Nicotine for COVID-19

There is an urgent need to address the devastating pandemic, COVID‐19, caused by SARS‐CoV‐2. The efforts to understand the details of this disease in hope of providing effective treatments are commendable. It is clear now that the virus can cause far more damage in patients with comorbid conditions—particularly in those with respiratory, cardiovascular, or immune‐compromised system—than in patients without such comorbidities. Drug use can further exacerbate the condition. In this regard, the ill effects of smoking are amply documented, and no doubt can be a confounding factor in COVID‐19 progression. Although conflicting hypotheses on the potential role of nicotine in COVID‐19 pathology have recently been offered, we believe that nicotine itself, through its interaction with the nicotinic cholinergic system, as well as ACE2, may not only be of use in a variety of neuropsychiatric and neurodegenerative diseases, but may also be of potential use in COVID‐19. Thus, on one hand, while we strongly support smoking cessation as a means of harm reduction associated with COVID‐19, on the other hand, we support a potential therapeutic role for nicotine, nicotinic agonists, or positive allosteric modulators of nicotinic cholinergic receptors in COVID‐19, owing to their varied effects including mood regulation, anti‐inflammatory, and purported interference with SARS‐CoV‐2 entry and/or replication.

ABSTRACTBackgroundThe Omicron (B.1.1.529) variant of SARS-CoV-2 has rapidly achieved global dissemination, accounting for most infections in the United States by December 2021. Risk of severe outcomes associated with Omicron infections, as compared to earlier SARS-CoV-2 variants, remains unclear.MethodsWe analyzed clinical and epidemiologic data from cases testing positive for SARS-CoV-2 infection within the Kaiser Permanente Southern California healthcare system from November 30, 2021 to January 1, 2022, using S gene target failure (SGTF) as assessed by the ThermoFisher TaqPath ComboKit assay as a proxy for Omicron infection. We fit Cox proportional hazards models to compare time to any hospital admission and hospital admissions associated with new-onset respiratory symptoms, intensive care unit (ICU) admission, mechanical ventilation, and mortality among cases with Omicron and Delta (non-SGTF) variant infections. We fit parametric competing risk models to compare lengths of hospital stay among admitted cases with Omicron and Delta variant infections.ResultsOur analyses included 52,297 cases with SGTF (Omicron) and 16,982 cases with non-SGTF (Delta [B.1.617.2]) infections, respectively. Hospital admissions occurred among 235 (0.5%) and 222 (1.3%) of cases with Omicron and Delta variant infections, respectively. Among cases first tested in outpatient settings, the adjusted hazard ratios for any subsequent hospital admission and symptomatic hospital admission associated with Omicron variant infection were 0.48 (0.36-0.64) and 0.47 (0.35-0.62), respectively. Rates of ICU admission and mortality after an outpatient positive test were 0.26 (0.10-0.73) and 0.09 (0.01-0.75) fold as high among cases with Omicron variant infection as compared to cases with Delta variant infection. Zero cases with Omicron variant infection received mechanical ventilation, as compared to 11 cases with Delta variant infections throughout the period of follow-up (two-sided p<0.001). Median duration of hospital stay was 3.4 (2.8-4.1) days shorter for hospitalized cases with Omicron variant infections as compared to hospitalized patients with Delta variant infections, reflecting a 69.6% (64.0-74.5%) reduction in hospital length of stay.ConclusionsDuring a period with mixed Delta and Omicron variant circulation, SARS-CoV-2 infections with presumed Omicron variant infection were associated with substantially reduced risk of severe clinical endpoints and shorter durations of hospital stay.Trial registrationNot applicable

AbstractFollowing a SARS-CoV-2 infection, many individuals suffer from post-COVID-19 syndrome. It makes them unable to proceed with common everyday activities due to weakness, memory lapses, pain, dyspnea and other unspecific physical complaints. Several investigators could demonstrate that the SARS-CoV-2 related spike glycoprotein (SGP) attaches not only to ACE-2 receptors but also shows DNA sections highly affine to nicotinic acetylcholine receptors (nAChRs). The nAChR is the principal structure of cholinergic neuromodulation and is responsible for coordinated neuronal network interaction. Non-intrinsic viral nAChR attachment compromises integrative interneuronal communication substantially. This explains the cognitive, neuromuscular and mood impairment, as well as the vegetative symptoms, characterizing post-COVID-19 syndrome. The agonist ligand nicotine shows an up to 30-fold higher affinity to nACHRs than acetylcholine (ACh). We therefore hypothesize that this molecule could displace the virus from nAChR attachment and pave the way for unimpaired cholinergic signal transmission. Treating several individuals suffering from post-COVID-19 syndrome with a nicotine patch application, we witnessed improvements ranging from immediate and substantial to complete remission in a matter of days.

The severe acute respiratory syndrome coronavirus 2 (SARSCoV 2) is a coronavirus variation responsible for COVID19, the respiratory disease that triggered the COVID19 pandemic. The primary aim of our study is to elucidate the complex network of interactions between SARS CoV 2, tuberculosis, and lung cancer employing a bioinformatics and network biology approach. Lung cancer is the leading cause of significant illness and death connected to cancer worldwide. Tuberculosis (TB) is a prevalent medical condition induced by the Mycobacterium bacteria. It mostly affects the lungs but may also have an influence on other areas of the body. Coronavirus disease (COVID19) causes a risk of respiratory complications between lung cancer and tuberculosis. SARSCoV 2 impacts the lower respiratory system and causes severe pneumonia, which can significantly increase the mortality risk in individuals with lung cancer. We conducted transcriptome analysis to determine molecular biomarkers and common pathways in lung cancer, TB, and COVID19, which provide understanding into the association of SARSCoV 2 to lung cancer and tuberculosis. Based on the compatible RNA-seq data, our research employed GREIN and NCBI's Gene Expression Omnibus (GEO) to perform differential gene expression analysis. Our study exploited three RNAseq datasets from the Gene Expression Omnibus (GEO) GSE171110, GSE89403, and GSE81089 to identify distinct relationships between differentially expressed genes (DEGs) in SARSCoV 2, tuberculosis, and lung cancer. We identified 30 common genes among SARSCoV 2, tuberculosis, and lung cancer (25 upregulated genes and 5 downregulated genes). We analyzed the following five databases: WikiPathway, KEGG, Bio Carta, Elsevier Pathway and Reactome. Using Cytohubba's MCC and Degree methods, We determined the top 15 hub genes resulting from the PPI interaction. These hub genes can serve as potential biomarkers, leading to novel treatment strategies for disorders under investigation. Transcription factors (TFs) and microRNAs (miRNAs) were identified as the molecules that control the differentially expressed genes (DEGs) of interest, either during transcription or after transcription. We identified 35 prospective therapeutic compounds that form significant differentially expressed genes (DEGs) in SARSCoV 2, lung cancer, and tuberculosis, which could potentially serve as medications. We hypothesized that the potential medications that emerged from this investigation may have therapeutic benefits.

AbstractThe recent outbreak of the COVID-19 pandemic caused by severe acute respiratory syndrome-Coronavirus-2 (SARS-CoV-2) has shown the necessity for fast and broad drug discovery methods to enable us to react quickly to novel and highly infectious diseases. A well-known SARS-CoV-2 target is the viral main 3-chymotrypsin-like cysteine protease (Mpro), known to control coronavirus replication, which is essential for the viral life cycle. Here, we applied an interaction-based drug repositioning algorithm on all protein-compound complexes available in the protein database (PDB) to identify Mpro inhibitors and potential novel compound scaffolds against SARS-CoV-2. The screen revealed a heterogeneous set of 692 potential Mpro inhibitors containing known ones such as Dasatinib, Amodiaquine, and Flavin mononucleotide, as well as so far untested chemical scaffolds. In a follow-up evaluation, we used publicly available data published almost two years after the screen to validate our results. In total, we are able to validate 17% of the top 100 predictions with publicly available data and can furthermore show that predicted compounds do cover scaffolds that are yet not associated with Mpro. Finally, we detected a potentially important binding pattern consisting of 3 hydrogen bonds with hydrogen donors of an oxyanion hole within the active side of Mpro. Overall, these results give hope that we will be better prepared for future pandemics and that drug development will become more efficient in the upcoming years.

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.