scholarly journals Mapping Systemic Inflammation and Antibody Responses in Multisystem Inflammatory Syndrome in Children (MIS-C)

2020 ◽  
Author(s):  
Conor Gruber ◽  
Roosheel Patel ◽  
Rebecca Trachman ◽  
Lauren Lepow ◽  
Fatima Amanat ◽  
...  
Keyword(s):  
Immune Cell ◽  
Severe Disease ◽  
Immune Dysregulation ◽  
Antibody Responses ◽  
High Dimensional ◽  
Mass Cytometry ◽  
Initial Wave ◽  
Inflammatory Syndrome ◽  
Classical Monocytes ◽  
Antigen Reactivity

Initially, the global outbreak of COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spared children from severe disease. However, after the initial wave of infections, clusters of a novel hyperinflammatory disease have been reported in regions with ongoing SARS-CoV-2 epidemics. While the characteristic clinical features are becoming clear, the pathophysiology remains unknown. Herein, we report on the immune profiles of eight Multisystem Inflammatory Syndrome in Children (MIS-C) cases. We document that all MIS-C patients had evidence of prior SARS-CoV-2 exposure, mounting an antibody response with normal isotype-switching and neutralization capability. We further profiled the secreted immune response by high-dimensional cytokine assays, which identified elevated signatures of inflammation (IL-18 and IL-6), lymphocytic and myeloid chemotaxis and activation (CCL3, CCL4, and CDCP1) and mucosal immune dysregulation (IL-17A, CCL20, CCL28). Mass cytometry immunophenotyping of peripheral blood revealed reductions of mDC1 and non-classical monocytes, as well as both NK- and T- lymphocytes, suggesting extravasation to affected tissues. Markers of activated myeloid function were also evident, including upregulation of ICAM1 and FcR1 in neutrophil and non-classical monocytes, well-documented markers in autoinflammation and autoimmunity that indicate enhanced antigen presentation and Fc-mediated responses. Finally, to assess the role for autoimmunity secondary to infection, we profiled the auto-antigen reactivity of MIS-C plasma, which revealed both known disease-associated autoantibodies (anti-La) and novel candidates that recognize endothelial, gastrointestinal and immune-cell antigens. All patients were treated with anti- IL6R antibody or IVIG, which led to rapid disease resolution tracking with normalization of inflammatory markers.

OP27 High-dimensional mass cytometry reveals the immune cell landscape in inflammatory bowel disease

2019 ◽  
Vol 13 (Supplement_1) ◽  
pp. S020-S020
Author(s):  
V van Unen ◽  
N Li ◽  
T Abdelaal ◽  
Y Kooy-Winkelaar ◽  
L Ouboter ◽  
...  
Keyword(s):  
Inflammatory Bowel Disease ◽  
Bowel Disease ◽  
Immune Cell ◽  
High Dimensional ◽  
Mass Cytometry ◽  
Inflammatory Bowel

scholarly journals High dimensional immunotyping of the obese tumor microenvironment reveals model specific adaptation

2020 ◽  
Author(s):  
Cara E Wogsland ◽  
Hilde E Lien ◽  
Line Pedersen ◽  
Pahul Hanjra ◽  
Sturla M Grondal ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Immune Cell ◽  
Cell Types ◽  
High Dimensional ◽  
Low Grade ◽  
Cancer Model ◽  
Mass Cytometry ◽  
Batch Correction ◽  
Breast Cancer Model ◽  
Cancer Types

AbstractObesity is a disease characterized by chronic low-grade systemic inflammation and has been causally linked to the development of 13 cancer types. Several studies have been undertaken to determine if tumors evolving in obese environments adapt differential interactions with immune cells and if this can be connected to disease outcome. Most of these studies have been limited to single cell lines and tumor models and analysis of limited immune cell populations. Given the multicellular complexity of the immune system and its dysregulation in obesity, we applied high-dimensional suspension mass cytometry to investigate how obesity affects tumor immunity. We used a 36-marker immune-focused mass cytometry panel to interrogate the immune landscape of orthotopic syngeneic mouse models of pancreatic and breast cancer. Unanchored batch correction was implemented to enable simultaneous analysis of tumor cohorts to uncover the immunotypes of each cancer model and reveal remarkably model-specific immune regulation. In the E0771 breast cancer model, we demonstrate an important link to obesity with an increase in two T cell suppressive cell types and a decrease in CD8 T-cells.

scholarly journals High dimensional immunotyping of tumors grown in obese and non-obese mice

2021 ◽  
pp. dmm.048977
Author(s):  
Cara E. Wogsland ◽  
Hilde E. Lien ◽  
Line Pedersen ◽  
Pahul Hanjra ◽  
Sturla M. Grondal ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Immune Cell ◽  
Cell Types ◽  
High Dimensional ◽  
Low Grade ◽  
Cancer Model ◽  
Mass Cytometry ◽  
Batch Correction ◽  
Breast Cancer Model ◽  
Cancer Types

Obesity is a disease characterized by chronic low-grade systemic inflammation and has been causally linked to the development of 13 cancer types. Several studies have been undertaken to determine if tumors evolving in obese environments adapt differential interactions with immune cells and if this can be connected to disease outcome. Most of these studies have been limited to single cell lines and tumor models and analysis of limited immune cell populations. Given the multicellular complexity of the immune system and its dysregulation in obesity, we applied high-dimensional suspension mass cytometry to investigate how obesity affects tumor immunity. We used a 36-marker immune-focused mass cytometry panel to interrogate the immune landscape of orthotopic syngeneic mouse models of pancreatic and breast cancer. Unanchored batch correction was implemented to enable simultaneous analysis of tumor cohorts to uncover the immunotypes of each cancer model and reveal remarkably model-specific immune regulation. In the E0771 breast cancer model, we demonstrate an important link to obesity with an increase in two T cell suppressive cell types and a decrease in CD8 T-cells.

scholarly journals COVID-19 genetic risk variants are associated with expression of multiple genes in diverse immune cell types

2020 ◽  
Author(s):  
Benjamin J. Schmiedel ◽  
Vivek Chandra ◽  
Job Rocha ◽  
Cristian Gonzalez-Colin ◽  
Sourya Bhattacharyya ◽  
...  
Keyword(s):  
Genetic Risk ◽  
Immune Cell ◽  
Severe Disease ◽  
Regulatory Region ◽  
Gene Promoter ◽  
Cell Types ◽  
Risk Variants ◽  
Wide Range ◽  
Classical Monocytes ◽  
Genetic Risk Variants

ABSTRACTCommon genetic polymorphisms associated with severity of COVID-19 illness can be utilized for discovering molecular pathways and cell types driving disease pathogenesis. Here, we assessed the effects of 679 COVID-19-risk variants on gene expression in a wide-range of immune cell types. Severe COVID-19-risk variants were significantly associated with the expression of 11 protein-coding genes, and overlapped with either target gene promoter or cis-regulatory regions that interact with target promoters in the cell types where their effects are most prominent. For example, we identified that the association between variants in the 3p21.31 risk locus and the expression of CCR2 in classical monocytes is likely mediated through an active cis-regulatory region that interacted with CCR2 promoter specifically in monocytes. The expression of several other genes showed prominent genotype-dependent effects in non-classical monocytes, NK cells, B cells, or specific T cell subtypes, highlighting the potential of COVID-19 genetic risk variants to impact the function of diverse immune cell types and influence severe disease manifestations.

scholarly journals Mapping the recovery of critically ill COVID19 patients by high-dimensional profiling identifies longitudinal blood immunotypes

2020 ◽  
Author(s):  
Penttilä PA ◽  
Van Gassen S ◽  
Panovska D ◽  
Vanderbeke L ◽  
Van Herck Y ◽  
...  
Keyword(s):  
Critically Ill ◽  
Immune Cell ◽  
Significant Proportion ◽  
Acute Phase Reactant ◽  
High Dimensional ◽  
Economic Systems ◽  
Hla Dr ◽  
Longitudinal Sampling ◽  
Classical Monocytes ◽  
Sampling Times

Abstract The COVID-19 pandemic poses a major burden on health-care and economic systems across the globe. Even though a majority of the population only develops minor symptoms upon SARS-CoV2 infection, a significant proportion are hospitalized at intensive care units (ICU) requiring critical care. While insights into the early stages of the disease are gradually expanding, the dynamic immunological processes occurring in critically ill patients throughout their recovery at ICU are far less understood. Here, we have analysed longitudinally collected, whole blood samples of 40 surviving COVID-19 patients during their recovery at ICU using high-dimensional cytometry by time-of-flight (CyTOF) and cytokine multiplexing. Based on the neutrophil to lymphocyte ratio (NLR), we defined 4 sequential immunotypes during recovery that correlated to various clinical parameters, including the level of respiratory support at concomitant sampling times. We also identified classical monocytes as the first immune cell type to recover by restoring HLA-DR-positivity and by reducing the immunosuppressive CD163+ monocyte population, followed by the recovery of CD8+ and CD4+ T cell, and mDC populations. The identified immunotypes also correlated to aberrant cytokine and acute-phase reactant levels. Finally, integrative analysis of cytokines and immune cell profiles showed a shift from an initially dysregulated immune response to a more coordinated immunogenic interplay, highlighting the importance of longitudinal sampling to understand the pathophysiology underlying recovery from severe COVID-19.

targetSCAPE and ultraSCAPE: Simultaneous identification and deep profiling of human antigen-specific T cells and other immune cell subsets by mass cytometry.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e15204-e15204
Author(s):  
Brian Abel ◽  
Faris Kairi ◽  
Alessandra Nardin ◽  
Evan Newell ◽  
Michael Fehlings
Keyword(s):  
T Cells ◽  
T Cell ◽  
Immune Cell ◽  
T Cell Subsets ◽  
Single Sample ◽  
High Dimensional ◽  
Cell Populations ◽  
Mass Cytometry ◽  
Immune Cell Subsets

e15204 Background: During clinical trial immune monitoring, especially in the field of immunotherapy, it is critical to collect in-depth phenotypic information from multiple immune cell populations in order to assess the biological activity of the immunotherapy, to identify biomarkers of response or disease progression, and/or to identify new drug targets. However, patient samples such as peripheral blood mononuclear cells or tissues, are often scarce and current methods face limitations in either achieving a sufficient depth of analysis and/or cell throughput. Methods: In order to identify therapy-relevant antigens and to facilitate a concurrent in-depth characterization of T cells directed towards these targets, immunoSCAPE leverages the high-dimensional immune profiling capabilities of mass cytometry and a unique methodology allowing the identification and characterization of rare antigen-specific T-cell subsets (targetSCAPE). By implementing a new cutting-edge technology that combines flow and mass cytometry in parallel with a combinatorial live cell barcoding strategy, we further increased the high-dimensional phenotyping capacities to over 100 different marker molecules on up to four different immune cell subsets simultaneously within the same sample. Results: We isolated 4 different immune cell populations from a single sample and combined 3 different phenotypic panels consisting of 35 makers each together with a combinatorial tetramer multiplex and phenotyping panel for deep profiling of myeloid cells, NK cells, B cells and T cells. We demonstrate the potential of this novel immuno-phenotyping method, by tracking virus-specific T cells while simultaneously characterizing 4 immune cell subsets with over 100 distinct phenotypic markers from a single sample, which is currently impossible employing modern flow cytometers or classical mass cytometry methods. Conclusions: With its ability to provide an unprecedented picture of the immune status within a single sample, including T cell specificity information and in-depth profiling of relevant immune cell subsets, ultraSCAPE in combination with targetSCAPE can provide detailed insights on the effects of immunotherapy on the immune cell population. Information learned from in-depth immune phenotyping of several immune cell subsets such as T, B, NK and myeloid cell subsets can be leveraged for the development of novel diagnostics, biomarker discovery and monitoring therapeutic strategies in immunotherapy clinical trials.

scholarly journals Immunoprofiling of early, untreated rheumatoid arthritis using mass cytometry reveals an activated basophil subset inversely linked to ACPA status

2021 ◽  
Vol 23 (1) ◽  
Author(s):  
H. Koppejan ◽  
M. Hameetman ◽  
G. Beyrend ◽  
V. van Unen ◽  
J. C. Kwekkeboom ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Immune Cell ◽  
Nk Cell ◽  
Severe Disease ◽  
Cell Subset ◽  
Mass Cytometry ◽  
Autoantibody Production ◽  
Cell Composition ◽  
The Difference ◽  
Acpa Status

Abstract Background Autoantibody production is a hallmark of rheumatoid arthritis (RA). Anti-citrullinated protein antibodies (ACPA) are highly disease-specific, and their presence is associated with more severe disease and poor prognosis compared to ACPA-negative patients. However, the immune cell composition associated with antibody-positive/negative disease is incompletely defined. Mass cytometry (MC) is a high-dimensional technique offering new possibilities in the determination of the immune cell composition in rheumatic diseases. Here, we set up a broad phenotyping panel to study the immune cell profile of early untreated RA to investigate if specific immune cell subsets are associated with ACPA+ versus ACPA− RA. Methods Freshly obtained PBMCs of early, untreated RA patients (8 ACPA+ and 7 ACPA−) were analysed using a 36-marker MC panel, including markers related to various immune lineages. Data were processed using Cytosplore for dimensional reduction (HSNE) and clustering. Groups were compared using Cytofast. A second validation cohort of cryopreserved PBMCs obtained from early RA patients (27 ACPA+ and 20 ACPA−) was used to confirm MC data by flow cytometry (FC). FC data were processed and analysed using both an unsupervised analysis pipeline and through manual gating. Results MC indicated no differences when comparing major immune lineages (i.e. monocytes, T and B cells), but highlighted two innate subsets: CD62L+ basophils (p = 0.33) and a subset of CD16− NK cells (p = 0.063). Although the NK cell subset did not replicate by FC, FC replication confirmed the difference in CD62L+ basophil frequency when comparing ACPA+ to ACPA− patients (mean 0.32% vs. 0.13%; p = 0.01). Conclusions Although no differences in major lineages were found between early ACPA+ and ACPA− RA, this study identified the reduced presence of activated basophils in ACPA-negative disease as compared to ACPA-positive disease and thereby provides the first evidence for a connection between activated basophils and ACPA status.

scholarly journals Two new immature and dysfunctional neutrophil cell subsets define a predictive signature of sepsis useable in clinical practice

2020 ◽  
Author(s):  
Aïda Meghraoui-Kheddar ◽  
Benjamin G. Chousterman ◽  
Noëlline Guillou ◽  
Sierra M. Barone ◽  
Samuel Granjeaud ◽  
...  
Keyword(s):  
Immune Cell ◽  
Clinical Care ◽  
Cell Subset ◽  
Clinical Severity ◽  
Mass Cytometry ◽  
Sepsis Diagnosis ◽  
Inflammatory Conditions ◽  
Inflammatory Syndrome ◽  
First Time ◽  
Neutrophil Cell

AbstractSepsis is the leading cause of death in adult intensive care units. At present, sepsis diagnosis relies on non-specific clinical features. It could transform clinical care to have objective immune cell biomarkers that could predict sepsis diagnosis and guide treatment. For decades, neutrophil phenotypes have been studied in sepsis, but a diagnostic cell subset has yet to be identified. Here, high dimensional mass cytometry was used to reveal for the first time a specific neutrophil signature of sepsis severity that does not overlap with other inflammatory biomarkers, and that distinguishes patients with sepsis from those with non-infectious inflammatory syndrome. Unsupervised analysis of 42-dimesional mass cytometry data characterized previously unappreciated heterogeneity within the CD64+ immature neutrophils and revealed two new subsets distinguished by CD123 and PD-L1 expression. These immature neutrophils exhibited diminished activation and phagocytosis functions. The proportion of CD123-expressing neutrophils also correlated with clinical severity. Critically, this study showed that these two new neutrophil subsets were specific to sepsis and detectable by routine flow cytometry using seven markers. The demonstration here that a simple blood test distinguishes sepsis from other inflammatory conditions represents a key biological milestone that can be immediately translated into improvements in patient care.One Sentence SummaryCD123+ and/or PD-L1+ immature and dysfunctional neutrophil subsets identified by mass cytometry, define an early human blood signature of sepsis

scholarly journals A distinct innate immune signature marks progression from mild to severe COVID-19

2020 ◽  
Author(s):  
Stéphane Chevrier ◽  
Yves Zurbuchen ◽  
Carlo Cervia ◽  
Sarah Adamo ◽  
Miro E. Raeber ◽  
...  
Keyword(s):  
Inflammatory Response ◽  
Symptom Onset ◽  
Immune Cell ◽  
Severe Disease ◽  
Innate Immune ◽  
Innate Immune Responses ◽  
Serum Proteomics ◽  
Early Inflammatory Response ◽  
Temporal Trajectory ◽  
Classical Monocytes

AbstractCoronavirus disease 2019 (COVID-19) manifests with a range of severities, but immune signatures of mild and severe disease are still not fully understood. Excessive inflammation has been postulated to be a major factor in the pathogenesis of severe COVID-19 and innate immune mechanisms are likely to be central in the inflammatory response. We used 40-plex mass cytometry and targeted serum proteomics to profile innate immune cell populations from peripheral blood of patients with mild or severe COVID-19 and healthy controls. Sampling at different stages of COVID-19 allowed us to reconstruct a pseudo-temporal trajectory of the innate immune response. Despite the expected patient heterogeneity, we identified consistent changes during the course of the infection. A rapid and early surge of CD169+ monocytes associated with an IFNγ+MCP-2+ signature quickly followed symptom onset; at symptom onset, patients with mild and severe COVID-19 had a similar signature, but over the course of the disease, the differences between patients with mild and severe disease increased. Later in the disease course, we observed a more pronounced re-appearance of intermediate/non-classical monocytes and mounting systemic CCL3 and CCL4 levels in patients with severe disease. Our data provide new insights into the dynamic nature of the early inflammatory response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and identifies sustained pathological innate immune responses as a likely key mechanism in severe COVID-19, further supporting investigation of targeted anti-inflammatory interventions in severe COVID-19.

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