Genetic landscape and autoimmunity of monocytes in developing Vogt-Koyanagi-Harada disease

Monocytes in type 1 diabetes families exhibit high cytolytic activity and subset abundances that correlate with clinical progression

Monocytes are immune regulators implicated in the pathogenesis of type 1 diabetes (T1D), an autoimmune disease that targets insulin-producing pancreatic β cells. We determined that monocytes of recent onset (RO) T1D patients and their healthy siblings express proinflammatory/cytolytic transcriptomes and hypersecrete cytokines in response to lipopolysaccharide exposure compared to unrelated healthy controls (uHCs). Flow cytometry measured elevated circulating abundances of intermediate monocytes and >2-fold more CD14+CD16+HLADR+KLRD1+PRF1+ NK-like monocytes among patients with ROT1D compared to uHC. The intermediate to nonclassical monocyte ratio among ROT1D patients correlated with the decline in functional β cell mass during the first 24 months after onset. Among sibling nonprogressors, temporal decreases were measured in the intermediate to nonclassical monocyte ratio and NK-like monocyte abundances; these changes coincided with increases in activated regulatory T cells. In contrast, these monocyte populations exhibited stability among T1D progressors. This study associates heightened monocyte proinflammatory/cytolytic activity with T1D susceptibility and progression and offers insight to the age-dependent decline in T1D susceptibility.

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.

Global Research Status Regarding Uveitis in the Last Decade

PURPOSE

To provide an overview on global uveitis research in the last decade in terms of countries/regions, organizations, scholars, journals, trending topics, and fundings.

METHODS

This cross-sectional bibliometric analysis yielded 10656 uveitis publications in English for subsequent bibliometric analysis.

RESULTS

In terms of the number of publications, the leading country/region was the USA (3007). The most productive organization was the University College London (420). The most productive research team was Professor Yang's group (146). A higher h-index was noted in University College London (48). Professor Rosenbaum was the first h-index holder (32). Keywords of interest included topics such as biologics, COVID and OCT. Publications by Ocular Immunology and Inflammation (968) ranked the first position.

CONCLUSIONS

The USA is the leading force in uveitis study. Asian countries/regions, such as China (mainland) and India, are exerting a substantial role worldwide. Trendy topics cover COVID-19, OCTA.

scCensus: Off-target scRNA-seq reads reveal meaningful biology

Single-cell RNA-sequencing (scRNA-seq) provides unprecedented insights into cellular heterogeneity. Although scRNA-seq reads from most prevalent and popular tagged-end protocols are expected to arise from the 3' end of polyadenylated RNAs, recent studies have shown that "off-target" reads can constitute a substantial portion of the read population. In this work, we introduced scCensus, a comprehensive analysis workflow for systematically evaluating and categorizing off-target reads in scRNA-seq. We applied scCensus to seven scRNA-seq datasets. Our analysis of intergenic reads shows that these off-target reads contain information about chromatin structure and can be used to identify similar cells across modalities. Our analysis of antisense reads suggests that these reads can be used to improve gene detection and capture interesting transcriptional activities like antisense transcription. Furthermore, using splice-aware quantification, we find that spliced and unspliced reads provide distinct information about cell clusters and biomarkers, suggesting the utility of integrating signals from reads with different splicing statuses. Overall, our results suggest that off-target scRNA-seq reads contain underappreciated information about various transcriptional activities. These observations about yet-unexploited information in existing scRNA-seq data will help guide and motivate the community to improve current algorithms and analysis methods, and to develop novel approaches that utilize off-target reads to extend the reach and accuracy of single-cell data analysis pipelines.

Machine Learning Made Easy (MLme): a comprehensive toolkit for machine learning-driven data analysis

BACKGROUND

Machine learning (ML) has emerged as a vital asset for researchers to analyze and extract valuable information from complex datasets. However, developing an effective and robust ML pipeline can present a real challenge, demanding considerable time and effort, thereby impeding research progress. Existing tools in this landscape require a profound understanding of ML principles and programming skills. Furthermore, users are required to engage in the comprehensive configuration of their ML pipeline to obtain optimal performance.

RESULTS

To address these challenges, we have developed a novel tool called Machine Learning Made Easy (MLme) that streamlines the use of ML in research, specifically focusing on classification problems at present. By integrating 4 essential functionalities-namely, Data Exploration, AutoML, CustomML, and Visualization-MLme fulfills the diverse requirements of researchers while eliminating the need for extensive coding efforts. To demonstrate the applicability of MLme, we conducted rigorous testing on 6 distinct datasets, each presenting unique characteristics and challenges. Our results consistently showed promising performance across different datasets, reaffirming the versatility and effectiveness of the tool. Additionally, by utilizing MLme's feature selection functionality, we successfully identified significant markers for CD8+ naive (BACH2), CD16+ (CD16), and CD14+ (VCAN) cell populations.

CONCLUSION

MLme serves as a valuable resource for leveraging ML to facilitate insightful data analysis and enhance research outcomes, while alleviating concerns related to complex coding scripts. The source code and a detailed tutorial for MLme are available at https://github.com/FunctionalUrology/MLme.

Comprehensive analyses identify potential biomarkers for encephalitis in HIV infection

Human immunodeficiency virus encephalitis (HIVE) is a severe neurological complication after HIV infection. Evidence shows that genetic factors play an important role in HIVE. The aim of the present study was to identify new potential therapeutic targets for HIVE. Differentially expressed gene (DEG), functional annotation and pathway, and protein-protein interaction analyses were performed to identify the hub genes associated with HIVE. Gene co-expression analysis was carried out to confirm the association between the hub genes and HIVE. Finally, the role of the hub genes in HIVE therapy was evaluated by conducting drug-gene interaction analysis. A total of 20 overlapping DEGs closely related to HIVE were identified. Functional annotation and pathway enrichment analysis indicated that the markedly enriched DEG terms included ion transport, type II interferon signaling, and synaptic signaling. Moreover, protein-protein interaction analysis revealed that 10 key HIVE-related genes were hub genes, including SCN8A, CDK5R2, GRM5, SCN2B, IFI44L, STAT1, SLC17A7, ISG15, FGF12, and FGF13. Furthermore, six hub genes were co-expressed with HIVE-associated host genes in human brain tissue. Finally, three hub genes (STAT1, ISG15, and SCN2B) interacted with several inflammation-associated drugs. These findings suggested that SCN8A, CDK5R2, GRM5, SCN2B, IFI44L, STAT1, SLC17A7, ISG15, FGF12, and FGF13 may be new targets for diagnosis and therapy of HIVE.

Autoimmune uveitis in Behçet's disease and Vogt-Koyanagi-Harada disease differ in tissue immune infiltration and T cell clonality

Objectives

Non-infectious uveitis is often secondary to systemic autoimmune diseases, with Behçet's disease (BD) and Vogt-Koyanagi-Harada disease (VKHD) as the two most common causes. Uveitis in BD and VKHD can show similar clinical manifestations, but the underlying immunopathogenesis remains unclear.

Methods

To understand immune landscapes in inflammatory eye tissues, we performed single-cell RNA paired with T cell receptor (TCR) sequencing of immune cell infiltrates in aqueous humour from six patients with BD (N = 3) and VKHD (N = 3) uveitis patients.

Results

Although T cells strongly infiltrated in both types of autoimmune uveitis, myeloid cells only significantly presented in BD uveitis but not in VKHD uveitis. Conversely, VKHD uveitis but not BD uveitis showed an overwhelming dominance by CD4+ T cells (> 80%) within the T cell population due to expansion of CD4+ T cell clusters with effector memory (Tem) phenotypes. Correspondingly, VKHD uveitis demonstrated a selective expansion of CD4+ T cell clones which were enriched in pro-inflammatory Granzyme H+ CD4+ Tem cluster and showed TCR and Th1 pathway activation. In contrast, BD uveitis showed a preferential expansion of CD8+ T cell clones in pro-inflammatory Granzyme H+ CD8+ Tem cluster, and pathway activation for cytoskeleton remodelling, cellular adhesion and cytotoxicity.

Conclusion

Single-cell analyses of ocular tissues reveal distinct landscapes of immune cell infiltration and T-cell clonal expansions between VKHD and BD uveitis. Preferential involvements of pro-inflammatory CD4+ Th1 cells in VKHD and cytotoxic CD8+ T cells in BD suggest a difference in disease immunopathogenesis and can guide precision disease management.

Therapeutic Effects of Upadacitinib on Experimental Autoimmune Uveitis: Insights From Single-Cell Analysis

Purpose

This study aimed to elucidate the impact of upadacitinib, a Janus kinase 1 (JAK1)-specific inhibitor, on experimental autoimmune uveitis (EAU) and explore its underlying mechanisms.

Methods

We utilized single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) to investigate the JAK/signal transducer and activator of transcription (STAT) pathway in peripheral blood mononuclear cells (PBMCs) of 12 patients with Vogt-Koyanagi-Harada (VKH) disease and cervical draining lymph node (CDLN) cells of EAU. After treating EAU with upadacitinib, we analyzed immune cell gene expression and cell-cell communication by integrating scRNA data. Additionally, we applied flow cytometry and western blot to analyze the CDLN cells.

Results

The JAK/STAT pathway was found to be upregulated in patients with VKH disease and EAU. Upadacitinib effectively alleviated EAU symptoms, reduced JAK1 protein expression, and suppressed pathogenic CD4 T cell (CD4TC) proliferation and pathogenicity while promoting Treg proliferation. The inhibition of pathogenic CD4TCs by upadacitinib was observed in both flow cytometry and scRNA data. Additionally, upadacitinib was found to rescue the interferon-stimulated gene 15 (ISG15)+ CD4TCs and CD8 T and B cell ratios and reduce expression of inflammatory-related genes. Upadacitinib demonstrated the ability to inhibit abnormally activated cell-cell communication, particularly the CXCR4-mediated migration pathway, which has been implicated in EAU pathogenesis. CXCR4 inhibitors showed promising therapeutic effects in EAU.

Conclusions

Our findings indicate that the JAK1-mediated signaling pathway is significantly upregulated in uveitis, and upadacitinib exhibits therapeutic efficacy against EAU. Furthermore, targeting the CXCR4-mediated migration pathway could be a promising therapeutic strategy.

Single-cell multi-omics topic embedding reveals cell-type-specific and COVID-19 severity-related immune signatures

The advent of single-cell multi-omics sequencing technology makes it possible for researchers to leverage multiple modalities for individual cells and explore cell heterogeneity. However, the high-dimensional, discrete, and sparse nature of the data make the downstream analysis particularly challenging. Here, we propose an interpretable deep learning method called moETM to perform integrative analysis of high-dimensional single-cell multimodal data. moETM integrates multiple omics data via a product-of-experts in the encoder and employs multiple linear decoders to learn the multi-omics signatures. moETM demonstrates superior performance compared with six state-of-the-art methods on seven publicly available datasets. By applying moETM to the scRNA + scATAC data, we identified sequence motifs corresponding to the transcription factors regulating immune gene signatures. Applying moETM to CITE-seq data from the COVID-19 patients revealed not only known immune cell-type-specific signatures but also composite multi-omics biomarkers of critical conditions due to COVID-19, thus providing insights from both biological and clinical perspectives.

Comparative analyses of monocyte memory dynamics from mice to humans

BACKGROUND

Innate monocytes can adopt dynamic "memory" states ranging from low-grade inflammation to pathogenic exhaustion, dependent upon signal strength and history of challenges. Low-grade inflammatory monocytes facilitate the pathogenesis of chronic inflammatory diseases, while exhausted monocytes drive the pathogenesis of severe sepsis. Although clinical and basic studies suggest the conservation of key features of exhausted monocytes from human and murine sepsis, systems analyses of monocyte exhaustion among human and murine monocytes are lacking.

METHODS

We performed cross examination of septic monocytes scRNAseq data recently collected from human sepsis patients as well as experimental septic mice, in reference to monocytes experimentally exhausted in vitro. Furthermore, we performed pseudo-time analyses of in vitro programmed monocytes following prolonged challenges causing either low-grade inflammation or exhaustion. Additional comparative analyses of low-grade inflammatory monocytes were performed with scRNAseq data from selected human patients with chronic low-grade inflammatory diseases.

RESULTS

Our systems analyses reveal key features of monocyte exhaustion including reduced differentiation, pathogenic inflammation and immune suppression that are highly conserved in human and murine septic monocytes, and captured by in vitro experimental exhaustion. Pseudo-time analyses reveal that monocytes initially transition into a less-differentiated state with proliferative potential. The expansion of proliferative monocytes can be observed not only in experimentally challenged monocytes, but also in tissues of murine sepsis and human septic blood. We observed that monocytes similarly transition into the less-differentiated state when challenged with a subclinical dose endotoxin under chronic inflammatory conditions. Instead of being exhausted, monocytes with prolonged challenges with super-low dose endotoxin bifurcate into the low-grade inflammatory immune-enhancing or the chemotactic/adhesive state, often see in atherosclerosis or auto-immune diseases.

CONCLUSIONS

Key features of monocyte memory dynamics are identified and conserved in human and murine monocytes, which can be captured by prolonged challenges of innate signals with varying signal strength.

Machine Learning Made Easy (MLme): A Comprehensive Toolkit for Machine Learning-Driven Data Analysis

Background

Machine learning (ML) has emerged as a vital asset for researchers to analyze and extract valuable information from complex datasets. However, developing an effective and robust ML pipeline can present a real challenge, demanding considerable time and effort, thereby impeding research progress. Existing tools in this landscape require a profound understanding of ML principles and programming skills. Furthermore, users are required to engage in the comprehensive configuration of their ML pipeline to obtain optimal performance.

Results

To address these challenges, we have developed a novel tool called Machine Learning Made Easy (MLme) that streamlines the use of ML in research, specifically focusing on classification problems at present. By integrating four essential functionalities, namely Data Exploration, AutoML, CustomML, and Visualization, MLme fulfills the diverse requirements of researchers while eliminating the need for extensive coding efforts. To demonstrate the applicability of MLme, we conducted rigorous testing on six distinct datasets, each presenting unique characteristics and challenges. Our results consistently showed promising performance across different datasets, reaffirming the versatility and effectiveness of the tool. Additionally, by utilizing MLme's feature selection functionality, we successfully identified significant markers for CD8+ naive (BACH2), CD16+ (CD16), and CD14+ (VCAN) cell populations.

Conclusion

MLme serves as a valuable resource for leveraging machine learning (ML) to facilitate insightful data analysis and enhance research outcomes, while alleviating concerns related to complex coding scripts. The source code and a detailed tutorial for MLme are available at https://github.com/FunctionalUrology/MLme.

Single-cell multi-omic topic embedding reveals cell-type-specific and COVID-19 severity-related immune signatures

The advent of single-cell multi-omics sequencing technology makes it possible for re-searchers to leverage multiple modalities for individual cells and explore cell heterogeneity. However, the high dimensional, discrete, and sparse nature of the data make the downstream analysis particularly challenging. Most of the existing computational methods for single-cell data analysis are either limited to single modality or lack flexibility and interpretability. In this study, we propose an interpretable deep learning method called multi-omic embedded topic model (moETM) to effectively perform integrative analysis of high-dimensional single-cell multimodal data. moETM integrates multiple omics data via a product-of-experts in the encoder for efficient variational inference and then employs multiple linear decoders to learn the multi-omic signatures of the gene regulatory programs. Through comprehensive experiments on public single-cell transcriptome and chromatin accessibility data (i.e., scRNA+scATAC), as well as scRNA and proteomic data (i.e., CITE-seq), moETM demonstrates superior performance compared with six state-of-the-art single-cell data analysis methods on seven publicly available datasets. By applying moETM to the scRNA+scATAC data in human bone marrow mononuclear cells (BMMCs), we identified sequence motifs corresponding to the transcription factors that regulate immune gene signatures. Applying moETM analysis to CITE-seq data from the COVID-19 patients revealed not only known immune cell-type-specific signatures but also composite multi-omic biomarkers of critical conditions due to COVID-19, thus providing insights from both biological and clinical perspectives.

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.

Single-cell mass cytometry on peripheral cells in Myasthenia Gravis identifies dysregulation of innate immune cells

Myasthenia Gravis (MG) is a neurological autoimmune disease characterized by disabling muscle weaknesses due to anti-acetylcholine receptor (AChR) autoantibodies. To gain insight into immune dysregulation underlying early-onset AChR⁺ MG, we performed an in-depth analysis of peripheral mononuclear blood cells (PBMCs) using mass cytometry. PBMCs from 24 AChR⁺ MG patients without thymoma and 16 controls were stained with a panel of 37 antibodies. Using both unsupervised and supervised approaches, we observed a decrease in monocytes, for all subpopulations: classical, intermediate, and non-classical monocytes. In contrast, an increase in innate lymphoid cells 2 (ILC2s) and CD27^- γδ T cells was observed. We further investigated the dysregulations affecting monocytes and γδ T cells in MG. We analyzed CD27^- γδ T cells in PBMCs and thymic cells from AChR⁺ MG patients. We detected the increase in CD27^- γδ T cells in thymic cells of MG patients suggesting that the inflammatory thymic environment might affect γδ T cell differentiation. To better understand changes that might affect monocytes, we analyzed RNA sequencing data from CD14⁺ PBMCs and showed a global decrease activity of monocytes in MG patients. Next, by flow cytometry, we especially confirmed the decrease affecting non-classical monocytes. In MG, as for other B-cell mediated autoimmune diseases, dysregulations are well known for adaptive immune cells, such as B and T cells. Here, using single-cell mass cytometry, we unraveled unexpected dysregulations for innate immune cells. If these cells are known to be crucial for host defense, our results demonstrated that they could also be involved in autoimmunity.

Insights gained from single-cell analysis of immune cells in tofacitinib treatment of Vogt-Koyanagi-Harada disease

Vogt-Koyanagi-Harada disease (VKH) is an important refractory uveitis mediated by pathological T cells (TCs). Tofacitinib (TOFA) is a JAK- targeted therapy for several autoimmune diseases. However, the specific pathogenesis and targeted therapeutics for VKH remain largely unknown. Based on single-cell RNA sequencing and mass cytometry, we present what we believe is the first multimodal, high-dimensional analysis to generate a comprehensive human immune atlas regarding subset composition, gene signatures, enriched pathways, and intercellular interactions of VKH patients undergoing TOFA therapy. Patients with VKH are characterized by TCs' polarization from naive to effector and memory subsets, together with accrued monocytes and upregulated cytokines and JAK/STAT signaling pathways. In vitro, TOFA reversed Th17/Treg imbalance and inhibited IL-2-induced STAT1/3 phosphorylation. TOFA alleviated VKH symptoms by restoring pathological TCs' polarization and functional marker expression and downregulating cytokine signaling and lymphocyte function. Remarkably, inflammation-related responses and intercellular interactions decreased after TOFA treatment, particularly in monocytes. Notably, we identified 2 inflammation- and JAK-associated monocyte subpopulations that were strongly implicated in VKH pathogenesis and mechanisms involved in TOFA treatment. Here, we provide a potentially novel JAK-targeted therapy for VKH and elaborate on the possible therapeutic mechanisms of TOFA, expanding our knowledge of VKH pathological patterns.

Single-cell multiomics revealed the dynamics of antigen presentation, immune response and T cell activation in the COVID-19 positive and recovered individuals

Introduction

Despite numerous efforts to describe COVID-19's immunological landscape, there is still a gap in our understanding of the virus's infections after-effects, especially in the recovered patients. This would be important to understand as we now have huge number of global populations infected by the SARS-CoV-2 as well as variables inclusive of VOCs, reinfections, and vaccination breakthroughs. Furthermore, single-cell transcriptome alone is often insufficient to understand the complex human host immune landscape underlying differential disease severity and clinical outcome.

Methods

By combining single-cell multi-omics (Whole Transcriptome Analysis plus Antibody-seq) and machine learning-based analysis, we aim to better understand the functional aspects of cellular and immunological heterogeneity in the COVID-19 positive, recovered and the healthy individuals.

Results

Based on single-cell transcriptome and surface marker study of 163,197 cells (124,726 cells after data QC) from the 33 individuals (healthy=4, COVID-19 positive=16, and COVID-19 recovered=13), we observed a reduced MHC Class-I-mediated antigen presentation and dysregulated MHC Class-II-mediated antigen presentation in the COVID-19 patients, with restoration of the process in the recovered individuals. B-cell maturation process was also impaired in the positive and the recovered individuals. Importantly, we discovered that a subset of the naive T-cells from the healthy individuals were absent from the recovered individuals, suggesting a post-infection inflammatory stage. Both COVID-19 positive patients and the recovered individuals exhibited a CD40-CD40LG-mediated inflammatory response in the monocytes and T-cell subsets. T-cells, NK-cells, and monocyte-mediated elevation of immunological, stress and antiviral responses were also seen in the COVID-19 positive and the recovered individuals, along with an abnormal T-cell activation, inflammatory response, and faster cellular transition of T cell subtypes in the COVID-19 patients. Importantly, above immune findings were used for a Bayesian network model, which significantly revealed FOS, CXCL8, IL1β, CST3, PSAP, CD45 and CD74 as COVID-19 severity predictors.

Discussion

In conclusion, COVID-19 recovered individuals exhibited a hyper-activated inflammatory response with the loss of B cell maturation, suggesting an impeded post-infection stage, necessitating further research to delineate the dynamic immune response associated with the COVID-19. To our knowledge this is first multi-omic study trying to understand the differential and dynamic immune response underlying the sample subtypes.

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.

Single-cell RNA sequencing reveals a landscape and targeted treatment of ferroptosis in retinal ischemia/reperfusion injury

BACKGROUND

The aim of this study was to establish a complete retinal cell atlas of ischemia-reperfusion injury by single-cell RNA sequencing, and to explore the underlying mechanism of retinal ischemia-reperfusion injury in mice.

METHODS

Single-cell RNA sequencing was used to evaluate changes in the mouse retinal ischemia reperfusion model. In vivo and in vitro experiments were performed to verify the protective effect of inhibiting ferroptosis in retinal ischemia-reperfusion injury.

RESULTS

After ischemia-reperfusion injury, retinal cells were significantly reduced, accompanied by the activation of myeloid and a large amount of blood-derived immune cell infiltration. The IFNG, MAPK and NFKB signaling pathways in retinal neuronal cells, together with the TNF signaling pathway in myeloid give rise to a strong inflammatory response in the I/R state. Besides, the expression of genes implicating iron metabolism, oxidative stress and multiple programed cell death pathways have changed in cell subtypes described above. Especially the ferroptosis-related genes and blocking this process could apparently alleviate the inflammatory immune responses and enhance retinal ganglion cells survival.

CONCLUSIONS

We established a comprehensive landscape of mouse retinal ischemia-reperfusion injury at the single-cell level, revealing the important role of ferroptosis during this injury, and targeted inhibition of ferroptosis can effectively protect retinal structure and function.

Distinct responses of newly identified monocyte subsets to advanced gastrointestinal cancer and COVID-19

Monocytes are critical cells of the immune system but their role as effectors is relatively poorly understood, as they have long been considered only as precursors of tissue macrophages or dendritic cells. Moreover, it is known that this cell type is heterogeneous, but our understanding of this aspect is limited to the broad classification in classical/intermediate/non-classical monocytes, commonly based on their expression of only two markers, i.e. CD14 and CD16. We deeply dissected the heterogeneity of human circulating monocytes in healthy donors by transcriptomic analysis at single-cell level and identified 9 distinct monocyte populations characterized each by a profile suggestive of specialized functions. The classical monocyte subset in fact included five distinct populations, each enriched for transcriptomic gene sets related to either inflammatory, neutrophil-like, interferon-related, and platelet-related pathways. Non-classical monocytes included two distinct populations, one of which marked specifically by elevated expression levels of complement components. Intermediate monocytes were not further divided in our analysis and were characterized by high levels of human leukocyte antigen (HLA) genes. Finally, we identified one cluster included in both classical and non-classical monocytes, characterized by a strong cytotoxic signature. These findings provided the rationale to exploit the relevance of newly identified monocyte populations in disease evolution. A machine learning approach was developed and applied to two single-cell transcriptome public datasets, from gastrointestinal cancer and Coronavirus disease 2019 (COVID-19) patients. The dissection of these datasets through our classification revealed that patients with advanced cancers showed a selective increase in monocytes enriched in platelet-related pathways. Of note, the signature associated with this population correlated with worse prognosis in gastric cancer patients. Conversely, after immunotherapy, the most activated population was composed of interferon-related monocytes, consistent with an upregulation in interferon-related genes in responder patients compared to non-responders. In COVID-19 patients we confirmed a global activated phenotype of the entire monocyte compartment, but our classification revealed that only cytotoxic monocytes are expanded during the disease progression. Collectively, this study unravels an unexpected complexity among human circulating monocytes and highlights the existence of specialized populations differently engaged depending on the pathological context.

Identification of differently expressed mRNAs by peripheral blood mononuclear cells in Vogt-Koyanagi-Harada disease

Vogt-Koyanagi-Harada disease (VKH) is a rare autoimmune disease characterized by diffuse and bilateral uveitis, alopecia, tinnitus, hearing loss, vitiligo and headache. The transcriptional expression pattern of peripheral blood mononuclear cells (PBMC) in VKH remains largely unknown. In this study, mRNA sequencing was conducted in PBMC from VKH patients with active uveitis before treatment (n = 7), the same patients after prednisone combined with cyclosporine treatment (n = 7) and healthy control subjects strictly matched with gender and age (n = 7). We found 118 differentially expressed genes (DEGs) between VKH patients and healthy control subjects, and 21 DEGs between VKH patients before and after treatment. TRIB1 was selected as a potential biomarker to monitor the development of VKH according to the mRNA sequencing. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed to predict the possible biological functions and signaling pathways of DEGs. Neutrophil degranulation, peptidase regulator activity, secretory granule membrane, cellular response to peptide, growth factor binding and cell projection membrane were enriched as GO annotations of DEGs. Arachidonic acid metabolism and mitogen-activated protein kinase (MAPK) signaling pathway were potential signaling pathways involved in pathogenesis and drug response of VKH. A protein–protein interaction (PPI) network was constructed by STRING, and colony stimulating factor 1 receptor (CSF1R) was identified as the hubgene of all DEGs by Cytoscape. The cell type presumed to contribute to the aberrant expression of DEGs was analyzed with the use of publicly available single-cell sequencing data of PBMC from a healthy donor and single-cell sequencing dataset of monocytes from VKH patients. Our findings may help to decipher the underlying cellular and molecular pathogenesis of VKH and may lead novel therapeutic applications.

Single-cell and spatial mapping Identify cell types and signaling Networks in the human ureter

Tissue engineering offers a promising treatment strategy for ureteral strictures, but its success requires an in-depth understanding of the architecture, cellular heterogeneity, and signaling pathways underlying tissue regeneration. Here, we define and spatially map cell populations within the human ureter using single-cell RNA sequencing, spatial gene expression, and immunofluorescence approaches. We focus on the stromal and urothelial cell populations to enumerate the distinct cell types composing the human ureter and infer potential cell-cell communication networks underpinning the bi-directional crosstalk between these compartments. Furthermore, we analyze and experimentally validate the importance of the sonic hedgehog (SHH) signaling pathway in adult progenitor cell maintenance. The SHH-expressing basal cells support organoid generation in vitro and accurately predict the differentiation trajectory from basal progenitor cells to terminally differentiated umbrella cells. Our results highlight the essential processes involved in adult ureter tissue homeostasis and provide a blueprint for guiding ureter tissue engineering.

Single-Cell Transcriptome Analysis of Radiation Pneumonitis Mice

Radiation-induced lung injury (RILI), especially radiation pneumonitis (RP), is a common clinical complication associated with thoracic radiotherapy for malignant tumors. However, the specific contributions of each cell subtype to this process are unknown. Here, we provide the single-cell pathology landscape of the RP in a mouse model by unbiased single-cell RNA-seq (scRNA-seq). We found a decline of type 2 alveolar cells in the RP lung tissue, with an expansion of macrophages, especially the Fabp4low and Spp1high subgroup, while Fabp4high macrophages were almost depleted. We observed an elevated expression of multiple mitochondrial genes in the RP group, indicating a type 2 alveolar cell (AT2) response to oxidative stress. We also calculated the enrichment of a cGAS-STING signaling pathway, which may be involved in regulating inflammatory responses and cancer progression in AT2 cells of PR mice. We delineate markers and transcriptional states, identify a type 2 alveolar cell, and uncover fundamental determinants of lung fibrosis and inflammatory response in RP lung tissue of mice.

Identification of immune hub genes participating in the pathogenesis and progression of Vogt-Koyanagi-Harada disease

Background

Vogt-Koyanagi-Harada (VKH) disease is an autoimmune inflammatory disorder characterized by bilateral granulomatous uveitis. The objective of this study was to identify immune hub genes involved in the pathogenesis and progression of VKH disease.

Methods

High throughput sequencing data were downloaded from the Gene Expression Omnibus (GEO) and an immune dataset was downloaded from ImmPort. Immune differentially expressed genes (DEGs) were obtained from their intersection in the GEO and ImmPort datasets. Immune hub genes for VKH disease were selected through differential expression analyses, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Disease Ontology (DO), protein-protein interaction (PPI) network, and clustering analyses. Confidence in the immune hub genes was subsequently validated using box plots and receiver operating characteristic (ROC) curves.

Results

A total of 254 DEGs were screened and after the intersection with ImmPort, 20 genes were obtained as immune DEGs. Functional enrichment analysis indicated that the key genes were mainly involved in several types of immune pathways (such as the lymphocyte mediated and leukocyte mediated immune responses, natural killer cell mediated cytotoxicity, and antigen binding) and immunodeficiency diseases. Following PPI network analysis, the top seven genes in cluster 1 were selected as potential immune hub genes in VKH. After evaluating the accuracy of the hub genes, one gene (GNLY) was excluded because its expression level was statistically similar in VKH patients and healthy controls. Finally, six immune hub genes, namely KLRC2, KLRC3 SH2D1B, GZMB, KIR2DL3, and KIR3DL2 were identified as playing important roles in the occurrence and development of VKH disease.

Conclusion

Six immune hub genes (KLRC2, KLRC3 SH2D1B, GZMB, KIR2DL3, and KIR3DL2) identified by our bioinformatics analyses may provide new diagnostic and therapeutic targets for VKH disease.

A map of the spatial distribution and tumour-associated macrophage states in glioblastoma and grade-4 IDH-mutant astrocytoma

Tumour-associated macrophages (TAMs) abundantly infiltrate high-grade gliomas and orchestrate immune response, but their diversity in isocitrate dehydrogenase (IDH)-differential grade-4 gliomas remains largely unknown. This study aimed to dissect the transcriptional states, spatial distribution and clinicopathological significance of distinct monocyte-derived TAM (Mo-TAM) and microglia-derived TAM (Mg-TAM) clusters across glioblastoma-IDH-wildtype and astrocytoma-IDH-mutant-grade 4 (Astro-IDH-mut-G4). Single-cell RNA sequencing was performed on four cases of human glioblastoma and three cases of Astro-IDH-mut-G4. Cell clustering, single-cell regulatory network inference and gene set enrichment analysis were performed to characterize the functional states of myeloid clusters. Spatial distribution of TAM subsets was determined in human glioma tissues using multiplex immunostaining. The prognostic value of different TAM-cluster specific geneset was evaluated in the TCGA glioma cohort. Profiling and unbiased clustering of 24,227 myeloid cells from glioblastoma and Astro-IDH-mut-G4 identified 9 myeloid cell clusters including monocyte, six Mo/Mg-TAM subsets, dendritic cell, and proliferative myeloid cluster. Different Mo/Mg-TAM clusters manifest functional and transcriptional diversity controlled by specific regulons. Multiplex immunostaining of subset-specific markers identified spatial enrichment of distinct TAM clusters at peri-vascular/necrotic areas in tumour parenchyma or at tumour-brain interface. Glioblastoma harboured a substantially higher number of monocytes and Mo-TAM-inflammatory cluster, whereas Astro-IDH-mut-G4 was with higher proportion of TAM subset mediating antigen presentation. Glioblastomas with higher proportion of monocytes exhibited a mesenchymal signature, increased angiogenesis and worse patient outcome. Our findings provide insight into myeloid cell diversity and its clinical relevance in IDH-differential grade-4 gliomas, and may serve as a resource for immunotherapy development. This article is protected by copyright. All rights reserved.

Chromatin accessibility analysis reveals regulatory dynamics and therapeutic relevance of Vogt-Koyanagi-Harada disease

The barrier to curing Vogt-Koyanagi-Harada disease (VKH) is thought to reside in a lack of understanding in the roles and regulations of peripheral inflammatory immune cells. Here we perform a single-cell multi-omic study of 166,149 cells in peripheral blood mononuclear cells from patients with VKH, profile the chromatin accessibility and gene expression in the same blood samples, and uncover prominent cellular heterogeneity. Immune cells in VKH blood are highly activated and pro-inflammatory. Notably, we describe an enrichment of transcription targets for nuclear factor kappa B in conventional dendritic cells (cDCs) that governed inflammation. Integrative analysis of transcriptomic and chromatin maps shows that the RELA in cDCs is related to disease complications and poor prognosis. Ligand-receptor interaction pairs also identify cDC as an important predictor that regulated multiple immune subsets. Our results reveal epigenetic and transcriptional dynamics in auto-inflammation, especially the cDC subtype that might lead to therapeutic strategies in VKH.

Genetic landscape and autoimmunity of monocytes in developing Vogt-Koyanagi-Harada disease

Vogt-Koyanagi-Harada (VKH) disease is a systemic autoimmune disorder affecting multiple organs, including eyes, skin, and central nervous system. It is known that monocytes significantly contribute to the development of autoimmune disease. However, the subset heterogeneity with unique functions and signatures in human circulating monocytes and the identity of disease-specific monocytic populations remain largely unknown. Here, we employed an advanced single-cell RNA sequencing technology to systematically analyze 11,259 human circulating monocytes and genetically defined their subpopulations. We constructed a precise atlas of human blood monocytes, identified six subpopulations-including S100A12, HLA, CD16, proinflammatory, megakaryocyte-like, and NK-like monocyte subsets-and uncovered two previously unidentified subsets: HLA and megakaryocyte-like monocyte subsets. Relative to healthy individuals, cellular composition, gene expression signatures, and activation states were markedly alternated in VKH patients utilizing cell type-specific programs, especially the CD16 and proinflammatory monocyte subpopulations. Notably, we discovered a disease-relevant subgroup, proinflammatory monocytes, which showed a discriminative gene expression signature indicative of inflammation, antiviral activity, and pathologic activation, and converted into a pathologic activation state implicating the active inflammation during VKH disease. Additionally, we found the cell type-specific transcriptional signature of proinflammatory monocytes, ISG15, whose production might reflect the treatment response. Taken together, in this study, we present discoveries on accurate classification, molecular markers, and signaling pathways for VKH disease-associated monocytes. Therapeutically targeting this proinflammatory monocyte subpopulation would provide an attractive approach for treating VKH, as well as other autoimmune diseases.