The risk of common hypoglycemic and antihypertensive medications and COVID-19: A 2-sample Mendelian randomization study.

BACKGROUND: It has been reported that diabetes and hypertension increase the adverse outcomes of coronavirus disease 2019 (COVID-19). Aside from the inherent factors of diabetes and hypertension, it remains unclear whether antidiabetic or antihypertensive medications contribute to the increased adverse outcomes of COVID-19. The effect of commonly used antidiabetic and antihypertensive medications on COVID-19 outcomes has been inconsistently concluded in existing observational studies. Conducting a systematic study on the causal relationship between these medications and COVID-19 would be beneficial in guiding their use during the COVID-19 pandemic. METHODS: We employed the 2-sample Mendelian randomization approach to assess the causal relationship between 5 commonly used antidiabetic medications (SGLT-2 inhibitors, Sulfonylureas, Insulin analogues, Thiazolidinediones, GLP-1 analogues) and 3 commonly used antihypertensive medications (calcium channel blockers [CCB], ACE inhibitors, ß-receptor blockers [BB]), and COVID-19 susceptibility, hospitalization, and severe outcomes. The genetic variations in the drug targets of the 5 antidiabetic medications and 3 antihypertensive medications were utilized as instrumental variables. European population-specific genome-wide association analysis (GWAS) data on COVID-19 from the Host Genetics Initiative meta-analyses were obtained, including COVID-19 susceptibility (n = 2597,856), COVID-19 hospitalization (n = 2095,324), and COVID-19 severity (n = 1086,211). The random-effects inverse variance-weighted estimation method was employed as the primary assessment technique, with various sensitivity analyses conducted to evaluate heterogeneity and pleiotropy. RESULTS: There were no potential associations between the genetic variations in the drug targets of the 5 commonly used antidiabetic medications (SGLT-2 inhibitors, Sulfonylureas, Insulin analogues, Thiazolidinediones, GLP-1 analogues) and the 3 commonly used antihypertensive medications (CCBs, ACE inhibitors, BBs) with COVID-19 susceptibility, hospitalization, and severity (all P > .016). CONCLUSION: The findings from this comprehensive Mendelian randomization analysis suggest that there may be no causal relationship between the 5 commonly used antidiabetic medications (SGLT-2 inhibitors, Sulfonylureas, Insulin analogues, Thiazolidinediones, GLP-1 analogues) and the 3 commonly used antihypertensive medications (CCBs, ACE inhibitors, BBs) with COVID-19 susceptibility, hospitalization, and severity.

Comprehensive investigation of RNA-sequencing dataset reveals the hub genes and molecular mechanisms of coronavirus disease 2019 acute respiratory distress syndrome.

The goal of this study is to reveal the hub genes and molecular mechanisms of the coronavirus disease 2019 (COVID-19) acute respiratory distress syndrome (ARDS) based on the genome-wide RNA sequencing dataset. The RNA sequencing dataset of COVID-19 ARDS was obtained from GSE163426. A total of 270 differentially expressed genes (DEGs) were identified between COVID-19 ARDS and control group patients. Functional enrichment analysis of DEGs suggests that these DEGs may be involved in the following biological processes: response to cytokine, G-protein coupled receptor activity, ionotropic glutamate receptor signalling pathway and G-protein coupled receptor signalling pathway. By using the weighted correlation network analysis approach to analyse these DEGs, 10 hub DEGs that may play an important role in COVID-19 ARDS were identified. A total of 67 potential COVID-19 ARDS targetted drugs were identified by a complement map analysis. Immune cell infiltration analysis revealed that the levels of T cells CD4 naive, T cells follicular helper, macrophages M1 and eosinophils in COVID-19 ARDS patients were significantly different from those in control group patients. In conclusion, this study identified 10 COVID-19 ARDS-related hub DEGs and numerous potential molecular mechanisms through a comprehensive analysis of the RNA sequencing dataset and also revealed the difference in immune cell infiltration of COVID-19 ARDS.

Imbalance of γδT17/γδTreg cells in the pathogenesis of allergic asthma induced by ovalbumin.

We aimed to explore the imbalance between the T helper 17 γδT cells (γδT17) and the regulatory γδT cells (γδTreg) in asthmatic mice. Male Balb/c mice were randomly divided into the normal control group and the asthmatic model group. The asthmatic model group mice were intraperitoneally injected with the mixture of ovalbumin (OVA)/Al(OH)3 and then activated by exposure of the animals to OVA atomization. Airway hyperresponsiveness (AHR) was determined by a non-invasive lung function machine. Hematoxylin and eosin and Alcian blue-periodic acid Schiff staining were done for histopathological analysis. Interleukin (IL)-17 and IL-35 levels in bronchoalveolar lavage fluid were detected by ELISA. The percentage of IL-17+ γδT cells and Foxp3+ γδT cells in spleen cells suspension were detected and the transcription levels of RORγt and Foxp3 in the lung tissue were determined. Compared with the normal control, the severity of airway inflammation and AHR were higher in the asthmatic mice. Furthermore, mice in the asthmatic group displayed significant increases of IL-17+ γδT cells, expression of IL-17A, and RORγt, whereas control mice displayed marked decreases of Foxp3+ γδT cells, expression of IL-35, and transcription factor Foxp3. In addition, the mRNA expression of RORγt was positively correlated with the percentage of IL-17+γδT cells, and the mRNA level of Foxp3 was positively correlated with the percentage of Foxp3+ γδT cells. The imbalance of γδT17/γδTreg in the asthmatic mice may contribute to the pathogenesis of OVA-induced asthma.