Early immune markers of clinical, virological, and immunological outcomes in patients with COVID-19: a multi-omics study

Case report: A case of Acute Macular Neuroretinopathy secondary to Influenza A virus during Long COVID

Ocular abnormalities have been reported in association with viral infections, including Long COVID, a debilitating illness caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). This report presents a case of a female patient diagnosed with Acute Macular Neuroretinopathy (AMN) following an Influenza A virus infection during Long COVID who experienced severe inflammation symptoms and ocular complications. We hypothesize that the rare occurrence of AMN in this patient could be associated with the immune storm secondary to the viral infection during Long COVID.

Identification of toll-like receptor 5 and acyl-CoA synthetase long chain family member 1 as hub genes are correlated with the severe forms of COVID-19 by Weighted gene co-expression network analysis

Since a 25% mortality rate occurred in critical Coronavirus disease 2019 (COVID-19) patients, investigating the potential drivers remains to be important. Here, the authors applied Weighted Gene Co-expression Network Analysis to identify the potential drivers in the blood samples of multiple COVID-19 expression profiles. The authors found that the darkslateblue module was significantly correlated with critical COVID-19, and Gene Ontology analysis indicated terms associated with the inflammation pathway and apoptotic process. The authors intersected differentially expressed genes, Maximal Clique Centrality calculated hub genes, and COVID-19 related genes in the Genecards dataset, and two genes, toll-like receptor 5 (TLR5) and acyl-CoA synthetase long chain family member 1 (ACSL1), were screened out. The Gene Set Enrichment Analysis further supports their core role in the inflammatory pathway. Furthermore, the cell-type identification by estimating relative subsets of RNA transcript demonstrated that TLR5 and ACSL1 were associated with neutrophil enrichment in critical COVID-19 patients. Collectively, the aurthors identified two hub genes that were strongly correlated with critical COVID-19. These may help clarify the pathogenesis and assist the immunotherapy development.

The two-stage molecular scenery of SARS-CoV-2 infection with implications to disease severity: An in-silico quest

Introduction

The two-stage molecular profile of the progression of SARS-CoV-2 (SCOV2) infection is explored in terms of five key biological/clinical questions: (a) does SCOV2 exhibits a two-stage infection profile? (b) SARS-CoV-1 (SCOV1) vs. SCOV2: do they differ? (c) does and how SCOV2 differs from Influenza/INFL infection? (d) does low viral-load and (e) does COVID-19 early host response relate to the two-stage SCOV2 infection profile? We provide positive answers to the above questions by analyzing the time-series gene-expression profiles of preserved cell-lines infected with SCOV1/2 or, the gene-expression profiles of infected individuals with different viral-loads levels and different host-response phenotypes.

Methods

Our analytical methodology follows an in-silico quest organized around an elaborate multi-step analysis pipeline including: (a) utilization of fifteen gene-expression datasets from NCBI's gene expression omnibus/GEO repository; (b) thorough designation of SCOV1/2 and INFL progression stages and COVID-19 phenotypes; (c) identification of differentially expressed genes (DEGs) and enriched biological processes and pathways that contrast and differentiate between different infection stages and phenotypes; (d) employment of a graph-based clustering process for the induction of coherent groups of networked genes as the representative core molecular fingerprints that characterize the different SCOV2 progression stages and the different COVID-19 phenotypes. In addition, relying on a sensibly selected set of induced fingerprint genes and following a Machine Learning approach, we devised and assessed the performance of different classifier models for the differentiation of acute respiratory illness/ARI caused by SCOV2 or other infections (diagnostic classifiers), as well as for the prediction of COVID-19 disease severity (prognostic classifiers), with quite encouraging results.

Results

The central finding of our experiments demonstrates the down-regulation of type-I interferon genes (IFN-1), interferon induced genes (ISGs) and fundamental innate immune and defense biological processes and molecular pathways during the early SCOV2 infection stages, with the inverse to hold during the later ones. It is highlighted that upregulation of these genes and pathways early after infection may prove beneficial in preventing subsequent uncontrolled hyperinflammatory and potentially lethal events.

Discussion

The basic aim of our study was to utilize in an intuitive, efficient and productive way the most relevant and state-of-the-art bioinformatics methods to reveal the core molecular mechanisms which govern the progression of SCOV2 infection and the different COVID-19 phenotypes.

Cytokine Response Following SARS-CoV-2 Antigen Stimulation in Patients with Predominantly Antibody Deficiencies

Predominantly antibody deficiencies (PADs) are inborn disorders characterized by immune dysregulation and increased susceptibility to infections. Response to vaccination, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), may be impaired in these patients, and studies on responsiveness correlates, including cytokine signatures to antigen stimulation, are sparse. In this study, we aimed to describe the spike-specific cytokine response following whole-blood stimulation with SARS-CoV-2 spike peptides in patients with PAD (n = 16 with common variable immunodeficiency and n = 15 with selective IgA deficiency) and its relationship with the occurrence of coronavirus disease 2019 (COVID-19) during up to 10-month follow-up period. Spike-induced antibody and cytokine production was measured using ELISA (anti-spike IgG, IFN-γ) and xMAP technology (interleukin-1β (IL-1β), IL-4, IL-6, IL-10, IL-15, IL-17A, IL-21, TNF-α, TGF-β1). No difference was found in the production of cytokines between patients with PAD and controls. Anti-spike IgG and cytokine levels did not predict contraction of COVID-19. The only cytokine that distinguished between vaccinated and naturally infected unvaccinated PAD patients was IFN-γ (median 0.64 (IQR = 1.08) in vaccinated vs. 0.10 (IQR = 0.28) in unvaccinated). This study describes the spike-specific cytokine response to SARS-CoV-2 antigens, which is not predictive of contracting COVID-19 during the follow-up.

Proteomic Research of Extracellular Vesicles in Clinical Biofluid

Extracellular vesicles (EVs), the lipid bilayer membranous structures of particles, are produced and released from almost all cells, including eukaryotes and prokaryotes. The versatility of EVs has been investigated in various pathologies, including development, coagulation, inflammation, immune response modulation, and cell-cell communication. Proteomics technologies have revolutionized EV studies by enabling high-throughput analysis of their biomolecules to deliver comprehensive identification and quantification with rich structural information (PTMs, proteoforms). Extensive research has highlighted variations in EV cargo depending on vesicle size, origin, disease, and other features. This fact has sparked activities to use EVs for diagnosis and treatment to ultimately achieve clinical translation with recent endeavors summarized and critically reviewed in this publication. Notably, successful application and translation require a constant improvement of methods for sample preparation and analysis and their standardization, both of which are areas of active research. This review summarizes the characteristics, isolation, and identification approaches for EVs and the recent advances in EVs for clinical biofluid analysis to gain novel knowledge by employing proteomics. In addition, the current and predicted future challenges and technical barriers are also reviewed and discussed.

SARS-CoV-2 viral load and shedding kinetics

SARS-CoV-2 viral load and detection of infectious virus in the respiratory tract are the two key parameters for estimating infectiousness. As shedding of infectious virus is required for onward transmission, understanding shedding characteristics is relevant for public health interventions. Viral shedding is influenced by biological characteristics of the virus, host factors and pre-existing immunity (previous infection or vaccination) of the infected individual. Although the process of human-to-human transmission is multifactorial, viral load substantially contributed to human-to-human transmission, with higher viral load posing a greater risk for onward transmission. Emerging SARS-CoV-2 variants of concern have further complicated the picture of virus shedding. As underlying immunity in the population through previous infection, vaccination or a combination of both has rapidly increased on a global scale after almost 3 years of the pandemic, viral shedding patterns have become more distinct from those of ancestral SARS-CoV-2. Understanding the factors and mechanisms that influence infectious virus shedding and the period during which individuals infected with SARS-CoV-2 are contagious is crucial to guide public health measures and limit transmission. Furthermore, diagnostic tools to demonstrate the presence of infectious virus from routine diagnostic specimens are needed.

Longitudinal home self-collection of capillary blood using homeRNA correlates interferon and innate viral defense pathways with SARS-CoV-2 viral clearance

Blood transcriptional profiling is a powerful tool to evaluate immune responses to infection; however, blood collection via traditional phlebotomy remains a barrier to precise characterization of the immune response in dynamic infections (e.g., respiratory viruses). Here we present an at-home self-collection methodology, homeRNA, to study the host transcriptional response during acute SARS-CoV-2 infections. This method uniquely enables high frequency measurement of the host immune kinetics in non-hospitalized adults during the acute and most dynamic stage of their infection. COVID-19+ and healthy participants self-collected blood every other day for two weeks with daily nasal swabs and symptom surveys to track viral load kinetics and symptom burden, respectively. While healthy uninfected participants showed remarkably stable immune kinetics with no significant dynamic genes, COVID-19+ participants, on the contrary, depicted a robust response with over 418 dynamic genes associated with interferon and innate viral defense pathways. When stratified by vaccination status, we detected distinct response signatures between unvaccinated and breakthrough (vaccinated) infection subgroups; unvaccinated individuals portrayed a response repertoire characterized by higher innate antiviral responses, interferon signaling, and cytotoxic lymphocyte responses while breakthrough infections portrayed lower levels of interferon signaling and enhanced early cell-mediated response. Leveraging cross-platform longitudinal sampling (nasal swabs and blood), we observed that IFI27, a key viral response gene, tracked closely with SARS-CoV-2 viral clearance in individual participants. Taken together, these results demonstrate that at-home sampling can capture key host antiviral responses and facilitate frequent longitudinal sampling to detect transient host immune kinetics during dynamic immune states.