 37 drugs showing potential reversal roles in at least four of the seven disease signatures. Notably, over 70% (27/37) of the drugs have been linked to COVID-19 from other studies, and among them, eight drugs are supported by ongoing/completed clinical trials. For example, TReD identifies the well-studied JAK1/JAK2 inhibitor baricitinib, the first FDA-approved immunomodulatory treatment for COVID-19. Novel potential candidates, including enzastaurin, a selective inhibitor of PKC-beta which can be activated by SARS-CoV-2, are also identified. In summary, we propose a comprehensive genetics-anchored framework integrating population-level signatures and cell-based screens that can accelerate the search for new therapeutic strategies.

Widespread wildfires over the western United States in 2020 linked to emissions reductions during COVID‐19

Widespread wildfires struck the western United States in 2020, damaging properties and threating human lives. Meanwhile, the COVID‐19 pandemic spread across the globe, which disrupted human activities. Here, we investigate the effects of the emissions reductions during the pandemic on fire weather in 2020 over the western United States by using an earth system model together with observations. We show that reductions in aerosols dominate the increases in wildfire risks, whereas greenhouse gas decrease counteracts this influence. The aerosol emissions reductions increased surface air temperature and decreased precipitation and relative humidity due to a weakened moisture transport, which explains one‐third of the observed increase in wildfire risks during August–November over the western United States in 2020. This study suggests that COVID‐19‐related emissions reductions have an unexpected influence on wildfires, highlighting a different but important role of human activities in affecting wildfire risks. Key Points The impacts of COVID‐19 emissions reductions on weather conditions for wildfire over the western United States in 2020 were investigated The COVID‐19 emissions reductions increased surface air temperature and decreased precipitation and relative humidity Reductions in aerosols explain one‐third of the observed wildfire risk increase, whereas greenhouse gas decrease counteracts this influence

Mitoxantrone modulates a glycosaminoglycan-spike complex to inhibit SARS-CoV-2 infection (preprint)

Spike-mediated entry of SARS-CoV-2 into human airway epithelial cells is an attractive therapeutic target for COVID-19. In addition to protein receptors, the SARS-CoV-2 spike (S) protein also interacts with heparan sulfate, a negatively charged glycosaminoglycan (GAG) attached to certain membrane proteins on the cell surface. This interaction facilitates the engagement of spike with a downstream receptor to promote viral entry. Here, we show that Mitoxantrone, an FDA-approved topoisomerase inhibitor, targets a spike-GAG complex to compromise the fusogenic function of spike in viral entry. As a single agent, Mitoxantrone inhibits the infection of an authentic SARS-CoV-2 strain in a cell-based model and in human lung EpiAirway 3D tissues. Gene expression profiling supports the plasma membrane as a major target of Mitoxantrone but also underscores an undesired activity targeting nucleosome dynamics. We propose that Mitoxantrone analogs bearing similar GAG-binding activities but with reduced affinity for DNA topoisomerase may offer an alternative therapy to overcome breakthrough infections in the post-vaccine era.

Fast climate responses to aerosol emission reductions during the COVID-19 pandemic. (Special Section: The COVID-19 pandemic: linking health, society, and environment.)

The reduced human activities and associated decreases in aerosol emissions during the COVID-19 pandemic are expected to affect climate. Assuming emission changes during lockdown, back-to-work and post-lockdown stages of COVID-19, climate model simulations show a surface warming over continental regions of the Northern Hemisphere. In January-March, there was an anomalous warming of 0.05-0.15 K in eastern China, and the surface temperature increase was 0.04-0.07 K in Europe, eastern United States, and South Asia in March-May. The longer the emission reductions undergo, the warmer the climate would become. The emission reductions explain the observed temperature increases of 10-40% over eastern China relative to 2019. A southward shift of the ITCZ is also seen in the simulations. This study provides an insight into the impact of COVID-19 pandemic on global and regional climate and implications for immediate actions to mitigate fast global warming.

Enhanced PM2.5 Decreases and O3 Increases in China During COVID-19 Lockdown by Aerosol-Radiation Feedback.

We apply an online-coupled meteorology-chemistry model (WRF-Chem) embedded with an improved process analysis to examine aerosol-radiation feedback (ARF) impacts on effectiveness of emission control due to Coronavirus Disease 2019 (COVID-19) lockdown over North China Plain. Emission reduction alone induces PM2.5 decrease by 16.3 µg m-3 and O3 increase by 10.2 ppbv during COVID-19 lockdown. The ARF enhances PM2.5 decrease by 2.7 µg m-3 (16.6%) and O3 increase by 0.8 ppbv (7.8%). The ARF-induced enhancement of PM2.5 decline is mostly attributed to aerosol chemistry process, while enhancement of O3 rise is ascribed to physical advection and vertical mixing processes. A set of sensitivity experiments with emission reductions in different degrees indicate that the ARF-induced enhancements of PM2.5 declines (O3 rises) follow a robust linear relationship with the emission-reduction-induced PM2.5 decreases. The fitted relationship has an important implication for assessing the effectiveness of emission abatement at any extent.

Decreased Anthropogenic CO2 Emissions during the COVID-19 Pandemic Estimated from FTS and MAX-DOAS Measurements at Urban Beijing

The COVID-19 pandemic has led to ongoing reductions in economic activity and anthropogenic emissions. Beijing was particular badly affected by lockdown measures during the early months of the COVID-19 pandemic. It has significantly reduced the CO2 emission and toxic air pollution (CO and NO2). We use column-averaged dry-air mole fractions of CO2 and CO (XCO2 and XCO) observed by a ground-based EM27/SUN Fourier transform spectrometer (FTS), the tropospheric NO2 column observed by MAX-DOAS and satellite remote sensing data (GOSAT and TROPOMI) to investigate the variations in anthropogenic CO2 emission related to COVID-19 lockdown in Beijing. The anomalies describe the spatio-temporal enhancement of gas concentration, which relates to the emission. Anomalies in XCO2 and XCO, and XNO2 (ΔXCO2, ΔXCO, and ΔXNO2) for ground-based measurements were calculated from the diurnal variability. Highly correlated daily XCO and XCO2 anomalies derived from FTS time series data provide the ΔXCO to ΔXCO2 ratio (the correlation slope). The ΔXCO to ΔXCO2 ratio in Beijing was lower in 2020 (8.2 ppb/ppm) than in 2019 (9.6 ppb/ppm). The ΔXCO to ΔXCO2 ratio originating from a polluted area was significantly lower in 2020. The reduction in anthropogenic CO2 emission was estimated to be 14.2% using FTS data. A comparable value reflecting the slowdown in growth of atmospheric CO2 over the same time period was estimated to be 15% in Beijing from the XCO2 anomaly from GOSAT, which was derived from the difference between the target area and the background area. The XCO anomaly from TROPOMI is reduced by 8.7% in 2020 compared with 2019, which is much smaller than the reduction in surface air pollution data (17%). Ground-based NO2 observation provides a 21.6% decline in NO2. The NO2 to CO2 correlation indicates a 38.2% decline in the CO2 traffic emission sector. Overall, the reduction in anthropogenic CO2 emission relating to COVID-19 lockdown in Beijing can be detected by the Bruker EM27/SUN Fourier transform spectrometer (FTS) and MAX-DOAS in urban Beijing.

Author Correction: Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic.

A Correction to this paper has been published: https://doi.org/10.1038/s41467-020-20254-5.

Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic.

The COVID-19 pandemic is impacting human activities, and in turn energy use and carbon dioxide (CO2) emissions. Here we present daily estimates of country-level CO2 emissions for different sectors based on near-real-time activity data. The key result is an abrupt 8.8% decrease in global CO2 emissions (-1551 Mt CO2) in the first half of 2020 compared to the same period in 2019. The magnitude of this decrease is larger than during previous economic downturns or World War II. The timing of emissions decreases corresponds to lockdown measures in each country. By July 1st, the pandemic's effects on global emissions diminished as lockdown restrictions relaxed and some economic activities restarted, especially in China and several European countries, but substantial differences persist between countries, with continuing emission declines in the U.S. where coronavirus cases are still increasing substantially.

Targeting heparan sulfate proteoglycan-assisted endocytosis as a COVID-19 therapeutic option (preprint)

Drugs capable of blocking the infectious cycle of the coronavirus SARS-CoV-2 are urgently needed to tackle the ongoing COVID-19 pandemic. To this end, the cell entry of SARS-CoV-2, initiated by the binding of the viral Spike (S) protein to human ACE2, has emerged as an attractive drug repurposing target. Here we use murine leukemia viruses pseudotyped with Spike from SARS-CoV or SARS-CoV-2 to demonstrate that ACE2-mediated coronavirus entry can be mitigated by heparin, a heparan sulfate-related glycan, or by genetic ablation of biosynthetic enzymes for the cell surface heparan sulfate proteoglycans (HSPGs). A drug repurposing screen targeting HSPG-dependent endocytosis identifies pharmacologically active endocytosis inhibitors that also abrogate coronavirus cell entry. Among them, Mitoxantrone (EC50=~10 nM) targets HSPGs directly, whereas Sunitinib and BNTX disrupt the actin network to impair HSPG-assisted viral entry. Gene expression profiling suggests potential combination regimens that optimally target HSPG-dependent viral entry. Altogether, our study establishes HSPGs as an assisting factor for ACE2 in endocytosis-mediated coronavirus entry and identifies drugs that can be repurposed to target this important stage in the viral life cycle.

Early predictors and screening tool developing for severe patients with COVID-19 (preprint)

Background Coronavirus disease 2019 (COVID-19) is a declared global pandemic, causing a lot of death. How to quickly screen risk population for severe patients is essential for decreasing the mortality. Methods This retrospective study included all the 813 confirmed cases diagnosed with COVID-19 before March 2nd, 2020 in a city of Hubei Province in China. Data of the COVID-19 patients including clinical and epidemiological features were collected through Chinese Disease Control and Prevention Information System. Predictors were selected by logistic regression, and then categoried to four different level risk factor. A screening tool for severe patient with COVID-19 was developed and tested by ROC curve. Results Seven early predictors for severe patients with COVID-19 were selected, including chronic kidney disease (OR=14.7), age above 60 (OR=5.6), lymphocyte count less than <0.8 × 109 per L (OR=2.5), Neutrophile to Lymphocyte Ratio larger than 4.7 (OR=2.2), high fever with temperature ≥38.5℃ (OR=2.2), male (OR=2.2), cardiovascular related diseases (OR=2.0). The Area Under the Curve of the screening tool developed by above seven predictors was 0.798 (95%CI: 0.747~0.849), and its best cut-off value is >4.5, with sensitivity 72.0% and specificity 75.3%. Conclusions  This newly developed screening tool can be a good choice for early prediction and alert for severe case especially in the condition of overload health service. 

Blood Biomarkers Dynamic Detection, Especially Eosinophils has Certain Value in the Clinical Diagnosis, Severity Classification and Prognosis Judgment of COVID-19 (preprint)

In December 2019, coronavirus disease 2019 (COVID-19) was first found in Wuhan, China and soon was reported all around the world. Novel coronavirus (COVID-19) is highly infectious and requires early detection, isolation, and treatment. We tried to find some useful information by analyzing the covid-19 screening data, so as to provide help for clinical practice. In this prospective study, we retrospectively analyzed the clinical data of 131 patients with COVID-19 and 119 controls. For confirmed cases, the data of blood routine examination were analyzed among severe patients and non-severe group. The blood routine examination results were dynamically observed in the survivors and nonsurvivors. We find that patients with COVID-19 have lower counts of leucocytes, lymphocytes, eosinophils, which were compared with controls (P < 0.001). In severe group, patients have the lower count of lymphocytes and eosinophils, but the higher leucocytes count (all P values < 0.01). Eosinophils have high diagnostic efficacy analysis of severe COVID-19, and its area under the curve reached 0.750. Patients whose eosinophils returned to normal early had significantly longer survival times than those who did not(P < 0.001). Patients with COVID-19 have abnormal peripheral blood routine examination results. Dynamic surveillance of peripheral blood system especially eosinophils is helpful in the diagnosis, assess the prognosis and prediction of severe COVID-19 cases.