T-cell immune profile in blood of systemic mastocytosis: Association with disease features

BACKGROUND

Systemic mastocytosis (SM) is a heterogeneous disease characterized by an expansion of KIT-mutated mast cells (MC). KIT-mutated MC display activated features and release MC mediators that might act on the tumour microenvironment and other immune cells. Here, we investigated the distribution of lymphocyte subsets in blood of patients with distinct subtypes of SM and determined its association with other disease features.

METHODS

We studied the distribution of TCD4+ and TCD4- cytotoxic cells and their subsets, as well as total NK- and B cells, in blood of 115 SM patients-38 bone marrow mastocytosis (BMM), 67 indolent SM (ISM), 10 aggressive SM (ASM)- and 83 age-matched healthy donors (HD), using spectral flow cytometry and the EuroFlow Immunomonitoring panel, and correlated it with multilineage KITD816V , the alpha-tryptasemia genotype (HαT) and the clinical manifestations of the disease.

RESULTS

SM patients showed decreased counts (vs. HD) of TCD4- cytotoxic cells, NK cells and several functional subsets of TCD4+ cells (total Th1, Th2-effector memory, Th22-terminal effector and Th1-like Tregs), together with increased T-follicular-helper and Th1/Th17-like Treg counts, associated with different immune profiles per diagnostic subtype of SM, in multilineal versus MC-restricted KITD816V and in cases with a HαT+ versus HαT- genotype. Unique immune profiles were found among BMM and ISM patients with MC-restricted KITD816V who displayed HαT, anaphylaxis, hymenoptera venom allergy, bone disease, pruritus, flushing and GI symptoms.

CONCLUSION

Our results reveal altered T- and NK-cell immune profiles in blood of SM, which vary per disease subtype, the pattern of involvement of haematopoiesis by KITD816V , the HαT genotype and specific clinical manifestations of the disease.

Immune cell kinetics and antibody response in COVID-19 patients with low-count monoclonal B-cell lymphocytosis

Low-count monoclonal B-cell lymphocytosis (MBLlo ) has been associated with an underlying immunodeficiency and has recently emerged as a new risk factor for severe COVID-19. Here, we investigated the kinetics of immune cell and antibody responses in blood during COVID-19 of MBLlo versus non-MBL patients. For this study, we analyzed the kinetics of immune cells in blood of 336 COVID-19 patients (74 MBLlo and 262 non-MBL), who had not been vaccinated against SARS-CoV-2, over a period of 43 weeks since the onset of infection, using high-sensitivity flow cytometry. Plasma levels of anti-SARS-CoV-2 antibodies were measured in parallel by ELISA. Overall, early after the onset of symptoms, MBLlo COVID-19 patients showed increased neutrophil, monocyte, and particularly, plasma cell (PC) counts, whereas eosinophil, dendritic cell, basophil, and lymphocyte counts were markedly decreased in blood of a variable percentage of samples, and with a tendency toward normal levels from week +5 of infection onward. Compared with non-MBL patients, MBLlo COVID-19 patients presented higher neutrophil counts, together with decreased pre-GC B-cell, dendritic cell, and innate-like T-cell counts. Higher PC levels, together with a delayed PC peak and greater plasma levels of anti-SARS-CoV-2-specific antibodies (at week +2 to week +4) were also observed in MBLlo patients. In summary, MBLlo COVID-19 patients share immune profiles previously described for patients with severe SARS-CoV-2 infection, associated with a delayed but more pronounced PC and antibody humoral response once compared with non-MBL patients.

Automated EuroFlow approach for standardized in-depth dissection of human circulating B-cells and plasma cells

Background

Multiparameter flow cytometry (FC) immunophenotyping is a key tool for detailed identification and characterization of human blood leucocytes, including B-lymphocytes and plasma cells (PC). However, currently used conventional data analysis strategies require extensive expertise, are time consuming, and show limited reproducibility.

Objective

Here, we designed, constructed and validated an automated database-guided gating and identification (AGI) approach for fast and standardized in-depth dissection of B-lymphocyte and PC populations in human blood.

Methods

For this purpose, 213 FC standard (FCS) datafiles corresponding to umbilical cord and peripheral blood samples from healthy and patient volunteers, stained with the 14-color 18-antibody EuroFlow BIgH-IMM panel, were used.

Results

The BIgH-IMM antibody panel allowed identification of 117 different B-lymphocyte and PC subsets. Samples from 36 healthy donors were stained and 14 of the datafiles that fulfilled strict inclusion criteria were analysed by an expert flow cytometrist to build the EuroFlow BIgH-IMM database. Data contained in the datafiles was then merged into a reference database that was uploaded in the Infinicyt software (Cytognos, Salamanca, Spain). Subsequently, we compared the results of manual gating (MG) with the performance of two classification algorithms -hierarchical algorithm vs two-step algorithm- for AGI of the cell populations present in 5 randomly selected FCS datafiles. The hierarchical AGI algorithm showed higher correlation values vs conventional MG (r2 of 0.94 vs. 0.88 for the two-step AGI algorithm) and was further validated in a set of 177 FCS datafiles against conventional expert-based MG. For virtually all identifiable cell populations a highly significant correlation was observed between the two approaches (r2>0.81 for 79% of all B-cell populations identified), with a significantly lower median time of analysis per sample (6 vs. 40 min, p=0.001) for the AGI tool vs. MG, respectively and both intra-sample (median CV of 1.7% vs. 10.4% by MG, p<0.001) and inter-expert (median CV of 3.9% vs. 17.3% by MG by 2 experts, p<0.001) variability.

Conclusion

Our results show that compared to conventional FC data analysis strategies, the here proposed AGI tool is a faster, more robust, reproducible, and standardized approach for in-depth analysis of B-lymphocyte and PC subsets circulating in human blood.

Pericardial and myocardial involvement after SARS-CoV-2 infection: a cross-sectional descriptive study in healthcare workers

Introduction and objectives

The cardiac sequelae of SARS-CoV-2 infection are still poorly documented. We conducted a cross-sectional study in healthcare workers to report evidence of pericardial and myocardial involvement after SARS-CoV-2 infection.

Methods

We studied 139 healthcare workers with confirmed past SARS-CoV-2 infection. Participants underwent clinical assessment, electrocardiography, and laboratory tests, including immune cell profiling and cardiac magnetic resonance (CMR). Clinically suspected pericarditis was diagnosed when classic criteria were present and clinically suspected myocarditis was based on the combination of at least 2 CMR criteria.

Results

Median age was 52 (41-57) years, 71.9% were women, and 16.5% were previously hospitalized for COVID-19 pneumonia. On examination (10.4 [9.3-11.0] weeks after infection-like symptoms), participants showed hemodynamic stability. Chest pain, dyspnea or palpitations were present in 41.7% participants, electrocardiographic abnormalities in 49.6%, NT-proBNP elevation in 7.9%, troponin in 0.7%, and CMR abnormalities in 60.4%. A total of 30.9% participants met criteria for either pericarditis and/or myocarditis: isolated pericarditis was diagnosed in 5.8%, myopericarditis in 7.9%, and isolated myocarditis in 17.3%. Most participants (73.2%) showed altered immune cell counts in blood, particularly decreased eosinophil (27.3%; P < .001) and increased cytotoxic T cell numbers (17.3%; P < .001). Clinically suspected pericarditis was associated (P < .005) with particularly elevated cytotoxic T cells and decreased eosinophil counts, while participants diagnosed with clinically suspected myopericarditis or myocarditis had lower (P < .05) neutrophil counts, natural killer-cells, and plasma cells.

Conclusions

Pericardial and myocardial involvement with clinical stability are frequent after SARS-CoV-2 infection and are associated with specific immune cell profiles.

Automated identification of leukocyte subsets improves standardization of database-guided expert-supervised diagnostic orientation in acute leukemia: a EuroFlow study

Precise classification of acute leukemia (AL) is crucial for adequate treatment. EuroFlow has previously designed an AL orientation tube (ALOT) to guide toward the relevant classification panel and final diagnosis. In this study, we designed and validated an algorithm for automated (database-supported) gating and identification (AGI tool) of cell subsets within samples stained with ALOT. A reference database of normal peripheral blood (PB, n = 41) and bone marrow (BM; n = 45) samples analyzed with the ALOT was constructed, and served as a reference for the AGI tool to automatically identify normal cells. Populations not unequivocally identified as normal cells were labeled as checks and were classified by an expert. Additional normal BM (n = 25) and PB (n = 43) and leukemic samples (n = 109), analyzed in parallel by experts and the AGI tool, were used to evaluate the AGI tool. Analysis of normal PB and BM samples showed low percentages of checks (<3% in PB, <10% in BM), with variations between different laboratories. Manual analysis and AGI analysis of normal and leukemic samples showed high levels of correlation between cell numbers (r² > 0.95 for all cell types in PB and r² > 0.75 in BM) and resulted in highly concordant classification of leukemic cells by our previously published automated database-guided expert-supervised orientation tool for immunophenotypic diagnosis and classification of acute leukemia (Compass tool). Similar data were obtained using alternative, commercially available tubes, confirming the robustness of the developed tools. The AGI tool represents an innovative step in minimizing human intervention and requirements in expertise, toward a "sample-in and result-out" approach which may result in more objective and reproducible data analysis and diagnostics. The AGI tool may improve quality of immunophenotyping in individual laboratories, since high percentages of checks in normal samples are an alert on the quality of the internal procedures.

From big flow cytometry datasets to smart diagnostic strategies: The EuroFlow approach

The rise in the analytical speed of mutiparameter flow cytometers made possible by the introduction of digital instruments, has brought up the possibility to manage progressively higher number of parameters simultaneously on significantly greater numbers of individual cells. This has led to an exponential increase in the complexity and volume of flow cytometry data generated about cells present in individual samples evaluated in a single measurement. This increase demands for new developments in flow cytometry data analysis, graphical representation, and visualization and interpretation tools to address the new big data challenges, i.e. processing data files of ≥10-25 parameters per cell in samples with >5-10 million cells (= up to 250 million data points per cell sample) obtained in a few minutes. Here, we present a comprehensive review of some of the tools developed by the EuroFlow consortium for processing flow cytometric big data files in diagnostic laboratories, particularly focused on automated EuroFlow approaches for: i) identification of all cell populations coexisting in a sample (automated gating); ii) smart classification of aberrant cell populations in routine diagnostics; iii) automated reporting; together with iv) new tools developed to visualize n-dimensional data in 2-dimensional plots to support expert-guided automated data analysis. The concept of using reference data bases implemented into software programs, in combination with multivariate statistical analysis pioneered by EuroFlow, provides an innovative, highly efficient and fast approach for diagnostic screening, classification and monitoring of patients with distinct hematological and immune disorders, as well as other diseases.