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.

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.

Base-editing mutagenesis maps alleles to tune human T cell functions.

CRISPR-enabled screening is a powerful tool for the discovery of genes that control T cell function and has nominated candidate targets for immunotherapies1-6. However, new approaches are required to probe specific nucleotide sequences within key genes. Systematic mutagenesis in primary human T cells could reveal alleles that tune specific phenotypes. DNA base editors are powerful tools for introducing targeted mutations with high efficiency7,8. Here we develop a large-scale base-editing mutagenesis platform with the goal of pinpointing nucleotides that encode amino acid residues that tune primary human T cell activation responses. We generated a library of around 117,000 single guide RNA molecules targeting base editors to protein-coding sites across 385 genes implicated in T cell function and systematically identified protein domains and specific amino acid residues that regulate T cell activation and cytokine production. We found a broad spectrum of alleles with variants encoding critical residues in proteins including PIK3CD, VAV1, LCP2, PLCG1 and DGKZ, including both gain-of-function and loss-of-function mutations. We validated the functional effects of many alleles and further demonstrated that base-editing hits could positively and negatively tune T cell cytotoxic function. Finally, higher-resolution screening using a base editor with relaxed protospacer-adjacent motif requirements9 (NG versus NGG) revealed specific structural domains and protein-protein interaction sites that can be targeted to tune T cell functions. Base-editing screens in primary immune cells thus provide biochemical insights with the potential to accelerate immunotherapy design.

CRISPR screens decode cancer cell pathways that trigger γδ T cell detection.

γδ T cells are potent anticancer effectors with the potential to target tumours broadly, independent of patient-specific neoantigens or human leukocyte antigen background1-5. γδ T cells can sense conserved cell stress signals prevalent in transformed cells2,3, although the mechanisms behind the targeting of stressed target cells remain poorly characterized. Vγ9Vδ2 T cells-the most abundant subset of human γδ T cells4-recognize a protein complex containing butyrophilin 2A1 (BTN2A1) and BTN3A1 (refs. 6-8), a widely expressed cell surface protein that is activated by phosphoantigens abundantly produced by tumour cells. Here we combined genome-wide CRISPR screens in target cancer cells to identify pathways that regulate γδ T cell killing and BTN3A cell surface expression. The screens showed previously unappreciated multilayered regulation of BTN3A abundance on the cell surface and triggering of γδ T cells through transcription, post-translational modifications and membrane trafficking. In addition, diverse genetic perturbations and inhibitors disrupting metabolic pathways in the cancer cells, particularly ATP-producing processes, were found to alter BTN3A levels. This induction of both BTN3A and BTN2A1 during metabolic crises is dependent on AMP-activated protein kinase (AMPK). Finally, small-molecule activation of AMPK in a cell line model and in patient-derived tumour organoids led to increased expression of the BTN2A1-BTN3A complex and increased Vγ9Vδ2 T cell receptor-mediated killing. This AMPK-dependent mechanism of metabolic stress-induced ligand upregulation deepens our understanding of γδ T cell stress surveillance and suggests new avenues available to enhance γδ T cell anticancer activity.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Parsing multiomics landscape of activated synovial fibroblasts highlights drug targets linked to genetic risk of rheumatoid arthritis.

OBJECTIVES: Synovial fibroblasts (SFs) are one of the major components of the inflamed synovium in rheumatoid arthritis (RA). We aimed to gain insight into the pathogenic mechanisms of SFs through elucidating the genetic contribution to molecular regulatory networks under inflammatory condition. METHODS: SFs from RA and osteoarthritis (OA) patients (n=30 each) were stimulated with eight different cytokines (interferon (IFN)-α, IFN-γ, tumour necrosis factor-α, interleukin (IL)-1ß, IL-6/sIL-6R, IL-17, transforming growth factor-ß1, IL-18) or a combination of all 8 (8-mix). Peripheral blood mononuclear cells were fractioned into five immune cell subsets (CD4+ T cells, CD8+ T cells, B cells, natural killer (NK) cells, monocytes). Integrative analyses including mRNA expression, histone modifications (H3K27ac, H3K4me1, H3K4me3), three-dimensional (3D) genome architecture and genetic variations of single nucleotide polymorphisms (SNPs) were performed. RESULTS: Unstimulated RASFs differed markedly from OASFs in the transcriptome and epigenome. Meanwhile, most of the responses to stimulations were shared between the diseases. Activated SFs expressed pathogenic genes, including CD40 whose induction by IFN-γ was significantly affected by an RA risk SNP (rs6074022). On chromatin remodelling in activated SFs, RA risk loci were enriched in clusters of enhancers (super-enhancers; SEs) induced by synergistic proinflammatory cytokines. An RA risk SNP (rs28411362), located in an SE under synergistically acting cytokines, formed 3D contact with the promoter of metal-regulatory transcription factor-1 (MTF1) gene, whose binding motif showed significant enrichment in stimulation specific-SEs. Consistently, inhibition of MTF1 suppressed cytokine and chemokine production from SFs and ameliorated mice model of arthritis. CONCLUSIONS: Our findings established the dynamic landscape of activated SFs and yielded potential therapeutic targets associated with genetic risk of RA.

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.

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.

A gene module associated with dysregulated TCR signaling pathways in CD4+ T cell subsets in rheumatoid arthritis.

We analyzed the transcriptome of detailed CD4+ T cell subsets including them after abatacept treatment, and examined the difference among CD4+ T cell subsets and identified gene sets that are closely associated disease activity and abatacept treatment. Seven CD4+ T cell subsets (naive, Th1, Th17, Th1/17, nonTh1/17, Tfh and Treg) were sorted from PBMCs taken from 10 RA patients and 10 healthy controls, and three RA patients donated samples before and 6 months after abatacept treatment. Paired-end RNA sequencing was performed using HiSeq 2500. A total of 149 samples except for 12 outliers were analyzed. Overview of expression pattern of RA revealed that administration of abatacept exerts a large shift toward the expression pattern of HC. Most of differentially expressed gene (DEG) upregulated in RA (n = 1776) were downregulated with abatacept treatment (n = 1349). Inversely, most of DEG downregulated in RA (n = 1860) were upregulated with abatacept treatment (n = 1294). This DEG-based analysis revealed shared pathway changes in RA CD4+ T cell subsets. Knowledge-based pathway analysis revealed the upregulation of activation-related pathways in RA that was substantially ameliorated by abatacept. Weighted gene co-expression network analysis (WGCNA) evaluated CD4+ T cells collectively and identified a gene module that consisted of 227 genes and was correlated with DAS28-CRP (Spearman's rho = 0.46, p = 4 × 10-9) and abatacept administration (Spearman's rho = -0.91, p = 5 × 10-57). The most highly connected 30 genes of this module included ZAP70 and JAK3, and pathway analysis of this module revealed dysregulation of the TCR signaling pathway network, which was ameliorated by abatacept.

Efficacy of intensive immunosuppression in exacerbated rheumatoid arthritis-associated interstitial lung disease.

OBJECTIVES: Acute or subacute exacerbations are recognized as a severe complication of rheumatoid arthritis-associated interstitial lung disease (RA-ILD). Nevertheless, the role of intensive immunosuppression in RA-ILD remains elusive. We attempted to evaluate the clinical characteristics and efficacy of immunosuppressive treatment in exacerbated RA-ILD. METHODS: Clinical data, including respiratory function, imaging, treatment, and prognosis, were retrospectively collected for 17 patients with RA-ILD who required hospitalization at the University of Tokyo Hospital due to an acute exacerbation (12 patients) or subacute exacerbation (5 patients). RESULTS: Patients with RA-ILD demonstrated a significantly higher titers of anticyclic citrullinated peptide antibodies compared with RA patients in Japanese Ninja registry, suggesting the role of adaptive immunity. Immunosuppressive treatment suppressed the deterioration of pulmonary functions with improved ground grass opacity and consolidation. In particular, in patients with less fibrosis on computed tomography (CT) images showed a better response to treatment. Although five patients treated with combination therapy, including cyclophosphamide, showed a severely decreased lung volume, these intensive therapies provided a good prognosis without fatalities for the average observation period of 474 days. CONCLUSIONS: Immunosuppressive therapy is effective for exacerbations of RA-ILD. For severe cases with low respiratory function, intensive therapy, including cyclophosphamide, has a potential to improve the prognosis.

B cell receptor repertoire abnormalities in autoimmune disease.

B cells play a crucial role in the immune response and contribute to various autoimmune diseases. Recent studies have revealed abnormalities in the B cell receptor (BCR) repertoire of patients with autoimmune diseases, with distinct features observed among different diseases and B cell subsets. Classically, BCR repertoire was used as an identifier of distinct antigen-specific clonotypes, but the recent advancement of analyzing large-scale repertoire has enabled us to use it as a tool for characterizing cellular biology. In this review, we provide an overview of the BCR repertoire in autoimmune diseases incorporating insights from our latest research findings. In systemic lupus erythematosus (SLE), we observed a significant skew in the usage of VDJ genes, particularly in CD27+IgD+ unswitched memory B cells and plasmablasts. Notably, autoreactive clones within unswitched memory B cells were found to be increased and strongly associated with disease activity, underscoring the clinical significance of this subset. Similarly, various abnormalities in the BCR repertoire have been reported in other autoimmune diseases such as rheumatoid arthritis. Thus, BCR repertoire analysis holds potential for enhancing our understanding of the underlying mechanisms involved in autoimmune diseases. Moreover, it has the potential to predict treatment effects and identify therapeutic targets in autoimmune diseases.

Epigenetic targets of Janus kinase inhibitors are linked to genetic risks of rheumatoid arthritis.

BACKGROUND: Current strategies that target cytokines (e.g., tumor necrosis factor (TNF)-α), or signaling molecules (e.g., Janus kinase (JAK)) have advanced the management for allergies and autoimmune diseases. Nevertheless, the molecular mechanism that underpins its clinical efficacy have largely remained elusive, especially in the local tissue environment. Here, we aimed to identify the genetic, epigenetic, and immunological targets of JAK inhibitors (JAKis), focusing on their effects on synovial fibroblasts (SFs), the major local effectors associated with destructive joint inflammation in rheumatoid arthritis (RA). METHODS: SFs were activated by cytokines related to inflammation in RA, and were treated with three types of JAKis or a TNF-α inhibitor (TNFi). Dynamic changes in transcriptome and chromatin accessibility were profiled across samples to identify drug targets. Furthermore, the putative targets were validated using luciferase assays and clustered regularly interspaced short palindromic repeat (CRISPR)-based genome editing. RESULTS: We found that both JAKis and the TNFi targeted the inflammatory module including IL6. Conversely, specific gene signatures that were preferentially inhibited by either of the drug classes were identified. Strikingly, RA risk enhancers for CD40 and TRAF1 were distinctively regulated by JAKis and the TNFi. We performed luciferase assays and CRISPR-based genome editing, and successfully fine-mapped the single causal variants in these loci, rs6074022-CD40 and rs7021049-TRAF1. CONCLUSIONS: JAKis and the TNFi had a direct impact on different RA risk enhancers, and we identified nucleotide-resolution targets for both drugs. Distinctive targets of clinically effective drugs could be useful for tailoring the application of these drugs and future design of more efficient treatment strategies.