論文

The human leukocyte antigen (HLA) locus is associated with more complex diseases than any other locus in the human genome. In many diseases, HLA explains more heritability than all other known loci combined. In silico HLA imputation methods enable rapid and accurate estimation of HLA alleles in the millions of individuals that are already genotyped on microarrays. HLA imputation has been used to define causal variation in autoimmune diseases, such as type I diabetes, and in human immunodeficiency virus infection control. However, there are few guidelines on performing HLA imputation, association testing, and fine mapping. Here, we present a comprehensive tutorial to impute HLA alleles from genotype data. We provide detailed guidance on performing standard quality control measures for input genotyping data and describe options to impute HLA alleles and amino acids either locally or using the web-based Michigan Imputation Server, which hosts a multi-ancestry HLA imputation reference panel. We also offer best practice recommendations to conduct association tests to define the alleles, amino acids, and haplotypes that affect human traits. Along with the pipeline, we provide a step-by-step online guide with scripts and available software (https://github.com/immunogenomics/HLA_analyses_tutorial). This tutorial will be broadly applicable to large-scale genotyping data and will contribute to defining the role of HLA in human diseases across global populations.

Objectives: Unravelling the mechanisms underlying treatment response for targeted therapeutics in systemic lupus erythematosus (SLE) patients is challenging due to the limited understanding of diverse responses of circulating immune cells, particularly B cells. We investigated B lymphocyte dynamics during anti-BAFF treatment, utilizing longitudinal single-cell transcriptome data. Methods: We conducted single-cell RNA sequencing on peripheral blood mononuclear cells (PBMCs) in four Korean SLE patients before and after belimumab treatment at the following time points: 2 weeks, 1, 3, 6 and 12 months. Results: Analysing over 73 000 PBMCs, we identified eight distinct subsets of B cells and plasmablasts and analysed dynamic changes within these cell subsets: initial declines in naïve and transitional B cells followed by an increase at 3 months, contrasted by an initial increase and subsequent decrease in memory B cells by the third month. Meanwhile, plasmablasts exhibited a consistent decline throughout the treatment. B cell activation pathways, specifically in naïve and memory B cells, were downregulated during the third and sixth months. These findings were validated at the protein level throughout the first 4 weeks of treatment using flow cytometry. Comparative analysis with bulk transcriptome data from 22 Japanese SLE patients showed increased NR4A1 expression 6 months post-belimumab treatment, indicating its role in restricting self-reactive B cells, thereby contributing to the biological responses of anti-BAFF treatment. Conclusion: The observed B cell dynamics provided insights into the immunological mechanisms underlying the therapeutic effects of anti-BAFF in SLE patients. Furthermore, it underscores the need for research in predicting drug responses based on immune profiling.

Objective: Tofacitinib is an oral JAK inhibitor for the treatment of rheumatoid arthritis (RA), psoriatic arthritis, and ulcerative colitis, and has been previously investigated for psoriasis (PsO). This meta-analysis of genome-wide association studies (GWAS) was performed to identify genetic factors associated with increased risk/faster onset of herpes zoster (HZ) in subjects with RA or PsO receiving tofacitinib treatment, and to determine potential mechanisms that could be attributed to the varying rates of HZ across ethnicities. Methods: In an ethnicity/indication-specific, trans-ethnic, trans-population meta-analysis of GWAS in subjects with RA or PsO from phase II, phase III, and long-term extension studies of tofacitinib, 8 million genetic variants were evaluated for their potential association with time to an HZ event and incidence of an HZ event (case versus control) with tofacitinib treatment, using Cox proportional hazard and logistic regression analyses, respectively. Results: In total, 5,246 subjects were included (3,168 with RA and 2,078 with PsO). After adjustment for age, baseline absolute lymphocyte count, genetically defined ethnicity, and concomitant methotrexate use (in RA subjects only), 4 loci were significantly associated with faster onset of HZ in European subjects (P < 5 × 10−8), including a single-nucleotide polymorphism (SNP) near CD83 (frequency of risk allele ~2% in European subjects versus ~0.1% in East Asian subjects). In the trans-ethnic, trans-population meta-analysis, the CD83 SNP remained significant. Four additional significant loci were identified in the meta-analysis, among which a SNP near IL17RB was associated with faster onset of HZ (meta-analysis hazard ratio 3.6 [95% confidence interval 2.40–5.44], P = 7.6 × 10−10; frequency of risk allele ~12% in East Asian subjects versus <0.2% in European subjects). Conclusion: Genetic analysis of tofacitinib-treated subjects with RA or PsO identified multiple loci associated with increased HZ risk. Prevalent variants near the immune-relevant genes CD83 and IL17RB in European and East Asian populations, respectively, may contribute to risk of HZ in tofacitinib-treated subjects.

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.

Rheumatoid arthritis is a prototypical autoimmune disease that causes joint inflammation and destruction1. There is currently no cure for rheumatoid arthritis, and the effectiveness of treatments varies across patients, suggesting an undefined pathogenic diversity1,2. Here, to deconstruct the cell states and pathways that characterize this pathogenic heterogeneity, we profiled the full spectrum of cells in inflamed synovium from patients with rheumatoid arthritis. We used multi-modal single-cell RNA-sequencing and surface protein data coupled with histology of synovial tissue from 79 donors to build single-cell atlas of rheumatoid arthritis synovial tissue that includes more than 314,000 cells. We stratified tissues into six groups, referred to as cell-type abundance phenotypes (CTAPs), each characterized by selectively enriched cell states. These CTAPs demonstrate the diversity of synovial inflammation in rheumatoid arthritis, ranging from samples enriched for T and B cells to those largely lacking lymphocytes. Disease-relevant cell states, cytokines, risk genes, histology and serology metrics are associated with particular CTAPs. CTAPs are dynamic and can predict treatment response, highlighting the clinical utility of classifying rheumatoid arthritis synovial phenotypes. This comprehensive atlas and molecular, tissue-based stratification of rheumatoid arthritis synovial tissue reveal new insights into rheumatoid arthritis pathology and heterogeneity that could inform novel targeted treatments.

The discovery of genetic loci associated with complex diseases has outpaced the elucidation of mechanisms of disease pathogenesis. Here we conducted a genome-wide association study (GWAS) for coronary artery disease (CAD) comprising 181,522 cases among 1,165,690 participants of predominantly European ancestry. We detected 241 associations, including 30 new loci. Cross-ancestry meta-analysis with a Japanese GWAS yielded 38 additional new loci. We prioritized likely causal variants using functionally informed fine-mapping, yielding 42 associations with less than five variants in the 95% credible set. Similarity-based clustering suggested roles for early developmental processes, cell cycle signaling and vascular cell migration and proliferation in the pathogenesis of CAD. We prioritized 220 candidate causal genes, combining eight complementary approaches, including 123 supported by three or more approaches. Using CRISPR–Cas9, we experimentally validated the effect of an enhancer in MYO9B, which appears to mediate CAD risk by regulating vascular cell motility. Our analysis identifies and systematically characterizes >250 risk loci for CAD to inform experimental interrogation of putative causal mechanisms for CAD.

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.

Common variants strongly influence the risk of human autoimmunity. Two categories of variants contribute substantially to the risk: (i) coding variants of HLA genes and (ii) non-coding variants at the non-HLA loci. We recently developed a novel analytic pipeline of T cell receptor (TCR) repertoire to understand how HLA coding variants influence the risk. We identified that the risk variants increase the frequency of auto-reactive T cells. In addition, to understand how non-coding variants contribute to the risk, the researchers conducted integrative analyses using expression quantitative trait loci (eQTL) and splicing quantitative trait loci (sQTL) and demonstrated that the risk non-coding variants dysregulate specific genes’ expression and splicing. These studies provided novel insight into the immunological consequences of two major genetic risks, and we will introduce these research achievements in detail in this review.

Purpose: To investigate the genetic architecture of age-related macular degeneration (AMD) in a Japanese population. Design: Genome-wide association study (GWAS). Participants: Three thousand seven hundred seventy-two patients with AMD and 16 770 control participants from the Japanese population were enrolled in the association analyses. Methods: We conducted a meta-analysis of 2 independent GWASs that included a total of 2663 patients with AMD and 9471 control participants using the imputation reference panel for genotype imputation specified for the Japanese population (n = 3541). A replication study was performed using an independent set of 1109 patients with AMD and 7299 control participants. Main Outcome Measures: Associations of genetic variants with AMD. Results: A meta-analysis of the 2 GWASs identified 6 loci significantly associated with AMD (P < 5.0 × 10–8). Of these loci, 4 were known to be associated with AMD (CFH, C2/FB, TNFRSF10A, and ARMS2), and 2 were novel (rs4147157 near WBP1L and rs76228488 near GATA5). The newly identified associations were confirmed in a replication study (P < 0.01). After the meta-analysis of all datasets, we observed strong associations in these loci (P = 1.88 × 10–12 and P = 1.35 × 10–9 for meta-analysis for rs4147157 and rs76228488, respectively). When we looked up the associations in the reported central serous chorioretinopathy (CSC) GWAS conducted in the Japanese population, both loci were associated significantly with CSC (P = 4.86 × 10–3 and P = 4.28 × 10–3 for rs4147157 and rs76228488, respectively). We performed a genetic colocalization analysis for these loci and estimated that the posterior probabilities of shared causal variants between AMD and CSC were 0.39 and 0.60 for WBP1L and GATA5, respectively. Genetic correlation analysis focusing on the epidemiologically suggested clinical risk factors implicated shared polygenic architecture between AMD and smoking cessation (rg [the measure of genetic correlation] = –0.33; P = 0.01; false discovery rate, 0.099). Conclusions: Our findings imply shared genetic components conferring the risk of both AMD and CSC. Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references.

Human lifespan is reported to be heritable. Although previous genome-wide association studies (GWASs) have identified several loci, a limited number of studies have assessed the genetic associations with the real survival information on the participants. We conducted a GWAS to identify loci associated with survival time in the Japanese individuals participated in the BioBank Japan Project by carrying out sex-stratified GWASs involving 78,029 males and 59,664 females. Of them, 31,324 (22.7%) died during the mean follow-up period of 7.44 years. We found a novel locus associated with survival (BET1L; P = 5.89 × 10−9). By integrating with eQTL data, we detected a significant overlap with eQTL of BET1L in skeletal muscle. A gene-set enrichment analysis showed that genes related to the BCAR1 protein–protein interaction subnetwork influence survival time (P = 1.54 × 10−7). These findings offer the candidate genes and biological mechanisms associated with human lifespan.

Granzymes are a family of serine proteases that are mainly expressed by CD8+ T cells, natural killer cells and innate-like lymphocytes1. Although their primary function is thought to be the induction of cell death in virally infected cells and tumours, accumulating evidence indicates that some granzymes can elicit inflammation by acting on extracellular substrates1. We previously found that most tissue CD8+ T cells in rheumatoid arthritis synovium, and in inflamed organs for some other diseases, express granzyme K (GZMK)2, a tryptase-like protease with poorly defined function. Here, we show that GZMK can activate the complement cascade by cleaving the C2 and C4 proteins. The nascent C4b and C2b fragments form a C3 convertase that cleaves C3, enabling the assembly of a C5 convertase that cleaves C5. The resulting convertases generate all the effector molecules of the complement cascade: the anaphylatoxins C3a and C5a, the opsonins C4b and C3b, and the membrane attack complex. In rheumatoid arthritis synovium, GZMK is enriched in regions with abundant complement activation, and fibroblasts are the main producers of complement proteins that serve as substrates for GZMK-mediated complement activation. Furthermore, Gzmk-deficient mice are significantly protected from inflammatory disease, exhibiting reduced arthritis and dermatitis, with concomitant decreases in complement activation. Our findings describe the discovery of a previously unidentified mechanism of complement activation that is driven entirely by lymphocyte-derived GZMK. Given the widespread abundance of GZMK-expressing T cells in tissues in chronic inflammatory diseases, GZMK-mediated complement activation is likely to be an important contributor to tissue inflammation in multiple disease contexts.

Objective: Delayed detection of LN associates with worse outcomes. There are conflicting recommendations regarding a threshold level of proteinuria at which biopsy will likely yield actionable management. This study addressed the association of urine protein:creatinine ratios (UPCR) with clinical characteristics and investigated the incidence of proliferative and membranous histology in patients with a UPCR between 0.5 and 1. Methods: A total of 275 SLE patients (113 first biopsy, 162 repeat) were enrolled in the multicentre multi-ethnic/racial Accelerating Medicines Partnership across 15 US sites at the time of a clinically indicated renal biopsy. Patients were followed for 1 year. Results: At biopsy, 54 patients had UPCR <1 and 221 had UPCR ≥1. Independent of UPCR or biopsy number, a majority (92%) of patients had class III, IV, V or mixed histology. Moreover, patients with UPCR <1 and class III, IV, V, or mixed had a median activity index of 4.5 and chronicity index of 3, yet 39% of these patients had an inactive sediment. Neither anti-dsDNA nor low complement distinguished class I or II from III, IV, V or mixed in patients with UPCR <1. Of 29 patients with baseline UPCR <1 and class III, IV, V or mixed, 23 (79%) had a UPCR <0.5 at 1 year. Conclusion: In this prospective study, three-quarters of patients with UPCR <1 had histology showing class III, IV, V or mixed with accompanying activity and chronicity despite an inactive sediment or normal serologies. These data support renal biopsy at thresholds lower than a UPCR of 1.

Polymorphisms in the human leukocyte antigen (HLA) genes strongly influence autoimmune disease risk. HLA risk alleles may influence thymic selection to increase the frequency of T cell receptors (TCRs) reactive to autoantigens (central hypothesis). However, research in human autoimmunity has provided little evidence supporting the central hypothesis. Here we investigated the influence of HLA alleles on TCR composition at the highly diverse complementarity determining region 3 (CDR3), which confers antigen recognition. We observed unexpectedly strong HLA–CDR3 associations. The strongest association was found at HLA-DRB1 amino acid position 13, the position that mediates genetic risk for multiple autoimmune diseases. We identified multiple CDR3 amino acid features enriched by HLA risk alleles. Moreover, the CDR3 features promoted by the HLA risk alleles are more enriched in candidate pathogenic TCRs than control TCRs (for example, citrullinated epitope-specific TCRs in patients with rheumatoid arthritis). Together, these results provide genetic evidence supporting the central hypothesis.

Early detection and diagnosis of rheumatoid arthritis (RA) is crucial for initiating appropriate therapy promptly, thereby leading to increase the likelihood of achieving remission and eventual cure. In this article, we will discuss the contribution of genetic information in predicting and detecting RA.

TRAF1/C5 was among the first loci shown to confer risk for inflammatory arthritis in the absence of an associated coding variant, but its genetic mechanism remains undefined. Using Immunochip data from 3,939 patients with juvenile idiopathic arthritis (JIA) and 14,412 control individuals, we identified 132 plausible common non-coding variants, reduced serially by single-nucleotide polymorphism sequencing (SNP-seq), electrophoretic mobility shift, and luciferase studies to the single variant rs7034653 in the third intron of TRAF1. Genetically manipulated experimental cells and primary monocytes from genotyped donors establish that the risk G allele reduces binding of Fos-related antigen 2 (FRA2), encoded by FOSL2, resulting in reduced TRAF1 expression and enhanced tumor necrosis factor (TNF) production. Conditioning on this JIA variant eliminated attributable risk for rheumatoid arthritis, implicating a mechanism shared across the arthritis spectrum. These findings reveal that rs7034653, FRA2, and TRAF1 mediate a pathway through which a non-coding functional variant drives risk of inflammatory arthritis in children and adults.

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.

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.