Machine learning-driven immunophenotypic stratification of mixed connective tissue disease corroborating the clinical heterogeneity.

OBJECTIVES: To stratify patients with mixed connective tissue disease (MCTD) based on their immunophenotype. METHODS: We analyzed the immunophenotype and transcriptome of 24 immune cell subsets from patients with MCTD, systemic lupus erythematosus (SLE), idiopathic inflammatory myopathy (IIM), and systemic sclerosis (SSc) from our functional genome database, ImmuNexUT (https://www.immunexut.org/). MCTD patients were stratified by employing machine learning models including Random Forest, trained by immunophenotyping data from SLE, IIM, and SSc patients. Transcriptomes were analyzed with gene set variation analysis (GSVA) and clinical features of MCTD subgroups were compared. RESULTS: This study included 215 patients, including 22 patients with MCTD. Machine learning models, constructed to classify SLE, IIM, and SSc patients based on immunophenotyping, were applied to MCTD patients, resulting in 16 classified as SLE-immunophenotype and 6 as non-SLE-immunophenotype. Among MCTD patients, patients with the SLE-immunophenotype had higher proportions of Th1 cells [2.85% (interquartile range (IQR) 1.54-3.91) vs 1.33% (IQR 0.99-1.74) p= 0.027] and plasmablasts [6.35% (IQR 4.17-17.49) vs 2.00% (IQR 1.20-2.80) p= 0.010]. Notably, the number of SLE-related symptoms was higher in patients with the SLE-immunophenotype [2.0 (IQR 1.0-2.0) vs 1.0 (IQR1.0-1.0) p= 0.038]. Moreover, GSVA scores of interferon-α and -γ responses were significantly higher in patients with the SLE-immunophenotype in central memory CD8+ T cells, while hedgehog signalling was higher in non-SLE-immunophenotype patients in 5 cell subsets. CONCLUSION: This study describes the stratification of MCTD patients based on immunophenotyping, suggesting the presence of distinct immunological processes behind the clinical subtypes of MCTD.

Age-associated CD4+ T cells with B cell-promoting functions are regulated by ZEB2 in autoimmunity.

Aging is a significant risk factor for autoimmunity, and many autoimmune diseases tend to onset during adulthood. We conducted an extensive analysis of CD4+ T cell subsets from 354 patients with autoimmune disease and healthy controls via flow cytometry and bulk RNA sequencing. As a result, we identified a distinct CXCR3midCD4+ effector memory T cell subset that expands with age, which we designated "age-associated T helper (THA) cells." THA cells exhibited both a cytotoxic phenotype and B cell helper functions, and these features were regulated by the transcription factor ZEB2. Consistent with the highly skewed T cell receptor usage of THA cells, gene expression in THA cells from patients with systemic lupus erythematosus reflected disease activity and was affected by treatment with a calcineurin inhibitor. Moreover, analysis of single-cell RNA sequencing data revealed that THA cells infiltrate damaged organs in patients with autoimmune diseases. Together, our characterization of THA cells may facilitate improved understanding of the relationship between aging and autoimmune diseases.

Autoantibodies to nuclear valosin-containing protein-like protein: systemic sclerosis-specific antibodies revealed by in vitro human proteome.

OBJECTIVES: To identify and characterize undescribed systemic sclerosis (SSc)-specific autoantibodies targeting nucleolar antigens and to assess their clinical significance. METHODS: We conducted proteome-wide autoantibody screening (PWAS) against serum samples from SSc patients with nucleolar patterned anti-nuclear antibodies (NUC-ANAs) of specific antibodies (Abs) unknown, utilizing wet protein arrays fabricated from in vitro human proteome. Controls included SSc patients with already-known SSc-specific autoantibodies, patients with other connective tissue diseases, and healthy subjects. The selection of nucleolar antigens was performed by database search in the Human Protein Atlas. The Presence of autoantibodies was certified by immunoblots and immunoprecipitations. Indirect immunofluorescence assays on HEp-2 cells were also conducted. Clinical assessment was conducted by retrospective review of electric medical records. RESULTS: PWAS identified three candidate autoantibodies, including anti-nuclear valosin-containing protein-like (NVL) Ab. Additional measurements in disease controls revealed that only anti-NVL Abs are exclusively detected in SSc. Detection of anti-NVL Abs was reproduced by conventional assays such as immunoblotting and immunoprecipitation. Indirect immunofluorescence assays demonstrated homogeneous nucleolar patterns. Anti-NVL Ab-positive cases were characterized by significantly low prevalence of diffuse skin sclerosis and interstitial lung disease, compared with SSc cases with NUC-ANAs other than anti-NVL Abs, such as anti-U3-RNP and anti-Th/To Abs. CONCLUSION: Anti-NVL Ab is an SSc-specific autoantibody associated with a unique combination of clinical features, including limited skin sclerosis and lack of lung involvement.

Multimodal repertoire analysis unveils B cell biology in immune-mediated diseases.

OBJECTIVES: Despite the involvement of B cells in the pathogenesis of immune-mediated diseases (IMDs), biological mechanisms underlying their function are scarcely understood. To overcome this gap, here we constructed and investigated a large-scale repertoire catalogue of five B cell subsets of patients with IMDs. METHODS: We mapped B cell receptor regions from RNA sequencing data of sorted B cell subsets. Our dataset consisted of 595 donors under IMDs and health. We characterised the repertoire features from various aspects, including their association with immune cell transcriptomes and clinical features and their response to belimumab treatment. RESULTS: Heavy-chain complementarity-determining region 3 (CDR-H3) length among naïve B cells was shortened among autoimmune diseases. Strong negative correlation between interferon signature strength and CDR-H3 length was observed in naïve B cells and suggested the role for interferon in premature B cell development. VDJ gene usage was skewed especially in plasmablasts and unswitched-memory B cells of patients with systemic lupus erythematosus (SLE). We developed a scoring system to quantify this skewing, and it positively correlated with peripheral helper T cell transcriptomic signatures and negatively correlated with the amount of somatic hyper mutations in plasmablasts, suggesting the association of extrafollicular pathway. Further, this skewing led to high usage of IGHV4-34 gene with 9G4 idiotypes in unswitched-memory B cells, which showed a prominent positive correlation with disease activity in SLE. Gene usage skewing in unswitched-memory B cells was ameliorated after belimumab treatment. CONCLUSIONS: Our multimodal repertoire analysis enabled us the system-level understanding of B cell abnormality in diseases.

Synovial Tissue Heterogeneity in Japanese Patients With Rheumatoid Arthritis Elucidated Using a Cell-Type Deconvolution Approach.

OBJECTIVE: Recent advances in single-cell RNA sequencing technology have improved our understanding of the immunological landscape of rheumatoid arthritis (RA). We aimed to stratify the synovium from East Asian patients with RA by immune cell compositions and gain insight into the inflammatory drivers of each synovial phenotype. METHODS: Synovial tissues were obtained from East Asian patients in Japan with RA (n = 41) undergoing articular surgery. The cellular composition was quantified by a deconvolution approach using a public single-cell-based reference. Inflammatory pathway activity was calculated by gene set variation analysis, and chromatin accessibility was evaluated using assay of transposase accessible chromatin-sequencing. RESULTS: We stratified RA synovium into three distinct subtypes based on the hierarchical clustering of cellular composition data. One subtype was characterized by abundant HLA-DRAhigh synovial fibroblasts, autoimmune-associated B cells, GZMK+ GZMB+ CD8+ T cells, interleukin (IL)1-ß+ monocytes, and plasmablasts. In addition, tumor necrosis factor (TNF)-α, interferons (IFNs), and IL-6 signaling were highly activated in this subtype, and the expression of various chemokines was significantly enhanced. Moreover, we found an open chromatin region overlapping with RA risk locus rs9405192 near the IRF4 gene, suggesting the genetic background influences the development of this inflammatory synovial state. The other two subtypes were characterized by increased IFNs and IL-6 signaling, and expression of molecules associated with degeneration, respectively. CONCLUSION: This study adds insights into the synovial heterogeneity in East Asian patients and shows a promising link with predominant inflammatory signals. Evaluating the site of inflammation has the potential to lead to appropriate drug selection that matches the individual pathology.

Functional evaluation of rare OASL variants by analysis of SLE patient-derived iPSCs.

BACKGROUND: Systemic lupus erythematosus (SLE) is a chronic systemic autoimmune disease characterized by genetic heterogeneity and an interferon (IFN) signature. The overall landscapes of the heritability of SLE remains unclear. OBJECTIVES: To identify and elucidate the biological functions of rare variants underlying SLE, we conducted analyses of patient-derived induced pluripotent stem cells (iPSCs) in combination with genetic analysis. METHODS: Two familial SLE patient- and two healthy donor (HD)-derived iPSCs were established. Type 1 IFN-secreting dendritic cells (DCs) were differentiated from iPSCs. Genetic analyses of SLE-iPSCs, and 117 SLE patients and 107 HDs in the ImmuNexUT database were performed independently. Genome editing of the variants on iPSCs was performed with the CRISPR/Cas9 system. RESULTS: Type 1 IFN secretion was significantly increased in DCs differentiated from SLE-iPSCs compared to HD-iPSCs. Genetic analyses revealed a rare variant in the 2'-5'-Oligoadenylate Synthetase Like (OASL) shared between SLE-iPSCs and another independent SLE patient, and significant accumulation of OASL variants among SLE patients (HD 0.93%, SLE 6.84%, OR 8.387) in the database. Genome editing of mutated OASL 202Q to wild-type 202 R or wild-type OASL 202 R to mutated 202Q resulted in reduced or enhanced Type 1 IFN secretion of DCs. Three other OASL variants (R60W, T261S and A447V) accumulated in SLE patients had also capacities to enhance Type 1 IFN secretion in response to dsRNA. CONCLUSIONS: We established a patient-derived iPSC-based strategy to investigate the linkage of genotype and phenotype in autoimmune diseases. Detailed case-based investigations using patient-derived iPSCs provide information to unveil the heritability of the pathogenesis of autoimmune diseases.

Immunomics analysis of rheumatoid arthritis identified precursor dendritic cells as a key cell subset of treatment resistance.

OBJECTIVES: Little is known about the immunology underlying variable treatment response in rheumatoid arthritis (RA). We performed large-scale transcriptome analyses of peripheral blood immune cell subsets to identify immune cells that predict treatment resistance. METHODS: We isolated 18 peripheral blood immune cell subsets of 55 patients with RA requiring addition of new treatment and 39 healthy controls, and performed RNA sequencing. Transcriptome changes in RA and treatment effects were systematically characterised. Association between immune cell gene modules and treatment resistance was evaluated. We validated predictive value of identified parameters for treatment resistance using quantitative PCR (qPCR) and mass cytometric analysis cohorts. We also characterised the identified population by synovial single cell RNA-sequencing analysis. RESULTS: Immune cells of patients with RA were characterised by enhanced interferon and IL6-JAK-STAT3 signalling that demonstrate partial normalisation after treatment. A gene expression module of plasmacytoid dendritic cells (pDC) reflecting the expansion of dendritic cell precursors (pre-DC) exhibited strongest association with treatment resistance. Type I interferon signalling was negatively correlated to pre-DC gene expression. qPCR and mass cytometric analysis in independent cohorts validated that the pre-DC associated gene expression and the proportion of pre-DC were significantly higher before treatment in treatment-resistant patients. A cluster of synovial DCs showed both features of pre-DC and pro-inflammatory conventional DC2s. CONCLUSIONS: An increase in pre-DC in peripheral blood predicted RA treatment resistance. Pre-DC could have pathophysiological relevance to RA treatment response.

Significance of anti-transcobalamin receptor antibodies in cutaneous arteritis revealed by proteome-wide autoantibody screening.

Cutaneous arteritis (CA) is a single-organ vasculitis that exclusively affects the small to medium-sized arteries of the skin. Diagnosis depends on a histological investigation with skin biopsy, which could be burdensome for both patients and clinicians. Moreover, the pathogenesis of CA remains unstudied, and treatment has not yet been established. Herein, we applied our proteome-wide autoantibody screening method to explore autoantibodies in the serum of CA patients. As a result, anti-transcobalamin receptor (TCblR) antibodies (Abs) were specifically detected in 24% of CA patients. Patients with positive anti-TCblR Abs were spared from peripheral neuropathy compared to those with negative anti-TCblR Abs, showing characteristics as CA confined to the skin. In addition, we revealed that anti-TCblR Abs trigger the autocrine loop of interleukin-6 mediated by tripartite motif-containing protein 21 in human endothelial cells and induce periarterial inflammation in murine skin. Furthermore, we demonstrated that methylcobalamin, a ligand of TCblR, ameliorates inflammation caused by anti-TCblR Abs both in vitro and in vivo. Collectively, our investigation unveils the pathologic significance of anti-TCblR Abs in CA and their potential as a diagnostic marker and a pathophysiology-oriented therapeutic target.

Transcriptome Profiling of Immune Cell Types in Peripheral Blood Reveals Common and Specific Pathways Involved in the Pathogenesis of Myositis-Specific Antibody-Positive Inflammatory Myopathies.

OBJECTIVE: Idiopathic inflammatory myopathies (IIM) demonstrate characteristic clinical phenotypes depending on the myositis-specific antibody (MSAs) present. We aimed to identify common or MSA-specific immunological pathways in different immune cell types from peripheral blood by transcriptome analysis. METHODS: We recruited 33 patients with IIM who were separated into the following groups: 15 patients with active disease at onset and 18 with inactive disease under treatment. All patients were positive for MSAs: anti-melanoma differentiation-associated gene 5 (MDA5) antibody (Ab) in 10 patients, anti-Mi-2 Ab in 7, and anti-aminoacyl-transfer RNA synthetase (ARS) Ab in 16. The patients were compared with 33 healthy controls. Twenty-four immune cell types sorted from peripheral blood were analyzed by flow cytometry, RNA sequencing, and differentially expressed gene analysis combined with pathway analysis. RESULTS: The frequencies of memory B cell types were significantly decreased in active patients, and the frequency of plasmablasts was prominently increased in active patients with anti-MDA5 Ab in comparison with healthy controls. The expression of type I interferon (IFN)-stimulated genes of all immune cell types was increased in the active, but not inactive, patients. Endoplasmic reticulum stress-related genes in all IIM memory B cells and oxidative phosphorylation-related genes in inactive IIM double negative B cells were also increased, suggesting prominent B cell activation in IIM. Furthermore, active patients with anti-MDA5 Ab, anti-Mi-2 Ab, or anti-ARS Ab were distinguished by IFN-stimulated and oxidative phosphorylation-related gene expression in plasmablasts. CONCLUSION: Unique gene expression patterns in patients with IIM with different disease activity levels and MSA types suggest different pathophysiologies. Especially, B cells may contribute to common and MSA-specific immunological pathways in IIM.

Combined plasma metabolomic and transcriptomic analysis identify histidine as a biomarker and potential contributor in SLE pathogenesis.

OBJECTIVES: To investigate metabolite alterations in the plasma of SLE patients to identify novel biomarkers and provide insight into SLE pathogenesis. METHODS: Patients with SLE (n = 41, discovery cohort and n = 37, replication cohort), healthy controls (n = 30 and n = 29) and patients with RA (n = 19, disease control) were recruited. Metabolic profiles of the plasma samples were analysed using liquid chromatography-time-of-flight mass spectrometry and capillary electrophoresis-time-of-flight mass spectrometry. Transcriptome data was analysed using RNA-sequencing for 18 immune cell subsets. The importance of histidine (His) in plasmablast differentiation was investigated by using mouse splenic B cells. RESULTS: We demonstrate that a specific amino acid combination including His can effectively distinguish between SLE patients and healthy controls. Random forest and partial least squares-discriminant analysis identified His as an effective classifier for SLE patients. A decrease in His plasma levels correlated with damage accrual independent of prednisolone dosage and type I IFN signature. The oxidative phosphorylation signature in plasmablasts negatively correlated with His levels. We also showed that plasmablast differentiation induced by innate immune signals was dependent on His. CONCLUSIONS: Plasma His levels are a potential biomarker for SLE patients and are associated with damage accrual. Our data suggest the importance of His as a pathogenic metabolite in SLE pathogenesis.

Serum extracellular traps associate with the activation of myeloid cells in SLE patients with the low level of anti-DNA antibodies.

Neutrophil extracellular traps (NETs) are involved in systemic lupus erythematosus (SLE). We sought to cluster SLE patients based on serum NET levels. Serum NET levels were higher in SLE patients than healthy controls. Frequencies of pleuritis and myositis were increased in patients with high serum NET levels. Serum NET levels negatively correlated with anti-double stranded DNA (anti-dsDNA) antibody titers and C1q-binding immune complexes, but positively correlated with C-reactive protein (CRP) and monocyte counts. Neutrophil transcriptome analysis demonstrated no difference in NET-associated signatures, irrespective of serum NET levels, suggesting anti-dsDNA antibody-mediated clearance of NETs. In serum, NET levels were significantly correlated with myeloid cell-derived inflammatory molecules. Serum NET-based cluster analysis revealed 3 groups of patients based on serum NET and CRP levels, anti-dsDNA antibody titers, and monocyte count. Monocytes were consistently activated following NET-containing immune complex (NET-IC) stimulation. In conclusion, SLE patients with high serum NET levels had lower anti-dsDNA antibody titers and higher inflammatory responses. NET-IC-stimulated monocytes might associate with an inflammatory response characterized by elevated CRP levels. These findings can apply to precision medicine, as inflammatory processes, rather than antibody-dependent processes, can be targeted in specific subpopulations of SLE patients.

Autotaxin is a potential link between genetic risk factors and immunological disturbances of plasmacytoid dendritic cells in systematic lupus erythematosus.

BACKGROUND: The importance of autotaxin, an enzyme that catalyzes lysophospholipid production, has recently been recognized in various diseases, including cancer and autoimmune diseases. Herein, we examined the role of autotaxin in systemic lupus erythematosus (SLE), utilizing data from ImmuNexUT, a comprehensive database consisting of transcriptome data and expression quantitative trait locus (eQTL) data of immune cells from patients with immune-mediated disorders. METHODS: Serum autotaxin concentrations in patients with SLE and healthy controls (HCs) were compared. The transcriptome data of patients with SLE and age- and sex-matched HCs were obtained from ImmuNexUT. The expression of ENPP2, the gene encoding autotaxin, was examined in peripheral blood immune cells. Next, weighted gene correlation network analysis (WGCNA) was performed to identify genes with expression patterns similar to ENPP2. The ImmuNexUT eQTL database and public epigenomic databases were used to infer the relationship between autotaxin and pathogenesis of SLE. RESULTS: Autotaxin levels were elevated in the serum of patients with SLE compared to HCs. Furthermore, the expression of ENPP2 was higher in plasmacytoid dendritic cells (pDCs) than in other immune cell subsets, and its expression was elevated in pDCs of patients with SLE compared to HCs. In WGCNA, ENPP2 belonged to a module that correlated with disease activity. This module was enriched in interferon-associated genes and included genes whose expression was influenced by single-nucleotide polymorphisms associated with SLE, suggesting that it is a key module connecting genetic risk factors of SLE with disease pathogenesis. Analysis utilizing the ImmuNexUT eQTL database and public epigenomic databases suggested that the increased expression of ENPP2 in pDCs from patients with SLE may be caused by increased expression of interferon-associated genes and increased binding of STAT3 complexes to the regulatory region of ENPP2. CONCLUSIONS: Autotaxin may play a critical role in connecting genetic risk factors of SLE to disease pathogenesis in pDCs.

Control of naive and effector CD4 T cell receptor repertoires by rheumatoid-arthritis-risk HLA alleles.

OBJECTIVE: Human Leukocyte Antigen (HLA) alleles regulate susceptibility to rheumatoid arthritis (RA) and immune-mediated diseases. This study aims to elucidate the impact of HLA alleles to T cell subsets. METHODS: We performed genome-wide and HLA allele association analysis for T cell receptor (TCR) beta chain repertoire in 13 purified T cell subsets from the ImmuNexUT database, consisting of 407 donors with ten immune-mediated diseases and healthy controls. RESULTS: HLA class II alleles were associated with TRBV gene usage and the public clones of CD4 T cells, while HLA class I alleles were associated with CD8 T cells. RA-risk and immune-mediated diseases-risk HLA alleles were associated with TRBV gene usage of naive and effector CD4 T cell subsets and public clones accumulating in Th17. Clonal diversity was independent of HLA alleles and was correlated with transcriptome changes that reflect TCR signaling. CONCLUSION: This study revealed in vivo evidence that both HLA alleles and environmental factors shape naive and effector TCR repertoires in RA and immune-mediated diseases patients.

Distinct transcriptome architectures underlying lupus establishment and exacerbation.

Systemic lupus erythematosus (SLE) is a complex autoimmune disease involving multiple immune cells. To elucidate SLE pathogenesis, it is essential to understand the dysregulated gene expression pattern linked to various clinical statuses with a high cellular resolution. Here, we conducted a large-scale transcriptome study with 6,386 RNA sequencing data covering 27 immune cell types from 136 SLE and 89 healthy donors. We profiled two distinct cell-type-specific transcriptomic signatures: disease-state and disease-activity signatures, reflecting disease establishment and exacerbation, respectively. We then identified candidate biological processes unique to each signature. This study suggested the clinical value of disease-activity signatures, which were associated with organ involvement and therapeutic responses. However, disease-activity signatures were less enriched around SLE risk variants than disease-state signatures, suggesting that current genetic studies may not well capture clinically vital biology. Together, we identified comprehensive gene signatures of SLE, which will provide essential foundations for future genomic and genetic studies.

Transcriptome analysis of immune cells from Behçet's syndrome patients: the importance of IL-17-producing cells and antigen-presenting cells in the pathogenesis of Behçet's syndrome.

BACKGROUND: Behçet's syndrome (BS) is an immune-mediated disease characterized by recurrent oral ulcers, genital ulcers, uveitis, and skin symptoms. HLA-B51, as well as other genetic polymorphisms, has been reported to be associated with BS; however, the pathogenesis of BS and its relationship to genetic risk factors still remain unclear. To address these points, we performed immunophenotyping and transcriptome analysis of immune cells from BS patients and healthy donors. METHODS: ImmuNexUT is a comprehensive database consisting of RNA sequencing data and eQTL database of immune cell subsets from patients with immune-mediated diseases and healthy donors, and flow cytometry data and transcriptome data from 23 BS patients and 28 healthy donors from the ImmuNexUT study were utilized for this study. Differential gene expression analysis and weighted gene co-expression network analysis (WGCNA) were performed to identify genes associated with BS and clinical features of BS. eQTL database was used to assess the relationship between genetic risk factors of BS with those genes. RESULTS: The frequency of Th17 cells was increased in BS patients, and transcriptome analysis of Th17 cells suggested the activation of the NFκB pathway in Th17 cells of BS patients. Next, WGCNA was used to group genes into modules with similar expression patterns in each subset. Modules of antigen-presenting cells were associated with BS, and pathway analysis suggested the activation of antigen-presenting cells of BS patients. Further examination of genes in BS-associated modules indicated that the expression of YBX3, a member of a plasmacytoid dendritic cell (pDC) gene module associated with BS, is influenced by a BS risk polymorphism, rs2617170, in pDCs, suggesting that YBX3 may be a key molecule connecting genetic risk factors of BS with disease pathogenesis. Furthermore, pathway analysis of modules associated with HLA-B51 indicated that the association of IL-17-associated pathways in memory CD8+ T cells with HLA-B51; therefore, IL-17-producing CD8+ T cells, Tc17 cells, may play a critical role in BS. CONCLUSIONS: Various cells including CD4+ T cells, CD8+ T cells, and antigen-presenting cells are important in the pathogenesis of BS. Tc17 cells and YBX3 may be potential therapeutic targets in BS.

Immune cell multiomics analysis reveals contribution of oxidative phosphorylation to B-cell functions and organ damage of lupus.

OBJECTIVE: Systemic lupus erythematosus (SLE) is the prototypical systemic autoimmune disease. While the long-term prognosis has greatly improved, better long-term survival is still necessary. The type I interferon (IFN) signature, a prominent feature of SLE, is not an ideal therapeutic target or outcome predictor. To explore immunological pathways in SLE more precisely, we performed transcriptomic, epigenomic and genomic analyses using 19 immune cell subsets from peripheral blood. METHODS: We sorted 19 immune cell subsets and identified the mRNA expression profiles and genetic polymorphisms in 107 patients with SLE and 92 healthy controls. Combined differentially expressed genes and expression quantitative trait loci analysis was conducted to find key driver genes in SLE pathogenesis. RESULTS: We found transcriptomic, epigenetic and genetic importance of oxidative phosphorylation (OXPHOS)/mitochondrial dysfunction in SLE memory B cells. Particularly, we identified an OXPHOS-regulating gene, PRDX6 (peroxiredoxin 6), as a key driver in SLE B cells. Prdx6-deficient B cells showed upregulated mitochondrial respiration as well as antibody production. We revealed OXPHOS signature was associated with type I IFN signalling-related genes (ISRGs) signature in SLE memory B cells. Furthermore, the gene sets related to innate immune signalling among ISRGs presented correlation with OXPHOS and these two signatures showed associations with SLE organ damage as well as specific clinical phenotypes. CONCLUSION: This work elucidated the potential prognostic marker for SLE. Since OXPHOS consists of the electron transport chain, a functional unit in mitochondria, these findings suggest the importance of mitochondrial dysfunction as a key immunological pathway involved in SLE.

Dysregulation of the gene signature of effector regulatory T cells in the early phase of systemic sclerosis.

OBJECTIVES: We evaluated flow-cytometric and transcriptome features of peripheral blood immune cells from early-phase (disease duration <5 years) SSc in comparison with late-phase SSc. METHODS: Fifty Japanese patients with SSc (12 early SSc cases and 38 late SSc cases) and 50 age- and sex-matched healthy controls were enrolled. A comparison of flow-cytometric subset proportions and RNA-sequencing of 24 peripheral blood immune cell subsets was performed. We evaluated differentially expressed genes (DEGs), characterized the co-expressed gene modules, and estimated the composition of subpopulations by deconvolution based on single-cell RNA-sequencing data. As a disease control, idiopathic inflammatory myositis (IIM) patients were also evaluated. RESULTS: Analysing the data from early and late SSc, fraction II effector regulatory T cell (Fr. II eTreg) genes showed a remarkable differential gene expression, enriched for genes related to oxidative phosphorylation. Although the flow-cytometric proportion of Fr. II eTregs was not changed in early SSc, deconvolution indicated expansion of the activated subpopulation. Co-expressed gene modules of Fr. II eTregs demonstrated enrichment of the DEGs of early SSc and correlation with the proportion of the activated subpopulation. These results suggested that DEGs in Fr. II eTregs from patients with early SSc were closely associated with the increased proportion of the activated subpopulation. Similar dysregulation of Fr. II eTregs was also observed in data from patients with early IIM. CONCLUSIONS: RNA-seq of immune cells indicated the dysregulation of Fr. II eTregs in early SSc with increased proportion of the activated subpopulation.

Dynamic landscape of immune cell-specific gene regulation in immune-mediated diseases.

Genetic studies have revealed many variant loci that are associated with immune-mediated diseases. To elucidate the disease pathogenesis, it is essential to understand the function of these variants, especially under disease-associated conditions. Here, we performed a large-scale immune cell gene-expression analysis, together with whole-genome sequence analysis. Our dataset consists of 28 distinct immune cell subsets from 337 patients diagnosed with 10 categories of immune-mediated diseases and 79 healthy volunteers. Our dataset captured distinctive gene-expression profiles across immune cell types and diseases. Expression quantitative trait loci (eQTL) analysis revealed dynamic variations of eQTL effects in the context of immunological conditions, as well as cell types. These cell-type-specific and context-dependent eQTLs showed significant enrichment in immune disease-associated genetic variants, and they implicated the disease-relevant cell types, genes, and environment. This atlas deepens our understanding of the immunogenetic functions of disease-associated variants under in vivo disease conditions.

Identifying the most influential gene expression profile in distinguishing ANCA-associated vasculitis from healthy controls.

OBJECTIVE: Previous gene expression analyses seeking genes specific to antineutrophil cytoplasmic antibody-associated vasculitis (AAV) have been limited due to crude cell separation and the use of microarrays. This study aims to identify AAV-specific gene expression profiles in a way that overcomes those limitations. METHODS: Blood samples were collected from 26 AAV patients and 28 healthy controls (HCs). Neutrophils were isolated by negative selection, whereas 19 subsets of peripheral blood mononuclear cells were sorted by fluorescence assisted cell sorting. RNA-sequencing was then conducted for each sample, and iterative weighted gene correlation network analysis (iterativeWGCNA) and random forest were consecutively applied to identify the most influential gene module in distinguishing AAV from HCs. Correlations of the identified module with clinical parameters were evaluated, and the biological role was assessed with hub gene identification and pathway analysis. Particularly, the module's association with neutrophil extracellular trap formation, NETosis, was analyzed. Finally, the module's overlap with GWAS-identified autoimmune disease genes (GADGs) was assessed for validation. RESULTS: A neutrophil module (Neu_M20) was ranked top in the random forest analysis among 255 modules created by iterativeWGCNA. Neu_M20 correlated with disease activity and neutrophil counts but not with the presence of antineutrophil cytoplasmic antibody. The module comprised pro-inflammatory genes, including those related to NETosis, supported by experimental evidence. The genes in the module significantly overlapped GADGs. CONCLUSION: We identified the distinct group of pro-inflammatory genes in neutrophils, which characterize AAV. Further investigations are warranted to confirm our findings as they could serve as novel therapeutic targets.

Integrated bulk and single-cell RNA-sequencing identified disease-relevant monocytes and a gene network module underlying systemic sclerosis.

OBJECTIVE: Immunological disturbances have been reported in systemic sclerosis (SSc). This study assessed the transcriptome disturbances in immune cell subsets in SSc and characterized a disease-related gene network module and immune cell cluster at single cell resolution. METHODS: Twenty-one Japanese SSc patients were enrolled and compared with 13 age- and sex-matched healthy controls (HC). Nineteen peripheral blood immune cell subsets were sorted by flow cytometry and bulk RNA-seq analysis was performed for each. Differential expression and pathway analyses were conducted. Iterative weighted gene correlation network analysis (iWGCNA) of each subset revealed clustered co-expressed gene network modules. Random forest analysis prioritized a disease-related gene module. Single cell RNA-seq analysis of 878 monocytes was integrated with bulk RNA-seq analysis and with a public database for single cell RNA-seq analysis of SSc patients. RESULTS: Inflammatory pathway genes were differentially expressed in widespread immune cell subsets of SSc. An inflammatory gene module from CD16+ monocytes, which included KLF10, PLAUR, JUNB and JUND, showed the greatest discrimination between SSc and HC. One of the clusters of SSc monocytes identified by single-cell RNA-seq analysis characteristically expressed these inflammatory co-expressed genes and was similar to lung infiltrating FCN1hi monocytes expressing IL1B. CONCLUSIONS: Our integrated analysis of bulk and single cell RNA-seq analysis identified an inflammatory gene module and a cluster of monocytes that are relevant to SSc pathophysiology. They could serve as candidate novel therapeutic targets in SSc.