The Functional Roles of MDSCs in Severe COVID-19 Pathogenesis

Alzheimer's disease following COVID-19: a two player match?

Common pathways may underlie the association between COVID-19 and risk for Alzheimer's disease (AD). We conjecture that severe COVID-19 may contribute to AD onset in predisposed individuals through aberrant MDSCs expression and increased IL-6 expression levels leading to immunosuppression in inflamed brains. Research studies are needed to gain empirical evidence to strengthen the hypothesis of the involvement of MDSCs and IL-6 in the formation of AD following COVID-19 infection and possibly vaccination enabling a more in-depth understanding of the role of immunosuppression in the onset of neurodegenerative diseases at any age. Identifying why those who get severe COVID-19 are more likely to develop AD may offer a novel therapeutic approach to delay or prevent cognitive decline.

Potential hypothesis for the increased risk of Parkinson´s disease following COVID-19

Patients with severe COVID-19 may be more likely to develop PD as a result of shared biological pathways including a great expansion of MDSCs and an imbalance in Th17/Tregs ratio. We think that these shared pathogenic features may mechanistically explain the COVID-19 - PD axis. Thus, we assume that patients who recovered from critical COVID-19 should be selected based upon a potential higher risk of developing PD. Further studies are needed to better define the possible relationship between COVID-19 and neuroinflammation and identify whether some people are more likely to develop PD after contracting COVID-19 than others with special emphasis to ascertain possible vulnerable genetic backgrounds or epigenetic factors acting on brain which may promote PD during SARS COV-2 infection. Finally, we think that regular physical activity should be performed and encouraged in patients with PD.

Bioinformatics and molecular biology tools for diagnosis, prevention, treatment and prognosis of COVID-19

Since December 2019, a new form of Severe Acute Respiratory Syndrome (SARS) has emerged worldwide, caused by SARS coronavirus 2 (SARS-CoV-2). This disease was called COVID-19 and was declared a pandemic by the World Health Organization in March 2020. Symptoms can vary from a common cold to severe pneumonia, hypoxemia, respiratory distress, and death. During this period of world stress, the medical and scientific community were able to acquire information and generate scientific data at unprecedented speed, to better understand the disease and facilitate vaccines and therapeutics development. Notably, bioinformatics tools were instrumental in decoding the viral genome and identifying critical targets for COVID-19 diagnosis and therapeutics. Through the integration of omics data, bioinformatics has also improved our understanding of disease pathogenesis and virus-host interactions, facilitating the development of targeted treatments and vaccines. Furthermore, molecular biology techniques have accelerated the design of sensitive diagnostic tests and the characterization of immune responses, paving the way for precision medicine approaches in treating COVID-19. Our analysis highlights the indispensable contributions of bioinformatics and molecular biology to the global effort against COVID-19. In this review, we aim to revise the COVID-19 features, diagnostic, prevention, treatment options, and how molecular biology, modern bioinformatic tools, and collaborations have helped combat this pandemic. An integrative literature review was performed, searching articles on several sites, including PUBMED and Google Scholar indexed in referenced databases, prioritizing articles from the last 3 years. The lessons learned from this COVID-19 pandemic will place the world in a much better position to respond to future pandemics.

Integrated Bioinformatics Exploration and Preliminary Clinical Verification for the Identification of Crucial Biomarkers in Severe Cases of COVID-19

Background

Coronavirus disease 2019 (COVID-19) is a respiratory infectious illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The objective of this study is to identify reliable and accurate biomarkers for the early stratification of disease severity, a crucial aspect that is currently lacking for the impending phases of the next COVID-19 pandemic.

Methods

In this study, we identified important module and hub genes related to clinical severe COVID-19 using differentially expressed genes (DEGs) screening combing weighted gene co-expression network analysis (WGCNA) in dataset GSE213313. We further screened and confirmed these hub genes in another two new independent datasets (GSE172114 and GSE157103). In order to evaluate these key genes' stability and robustness for diagnosing or predicting the progression of illness, we used RT-PCR validation of selected genes in blood samples obtained from hospitalized COVID-19 patients.

Results

A total of 968 and 52 DEGs were identified between COVID-19 patients and normal people, critical and non-critical patients, respectively. Then, using WGCNA, 10 modules were constructed. Among them, the blue module positively associated with clinic disease severity of COVID-19. From overlapped section between DEGs and blue module, 12 intersected common differential genes were obtained. Subsequently, these hub genes were validated in another two new independent datasets as well and 9 genes that overlapped showed a highly correlation with disease severity. Finally, the mRNA expression levels of these hub genes were tested in blood samples from COVID-19 patients. In severe cases, there was increased expression of MCEMP1, ANXA3, CD177, and SCN9A. In particular, MCEMP1 increased with disease severity, which suggested an unfavorable development and a frustrating prognosis.

Conclusion

Using comprehensive bioinformatical analysis and the validation of clinical samples, we identified four major candidate genes, MCEMP1, ANXA3, CD177, and SCN9A, which are essential for diagnosis or development of COVID-19.