Rosuvastatin for COVID-19

ABSTRACTBACKGROUNDThe effectiveness of rosuvastatin plus colchicine, emtricitabine/tenofovir, and of their combined use in hospitalized patients with coronavirus disease 2019 (Covid-19) pneumonia is unclear.METHODSIn each hospital, hospitalized adults with Covid-19 pneumonia, were randomly assigned, in a 1:1 ratio, to receive: a) standard of care; or b) emtricitabine/tenofovir; or c) colchicine + rosuvastatin; or d) emtricitabine/tenofovir + colchicine + rosuvastatin. The primary outcome was all-cause mortality within the first 28 days after randomization. Severe adverse events (SAE) were those with a high probability of being treatment-related.RESULTS633 patients were randomized in 6 hospitals in Bogota, Colombia. Overall, 98% of the patients received glucocorticoids during hospitalization. The cumulative incidence of death through day 28 was 10.7% in the emtricitabine/tenofovir + colchicine + rosuvastatin arm, 14.4% in the colchicine + rosuvastatin arm, 13.8% in the emtricitabine/tenofovir arm, and 17.4% in the standard of care arm, with adjusted risk differences (aRD) against the standard treatment of -0.07 (95% confidence interval [CI], -0.17 to 0.04), aRD -0.03 (95%CI: -0.11 to 0.05) and aRD: -0.05 (95%CI: -0.15 to 0.05), respectively. Need for invasive mechanical ventilation was lower in the emtricitabine/tenofovir + colchicine + rosuvastatin arm compared to the standard treatment arm, aRD: -0.06 (95%CI: -0.11 to -0,01), but no differences were found between the other comparisons. SAE occurred in 3 patients distributed in the 3 treatment arms.CONCLUSIONSAmong patients hospitalized with moderate and severe SARS Covid-19, the use of the emtricitabine/tenofovir + colchicine + rosuvastatin combination emerges as a treatment alternative.ClinicalTrials.gov number: NCT04359095

The new strain of Coronaviruses (SARS-CoV-2), and the resulting Covid-19 disease has spread swiftly across the globe after its initial detection in late December 2019 in Wuhan, China, resulting in a pandemic status declaration by WHO within 3 months. Given the heavy toll of this pandemic, researchers are actively testing various strategies including new and repurposed drugs as well as vaccines. In the current brief report, we adopted a repositioning approach using insilico molecular modeling screening using FDA approved drugs with established safety profiles for potential inhibitory effects on Covid-19 virus. We started with structure based drug design by screening more than 2000 FDA approved drugsagainst Covid-19 virus main protease enzyme (Mpro) substrate-binding pocket to identify potential hits based on their binding energies, binding modes, interacting amino acids, and therapeutic indications. In addition, we elucidate preliminary pharmacophore features for candidates bound to Covid-19 virus Mpro substratebinding pocket. The top hits include anti-viral drugs such as Darunavir, Nelfinavirand Saquinavir, some of which are already being tested in Covid-19 patients. Interestingly, one of the most promising hits in our screen is the hypercholesterolemia drug Rosuvastatin. These results certainly do not confirm or indicate antiviral activity, but can rather be used as a starting point for further in vitro and in vivo testing, either individually or in combination.

Drug repurposing is a fast way to rapidly discover a drug for clinical use. In such circumstances of the spreading of the highly contagious COVID-19, searching for already known drugs is a worldwide demand. In this study, many drugs were evaluated by molecular docking. Among the test compounds, aliskiren (the best), dipyridamole, mopidamol and rosuvastatin showed higher energies of binding than that of the co-crystallized ligand N3 with COVID-19 main protease Mpro. Rolitetracycline showed the best binding with the catalytic center of the protease enzyme through binding with CYS 145 and HIS 41. Metamizole showed about 86 % of the binding energy of the ligand N3 while the protease inhibitor darunavir showed little bit lower binding energy than N3. These results are promising for using these drugs in the treatment and management of the spreading of COVID-19 virus. Also, it could stimulate clinical trials for the use of these drugs by systemic or inhalation route.The results stimulate the evaluation of these drugs as anti COVID-19 especially aliskiren which showed the highest score of binding with the binding site of N3. This will be added to its renin inhibition and advantage of renin inhibition and possibility of the reduced expression of ACE2[12]. Dipyridamole and mopidamol showed a potential to be more Mpro inhibitor than ligand N3 and darunavir. Also, dipyridamole has the property of antiviral activity beside its use to decrease the hypercoagulabilty that happens due to COVID infection in addition to the property of promoting type I interferon (IFN) responses and protect mice from viral pneumonia [30]. Rolitetracycling is an amazing in its binding mode in the active site of the protease pocket it seemed as it is tailored to be buried in that pocket. Mopidamol and rosuvastatin are slightly better than the co-crystallized ligand N3 and darunavir in binding mode which nominate the as COVID-19 protease inhibitors. Hopefully this study will help in the repurposing a drug for the treatment of COVID-19.

AbstractThe coronavirus disease 2019 (COVID-19) caused by coronavirus SARS-CoV-2 infection has become a global pandemic due to the high viral transmissibility and pathogenesis, bringing enormous burden to our society. Most patients infected by SARS-CoV-2 are asymptomatic or have mild symptoms. Although only a small proportion of patients progressed to severe COVID-19 with symptoms including acute respiratory distress syndrome (ARDS), disseminated coagulopathy, and cardiovascular disorders, severe COVID-19 is accompanied by high mortality rates with near 7 million deaths. Nowadays, effective therapeutic patterns for severe COVID-19 are still lacking. It has been extensively reported that host metabolism plays essential roles in various physiological processes during virus infection. Many viruses manipulate host metabolism to avoid immunity, facilitate their own replication, or to initiate pathological response. Targeting the interaction between SARS-CoV-2 and host metabolism holds promise for developing therapeutic strategies. In this review, we summarize and discuss recent studies dedicated to uncovering the role of host metabolism during the life cycle of SARS-CoV-2 in aspects of entry, replication, assembly, and pathogenesis with an emphasis on glucose metabolism and lipid metabolism. Microbiota and long COVID-19 are also discussed. Ultimately, we recapitulate metabolism-modulating drugs repurposed for COVID-19 including statins, ASM inhibitors, NSAIDs, Montelukast, omega-3 fatty acids, 2-DG, and metformin.

According to the World Health Organization (WHO), in the second half of 2022, there are about 606 million confirmed cases of COVID-19 and almost 6,500,000 deaths around the world. A pandemic was declared by the WHO in March 2020 when the new coronavirus spread around the world. The short time between the first cases in Wuhan and the declaration of a pandemic initiated the search for ways to stop the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or to attempt to cure the disease COVID-19. More than ever, research groups are developing vaccines, drugs, and immunobiological compounds, and they are even trying to repurpose drugs in an increasing number of clinical trials. There are great expectations regarding the vaccine’s effectiveness for the prevention of COVID-19. However, producing sufficient doses of vaccines for the entire population and SARS-CoV-2 variants are challenges for pharmaceutical industries. On the contrary, efforts have been made to create different vaccines with different approaches so that they can be used by the entire population. Here, we summarize about 8162 clinical trials, showing a greater number of drug clinical trials in Europe and the United States and less clinical trials in low-income countries. Promising results about the use of new drugs and drug repositioning, monoclonal antibodies, convalescent plasma, and mesenchymal stem cells to control viral infection/replication or the hyper-inflammatory response to the new coronavirus bring hope to treat the disease.

Despite the extensive vaccination campaigns in many countries, COVID-19 is still a major worldwide health problem because of its associated morbidity and mortality. Therefore, finding efficient treatments as fast as possible is a pressing need. Drug repurposing constitutes a convenient alternative when the need for new drugs in an unexpected medical scenario is urgent, as is the case with COVID-19. Using data from a central registry of electronic health records (the Andalusian Population Health Database, BPS), the effect of prior consumption of drugs for other indications previous to the hospitalization with respect to patient survival was studied on a retrospective cohort of 15,968 individuals, comprising all COVID-19 patients hospitalized in Andalusia between January and November 2020. Covariate-adjusted hazard ratios and analysis of lymphocyte progression curves support a significant association between consumption of 21 different drugs and better patient survival. Contrarily, one drug, furosemide, displayed a significant increase in patient mortality.

Background 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. Here we explored the possibility that different statins might differ in their ability to exert protective effects based on computational predictions. Methods 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, with a total of 2,436 drugs investigated. Top drug predictions included statins, which were tested in Vero E6 cells infected with SARS-CoV-2 and human endothelial cells infected with a related OC43 coronavirus. A database containing over 4,000 COVID-19 patients on statins was also analyzed to determine mortality risk in patients prescribed specific statins versus untreated matched controls. Findings Simvastatin was among the most highly predicted compounds (14/14 datasets) and five other statins were predicted to be active in > 50% of analyses. In vitro testing of SARS-CoV-2 infected cells revealed simvastatin to be a potent inhibitor whereas most other statins were less effective. Simvastatin also inhibited OC43 infection and reduced cytokine production in endothelial cells. 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. Interpretation Different statins may differ in their ability to sustain the lives of COVID-19 patients despite having a shared target and lipid-modifying mechanism of action. These findings highlight the value of target-agnostic drug prediction coupled with patient databases to identify and validate non-obvious mechanisms and drug repurposing opportunities. Funding DARPA, Wyss Institute, Hess Research Fund, UCSF Program for Breakthrough Biomedical Research, and NIH

The active global SARS-CoV-2 pandemic caused more than 426 million cases and 5.8 million deaths worldwide. The development of completely new drugs for such a novel disease is a challenging, time intensive process. Despite researchers around the world working on this task, no effective treatments have been developed yet. This emphasizes the importance of drug repurposing, where treatments are found among existing drugs that are meant for different diseases. A common approach to this is based on \emph{knowledge graphs}, that condense relationships between entities like drugs, diseases and genes. Graph neural networks (GNNs) can then be used for the task at hand by predicting links in such knowledge graphs. Expanding on state-of-the-art GNN research, Doshi {\sl et al.} recently developed the \drcov \ model. We further extend their work using additional output interpretation strategies. The best aggregation strategy derives a top-100 ranking of 8,070 candidate drugs, 32 of which are currently being tested in COVID-19-related clinical trials. Moreover, we present an alternative application for the model, the generation of additional candidates based on a given pre-selection of drug candidates using collaborative filtering. In addition, we improved the implementation of the \drcov \ model by significantly shortening the inference and pre-processing time by exploiting data-parallelism. As drug repurposing is a task that requires high computation and memory resources, we further accelerate the post-processing phase using a new emerging hardware --- we propose a new approach to leverage the use of high-capacity Non-Volatile Memory for aggregate drug ranking.

Background:Until coronavirus disease 2019 (COVID-19) drugs specifically developed to treat COVID-19 become more widely accessible, it is crucial to identify whether existing medications have a protective effect against severe disease. Toward this objective, we conducted a large population study in Clalit Health Services (CHS), the largest healthcare provider in Israel, insuring over 4.7 million members.Methods:Two case-control matched cohorts were assembled to assess which medications, acquired in the last month, decreased the risk of COVID-19 hospitalization. Case patients were adults aged 18 to 95 hospitalized for COVID-19. In the first cohort, five control patients, from the general population, were matched to each case (n=6202); in the second cohort, two non-hospitalized SARS-CoV-2 positive control patients were matched to each case (n=6919). The outcome measures for a medication were: odds ratio (OR) for hospitalization, 95% confidence interval (CI), and the p-value, using Fisher’s exact test. False discovery rate was used to adjust for multiple testing.Results:Medications associated with most significantly reduced odds for COVID-19 hospitalization include: ubiquinone (OR=0.185, 95% CI [0.058 to 0.458], p<0.001), ezetimibe (OR=0.488, 95% CI [0.377 to 0.622], p<0.001), rosuvastatin (OR=0.673, 95% CI [0.596 to 0.758], p<0.001), flecainide (OR=0.301, 95% CI [0.118 to 0.641], p<0.001), and vitamin D (OR=0.869, 95% CI [0.792 to 0.954], p<0.003). Remarkably, acquisition of artificial tears, eye care wipes, and several ophthalmological products were also associated with decreased risk for hospitalization.Conclusions:Ubiquinone, ezetimibe, and rosuvastatin, all related to the cholesterol synthesis pathway were associated with reduced hospitalization risk. These findings point to a promising protective effect which should be further investigated in controlled, prospective studies.Funding:This research was supported in part by the Intramural Research Program of the National Institutes of Health, NCI.