High dimensional profiling identifies specific immune types along the recovery trajectories of critically ill COVID19 patients

Immunomodulatory approaches in managing lung inflammation in COVID-19: A double-edge sword

INTRODUCTION

The novel coronavirus infectious disease 2019 (COVID-19) which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has emerged as a gigantic problem. The lung is the major target organ of SARS-CoV-2 and some of its variants like Delta and Omicron variant adapted in such a way that these variants can significantly damage this vital organ of the body. These variants raised a few eyebrows as the outbreaks have been seen in the vaccinated population. Patients develop severe respiratory illnesses which eventually prove fatal unless treated early.

MAIN BODY

Studies have shown that SARS-CoV-2 causes the release of pro-inflammatory cytokines such as interleukin (IL)-6, IL-1β and tumor necrosis factor (TNF)-α which are mediators of lung inflammation, lung damage, fever, and fibrosis. Additionally, various chemokines have been found to play an important role in the disease progression. A plethora of pro-inflammatory cytokines "cytokine storm" has been observed in severe cases of SARS-CoV-2 infection leading to acute respiratory distress syndrome (ARDS) and pneumonia that may prove fatal. To counteract cytokine storm-inducing lung inflammation, several promising immunomodulatory approaches are being investigated in numerous clinical trials. However, the benefits of using these strategies should outweigh the risks involved as the use of certain immunosuppressive approaches might lead the host susceptible to secondary bacterial infections.

CONCLUSION

The present review discusses promising immunomodulatory approaches to manage lung inflammation in COVID-19 cases which may serve as potential therapeutic options in the future and may prove lifesaving.

Single-cell molecular profiling using ex vivo functional readouts fuels precision oncology in glioblastoma

BACKGROUND

Functional profiling of freshly isolated glioblastoma (GBM) cells is being evaluated as a next-generation method for precision oncology. While promising, its success largely depends on the method to evaluate treatment activity which requires sufficient resolution and specificity.

METHODS

Here, we describe the 'precision oncology by single-cell profiling using ex vivo readouts of functionality' (PROSPERO) assay to evaluate the intrinsic susceptibility of high-grade brain tumor cells to respond to therapy. Different from other assays, PROSPERO extends beyond life/death screening by rapidly evaluating acute molecular drug responses at single-cell resolution.

RESULTS

The PROSPERO assay was developed by correlating short-term single-cell molecular signatures using mass cytometry by time-of-flight (CyTOF) to long-term cytotoxicity readouts in representative patient-derived glioblastoma cell cultures (n = 14) that were exposed to radiotherapy and the small-molecule p53/MDM2 inhibitor AMG232. The predictive model was subsequently projected to evaluate drug activity in freshly resected GBM samples from patients (n = 34). Here, PROSPERO revealed an overall limited capacity of tumor cells to respond to therapy, as reflected by the inability to induce key molecular markers upon ex vivo treatment exposure, while retaining proliferative capacity, insights that were validated in patient-derived xenograft (PDX) models. This approach also allowed the investigation of cellular plasticity, which in PDCLs highlighted therapy-induced proneural-to-mesenchymal (PMT) transitions, while in patients' samples this was more heterogeneous.

CONCLUSION

PROSPERO provides a precise way to evaluate therapy efficacy by measuring molecular drug responses using specific biomarker changes in freshly resected brain tumor samples, in addition to providing key functional insights in cellular behavior, which may ultimately complement standard, clinical biomarker evaluations.

Monocytic HLA-DR Expression in Immune Responses of Acute Pancreatitis and COVID-19

Acute pancreatitis is a common gastrointestinal disease with increasing incidence worldwide. COVID-19 is a potentially life-threatening contagious disease spread throughout the world, caused by severe acute respiratory syndrome coronavirus 2. More severe forms of both diseases exhibit commonalities with dysregulated immune responses resulting in amplified inflammation and susceptibility to infection. Human leucocyte antigen (HLA)-DR, expressed on antigen-presenting cells, acts as an indicator of immune function. Research advances have highlighted the predictive values of monocytic HLA-DR (mHLA-DR) expression for disease severity and infectious complications in both acute pancreatitis and COVID-19 patients. While the regulatory mechanism of altered mHLA-DR expression remains unclear, HLA-DR^-/low monocytic myeloid-derived suppressor cells are potent drivers of immunosuppression and poor outcomes in these diseases. Future studies with mHLA-DR-guided enrollment or targeted immunotherapy are warranted in more severe cases of patients with acute pancreatitis and COVID-19.

Machine learning of flow cytometry data reveals the delayed innate immune responses correlate with the severity of COVID-19

Introduction

The COVID-19 pandemic has posed a major burden on healthcare and economic systems across the globe for over 3 years. Even though vaccines are available, the pathogenesis is still unclear. Multiple studies have indicated heterogeneity of immune responses to SARS-CoV-2, and potentially distinct patient immune types that might be related to disease features. However, those conclusions are mainly inferred by comparing the differences of pathological features between moderate and severe patients, some immunological features may be subjectively overlooked.

Methods

In this study, the relevance scores(RS), reflecting which features play a more critical role in the decision-making process, between immunological features and the COVID-19 severity are objectively calculated through neural network, where the input features include the immune cell counts and the activation marker concentrations of particular cell, and these quantified characteristic data are robustly generated by processing flow cytometry data sets containing the peripheral blood information of COVID-19 patients through PhenoGraph algorithm.

Results

Specifically, the RS between immune cell counts and COVID-19 severity with time indicated that the innate immune responses in severe patients are delayed at the early stage, and the continuous decrease of classical monocytes in peripherial blood is significantly associated with the severity of disease. The RS between activation marker concentrations and COVID-19 severity suggested that the down-regulation of IFN-γ in classical monocytes, Treg, CD8 T cells, and the not down-regulation of IL_17a in classical monocytes, Tregs are highly correlated with the occurrence of severe disease. Finally, a concise dynamic model of immune responses in COVID-19 patients was generalized.

Discussion

These results suggest that the delayed innate immune responses in the early stage, and the abnormal expression of IL-17a and IFN-γ in classical monocytes, Tregs, and CD8 T cells are primarily responsible for the severity of COVID-19.

A cross entropy test allows quantitative statistical comparison of t-SNE and UMAP representations

The advent of high-dimensional single-cell data has necessitated the development of dimensionality-reduction tools. t-Distributed stochastic neighbor embedding (t-SNE) and uniform manifold approximation and projection (UMAP) are the two most frequently used approaches, allowing clear visualization of complex single-cell datasets. Despite the need for quantitative comparison, t-SNE and UMAP have largely remained visualization tools due to the lack of robust statistical approaches. Here, we have derived a statistical test for evaluating the difference between dimensionality-reduced datasets using the Kolmogorov-Smirnov test on the distributions of cross entropy of single cells within each dataset. As the approach uses the inter-relationship of single cells for comparison, the resulting statistic is robust and capable of identifying true biological variation. Further, the test provides a valid distance between single-cell datasets, allowing the organization of multiple samples into a dendrogram for quantitative comparison of complex datasets. These results demonstrate the largely untapped potential of dimensionality-reduction tools for biomedical data analysis beyond visualization.

Severe COVID-19 patients display hyper-activated NK cells and NK cell-platelet aggregates

COVID-19 is characterised by a broad spectrum of clinical and pathological features. Natural killer (NK) cells play an important role in innate immune responses to viral infections. Here, we analysed the phenotype and activity of NK cells in the blood of COVID-19 patients using flow cytometry, single-cell RNA-sequencing (scRNA-seq), and a cytotoxic killing assay. In the plasma of patients, we quantified the main cytokines and chemokines. Our cohort comprises COVID-19 patients hospitalised in a low-care ward unit (WARD), patients with severe COVID-19 disease symptoms hospitalised in intensive care units (ICU), and post-COVID-19 patients, who were discharged from hospital six weeks earlier. NK cells from hospitalised COVID-19 patients displayed an activated phenotype with substantial differences between WARD and ICU patients and the timing when samples were taken post-onset of symptoms. While NK cells from COVID-19 patients at an early stage of infection showed increased expression of the cytotoxic molecules perforin and granzyme A and B, NK cells from patients at later stages of COVID-19 presented enhanced levels of IFN-γ and TNF-α which were measured ex vivo in the absence of usual in vitro stimulation. These activated NK cells were phenotyped as CD49a⁺CD69a⁺CD107a⁺ cells, and their emergence in patients correlated to the number of neutrophils, and plasma IL-15, a key cytokine in NK cell activation. Despite lower amounts of cytotoxic molecules in NK cells of patients with severe symptoms, majority of COVID-19 patients displayed a normal cytotoxic killing of Raji tumour target cells. In vitro stimulation of patients blood cells by IL-12+IL-18 revealed a defective IFN-γ production in NK cells of ICU patients only, indicative of an exhausted phenotype. ScRNA-seq revealed, predominantly in patients with severe COVID-19 disease symptoms, the emergence of an NK cell subset with a platelet gene signature that we identified by flow and imaging cytometry as aggregates of NK cells with CD42a⁺CD62P⁺ activated platelets. Post-COVID-19 patients show slow recovery of NK cell frequencies and phenotype. Our study points to substantial changes in NK cell phenotype during COVID-19 disease and forms a basis to explore the contribution of platelet-NK cell aggregates to antiviral immunity against SARS-CoV-2 and disease pathology.

Immunomodulatory therapy for the management of critically ill patients with COVID-19: A narrative review

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the ongoing coronavirus disease 2019 (COVID-19) pandemic. Understanding the physiological and immunological processes underlying the clinical manifestations of COVID-19 is vital for the identification and rational design of effective therapies.

AIM

To describe the interaction of SARS-CoV-2 with the immune system and the subsequent contribution of hyperinflammation and abnormal immune responses to disease progression together with a complete narrative review of the different immunoadjuvant treatments used so far in COVID-19 and their indication in severe and life-threatening subsets.

METHODS

A comprehensive literature search was developed. Authors reviewed the selected manuscripts following the PRISMA recommendations for systematic review and meta-analysis documents and selected the most appropriate. Finally, a recommendation of the use of each treatment was established based on the level of evidence of the articles and documents reviewed. This recommendation was made based on the consensus of all the authors.

RESULTS

A brief rationale on the SARS-CoV-2 pathogenesis, immune response, and inflammation was developed. The usefulness of 10 different families of treatments related to inflammation and immunopathogenesis of COVID-19 was reviewed and discussed. Finally, based on the level of scientific evidence, a recommendation was established for each of them.

CONCLUSION

Although several promising therapies exist, only the use of corticosteroids and tocilizumab (or sarilumab in absence of this) have demonstrated evidence enough to recommend its use in critically ill patients with COVID-19. Endotypes including both, clinical and biological characteristics can constitute specific targets for better select certain therapies based on an individualized approach to treatment.

Alterations of blood monocyte subset distribution and surface phenotype are linked to infection severity in COVID-19 inpatients

Severe coronavirus disease 19 (COVID‐19) manifests with systemic immediate proinflammatory innate immune activation and altered iron turnover. Iron homeostasis, differentiation, and function of myeloid leukocytes are interconnected. Therefore, we characterized the cellularity, surface marker expression, and iron transporter phenotype of neutrophils and monocyte subsets in COVID‐19 patients within 72 h from hospital admission, and analyzed how these parameters relate to infection severity. Between March and November 2020, blood leukocyte samples from hospitalized COVID‐19 patients (n = 48) and healthy individuals (n = 7) were analyzed by flow cytometry enabling comparative analysis of 40 features. Inflammation‐driven neutrophil expansion, depletion of CD16⁺ nonclassical monocytes, and changes in surface expression of neutrophil and monocyte CD64 and CD86 were associated with COVID‐19 severity. By unsupervised self‐organizing map clustering, four patterns of innate myeloid response were identified and linked to varying levels of systemic inflammation, altered cellular iron trafficking and the severity of disease. These alterations of the myeloid leukocyte compartment during acute COVID‐19 may be hallmarks of inefficient viral control and immune hyperactivation and may help at risk prediction and treatment optimization.

Human immune diversity: from evolution to modernity

The extreme diversity of the human immune system, forged and maintained throughout evolutionary history, provides a potent defense against opportunistic pathogens. At the same time, this immune variation is the substrate upon which a plethora of immune-associated diseases develop. Genetic analysis suggests that thousands of individually weak loci together drive up to half of the observed immune variation. Intense selection maintains this genetic diversity, even selecting for the introgressed Neanderthal or Denisovan alleles that have reintroduced variation lost during the out-of-Africa migration. Variations in age, sex, diet, environmental exposure, and microbiome each potentially explain the residual variation, with proof-of-concept studies demonstrating both plausible mechanisms and correlative associations. The confounding interaction of many of these variables currently makes it difficult to assign definitive contributions. Here, we review the current state of play in the field, identify the key unknowns in the causality of immune variation, and identify the multidisciplinary pathways toward an improved understanding.