Target-agnostic drug prediction integrated with medical record analysis uncovers differential associations of statins with increased survival in COVID-19 patients.

Drug repurposing requires distinguishing established drug class targets from novel molecule-specific mechanisms and rapidly derisking their therapeutic potential in a time-critical manner, particularly in a pandemic scenario. In response to the challenge to rapidly identify treatment options for COVID-19, several studies reported that statins, as a drug class, reduce mortality in these patients. However, it is unknown if different statins exhibit consistent function or may have varying therapeutic benefit. A Bayesian network tool was used to predict drugs that shift the host transcriptomic response to SARS-CoV-2 infection towards a healthy state. Drugs were predicted using 14 RNA-sequencing datasets from 72 autopsy tissues and 465 COVID-19 patient samples or from cultured human cells and organoids infected with SARS-CoV-2. Top drug predictions included statins, which were then assessed using electronic medical records containing over 4,000 COVID-19 patients on statins to determine mortality risk in patients prescribed specific statins versus untreated matched controls. The same drugs were tested in Vero E6 cells infected with SARS-CoV-2 and human endothelial cells infected with a related OC43 coronavirus. Simvastatin was among the most highly predicted compounds (14/14 datasets) and five other statins, including atorvastatin, were predicted to be active in > 50% of analyses. Analysis of the clinical database revealed that reduced mortality risk was only observed in COVID-19 patients prescribed a subset of statins, including simvastatin and atorvastatin. In vitro testing of SARS-CoV-2 infected cells revealed simvastatin to be a potent direct inhibitor whereas most other statins were less effective. Simvastatin also inhibited OC43 infection and reduced cytokine production in endothelial cells. Statins may differ in their ability to sustain the lives of COVID-19 patients despite having a shared drug target and lipid-modifying mechanism of action. These findings highlight the value of target-agnostic drug prediction coupled with patient databases to identify and clinically evaluate non-obvious mechanisms and derisk and accelerate drug repurposing opportunities

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Not AvailableAs per the commitment of COP-21, reduction in greenhouse gas (GHG) emissions under various production systems without affecting productivity is one of the important challenges in addressing global warming. To address this, environmentally and economically efficient climate resilient management practices were identified under the National Initiative on Climate Resilient Agriculture (NICRA) project and were implemented in the sixteen study villages of four districts of Eastern India. In this study, the GHG emissions in terms of C balance in tCO2eq due to the adoption of climate resilient practices in agriculture, livestock and forestry were estimated using the EX-ACT model that was developed by the Food and Agriculture Organization (FAO) of the United Nations (UN). EX-ACT tool was found to be an user-friendly and easy tool to assess the C balance in small areas with diverse climate and soil types. The findings of this study reveal that there is a sink due to the adoption of mitigation strategies (climate resilient management practices) in annuals, perennials and afforestration, while a source (emissions) was observed in irrigated rice, land use change and fertilizer use (inputs). When all the components were considered instead of a single component, the overall C balance in the study villages was found negative, suggesting a sink.Not Availabl