Characterization of Phenotypes and Functional Activities of Leukocytes From Rheumatoid Arthritis Patients by Mass Cytometry

Distinct innate and adaptive immunity phenotypic profile at the circulating single-cell level in Psoriatic Arthritis

Mass cytometry was employed to investigate 47 circulating leukocyte subsets in patients with active psoriatic arthritis (PsA, n = 16) compared to healthy controls (n = 13), seropositive (RF and/or anti-CCP, n = 12) and seronegative (n = 9) RA patients. Comparing PsA to controls, different cell frequencies were found in both innate and adaptive immunity cell subsets, as well as in cells bridging innate and adaptive immunity. In some T-cell subsets increased costimulatory molecules' expression in PsA, was also noted..No changes were observed in patients who remained disease-active after 3 months of treatment, in contrast to those who achieved remission/low-disease activity. Comparing PsA to seropositive RA, elevated frequencies of naïve and activated CD8⁺ T-cells, B-cells, MAIT/iNKT and ILCs were found, while the opposite was the case for terminal effector, senescent, and Th2-like-cells. Strikingly, the composition of the leukocyte pool in PsA was comparable to seronegative RA, providing evidence for the pathogenetic similarities between these two entities.

T-cell exhaustion in immune-mediated inflammatory diseases: New implications for immunotherapy

Immune-mediated inflammatory diseases(IMIDs) are referred to as highly disabling chronic diseases affecting different organs and systems. Inappropriate or excessive immune responses with chronic inflammation are typical manifestations. Usually in patients with chronic infection and cancer, due to long-term exposure to persistent antigens and inflammation microenvironment, T-cells are continuously stimulated and gradually differentiate into an exhausted state. Exhausted T-cells gradually lose effector function and characteristics of memory T-cells. However, existing studies have found that exhausted T-cells are not only present in the infection and tumor environment, but also in autoimmunity, and are associated with better prognosis of IMIDs. This suggests new prospects for the application of this reversible process of T-cell exhaustion in the treatment of IMID. This review will focus on the research progress of T-cell exhaustion in several IMIDs and its potential application for diagnosis and treatment in IMIDs.

Leveraging whole blood based functional flow cytometry assays to open new perspectives for rheumatoid arthritis translational research

Despite introduction of biological disease modifying anti-rheumatic drugs (DMARDs) for Rheumatoid arthritis (RA) treatment, therapeutic strategies do not always lead to disease control and remission. Hence, a more efficient patient stratification and monitoring biomarkers and tools are needed to enable a more personalized medicine. We used a whole blood based functional flow cytometry assay to characterize immune cells from RA patients (treated or not), healthy donors and psoriatic arthritis (PsA) patients according to their responses to LPS and/or anti-TNFα (infliximab, IFX). Activation marker expression was measured using a 10-color flow cytometry panel following a no-wash protocol. Naïve-to-treatment RA patients had a stronger inflammatory profile in comparison to healthy donors at basal level. Higher expression of activation markers (CD69 and/or CD11b) on NK, B cells and granulocytes and lower expression of the adhesion molecule CD62L were measured on monocytes, granulocytes and B cells. After LPS, naïve RA patients' cells were less capable of regulating CD69, CD11b, CD16 or CD62L showing impaired activation capabilities. Upon LPS and IFX co-incubation, hierarchical clustering analysis showed different profiles between cohorts. We believe that this whole blood-based approach should further be assessed for RA patient characterization as it provides new perspectives for stratification and/or monitoring.

An Integrative Pharmacology Model for Decoding the Underlying Therapeutic Mechanisms of Ermiao Powder for Rheumatoid Arthritis

As a systemic inflammatory arthritis disease, rheumatoid arthritis (RA) is complex and hereditary. Traditional Chinese medicine (TCM) has evident advantages in treating complex diseases, and a variety of TCM formulas have been reported that have effective treatment on RA. Clinical and pharmacological studies showed that Ermiao Powder, which consists of Phellodendron amurense Rupr. (PAR) and Atractylodes lancea (Thunb.) DC. (ALD), can be used in the treatment of RA. Currently, most studies focus on the anti-inflammatory mechanism of PAR and ALD and are less focused on their coordinated molecular mechanism. In this research, we established an integrative pharmacological strategy to explore the coordinated molecular mechanism of the two herbs of Ermiao Powder in treating RA. To explore the potential coordinated mechanism of PAR and ALD, we firstly developed a novel mathematical model to calculate the contribution score of 126 active components and 85 active components, which contributed 90% of the total contribution scores that were retained to construct the coordinated functional space. Then, the knapsack algorithm was applied to identify the core coordinated functional components from the 85 active components. Finally, we obtained the potential coordinated functional components group (CFCG) with 37 components, including wogonin, paeonol, ethyl caffeate, and magnoflorine. Also, functional enrichment analysis was performed on the targets of CFCG to explore the potential coordinated molecular mechanisms of PAR and ALD. The results indicated that the CFCG could treat RA by coordinated targeting to the genes involved in immunity and inflammation-related signal pathways, such as phosphatidylinositol 3‑kinase/protein kinase B signaling pathway, mitogen-activated protein kinase signaling pathway, tumor necrosis factor signaling pathway, and nuclear factor-kappa B signaling pathway. The docking and in vitro experiments were used to predict the affinity and validate the effect of CFCG and further confirm the reliability of our method. Our integrative pharmacological strategy, including CFCG identification and verification, can provide the methodological references for exploring the coordinated mechanism of TCM in treating complex diseases and contribute to improving our understanding of the coordinated mechanism.

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

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13075-021-02630-8.

A Granulocytic Signature Identifies COVID-19 and Its Severity

Background

An unbiased approach of SARS-CoV-2-induced immune dysregulation has not been undertaken so far. We aimed to identify previously unreported immune markers able to discriminate COVID-19 patients from healthy controls and to predict mild and severe disease.

Methods

An observational, prospective, multicentric study was conducted in patients with confirmed COVID-19: mild/moderate (n=7) and severe (n=19). Immunophenotyping of whole blood leukocytes was performed in patients upon hospital ward or intensive care unit admission and in healthy controls (n=25). Clinically relevant associations were identified through unsupervised analysis.

Results

Granulocytic (neutrophil, eosinophil and basophil) markers were enriched during COVID-19 and discriminated between mild and severe patients. Increased counts of CD15 ⁺CD16 ⁺ neutrophils, decreased granulocytic expression of integrin CD11b, and Th2-related CRTH2 downregulation in eosinophils and basophils established a COVID-19 signature. Severity was associated with the emergence of PDL1 checkpoint expression in basophils and eosinophils. This granulocytic signature was accompanied by monocyte and lymphocyte immunoparalysis. Correlation with validated clinical scores supported pathophysiological relevance.

Conclusion

Phenotypic markers of circulating granulocytes are strong discriminators between infected and uninfected individuals as well as between severity stages. COVID-19 alters the frequency and functional phenotypes of granulocyte subsets with the emergence of CRTH2 as a disease biomarker.

Progress and applications of mass cytometry in sketching immune landscapes

Recently emerged mass cytometry (cytometry by time-of-flight [CyTOF]) technology permits the identification and quantification of inherently diverse cellular systems, and the simultaneous measurement of functional attributes at the single-cell resolution. By virtue of its multiplex ability with limited need for compensation, CyTOF has led a critical role in immunological research fields. Here, we present an overview of CyTOF, including the introduction of CyTOF principle and advantages that make it a standalone tool in deciphering immune mysteries. We then discuss the functional assays, introduce the bioinformatics to interpret the data yield via CyTOF, and depict the emerging clinical and research applications of CyTOF technology in sketching immune landscape in a wide variety of diseases.

From Bivariate to Multivariate Analysis of Cytometric Data: Overview of Computational Methods and Their Application in Vaccination Studies

Flow and mass cytometry are used to quantify the expression of multiple extracellular or intracellular molecules on single cells, allowing the phenotypic and functional characterization of complex cell populations. Multiparametric flow cytometry is particularly suitable for deep analysis of immune responses after vaccination, as it allows to measure the frequency, the phenotype, and the functional features of antigen-specific cells. When many parameters are investigated simultaneously, it is not feasible to analyze all the possible bi-dimensional combinations of marker expression with classical manual analysis and the adoption of advanced automated tools to process and analyze high-dimensional data sets becomes necessary. In recent years, the development of many tools for the automated analysis of multiparametric cytometry data has been reported, with an increasing record of publications starting from 2014. However, the use of these tools has been preferentially restricted to bioinformaticians, while few of them are routinely employed by the biomedical community. Filling the gap between algorithms developers and final users is fundamental for exploiting the advantages of computational tools in the analysis of cytometry data. The potentialities of automated analyses range from the improvement of the data quality in the pre-processing steps up to the unbiased, data-driven examination of complex datasets using a variety of algorithms based on different approaches. In this review, an overview of the automated analysis pipeline is provided, spanning from the pre-processing phase to the automated population analysis. Analysis based on computational tools might overcame both the subjectivity of manual gating and the operator-biased exploration of expected populations. Examples of applications of automated tools that have successfully improved the characterization of different cell populations in vaccination studies are also presented.