Buffy Coat Transcriptomic Analysis Reveals Alterations in Host Cell Protein Synthesis and Cell Cycle in Severe COVID-19 Patients

High Levels of NfL, GFAP, TAU, and UCH-L1 as Potential Predictor Biomarkers of Severity and Lethality in Acute COVID-19

Few studies showed that neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), total tubulin-associated unit (TAU), and ubiquitin carboxy-terminal hydrolase-L1 (UCH-L1) may be related to neurological manifestations and severity during and after SARS-CoV-2 infection. The objective of this work was to investigate the relationship among nervous system biomarkers (NfL, TAU, GFAP, and UCH-L1), biochemical parameters, and viral loads with heterogeneous outcomes in a cohort of severe COVID-19 patients admitted in Intensive Care Unit (ICU) of a university hospital. For that, 108 subjects were recruited within the first 5 days at ICU. In parallel, 16 mild COVID-19 patients were enrolled. Severe COVID-19 group was divided between "deceased" and "survivor." All subjects were positive for SARS-CoV-2 detection. NfL, total TAU, GFAP, and UCH-L1 quantification in plasma was performed using SIMOA SR-X platform. Of 108 severe patients, 36 (33.33%) presented neurological manifestation and 41 (37.96%) died. All four biomarkers - GFAP, NfL, TAU, and UCH-L1 - were significantly higher among deceased patients in comparison to survivors (p < 0.05). Analyzing biochemical biomarkers, higher Peak Serum Ferritin, D-Dimer Peak, Gamma-glutamyltransferase, and C-Reactive Protein levels were related to death (p < 0.0001). In multivariate analysis, GFAP, NfL, TAU, UCH-L1, and Peak Serum Ferritin levels were correlated to death. Regarding SARS-CoV-2 viral load, no statistical difference was observed for any group. Thus, Ferritin, NFL, GFAP, TAU, and UCH-L1 are early biomarkers of severity and lethality of SARS-COV-2 infection and may be important tools for therapeutic decision-making in the acute phase of disease.

Stimulation of PSTPIP1 to trigger proinflammatory responses in asymptomatic SARS-CoV-2 infections

Background

A hyperinflammatory response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection gravely worsens the clinical progression of coronavirus disease 2019 (COVID-19). Although the undesirable effects of inflammasome activation have been correlated to the severity of COVID-19, the mechanisms of this process in the asymptomatic infection and disease progression have not yet been clearly elucidated.

Methods

We performed strand-specific RNA sequencing in 39 peripheral blood mononuclear cell (PBMC) samples from asymptomatic individuals（n = 10）, symptomatic patients（n = 16） and healthy donors（n = 13）.

Results

Dysregulation of pyrin inflammasomes along with the proline-serine-threonine phosphatase-interacting protein 1 (PSTPIP1) gene was identified in SARS-COV-2 infection. Notably, the PSTPIP1 expression level showed a significant negative correlation with an adjacent long-noncoding RNA (lncRNA) RP11-797A18.6 in the asymptomatic individuals compared with the healthy controls. In addition, a decline in the nuclear factor kappa B subunit 1 (NFKB1) gene expression was observed in asymptomatic infection, followed by a rise in the mild and moderate disease stages, suggesting that altered NFKB1 expression and associated proinflammatory signals may trigger a disease progression.

Conclusions

Overall, our results indicate that PSTPIP1-dependent pyrin inflammasomes-mediated pyroptosis and NF-κB activation might be potential preventive targets for COVID-19 disease development and progression.

Molybdenum exposure induces inflammatory response via the regulatory effects of lncRNA-00072124/miR-308/OSMR crosstalk on JAK/STAT axis in duck kidneys

Molybdenum (Mo) is an essential nutrient in living organisms. Although numerous researchers have noticed the health damage caused by excessive Mo, the underlying mechanism of excessive Mo-induced nephrotoxicity remains poorly understood. A gene crosstalk called competitive endogenous RNAs (ceRNAs) can interpret many regulatory mechanisms molecularly. But there are few researches have tried to explain the damage mechanism of excess Mo to organisms through ceRNAs network. To clarify this, the study explored the changes in lncRNAs and miRNAs expression profiles in the kidney of ducks exposed to excess Mo for 16 weeks. The sequencing results showed that Mo exposure caused differential expression of 144 lncRNAs and 14 miRNAs. The occurrence of inflammation through the JAK/STAT axis was observed and the lncRNA-00072124/miR-308/OSMR axis was verified by a double luciferase reporter assay. Overexpression of miR-308 and RNA interference of OSMR reduced Mo-induced inflammatory factors, while miR-308 knockdown showed the opposite effect. Simultaneously, lncRNA-00072124 affected OSMR function as a ceRNA. Taken together, these results concluded that Mo exposure activated the JAK/STAT axis and induced inflammation mediated by the lncRNA-00072124/miR-308/OSMR crosstalk. The results might provide new views for revealing the toxic effects of excess Mo in duck kidneys.

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.

Clinical Profile and Risk Factors for Severe COVID-19 in Hospitalized Patients from Rio de Janeiro, Brazil: Comparison between the First and Second Pandemic Waves

Since COVID-19 was declared a pandemic, Brazil has become one of the countries most affected by this disease. A year into the pandemic, a second wave of COVID-19 emerged, with a rapid spread of a new SARS-CoV-2 lineage of concern. Several vaccines have been granted emergency-use authorization, leading to a decrease in mortality and severe cases in many countries. However, the emergence of SARS-CoV-2 variants raises the alert for potential new waves of transmission and an increase in pathogenicity. We compared the demographic and clinical data of critically ill patients infected with COVID-19 hospitalized in Rio de Janeiro during the first and second waves between July 2020 and October 2021. In total, 106 participants were included in this study; among them, 88% had at least one comorbidity, and 37% developed severe disease. Disease severity was associated with older age, pre-existing neurological comorbidities, higher viral load, and dyspnea. Laboratory biomarkers related to white blood cells, coagulation, cellular injury, inflammation, renal, and liver injuries were significantly associated with severe COVID-19. During the second wave of the pandemic, the necessity of invasive respiratory support was higher, and more individuals with COVID-19 developed acute hepatitis, suggesting that the progression of the second wave resulted in an increase in severe cases. These results can contribute to understanding the behavior of the COVID-19 pandemic in Brazil and may be helpful in predicting disease severity, which is a pivotal for guiding clinical care, improving patient outcomes, and defining public policies.

Classification of COVID-19 Patients into Clinically Relevant Subsets by a Novel Machine Learning Pipeline Using Transcriptomic Features

The persistent impact of the COVID-19 pandemic and heterogeneity in disease manifestations point to a need for innovative approaches to identify drivers of immune pathology and predict whether infected patients will present with mild/moderate or severe disease. We have developed a novel iterative machine learning pipeline that utilizes gene enrichment profiles from blood transcriptome data to stratify COVID-19 patients based on disease severity and differentiate severe COVID cases from other patients with acute hypoxic respiratory failure. The pattern of gene module enrichment in COVID-19 patients overall reflected broad cellular expansion and metabolic dysfunction, whereas increased neutrophils, activated B cells, T-cell lymphopenia, and proinflammatory cytokine production were specific to severe COVID patients. Using this pipeline, we also identified small blood gene signatures indicative of COVID-19 diagnosis and severity that could be used as biomarker panels in the clinical setting.