ABSTRACT
Aim To explore the active compound of Maxingganshi decoction in treatment of novel coronavirus pneumonia(COVID-19). Methods With the help of TCMSP database, the chemical components and action targets of ephedra, almond, licorice, and gypsum in Maxingganshi decoction were searched, and then a C-T network, protein interaction analysis, GO functional enrichment analysis, and KEGG pathway enrichment were constructed. Analysis was performed to predict its mechanism of action. Results A total of 120 compounds in Maxingganshi decoction corresponded to 222 targets. PTGS2, ESR1, PPARG, AR, NOS2, NCOA2 acted on PI3K-Akt signaling pathway, TNF signaling pathway, IL-17 signaling pathway, T cell receptor signaling pathways, etc. The results of molecular docking showed that the affinity of quercetin, kaempferol, glabridin and other core compounds was similar to recommended drugs in treatment of COVID-19. Conclusions The active compounds of Maxingganshi decoction can target multiple pathways to achieve the therapeutic effect of COVID-19.Copyright © 2020 Publication Centre of Anhui Medical University. All rights reserved.
ABSTRACT
Background: To search for molecular biomarkers of pulmonary pathologies using non-invasive samples, such as urine, is of high clinical relevance. However, there are almost no proteomic studies using urine applied to respiratory diseases. Aim(s): To develop a biomarker discovery strategy using non-targeted proteomics in urine with applicability to different pulmonary diseases. Method(s): Urine samples were centrifuged and DTT treated to decrease uromodulin (THP). Low-THP samples were concentrated (ultrafiltration), ultracentrifugated, and exosome free urine was analysed using LC-MS/MS. GO terms/Pathway analyses were performed using STRING database. Result(s): Urine proteome (765 proteins) was enriched (FDR < 0.05) in proteins from different tissues, including respiratory system (N = 124), lung (N = 107), and immune system (N = 88). We detected an enrichment of relevant pathways for respiratory diseases, including several innate (e.g., TLR and NFkB pathways, complement system), and adaptive (e.g., interleukin signalling) immune system pathways. Some of these proteins have been previously studied in respiratory system disease (e.g., MPO, NAPSA, CHL1, FREM2, PLG), lower respiratory tract disease (e.g., NCAM1, MTOR, SERPINA1), viral infectious disease (e.g., ITIH4, CD209, CLEC4M, CD55), or specific pathologies such as coronavirus infection (e.g., ACE2, TMPRSS2), bronchiectasis (e.g., SAA1, SAA2, ELANE) or asthma (e.g., IGFALS, IGFBP7, HSPG2, DPP4, CD44, IL6R, MASP1). Conclusion(s): We have developed a protocol for the detection of proteomic biomarkers in urine. This proteome is enriched in proteins from the immune and respiratory systems, with a potential clinical and translational relevance.
ABSTRACT
Background: The coronavirus disease (COVID-19) caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is characterised by a wide spectrum of clinical phenotypes ranging in acuteness from asymptomatic, symptomatic with mild or moderate manifestation and severe involving pneumonia and respiratory distress. COVID-19 susceptibility, severity and recovery have demonstrated high variability worldwide. Variances in the host genetic architecture may potentially control the inter-individual and population scale differences in COVID-19 presentation. Methods: We performed a genome-wide association study (GWAS) employing the genotyping data from Ancestry DNA COVID-19 host genetic study that included COVID-19 positive patients and healthy individuals who had tested negative for SARS-CoV-2 infection at the time of recruitment. We restricted our analysis only to the individuals of European descents to avoid genetic structure in the dataset, arising due to the presence of people from different ancestries. Further, we uniquely employed the asymptomatic individuals as controls instead of healthy individuals. Results and Discussion: Our data revealed striking genomic differences between COVID-19 asymptomatic and severely symptomatic individuals. We identified 621 genetic variants that were significantly distinct (Multiple-testing corrected P<0.001) between asymptomatic and acutely symptomatic COVID-19 patients. These variants were found to be associated with pathways governing host immunity, such as innate and adaptive immune system, interferon signaling, interleukin signaling, antigen processing by MHC, cytokine signaling and known COVID-19 comorbidities, such as obesity, cholesterol metabolism and smoking. Variants modulating drug responses including to anti-retroviral agents were also found to vary significantly between asymptomatic and severe patient groups.