Published papers

RAの診療は早期の診断、治療介入が必要である。2010年ACR/EULAR分類基準を使用する際は、十分な除外診断がなされなければならない。RAを疑う症例では、可能であれば専門医に紹介することが望ましい。CRP陰性、抗CCP抗体やRF陰性、関節X線写真正常でもRAは否定できない。抗CCP抗体陽性高値例では関節破壊の進行が早く、適切な治療が必要である。RAでは関節に限らず全身の臓器に病変を生じるため、合併症の評価が重要である。治療は臨床的寛解を治療ターゲットとして、3ヵ月ごとに再評価していく必要がある。また、患者の社会的背景、合併症などを十分考慮してよく相談しつつ決めていく必要がある。(著者抄録)

61歳女。四肢末端に異常感覚を認め、左上肢の疼痛、筋力低下を主訴に受診した。慢性腎不全を認めたが、尿蛋白、潜血は陰性であった。両下肢・前腕に出現消退する、浸潤を触れる紅斑を認めた。間欠的な発熱も出現した。その後、右下肢の疼痛を主訴に再受診し、脛骨、腓骨、腓腹神経障害を認めた。血管炎の診断でプレドニゾロン、エンドキサンパルス、タクロリムスを開始したところ、発熱、四肢紅斑は改善、CRPは陰性化した。その後、四肢の感覚異常が増強したため再入院した。手指の血管造影を施行し、手掌動脈弓部以遠が抽出されなかった。皮膚生検、血管造影とも病変の主座は中動脈であることから、結節性多発動脈炎による障害と判断し、プレドニゾロン、エンドキサンパルスを開始した。CRPは速やかに陰性化し、手指の異常感覚、皮膚潰瘍も星状神経節に対するスーパーライザー照射も併用して治癒した。

Abstract CD4+ T cell plasticity plays a pivotal role in immune homeostasis. However, evidence of T cell plasticity and its pathological role in human systemic lupus erythematosus (SLE) is missing due to the lack of a reporter system. Here we utilized T cell receptor (TCR) repertoire data as a molecular signatures alongside transcriptomic dataset. Using a large-scale ImmuNexUT database of autoimmune disease patients including 117 SLE cases, we quantified T cell plasticity across 13 fine-grained T cell-types. We analyzed 6,392 samples in total and identified two orthogonal signatures of repertoire and transcriptome, the cell-type and disease signatures, allowing us to investigate CD4+ T cell plasticity comprehensively. Among all possible patterns, the plasticity level was the highest in effector regulatory T cells (eTreg) to Th1 plasticity, which was replicated in an independent cohort. Moreover, eTreg-to-Th1 plasticity positively correlated with SLE disease activity. Our study provides novel evidence that Treg plasticity is involved in SLE pathology.

Transcribed enhancer maps can reveal nuclear interactions underpinning each cell type and connect specific cell types to diseases. Using a 5′ single-cell RNA sequencing approach, we defined transcription start sites of enhancer RNAs and other classes of coding and noncoding RNAs in human CD4 + T cells, revealing cellular heterogeneity and differentiation trajectories. Integration of these datasets with single-cell chromatin profiles showed that active enhancers with bidirectional RNA transcription are highly cell type–specific and that disease heritability is strongly enriched in these enhancers. The resulting cell type–resolved multimodal atlas of bidirectionally transcribed enhancers, which we linked with promoters using fine-scale chromatin contact maps, enabled us to systematically interpret genetic variants associated with a range of immune-mediated diseases.

Abstract Recent progress in statistical and experimental fine mapping of disease risk variants prompts us to focus on specific target loci for functional investigation. However, current genetics is hindered by a limited toolbox for target-loci analysis. To address this, we developed UNIChro-seq, a method that digitally counts accessible chromatin molecules at target loci. UNIChro-seq allows for accurate, sensitive, and efficient quantification of allelic effects compared to conventional methods. Using UNIChro-seq, we investigated the effects of 57 autoimmunity risk alleles on chromatin accessibility and estimated the causal effects of 20 artificial variants generated through genome editing. As a caveat, non-negligible fraction of the edited allele exhibited a falsely positive effect on chromatin accessibility, which can be effectively distinguished from the true causal effect through bi-directional genome editing. Finally, functional dissection of a fine-mapped risk variant at the LEF1 locus illuminated its impact on T cell pathology in rheumatoid arthritis. Together, these findings underscore the utility of combining UNIChro-seq with genome editing technology to enable precise and scalable functional analysis of disease-associated loci.

RATIONALE: Collagen type XI alpha 2 chain is a component of type XI collagen and is expressed in various tissues including articular cartilage and tectorial membrane of the cochlea. Variants in the COL11A2 gene, which encodes collagen type XI alpha 2 chain, has been reported to cause hearing loss and has been associated with osteoarthritis and ossification of the posterior longitudinal ligament of the spine. Despite the importance of type XI collagen in the joints, association of rheumatoid arthritis (RA) with COL11A2 has not been reported. PATIENT CONCERNS: The patient is a 60-year-old female, born to Japanese parents of no known consanguinity. She had progressive hearing loss since childhood. Her father also had progressive hearing loss before middle age. She developed joint pain in the knees and the hips in her forties. When she was 56, she developed polyarthritis. Rheumatoid factor and anti-CCP antibodies were positive. DIAGNOSES: She was diagnosed with osteoarthritis and RA. Whole exome analysis detected 2 rare variants, c.4201C>T, p.(Arg1401Trp) and c4265C>T, p.(Pro1422Leu), in the COL11A2 gene (NM_080680.2). Whole genome analysis with a long insert size confirmed 2 variants that are in trans. INTERVENTIONS AND OUTCOMES: She received a cochlear implant, which improved her hearing. She was treated with methotrexate, golimumab, tocilizumab, and upadacitinib with partial responses for her RA. LESSONS: We herein report a patient with RA with compound heterozygous variants in the COL11A2 gene. Autoantibodies against type XI collagen are detected in the sera of patients with RA, suggesting the possibility that type XI collagen may be involved in the pathogenesis of RA as an autoantigen. The hearing loss and osteoarthritis in this patient may be due to the compound heterozygous variants in the COL11A2 gene, and the conformational changes induced by the variants may have changed the immunogenicity of type XI collagen, leading to the development of RA.

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.

BACKGROUND: IKBKE is a negative regulator of T cell activation and one of the key activators of type I interferon (IFN) and NFκB signaling via non-classical pathways. The upstream single nucleotide polymorphism of IKBKE (rs2297550-G) is a genome-wide association study risk variant of systemic lupus erythematosus, and is associated with decreased IKBKE expression in T cells by expression quantitative trait locus analysis. CASE PRESENTATION: A 48-year-old female had a remittent fever, arthritis, and oral ulcers for 20 years. She had a poor response to corticosteroids or disease-modifying antirheumatic drugs, including the tumor necrosis factor-α antagonist, etanercept, and the anti-interleukin-6 receptor antibody, tocilizumab. METHOD: She participated in the Initiative on Rare and Undiagnosed Disease (IRUD), and whole-exome sequencing (WES) was performed. Functional analyses were conducted by transfecting the identified variants into reporter cells to assess the activation of NFAT and NFκB signaling. Additionally, peripheral blood RNA- sequencing (RNA-seq) data were compared with those from healthy individuals to evaluate the gene expression profiles of immune cells. RESULT: WES identified a novel heterozygous c.1877G>A, p(Cys626Tyr) variant in IKBKE. Functional analysis indicated that this variant led to increased activity of NFAT (p = 0.015) and decreased activity of NFκB and type I IFN (p = 0.00068 and 0.00044, respectively). The patient had a remarkably low proportion of Naïve CD4 T cells. RNA-seq of peripheral blood immune cell subsets revealed significant differences in gene expression, especially in T cells. CONCLUSION: A novel functional heterozygous variant in IKBKE is described in a patient with a remittent fever and arthritis. The data suggest that IKBKE is an important negative regulator of inflammation, particularly in T cells, and this IKBKE variant might be the underlying cause of a novel autoinflammatory pathology.

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.

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.

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.

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.

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.

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.

Alternative splicing events are a major causal mechanism for complex traits, but they have been understudied due to the limitation of short-read sequencing. Here, we generate a full-length isoform annotation of human immune cells from an individual by long-read sequencing for 29 cell subsets. This contains a number of unannotated transcripts and isoforms such as a read-through transcript of TOMM40-APOE in the Alzheimer’s disease locus. We profile characteristics of isoforms and show that repetitive elements significantly explain the diversity of unannotated isoforms, providing insight into the human genome evolution. In addition, some of the isoforms are expressed in a cell-type specific manner, whose alternative 3’-UTRs usage contributes to their specificity. Further, we identify disease-associated isoforms by isoform switch analysis and by integration of several quantitative trait loci analyses with genome-wide association study data. Our findings will promote the elucidation of the mechanism of complex diseases via alternative splicing.

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.