Altered Monocyte Subsets in Kawasaki Disease Revealed by Single-cell RNA-Sequencing

Regulation of immunomodulatory networks by Nrf2-activation in immune cells: Redox control and therapeutic potential in inflammatory diseases

Inflammatory diseases present a serious health challenge due to their widespread prevalence and the severe impact on patients' lives. In the quest to alleviate the burden of these diseases, nuclear factor erythroid 2-related factor 2 (Nrf2) has emerged as a pivotal player. As a transcription factor intimately involved in cellular defense against metabolic and oxidative stress, Nrf2's role in modulating the inflammatory responses of immune cells has garnered significant attention. Recent findings suggest that Nrf2's ability to alter the redox status of cells underlies its regulatory effects on immune responses. Our review delves into preclinical and clinical evidence that underscores the complex influence of Nrf2 activators on immune cell phenotypes, particularly in the inflammatory milieu. By offering a detailed analysis of Nrf2's role in different immune cell populations, we cast light on the potential of Nrf2 activators in shaping the immune response towards a more regulated state, mitigating the adverse effects of inflammation through modeling redox status of immune cells. Furthermore, we explore the innovative use of nanoencapsulation techniques that enhance the delivery and efficacy of Nrf2 activators, potentially advancing the treatment strategies for inflammatory ailments. We hope this review will stimulate the development and expansion of Nrf2-targeted treatments that could substantially improve outcomes for patients suffering from a broad range of inflammatory diseases.

CD14 down-modulation as a real-time biomarker in Kawasaki disease

Objectives

The objectives of this study were to investigate the pathophysiology of Kawasaki disease (KD) from immunological and oxidative stress perspectives, and to identify real-time biomarkers linked to innate immunity and oxidative stress in KD.

Methods

We prospectively enrolled 85 patients with KD and 135 patients with diverse conditions including immune, infectious and non-infectious diseases for this investigation. Flow cytometry was used to analyse the surface expression of CD14, CD38 and CD62L on monocytes, along with a quantitative assessment of CD14 down-modulation. Additionally, oxidative stress levels were evaluated using derivatives of reactive oxygen metabolites (d-ROMs) and antioxidant capacity measured by a free radical elective evaluator system.

Results

During the acute phase of KD, we observed a prominent CD14 down-modulation on monocytes, reflecting the indirect detection of circulating innate immune molecular patterns. Moreover, patients with KD showed a significantly higher CD14 down-modulation compared with infectious and non-infectious disease controls. Notably, the surface expression of CD14 on monocytes was restored concurrently with responses to intravenous immunoglobulin and infliximab treatment in KD. Furthermore, d-ROM levels in patients with KD were significantly elevated compared with patients with infectious and non-infectious diseases. Following intravenous immunoglobulin treatment, oxidative stress levels decreased in patients with KD.

Conclusion

Monitoring CD14 down-modulation on monocytes in real-time is a valuable strategy for assessing treatment response, distinguishing KD relapse from concomitant infections and selecting second-line therapy after IVIG treatment in KD patients. The interplay between inflammation and oxidative stress likely plays a crucial role in the development of KD.

Single-Cell Meta-Analysis of Neutrophil Activation in Kawasaki Disease and Multisystem Inflammatory Syndrome in Children Reveals Potential Shared Immunological Drivers

BACKGROUND

Kawasaki disease (KD) and multisystem inflammatory syndrome in children (MIS-C) share similar clinical manifestations, including cardiovascular complications, suggesting similar underlying immunopathogenic processes. Aberrant neutrophil activation may play a crucial role in the shared pathologies of KD and MIS-C; however, the associated pathogenic mechanisms and molecular drivers remain unknown.

METHODS

We performed a single-cell meta-analysis of neutrophil activation with 103 pediatric single-cell transcriptomic peripheral blood mononuclear cell data across 9 cohorts, including healthy controls, KD, MIS-C, compared with dengue virus infection, juvenile idiopathic arthritis, and pediatric celiac disease. We used a series of computational analyses to investigate the shared neutrophil transcriptional programs of KD and MIS-C that are linked to systemic damage and cardiac pathologies, and suggested Food and Drug Administration-approved drugs to consider as KD and MIS-C treatment.

RESULTS

We meta-analyzed 521 950 high-quality cells. We found that blood signatures associated with risks of cardiovascular events are enriched in neutrophils of KD and MIS-C. We revealed the expansion of CD177+ neutrophils harboring hyperactivated effector functions in both KD and MIS-C, but not in healthy controls or in other viral-, inflammatory-, or immune-related pediatric diseases. KD and MIS-C CD177+ neutrophils had highly similar transcriptomes, marked by conserved signatures and pathways related to molecular damage. We found the induction of a shared neutrophil expression program, potentially regulated by SPI1 (Spi-1 proto-oncogene), which confers enhanced effector functions, especially neutrophil degranulation. CD177 and shared neutrophil expression program expressions were associated with acute stages and attenuated during KD intravenous immunoglobulin treatment and MIS-C recovery. Network analysis identified hub genes that correlated with the high activation of CD177+ neutrophils. Disease-gene association analysis revealed that the KD and MIS-C CD177+ neutrophils' shared expression program was associated with the development of coronary and myocardial disorders. Last, we identified and validated TSPO (translocator protein) and S100A12 (S100 calcium-binding protein A12) as main molecular targets, for which the Food and Drug Administration-approved drugs methotrexate, zaleplon, metronidazole, lorazepam, clonazepam, temazepam, and zolpidem, among others, are primary candidates for drug repurposing.

CONCLUSIONS

Our findings indicate that CD177+ neutrophils may exert systemic pathological damage contributing to the shared morbidities in KD and MIS-C. We uncovered potential regulatory drivers of CD177+ neutrophil hyperactivation and pathogenicity that may be targeted as a single therapeutic strategy for either KD or MIS-C.

A machine learning model for distinguishing Kawasaki disease from sepsis

KD is an acute systemic vasculitis that most commonly affects children under 5 years old. Sepsis is a systemic inflammatory response syndrome caused by infection. The main clinical manifestations of both are fever, and laboratory tests include elevated WBC count, C-reactive protein, and procalcitonin. However, the two treatments are very different. Therefore, it is necessary to establish a dynamic nomogram based on clinical data to help clinicians make timely diagnoses and decision-making. In this study, we analyzed 299 KD patients and 309 sepsis patients. We collected patients' age, sex, height, weight, BMI, and 33 biological parameters of a routine blood test. After dividing the patients into a training set and validation set, the least absolute shrinkage and selection operator method, support vector machine and receiver operating characteristic curve were used to select significant factors and construct the nomogram. The performance of the nomogram was evaluated by discrimination and calibration. The decision curve analysis was used to assess the clinical usefulness of the nomogram. This nomogram shows that height, WBC, monocyte, eosinophil, lymphocyte to monocyte count ratio (LMR), PA, GGT and platelet are independent predictors of the KD diagnostic model. The c-index of the nomogram in the training set and validation is 0.926 and 0.878, which describes good discrimination. The nomogram is well calibrated. The decision curve analysis showed that the nomogram has better clinical application value and decision-making assistance ability. The nomogram has good performance of distinguishing KD from sepsis and is helpful for clinical pediatricians to make early clinical decisions.

CD16+ monocytes are involved in the hyper-inflammatory state of Prader-Willi Syndrome by single-cell transcriptomic analysis

Background

Patients with Prader-Willi syndrome (PWS) have a reduced life expectancy due to inflammation-related disease including cardiovascular disease and diabetes. Abnormal activation of peripheral immune system is postulated as a contributor. However, detailed features of the peripheral immune cells in PWS have not been fully elucidated.

Methods

Serum inflammatory cytokines were measured in healthy controls (n=13) and PWS patients (n=10) using a 65- multiplex cytokine assays. Changes of the peripheral immune cells in PWS was assessed by single-cell RNA sequencing (scRNA-seq) and high-dimensional mass cytometry (CyTOF) using peripheral blood mononuclear cells (PBMCs) from PWS patients (n=6) and healthy controls (n=12).

Results

PWS patients exhibited hyper-inflammatory signatures in PBMCs and monocytes were the most pronounced. Most inflammatory serum cytokines were increased in PWS, including IL-1β, IL-2R, IL-12p70, and TNF-α. The characteristics of monocytes evaluated by scRNA-seq and CyTOF showed that CD16⁺ monocytes were significantly increased in PWS patients. Functional pathway analysis revealed that CD16⁺ monocytes upregulated pathways in PWS were closely associated with TNF/IL-1β- driven inflammation signaling. The CellChat analysis identified CD16⁺ monocytes transmitted chemokine and cytokine signaling to drive inflammatory process in other cell types. Finally, we explored the PWS deletion region 15q11-q13 might be responsible for elevated levels of inflammation in the peripheral immune system.

Conclusion

The study highlights that CD16⁺ monocytes contributor to the hyper-inflammatory state of PWS which provides potential targets for immunotherapy in the future and expands our knowledge of peripheral immune cells in PWS at the single cell level for the first time.

Identification of Hub Biomarkers and Immune and Inflammation Pathways Contributing to Kawasaki Disease Progression with RT-qPCR Verification

Background. Kawasaki disease (KD) is characterized by a disordered inflammation response of unknown etiology. Immune cells are closely associated with its onset, although the immune-related genes’ expression and possibly involved immune regulatory mechanisms are little known. This study aims to identify KD-implicated significant immune- and inflammation-related biomarkers and pathways and their association with immune cell infiltration. Patients and Methods. Gene microarray data were collected from the Gene Expression Omnibus database. Differential expression analysis, weighted gene coexpression network analysis (WGCNA), least absolute shrinkage and selection operator (LASSO) regression, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) were used to find KD hub markers. GSEA was used to assess the infiltration by 28 immune cell types and their connections to essential gene markers. Receiver operating characteristic (ROC) curves were used to examine hub markers’ diagnostic effectiveness. Finally, hub genes’ expressions were validated in Chinese KD patients by reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Results. One hundred and fifty-one unique genes were found. Among 10 coexpression modules at WGCNA, one hub module exhibited the strongest association with KD. Thirty-six overlapping genes were identified. Six hub genes were potential biomarkers according to LASSO analysis. Immune infiltration revealed connections among activated and effector memory CD4+ T cells, neutrophils, activated dendritic cells, and macrophages. The six hub genes’ diagnostic value was shown by ROC curve analysis. Hub genes were enriched in immunological and inflammatory pathways. RT-qPCR verification results of FCGR1B ( $P<0.001$ ), GPR84 ( $P<0.001$ ), KREMEN1 ( $P<0.001$ ), LRG1 ( $P<0.001$ ), and TDRD9 ( $P<0.001$ ) upregulated expression in Chinese KD patients are consistent with our database analysis. Conclusion. Neutrophils, macrophages, and activated dendritic cells are strongly linked to KD pathophysiology. Through immune-related signaling pathways, hub genes such as FCGR1B, GPR84, KREMEN1, LRG1, and TDRD9 may be implicated in KD advancement.

Single cell RNA-seq resolution revealed CCR1+/SELL+/XAF+ CD14 monocytes mediated vascular endothelial cell injuries in Kawasaki disease and COVID-19

INTRODUCTION

The COVID-19 pandemic provide the opportunities to explore the numerous similarities in clinical symptoms with Kawasaki disease (KD), including severe vasculitis. Despite this, the underlying mechanisms of vascular injury in both KD and COVID-19 remain elusive. To identify these mechanisms, this study employs single-cell RNA sequencing to explore the molecular mechanisms of immune responses in vasculitis, and validate the results through in vitro experiments.

METHOD

The single-cell RNA sequencing (scRNA-seq) analysis of peripheral blood mononuclear cells (PBMCs) was carried out to investigate the molecular mechanisms of immune responses in vasculitis in KD and COVID-19. The analysis was performed on PBMCs from six children diagnosed with complete KD, three age-matched KD healthy controls (KHC), six COVID-19 patients (COV), three influenza patients (FLU), and four healthy controls (CHC). The results from the scRNA-seq analysis were validated through flow cytometry and immunofluorescence experiments on additional human samples. Subsequently, monocyte adhesion assays, immunofluorescence, and quantitative polymerase chain reaction (qPCR) were used to analyze the damages to endothelial cells post-interaction with monocytes in HUVEC and THP1 cultures.

RESULTS

The scRNA-seq analysis revealed the potential cellular types involved and the alterations in genetic transcriptions in the inflammatory responses. The findings indicated that while the immune cell compositions had been altered in KD and COV patients, and the ratio of CD14+ monocytes were both elevated in KD and COV. While the CD14+ monocytes share a large scale of same differentiated expressed geens between KD and COV. The differential activation of CD14 and CD16 monocytes was found to respond to both endothelial and epithelial dysfunctions. Furthermore, SELL+/CCR1+/XAF1+ CD14 monocytes were seen to enhance the adhesion and damage to endothelial cells. The results also showed that different types of B cells were involved in both KD and COV, while only the activation of T cells was recorded in KD.

CONCLUSION

In conclusion, our study demonstrated the role of the innate immune response in the regulation of endothelial dysfunction in both KD and COVID-19. Additionally, our findings indicate that the adaptive immunity activation differs between KD and COVID-19. Our results demonstrate that monocytes in COVID-19 exhibit adhesion to both endothelial cells and alveolar epithelial cells, thus providing insight into the mechanisms and shared phenotypes between KD and COVID-19.

Research progress of single-cell transcriptome sequencing in autoimmune diseases and autoinflammatory disease: A review

Autoimmunity refers to the phenomenon that the body's immune system produces antibodies or sensitized lymphocytes to its own tissues to cause an immune response. Immune disorders caused by autoimmunity can mediate autoimmune diseases. Autoimmune diseases have complicated pathogenesis due to the many types of cells involved, and the mechanism is still unclear. The emergence of single-cell research technology can solve the problem that ordinary transcriptome technology cannot be accurate to cell type. It provides unbiased results through independent analysis of cells in tissues and provides more mRNA information for identifying cell subpopulations, which provides a novel approach to study disruption of immune tolerance and disturbance of pro-inflammatory pathways on a cellular basis. It may fundamentally change the understanding of molecular pathways in the pathogenesis of autoimmune diseases and develop targeted drugs. Single-cell transcriptome sequencing (scRNA-seq) has been widely applied in autoimmune diseases, which provides a powerful tool for demonstrating the cellular heterogeneity of tissues involved in various immune inflammations, identifying pathogenic cell populations, and revealing the mechanism of disease occurrence and development. This review describes the principles of scRNA-seq, introduces common sequencing platforms and practical procedures, and focuses on the progress of scRNA-seq in 41 autoimmune diseases, which include 9 systemic autoimmune diseases and autoinflammatory diseases (rheumatoid arthritis, systemic lupus erythematosus, etc.) and 32 organ-specific autoimmune diseases (5 Skin diseases, 3 Nervous system diseases, 4 Eye diseases, 2 Respiratory system diseases, 2 Circulatory system diseases, 6 Liver, Gallbladder and Pancreas diseases, 2 Gastrointestinal system diseases, 3 Muscle, Bones and joint diseases, 3 Urinary system diseases, 2 Reproductive system diseases). This review also prospects the molecular mechanism targets of autoimmune diseases from the multi-molecular level and multi-dimensional analysis combined with single-cell multi-omics sequencing technology (such as scRNA-seq, Single cell ATAC-seq and single cell immune group library sequencing), which provides a reference for further exploring the pathogenesis and marker screening of autoimmune diseases and autoimmune inflammatory diseases in the future.

Expression of Eosinophilic Subtype Markers in Patients with Kawasaki Disease

PURPOSE

Eosinophils may rise to a higher level in the acute phase of Kawasaki disease (KD) both before and after intravenous immunoglobulin (IVIG) therapy. A substantial body of research was carried out on the association between KD and allergic diseases. Eosinophils play an important role in type 2 inflammation. Recent studies have shown that there are two distinct subtypes of eosinophils. In addition to their role in inflammation, lung-resident eosinophils (rEOS) also regulate homeostasis. Inflammatory eosinophils (iEOS) reflect type 2 inflammation in tissues. iEOS were considered the primary eosinophils in non-severe allergic asthma, while rEOS were thought to be the primary eosinophils in severe non-allergic eosinophilic asthma. This case-control study aimed to investigate the marker expression of eosinophilic subtypes in KD patients.

MATERIALS AND METHODS

The marker expressions of eosinophilic subtypes in the leukocytes of patients with KD were evaluated by the recently established KDmarkers online tool, a web server including gene expression data. Finally, the results were validated with a quantitative reverse transcriptase polymerase chain reaction (RT-PCR). We analyzed the mRNA expression levels of SELL and IL10RA in leukocytes from KD patients and febrile children.

RESULTS

Included in our screening tools were transcriptome arrays, which provided clues showing the importance of rEOS, whose role was identified by three genes (lower IL10RA, higher SELL, and SERPINB1 than controls). In contrast, the iEOS representative gene CD101 was not elevated in KD. It was found that the gene IL10RA, a marker of inflammatory eosinophilic leukocytes, was more highly expressed in the leukocytes of KD patients (n = 43) than febrile controls (n = 32), especially those without coronary artery lesions (CAL) (n = 26). Before treatment, SELL expression was higher in leukocytes of CAL patients (CAL, 1.33 ± 0.18, n = 39; non-CAL, 0.87 ± 0.12, n = 55; p = 0.012). SELL was significantly higher after half a year compared to febrile controls.

CONCLUSIONS

To our knowledge, this is the first study to demonstrate that KD patients have increased SELL than febrile controls after 6 months of treatment. We present evidence here that dynamically different eosinophilic involvement exists between KD patients with and without CAL. The role of eosinophilic subtypes in KD patients warrants further investigation.

Multiscale Methods for Signal Selection in Single-Cell Data

Analysis of single-cell transcriptomics often relies on clustering cells and then performing differential gene expression (DGE) to identify genes that vary between these clusters. These discrete analyses successfully determine cell types and markers; however, continuous variation within and between cell types may not be detected. We propose three topologically motivated mathematical methods for unsupervised feature selection that consider discrete and continuous transcriptional patterns on an equal footing across multiple scales simultaneously. Eigenscores (eigi) rank signals or genes based on their correspondence to low-frequency intrinsic patterning in the data using the spectral decomposition of the Laplacian graph. The multiscale Laplacian score (MLS) is an unsupervised method for locating relevant scales in data and selecting the genes that are coherently expressed at these respective scales. The persistent Rayleigh quotient (PRQ) takes data equipped with a filtration, allowing the separation of genes with different roles in a bifurcation process (e.g., pseudo-time). We demonstrate the utility of these techniques by applying them to published single-cell transcriptomics data sets. The methods validate previously identified genes and detect additional biologically meaningful genes with coherent expression patterns. By studying the interaction between gene signals and the geometry of the underlying space, the three methods give multidimensional rankings of the genes and visualisation of relationships between them.

Prediction of Immune Infiltration Diagnostic Gene Biomarkers in Kawasaki Disease

Kawasaki disease (KD) is characterized by disorder of immune response with unknown etiology. Immune cells may be closely related to the onset of KD. The focus of this research was to evaluate the significance of the infiltration of immune cells for this disease and find possible diagnostic biomarkers for KD. The Gene Expression Omnibus database was utilized to retrieve two freely accessible gene expression patterns (GSE68004 and GSE18606 datasets) from human KD and control specimens. 114 KD, as well as 46 control specimens, were searched for obtaining differentially expressed genes (DEGs). Candidate biological markers were determined utilizing the support vector machine recursive feature elimination and the least absolute shrinkage and selection operator regression model analysis. To assess discriminating capacity, the area under the receiver operating characteristic curve (AUC) was computed. The GSE73461 dataset was utilized to observe the biomarkers' expression levels and diagnostic significance in KD (78 KD patients and 55 controls). CIBERSORT was employed to assess the composition profiles of the 22 subtypes of immune cell fraction in KD on the basis of combined cohorts. 37 genes were discovered. The DEGs identified were predominantly involved in arteriosclerotic cardiovascular disease, atherosclerosis, autoimmune disease of the urogenital tract, and bacterial infectious disease. Gene sets related to complement and coagulation cascades, Toll-like receptor signaling pathway, Fc gamma R-mediated phagocytosis, NOD-like receptor signaling pathway, and regulation of actin cytoskeleton underwent differential activation in KD as opposed to the controls. KD diagnostic biomarkers, including the alkaline phosphatase (ALPL), endoplasmic reticulum degradation-enhancing alpha-mannosidase-like protein 2 (EDEM2), and histone cluster 2 (HIST2H2BE), were discovered (AUC = 1.000) and verified utilizing the GSE73461 dataset (AUC = 1.000). Analyses of immune cell infiltration demonstrated that ALPL, EDEM2, and HIST2H2BE were linked to CD4 memory resting T cells, monocytes, M0 macrophages, CD8 T cells, neutrophils, and memory CD4 T cells. ALPL, EDEM2, and HIST2H2BE could be utilized as KD diagnostic indicators, and they can also deliver useful information for future research on the disease's incidence and molecular processes.

Single-Cell Analysis Reveals the Role of the Neuropeptide Receptor FPR2 in Monocytes in Kawasaki Disease: A Bioinformatic Study

Exploring the role of neuropeptides in the communication between monocyte subtypes facilitates an investigation of the pathogenesis of Kawasaki disease (KD). We investigated the patterns of interaction between neuropeptide-associated ligands and receptors in monocyte subpopulations in KD patients. Single-cell analysis was employed for the identification of cell subpopulations in KD patients, and monocytes were classified into 3 subpopulations: classical monocytes (CMs), intermediate monocytes (IMs), and nonclassical monocytes (NCMs). Cell-cell communication and differential analyses were used to identify ligand-receptor interactions in monocytes. Five neuropeptide-related genes (SORL1, TNF, SORT1, FPR2, and ANXA1) were involved in cell-cell interactions, wherein FPR2, a neuropeptide receptor, was significantly highly expressed in KD. Weighted gene coexpression network analysis revealed a significant correlation between the yellow module and FPR2 (p < 0.001, CC = 0.43). Using the genes in the yellow module, we constructed a PPI network to assess the possible functions of the FPR2-associated gene network. Gene set enrichment analysis showed that increased FPR2 levels may be involved in immune system regulation. FPR2 in CMs mediates the control of inflammation in KD. The findings of this study may provide a novel target for the clinical treatment of KD.

Mechanisms of Immune Dysregulation in COVID-19 Are Different From SARS and MERS: A Perspective in Context of Kawasaki Disease and MIS-C

Coronaviruses have led to three major outbreaks to date-Severe Acute Respiratory Syndrome (SARS; 2002), Middle East Respiratory Syndrome (MERS; 2012) and the ongoing pandemic, Coronavirus Disease (COVID-19; 2019). Coronavirus infections are usually mild in children. However, a few children with MERS had presented with a severe phenotype in the acute phase resulting in progressive pneumonic changes with increasing oxygen dependency and acute respiratory distress requiring ventilatory support. A subset of children with a history of SARS-CoV-2 infection develops a multisystem hyper-inflammatory phenotype known as Multisystem Inflammatory Syndrome in Children (MIS-C). This syndrome occurs 4-6 weeks after infection with SARS-CoV-2 and has been reported more often from areas with high community transmission. Children with MIS-C present with high fever and often have involvement of cardiovascular, gastrointestinal and hematologic systems leading to multiorgan failure. This is accompanied by elevation of pro-inflammatory cytokines such as IL-6 and IL-10. MIS-C has several similarities with Kawasaki disease (KD) considering children with both conditions present with fever, rash, conjunctival injection, mucosal symptoms and swelling of hands and feet. For reasons that are still not clear, both KD and MIS-C were not reported during the SARS-CoV and MERS-CoV outbreaks. As SARS-CoV-2 differs from SARS-CoV by 19.5% and MERS by 50% in terms of sequence identity, differences in genomic and proteomic profiles may explain the varied disease immunopathology and host responses. Left untreated, MIS-C may lead to severe abdominal pain, ventricular dysfunction and shock. Immunological investigations reveal reduced numbers of follicular B cells, increased numbers of terminally differentiated CD4+T lymphocytes, and decreased IL-17A. There is still ambiguity about the clinical and immunologic risk factors that predispose some children to development of MIS-C while sparing others. Host-pathogen interactions in SARS, MERS and COVID-19 are likely to play a crucial role in the clinical phenotypes that manifest. This narrative review focuses on the immunological basis for development of MIS-C syndrome in the ongoing SARS-CoV-2 pandemic. To the best of our knowledge, these aspects have not been reviewed before.

Single Cell RNA Sequencing in Autoimmune Inflammatory Rheumatic Diseases: Current Applications, Challenges and a Step Toward Precision Medicine

Single cell RNA sequencing (scRNA-seq) represents a new large scale and high throughput technique allowing analysis of the whole transcriptome at the resolution of an individual cell. It has emerged as an imperative method in life science research, uncovering complex cellular networks and providing indices that will eventually lead to the development of more targeted and personalized therapies. The importance of scRNA-seq has been particularly highlighted through the analysis of complex biological systems, in which cellular heterogeneity is a key aspect, such as the immune system. Autoimmune inflammatory rheumatic diseases represent a group of disorders, associated with a dysregulated immune system and high patient heterogeneity in both pathophysiological and clinical aspects. This complicates the complete understanding of underlying pathological mechanisms, associated with limited therapeutic options available and their long-term inefficiency and even toxicity. There is an unmet need to investigate, in depth, the cellular and molecular mechanisms driving the pathogenesis of rheumatic diseases and drug resistance, identify novel therapeutic targets, as well as make a step forward in using stratified and informed therapeutic decisions, which could now be achieved with the use of single cell approaches. This review summarizes the current use of scRNA-seq in studying different rheumatic diseases, based on recent findings from published in vitro, in vivo, and clinical studies, as well as discusses the potential implementation of scRNA-seq in the development of precision medicine in rheumatology.

A Diagnostic Model for Kawasaki Disease Based on Immune Cell Characterization From Blood Samples

Background: Kawasaki disease (KD) is the leading cause of acquired heart disease in children. However, distinguishing KD from febrile infections early in the disease course remains difficult. Our goal was to estimate the immune cell composition in KD patients and febrile controls (FC), and to develop a tool for KD diagnosis. Methods: We used a machine-learning algorithm, CIBERSORT, to estimate the proportions of 22 immune cell types based on blood samples from children with KD and FC. Using these immune cell compositions, a diagnostic score for predicting KD was then constructed based on LASSO regression for binary outcomes. Results: In the training set (n = 496), a model was fit which consisted of eight types of immune cells. The area under the curve (AUC) values for diagnosing KD in a held-out test set (n = 212) and an external validation set (n = 36) were 0.80 and 0.77, respectively. The most common cell types in KD blood samples were monocytes, neutrophils, CD4⁺-naïve and CD8⁺ T cells, and M0 macrophages. The diagnostic score was highly correlated to genes that had been previously reported as associated with KD, such as interleukins and chemokine receptors, and enriched in reported pathways, such as IL-6/JAK/STAT3 and TNFα signaling pathways. Conclusion: Altogether, the diagnostic score for predicting KD could potentially serve as a biomarker. Prospective studies could evaluate how incorporating the diagnostic score into a clinical algorithm would improve diagnostic accuracy further.