The use of bioinformatics methods to identify the effects of SARS-CoV-2 and influenza viruses on the regulation of gene expression in patients

Background SARS-CoV-2 infection is a respiratory infectious disease similar to influenza virus infection. Numerous studies have reported similarities and differences in the clinical manifestations, laboratory tests, and mortality between these two infections. However, the genetic effects of coronavirus and influenza viruses on the host that lead to these characteristics have rarely been reported. Methods COVID-19 (GSE157103) and influenza (GSE111368, GSE101702) datasets were downloaded from the Gene Expression Ominbus (GEO) database. Differential gene, gene set enrichment, protein-protein interaction (PPI) network, gene regulatory network, and immune cell infiltration analyses were performed to identify the critical impact of COVID-19 and influenza viruses on the regulation of host gene expression. Results The number of differentially expressed genes in the COVID-19 patients was significantly higher than in the influenza patients. 22 common differentially expressed genes (DEGs) were identified between the COVID-19 and influenza datasets. The effects of the viruses on the regulation of host gene expression were determined using gene set enrichment and PPI network analyses. Five HUB genes were finally identified: IFI27, OASL, RSAD2, IFI6, and IFI44L. Conclusion We identified five HUB genes between COVID-19 and influenza virus infection, which might be helpful in the diagnosis and treatment of COVID-19 and influenza. This knowledge may also guide future mechanistic studies that aim to identify pathogen-specific interventions.

The use of bioinformatics methods to identify the effects of SARS-CoV-2 and influenza viruses on the regulation of gene expression in patients.

Background: SARS-CoV-2 infection is a respiratory infectious disease similar to influenza virus infection. Numerous studies have reported similarities and differences in the clinical manifestations, laboratory tests, and mortality between these two infections. However, the genetic effects of coronavirus and influenza viruses on the host that lead to these characteristics have rarely been reported. Methods: COVID-19 (GSE157103) and influenza (GSE111368, GSE101702) datasets were downloaded from the Gene Expression Ominbus (GEO) database. Differential gene, gene set enrichment, protein-protein interaction (PPI) network, gene regulatory network, and immune cell infiltration analyses were performed to identify the critical impact of COVID-19 and influenza viruses on the regulation of host gene expression. Results: The number of differentially expressed genes in the COVID-19 patients was significantly higher than in the influenza patients. 22 common differentially expressed genes (DEGs) were identified between the COVID-19 and influenza datasets. The effects of the viruses on the regulation of host gene expression were determined using gene set enrichment and PPI network analyses. Five HUB genes were finally identified: IFI27, OASL, RSAD2, IFI6, and IFI44L. Conclusion: We identified five HUB genes between COVID-19 and influenza virus infection, which might be helpful in the diagnosis and treatment of COVID-19 and influenza. This knowledge may also guide future mechanistic studies that aim to identify pathogen-specific interventions.

Ultrafast PCR Detection of COVID-19 by Using a Microfluidic Chip-Based System.

With the evolution of the pandemic caused by the Coronavirus disease of 2019 (COVID-19), reverse transcriptase-polymerase chain reactions (RT-PCR) have invariably been a golden standard in clinical diagnosis. Nevertheless, the traditional polymerase chain reaction (PCR) is not feasible for field application due to its drawbacks, such as time-consuming and laboratory-based dependence. To overcome these challenges, a microchip-based ultrafast PCR system called SWM-02 was proposed to make PCR assay in a rapid, portable, and low-cost strategy. This novel platform can perform 6-sample detection per run using multiple fluorescent channels and complete an ultrafast COVID-19 RT-PCR test within 40 min. Here, we evaluated the performance of the microdevice using the gradient-diluted COVID-19 reference samples and commercial PCR kit and determined its limit-of-detection (LoD) as 500 copies/mL, whose variation coefficients for the nucleocapsid (N) gene and open reading frame 1 ab region (ORF1ab) gene are 1.427% and 0.7872%, respectively. The system also revealed an excellent linear correlation between cycle threshold (Ct) values and dilution factors (R2 > 0.99). Additionally, we successfully detected the target RNAs and internal gene in the clinical samples by fast PCR, which shows strong consistency with conventional PCR protocol. Hence, with compact dimension, user-friendly design, and fast processing time, SWM-02 has the capability of offering timely and sensitive on-site molecular diagnosis for prevention and control of pathogen transmission.

The mutation features and geographical distributions of the surface glycoprotein (S gene) in SARS-CoV-2 strains: A comparative analysis of the early and current strains.

The surface glycoprotein (S protein) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was used to develop coronavirus disease 2019 (COVID-19) vaccines. However, SARS-CoV-2, especially the S protein, has undergone rapid evolution and mutation, which has remained to be determined. Here, we analyzed and compared the early (12 237) and the current (more than 10 million) SARS-CoV-2 strains to identify the mutation features and geographical distribution of the S gene and S protein. Results showed that in the early strains, most of the loci were with relative low mutation frequency except S: 23403 (4486 strains), while in the current strains, there was a surge in the mutation strains and frequency, with S: 23403 constantly being the highest one, but tremendously increased to approximately 1050 times. Furthermore, D614 (S: 23403) was one of the most highly frequent mutations in the S protein of Omicron as of March 2022, and most of the mutant strains were still from the United States, and the United Kingdom. Further analysis demonstrated that in the receptor-binding domain, most of the loci with low mutation frequency in the early strains, while S: 22995 was nowadays the most prevalent loci with 3 122 491 strains in the current strains. Overall, we compare the mutation features of the S region in SARS-CoV-2 strains between the early and the current stains, providing insight into further studies in concert with emerging SARS-CoV-2 variants for COVID-19 vaccines.

Corticosteroids Utilization in the Management of Critically Ill Coronavirus Disease-2019 Pneumonia

Background: There are controversies regarding corticosteroids using in coronavirus disease-2019 (COVID-19) pneumonia in the current pandemic. Objectives: This study investigates the efficacy and safety profiles of corticosteroids therapy in COVID-19 patients. Methods: Retrospective, multicenter study case series of consecutive patients with confirmed COVID-19 infection at the whole hospital from January 1 to March 1, 2020, were enrolled. Demographic, clinical, radiological, laboratory, and treatment data were collected and analyzed. The effect of corticosteroids therapy on death and organ-failure complications of pneumonia were analyzed by logistic regression. Results: A total of 470 COVID-19 patients at the whole hospital were enrolled. According to the time of corticosteroids initiation and severity of illness, there were 159 patients stratified into critical ill group and 64% (102 of 159) patients received corticosteroids treatments. Ninety-four percent (166 of 176) of corticosteroids were methylprednisolone. The median cumulative corticosteroids dosage was 300 mg equivalent of methylprednisolone over a median duration of 6 days. Multivariate regression analysis showed that corticosteroids use did not affect the mortality. However, corticosteroids therapy at moderate cumulative doses (total exposure 480 mg to 1200 mg) was associated with deceased occurrence of organ-failure complications in critically ill COVID-19. Conclusions: Corticosteroids have no effect to mortality in COVID-19 patients. The moderate cumulative doses of corticosteroids might decrease organ-failure complications in critically ill COVID-19. Further large-scale randomized controlled trials are warranted to confirm our findings, until then use of corticosteroids should be used with caution COVID-19 patients.

Differential Effects of Angiotensin-Converting Enzyme Inhibitors and Angiotensin II Receptor Blockers on COVID-19

Background: The effect of angiotensin-converting enzyme inhibitors/angiotensin receptor blockers (ACEIs/ARBs) on the coronavirus disease 2019 (COVID-19) remains controversial from clinic evidence. Objectives: The objectives of this study were to report the major characteristics and clinical outcomes of COVID-19 patients treated with ACEIs and ARBs and compare the different effects of the two drugs for outcomes of COVID-19 patients. Methods: This is a retrospective, two-center case series of 198 consecutive COVID-19 patients with a history of hypertension. Results: Among 198 patients, 58 (29.3%) and 16 (8.1%) were on ARB and ACEI, respectively. Patients who were on ARB or ACEI/ARB had a significantly lower rate of severe illness and acute respiratory distress syndrome (ARDS) when compared with patients treated with ACEI alone or not receiving RAAS blocker (P < 0.05). The Kaplan–Meier survival curve showed that patients with ARB in their antihypertensive regimen had a trend toward a higher survival rate when compared with individuals without ARB (adjusted hazard ratio, 0.27;95% confidence interval [CI], 0.07–1.02;P = 0.054). The occurrence rates of severe illness, ARDS, and death were similar in the two groups regardless of receiving ACEI. The Cox regression analyses showed a better survival in the ARB group than the ACEI group (adjusted hazard ratio, 0.03;95% CI, 0.00–0.58;P = 0.02). Conclusions: Our data may provide that some evidence of using ARB, but not ACEI, was associated with a reduced rate of severe illness and ARDS, indicating their potential protective impact in COVID-19. Further large sample sizes and multiethnic populations are warranted to confirm our findings.