COVID-19, Anti-NMDA Receptor Encephalitis and MicroRNA

Molecular Mimicry between SARS-CoV-2 Proteins and Human Self-Antigens Related with Autoimmune Central Nervous System (CNS) Disorders

SARS-CoV-2 can trigger autoimmune central nervous system (CNS) diseases in genetically susceptible individuals, a mechanism poorly understood. Molecular mimicry (MM) has been identified in other viral diseases as potential triggers of autoimmune CNS events. This study investigated if MM is the process through which SARS-CoV-2 induces the breakdown of immune tolerance. The frequency of autoimmune CNS disorders was evaluated in a prospective cohort with patients admitted to the COVID-19 Intense Care Unity (ICU) in Rio de Janeiro. Then, an in silico analysis was performed to identify the conserved regions that share a high identity between SARS-CoV-2 antigens and human proteins. The sequences with significant identity and antigenic properties were then assessed for their binding capacity to HLA subtypes. Of the 112 patients included, 3 were classified as having an autoimmune disorder. A total of eleven combinations had significant linear and three-dimensional overlap. NMDAR1, MOG, and MPO were the self-antigens with more significant combinations, followed by GAD65. All sequences presented at least one epitope with strong or intermediate binding capacity to the HLA subtypes selected. This study underscores the possibility that CNS autoimmune attacks observed in COVID-19 patients, including those in our population, could be driven by MM in genetically predisposed individuals.

The Potential of Collagen Treatment for Comorbid Diseases

Collagen, the most abundant protein in our bodies, plays a crucial role in maintaining the structural integrity of various tissues and organs. Beyond its involvement in skin elasticity and joint health, emerging research suggests that collagen may significantly impact the treatment of complex diseases, particularly those associated with tissue damage and inflammation. The versatile functions of collagen, including skin regeneration, improving joint health, and increasing bone strength, make it potentially useful in treating different diseases. To the best of my knowledge, the strategy of using collagen to treat comorbid diseases has not been widely studied. This paper aims to explore the potential of collagen in treating comorbid diseases, including rheumatoid arthritis, osteoarthritis, osteoporosis, psoriatic arthritis, sarcopenia, gastroesophageal reflux, periodontitis, skin aging, and diabetes mellitus. Collagen-based therapies have shown promise in managing comorbidities due to their versatile properties. The multifaceted nature of collagen positions it as a promising candidate for treating complex diseases and addressing comorbid conditions. Its roles in wound healing, musculoskeletal disorders, cardiovascular health, and gastrointestinal conditions highlight the diverse therapeutic applications of collagen in the context of comorbidity management.

Anti-N-methyl D-aspartate Receptor Encephalitis Following ChAdOx1 nCoV-19 Vaccination: A Case Report

As of December 2020, millions of people have been immunized using vaccines against SARS-CoV-2. A wide range of neurological adverse effects of SARS-CoV-2 vaccines have been reported so far. Here, we report a 23-year-old male who experienced psychiatric symptoms, loss of consciousness, language disintegration, and incontinency that happened 10 days after the first dosage of the COVID-19 AstraZeneca vaccine. Anti-NMDAR Encephalitis was diagnosed based on the results of the autoimmune panel. The patient responded to intravenous dexamethasone very well and experienced no other complications in 6 months of follow-up. Scientific reports of neurological side effects such as anti-NMDAR encephalitis after vaccination are necessary to optimize the safety and effectiveness of SARS-CoV-2 vaccines.

Differentially-regulated miRNAs in COVID-19: A systematic review

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is responsible for coronavirus disease of 2019 (COVID-19) that infected more than 760 million people worldwide with over 6.8 million deaths to date. COVID-19 is one of the most challenging diseases of our times due to the nature of its spread, its effect on multiple organs, and an inability to predict disease prognosis, ranging from being completely asymptomatic to death. Upon infection, SARS-CoV-2 alters the host immune response by changing host-transcriptional machinery. MicroRNAs (miRNAs) are regarded as post-transcriptional regulators of gene expression that can be perturbed by invading viruses. Several in vitro and in vivo studies have reported such dysregulation of host miRNA expression upon SARS-CoV-2 infection. Some of this could occur as an anti-viral response of the host to the viral infection. Viruses themselves can counteract that response by mounting their own pro-viral response that facilitates virus infection, an aspect which may cause pathogenesis. Thus, miRNAs could serve as possible disease biomarkers in infected people. In the current review, we have summarised and analysed the existing data about miRNA dysregulation in patients infected with SARS-CoV-2 to determine their concordance between studies, and identified those that could serve as potential biomarkers during infection, disease progression, and death, even in people with other co-morbidities. Having such biomarkers can be vital in not only predicting COVID-19 prognosis, but also the development of novel miRNA-based anti-virals and therapeutics which can become invaluable in case of the emergence of new viral variants with pandemic potential in the future.

A decrease in the incidence of encephalitis in South Korea during the COVID-19 pandemic: A nationwide study between 2010 and 2021

Limited data are available on the impact of the coronavirus disease (COVID-19) pandemic on encephalitis. Therefore, we evaluated trends in encephalitis in South Korea between 2010 and 2021 using data from the National Health Insurance Service. During the pandemic (February 2020 to 2021), the monthly incidence of encephalitis declined by 0.027 per 100 000 population (95% confidence interval [CI]: -0.055 to 0.001, p = 0.062) compared to that before the pandemic. In subgroup analysis, the estimated coefficient for level change during the pandemic in the 0-4 and 5-9 years age groups were -2.050 (95% CI: -2.972 to -1.128, p < 0.001) and -0.813 (95% CI: -1.399 to -0.227, p = 0.008), respectively. The annual incidence of encephalitis during the pandemic period significantly decreased in the 0-4 and 5-9 years age groups (incidence rate ratio: 0.34 [p = 0.007] and 0.28 [p = 0.024], respectively). The intensive care unit admission rate (39.1% vs. 58.9%, p  < 0.001) and cases of death (8.9% vs. 11.1%, p < 0.001) decreased significantly during the pandemic compared to the prepandemic. During the pandemic, the incidence of encephalitis decreased markedly in South Korea, particularly in children aged ≤9 years. In addition, there were changes in the clinical outcome of encephalitis during the COVID-19 pandemic.

The Human Pre-miRNA Distance Distribution for Exploring Disease Association

MicroRNAs (miRNAs), playing an important role in cell differentiation, development, gene regulation, and apoptosis, have attracted much attention in recent years. miRNAs were shown to be involved in the mechanisms of various diseases, and certainly, they can be employed as useful disease biomarkers. The phylogenetic tree analysis of miRNA biomarkers is a useful tool to investigate the association between various diseases as well as the association between viruses and disease. In addition to the phylogenetic tree analysis, a more advanced study is to use the miRNA distance distribution to evaluate the similarity of the miRNA biomarkers. The mature miRNA distance distribution based on mature miRNA sequences has been derived. The averages of the pairwise distances of miRNA biomarkers for several associated diseases were shown to be smaller than the overall mean of all miRNAs, which indicates the high similarity of miRNA biomarkers for associated diseases. In addition to the mature miRNA, the precursor miRNA (pre-miRNA) may be more useful to explore the similarity of miRNAs because the mature miRNA duplex is released from the pre-miRNA. Therefore, in this study, the distance distributions based on human pre-miRNA stem-loop sequences were derived. The 1917 human miRNA stem-loop sequences in the miRBase dataset were used to derive the pre-miRNA distance distribution, and this is the first study to provide the distance distribution based on the human pre-miRNAs. The similarity of miRNA biomarkers for several associated diseases or vaccines was examined using the derived distribution, and the results show that the similarity of pre-miRNA biomarkers may be a feasible way to help explore the disease association.

The distance distribution of human microRNAs in MirGeneDB database

MicroRNAs (miRNAs) are small single-stranded non-coding RNAs around 22 nucleotide lengths found in organisms, playing an important role in cell differentiation, development, gene regulation, and apoptosis. The distance of disease miRNA biomarkers has been used to explore the association between various diseases as well as the association between virus and disease in the literature. To date, there have been no studies on deriving the distribution of the pairwise distance of human miRNAs. As the pairwise distance of miRNA biomarkers might be a useful tool in studying the disease association, in this paper, the distance distributions of human miRNAs were derived such that they could be used to measure the closeness between miRNAs. Two distance models were used to calculate the pairwise distances of 567 Homo sapiens miRNA genes accessed from the MirGeneDB database. These miRNA pairwise distances were fitted by the normal distribution, gamma distribution, empirical cumulative distribution, and the kernel density estimation method. This is the first study to provide the distance distribution of human miRNAs. The similarity of miRNA biomarkers for several diseases was examined using the derived distributions.