The muscle tissue transcriptome of idiopathic inflammatory myopathy reflects the muscle damage process by monocytes and presence of skin lesions.

OBJECTIVE: To investigate transcriptomic and immunophenotypic features of muscle specimens from patients with idiopathic inflammatory myopathy (IIM). METHODS: Bulk RNA-sequencing was performed on muscle biopsy samples from 16 patients with dermatomyositis (DM) and 9 patients with polymyositis (PM). Seven tested positive for anti-aminoacyl t-RNA synthetase antibodies in the DM patients (ARS-DM). We conducted weighted gene coexpression network analysis (WGCNA), differentially expressed gene (DEG) analysis, and gene set variation analysis (GSVA) to assess contributions of specific pathways. Cell proportions in muscle specimens were estimated using a deconvolution approach. RESULTS: WGCNA revealed significant positive correlations between serum creatine kinase (CK) levels and gene modules involved in cellular respiration, phagocytosis, and oxidative phosphorylation (OXPHOS). Significant positive correlations were also observed between CK levels and proportions of CD16-positive and -negative monocytes and myeloid dendritic cells. Notably, DM patients demonstrated enrichment of complement and interferon-α and -γ pathway genes compared to those with PM. Furthermore, ARS-DM demonstrated a higher proportion of Th1 cells and DEGs related to OXPHOS. Additionally, serum Krebs von den Lungen-6 levels correlated with gene modules associated with extracellular matrix and transforming growth factor-ß signaling pathway. CONCLUSION: Our study highlights a significant involvement of monocytes in muscle damage and delineates pathological differences among IIM subtypes. DM was characterized by complement, interferon-α and -γ signaling, whilst ARS-DM was associated with OXPHOS. Distinctive gene expression variations in muscle specimens suggest that different pathologic mechanisms underlie muscle damage in each IIM phenotype.

Rare germline variants in pancreatic cancer and multiple primary cancers: an autopsy study.

BACKGROUND: There is a lack of information on rare germline variants of pancreatic cancer-predisposing genes. Risk genes for multiple primary cancers may overlap with those for pancreatic cancer. METHODS: A retrospective study of autopsy cases with a negative family history in the Japanese single nucleotide polymorphism for geriatric research database examined rare germline variants in the protein-coding regions of 61 genes. Targeted sequencing of these genes was performed and classified for pathogenicity using the American College of Medical Genetics and Genomics guidelines. Polyphen-2, SIFT and LoFtool algorithms were used to predict damage to protein function. RESULTS: Of the 189 subjects used (90 cancer and 99 non-cancer controls), 72 patients had pancreatic cancer (23 had multiple primary cancers) and 18 had no pancreatic cancer in multiple primary cancers. APC, BRCA2, BUB1B, ENG and MSH6 were associated with cancer predisposition, and pathogenic/likely pathogenic (P/LP) variants occurred in 6% [pancreatic cancer (4/72); all-cancer (5/90)] and 54% (49/90) carried only variants of uncertain significance (VUS) among cancer patients. Of these VUS, in pancreatic cancer patients, four DNA mismatch repair (MMR) genes ( MLH1, MSH2, MSH6 and PMS2 ), and POLQ in men were significantly associated (odds ratio = 3.83; P = 0.025; P = 0.027, respectively). The most abundant predictor of functionally damaging variants was POLQ . CONCLUSIONS: The frequency of P/LP variants in patients with sporadic pancreatic cancer suggests the need for genetic evaluation of individuals with no family history. VUS of MMR genes ( MLH1, MSH2, MSH6 and PMS2 ) and POLQ may be useful in predicting genetic trends in the potential risk of pancreatic cancer, especially in individuals lacking P/LP.

Polygenic Risk Score of Adolescent Idiopathic Scoliosis for Potential Clinical Use.

Adolescent idiopathic scoliosis (AIS) is a common disease causing three-dimensional spinal deformity in as many as 3% of adolescents. Development of a method that can accurately predict the onset and progression of AIS is an immediate need for clinical practice. Because the heritability of AIS is estimated as high as 87.5% in twin studies, prediction of its onset and progression based on genetic data is a promising option. We show the usefulness of polygenic risk score (PRS) for the prediction of onset and progression of AIS. We used AIS genomewide association study (GWAS) data comprising 79,211 subjects in three cohorts and constructed a PRS based on association statistics in a discovery set including 31,999 female subjects. After calibration using a validation data set, we applied the PRS to a test data set. By integrating functional annotations showing heritability enrichment in the selection of variants, the PRS demonstrated an association with AIS susceptibility (p = 3.5 × 10-40 with area under the receiver-operating characteristic [AUROC] = 0.674, sensitivity = 0.644, and specificity = 0.622). The decile with the highest PRS showed an odds ratio of as high as 3.36 (p = 1.4 × 10-10 ) to develop AIS compared with the fifth in decile. The addition of a predictive model with only a single clinical parameter (body mass index) improved predictive ability for development of AIS (AUROC = 0.722, net reclassification improvement [NRI] 0.505 ± 0.054, p = 1.6 × 10-8 ), potentiating clinical use of the prediction model. Furthermore, we found the Cobb angle (CA), the severity measurement of AIS, to be a polygenic trait that showed a significant genetic correlation with AIS susceptibility (rg = 0.6, p = 3.0 × 10-4 ). The AIS PRS demonstrated a significant association with CA. These results indicate a shared polygenic architecture between onset and progression of AIS and the potential usefulness of PRS in clinical settings as a predictor to promote early intervention of AIS and avoid invasive surgery. © 2021 American Society for Bone and Mineral Research (ASBMR).

HERV-Derived Ervpb1 Is Conserved in Simiiformes, Exhibiting Expression in Hematopoietic Cell Lineages Including Macrophages.

(1) Background: The ERVPb1 gene in humans is derived from an envelope (Env) gene of a human endogenous retrovirus group, HERV-P(b). The ERVPb1 gene reportedly has a conserved open reading frame (ORF) in Old World monkeys. Although its forced expression led to cell-fusion in an ex vivo cell culture system, like other Env-derived genes such as syncytin-1 and -2, its mRNA expression is not placenta-specific, but almost ubiquitous, albeit being quite low in human tissues and organs, implying a distinct role for ERVPb1. (2) Methods: To elucidate the cell lineage(s) in which the ERVPb1 protein is translated in human development, we developed a novel, highly sensitive system for detecting HERV-derived proteins/peptides expressed in the tissue differentiation process of human induced pluripotent stem cells (iPSCs). (3) Results: We first determined that ERVPb1 is also conserved in New World monkeys. Then, we showed that the ERVPb1 protein is translated from a uniquely spliced ERVPb1 transcript in hematopoietic cell lineages, including a subset of macrophages, and further showed that its mRNA expression is upregulated by lipopolysaccharide (LPS) stimulation in primary human monocytes. (4) Conclusions: ERVPb1 is unique to Simiiformes and actually translated in hematopoietic cell lineages, including a subset of macrophages.

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.

Cystoscopic Imaging for Bladder Cancer Detection Based on Stepwise Organic Transfer Learning with a Pretrained Convolutional Neural Network.

Background: Nonmuscle-invasive bladder cancer is diagnosed, treated, and monitored using cystoscopy. Artificial intelligence (AI) is increasingly used to augment tumor detection, but its performance is hindered by the limited availability of cystoscopic images required to form a large training data set. This study aimed to determine whether stepwise transfer learning with general images followed by gastroscopic images can improve the accuracy of bladder tumor detection on cystoscopic imaging. Materials and Methods: We trained a convolutional neural network with 1.2 million general images, followed by 8728 gastroscopic images. In the final step of the transfer learning process, the model was additionally trained with 2102 cystoscopic images of normal bladder tissue and bladder tumors collected at the University of Tsukuba Hospital. The diagnostic accuracy was evaluated using a receiver operating characteristic curve. The diagnostic performance of the models trained with cystoscopic images with or without stepwise organic transfer learning was compared with that of medical students and urologists with varying levels of experience. Results: The model developed by stepwise organic transfer learning had 95.4% sensitivity and 97.6% specificity. This performance was better than that of the other models and comparable with that of expert urologists. Notably, it showed superior diagnostic accuracy when tumors occupied >10% of the image. Conclusions: Our findings demonstrate the value of stepwise organic transfer learning in applications with limited data sets for training and further confirm the value of AI in medical diagnostics. Here, we applied deep learning to develop a tool to detect bladder tumors with an accuracy comparable with that of a urologist. To address the limitation that few bladder tumor images are available to train the model, we demonstrate that pretraining with general and gastroscopic images yields superior results.

Large-scale genome-wide association study in a Japanese population identifies novel susceptibility loci across different diseases.

The overwhelming majority of participants in current genetic studies are of European ancestry. To elucidate disease biology in the East Asian population, we conducted a genome-wide association study (GWAS) with 212,453 Japanese individuals across 42 diseases. We detected 320 independent signals in 276 loci for 27 diseases, with 25 novel loci (P < 9.58 × 10-9). East Asian-specific missense variants were identified as candidate causal variants for three novel loci, and we successfully replicated two of them by analyzing independent Japanese cohorts; p.R220W of ATG16L2 (associated with coronary artery disease) and p.V326A of POT1 (associated with lung cancer). We further investigated enrichment of heritability within 2,868 annotations of genome-wide transcription factor occupancy, and identified 378 significant enrichments across nine diseases (false discovery rate < 0.05) (for example, NKX3-1 for prostate cancer). This large-scale GWAS in a Japanese population provides insights into the etiology of complex diseases and highlights the importance of performing GWAS in non-European populations.

Support System of Cystoscopic Diagnosis for Bladder Cancer Based on Artificial Intelligence.

Introduction: Nonmuscle-invasive bladder cancer has a relatively high postoperative recurrence rate despite the implementation of conventional treatment methods. Cystoscopy is essential for diagnosing and monitoring bladder cancer, but lesions are overlooked while using white-light imaging. Using cystoscopy, tumors with a small diameter; flat tumors, such as carcinoma in situ; and the extent of flat lesions associated with the elevated lesions are difficult to identify. In addition, the accuracy of diagnosis and treatment using cystoscopy varies according to the skill and experience of physicians. Therefore, to improve the quality of bladder cancer diagnosis, we aimed to support the cystoscopic diagnosis of bladder cancer using artificial intelligence (AI). Materials and Methods: A total of 2102 cystoscopic images, consisting of 1671 images of normal tissue and 431 images of tumor lesions, were used to create a dataset with an 8:2 ratio of training and test images. We constructed a tumor classifier based on a convolutional neural network (CNN). The performance of the trained classifier was evaluated using test data. True-positive rate and false-positive rate were plotted when the threshold was changed as the receiver operating characteristic (ROC) curve. Results: In the test data (tumor image: 87, normal image: 335), 78 images were true positive, 315 true negative, 20 false positive, and 9 false negative. The area under the ROC curve was 0.98, with a maximum Youden index of 0.837, sensitivity of 89.7%, and specificity of 94.0%. Conclusion: By objectively evaluating the cystoscopic image with CNN, it was possible to classify the image, including tumor lesions and normality. The objective evaluation of cystoscopic images using AI is expected to contribute to improvement in the accuracy of the diagnosis and treatment of bladder cancer.

Exploring predictive biomarkers from clinical genome-wide association studies via multidimensional hierarchical mixture models.

Although the detection of predictive biomarkers is of particular importance for the development of accurate molecular diagnostics, conventional statistical analyses based on gene-by-treatment interaction tests lack sufficient statistical power for this purpose, especially in large-scale clinical genome-wide studies that require an adjustment for multiplicity of a huge number of tests. Here we demonstrate an alternative efficient multi-subgroup screening method using multidimensional hierarchical mixture models developed to overcome this issue, with application to stroke and breast cancer randomized clinical trials with genomic data. We show that estimated effect size distributions of single nucleotide polymorphisms (SNPs) associated with outcomes, which could provide clues for exploring predictive biomarkers, optimizing individualized treatments, and understanding biological mechanisms of diseases. Furthermore, using this method we detected three new SNPs that are associated with blood homocysteine levels, which are strongly associated with the risk of stroke. We also detected six new SNPs that are associated with progression-free survival in breast cancer patients.

Splicing variant of WDFY4 augments MDA5 signalling and the risk of clinically amyopathic dermatomyositis.

OBJECTIVES: Idiopathic inflammatory myopathies (IIMs) are a heterogeneous group of rare autoimmune diseases in which both genetic and environmental factors play important roles. To identify genetic factors of IIM including polymyositis, dermatomyositis (DM) and clinically amyopathic DM (CADM), we performed the first genome-wide association study for IIM in an Asian population. METHODS: We genotyped and tested 496 819 single nucleotide polymorphism for association using 576 patients with IIM and 6270 control subjects. We also examined the causal mechanism of disease-associated variants by in silico analyses using publicly available data sets as well as by in in vitro analyses using reporter assays and apoptosis assays. RESULTS: We identified a variant in WDFY4 that was significantly associated with CADM (rs7919656; OR=3.87; P=1.5×10-8). This variant had a cis-splicing quantitative trait locus (QTL) effect for a truncated WDFY4isoform (tr-WDFY4), with higher expression in the risk allele. Transexpression QTL analysis of this variant showed a positive correlation with the expression of NF-κB associated genes. Furthermore, we demonstrated that both WDFY4 and tr-WDFY4 interacted with pattern recognition receptors such as TLR3, TLR4, TLR9 and MDA5 and augmented the NF-κB activation by these receptors. WDFY4 isoforms also enhanced MDA5-induced apoptosis to a greater extent in the tr-WDFY4-transfected cells. CONCLUSIONS: As CADM is characterised by the appearance of anti-MDA5 autoantibodies and severe lung inflammation, the WDFY4 variant may play a critical role in the pathogenesis of CADM.

Polygenic burdens on cell-specific pathways underlie the risk of rheumatoid arthritis.

Recent evidence suggests that a substantial portion of complex disease risk alleles modify gene expression in a cell-specific manner. To identify candidate causal genes and biological pathways of immune-related complex diseases, we conducted expression quantitative trait loci (eQTL) analysis on five subsets of immune cells (CD4+ T cells, CD8+ T cells, B cells, natural killer (NK) cells and monocytes) and unfractionated peripheral blood from 105 healthy Japanese volunteers. We developed a three-step analytical pipeline comprising (i) prediction of individual gene expression using our eQTL database and public epigenomic data, (ii) gene-level association analysis and (iii) prediction of cell-specific pathway activity by integrating the direction of eQTL effects. By applying this pipeline to rheumatoid arthritis data sets, we identified candidate causal genes and a cytokine pathway (upregulation of tumor necrosis factor (TNF) in CD4+ T cells). Our approach is an efficient way to characterize the polygenic contributions and potential biological mechanisms of complex diseases.

Decreased severity of experimental autoimmune arthritis in peptidylarginine deiminase type 4 knockout mice.

BACKGROUND: Peptidylarginine deiminase type 4 (PADI4) has been identified as a susceptibility gene for rheumatoid arthritis (RA) by genome-wide association studies. PADI4 is highly expressed in the bone marrow, macrophages, neutrophils, and monocytes. Peptidyl citrulline is an interesting molecule in RA because it is a target antigen for anti-citrullinated peptide antibodies, and only PADs (translated proteins from PADI genes) can provide peptidyl citrulline via the modification of protein substrates. The aim of this study was to evaluate the importance of the PADI4 gene in the progression of RA. METHODS: We generated Padi4 knockout (Padi4(-/-)) DBA1J mice. The Padi4(-/-) DBA1J and wild-type mice were immunized with bovine type II collagen (CII) to develop collagen-induced arthritis (CIA). The expression of various inflammatory cytokines and Padi genes in immune cells was detected by the real-time TaqMan assay. Cytokine concentrations in sera were measured by enzyme-linked immunosorbent assays. Localization of the PAD4 and PAD2 proteins was indicated by immunohistochemistry. RESULTS: We demonstrated that the clinical disease score was significantly decreased in the Padi4(-/-) mice and Padi4 expression was induced by CII immunization. In the Padi4(-/-) mice, serum anti-type II collagen (CII) immunoglobulin M (IgM), IgG, and inflammatory cytokine levels were significantly decreased compared with those in the wild-type mice. Padi2 expression was induced in the immune cells of the Padi4(-/-) mice as a compensation for the defect in Padi4. CONCLUSIONS: Padi4 affected disease severity in the CIA mice and was involved in the enhancement of the collagen-initiated inflammatory responses.

Genetic basis of rheumatoid arthritis: a current review.

Rheumatoid arthritis (RA) is one of the most common autoimmune diseases. As with other complex traits, genome-wide association studies (GWASs) have tremendously enhanced our understanding of the complex etiology of RA. In this review, we describe the genetic architecture of RA as determined through GWASs and meta-analyses. In addition, we discuss the pathologic mechanism of the disease by examining the combined findings of genetic and functional studies of individual RA-associated genes, including HLA-DRB1, PADI4, PTPN22, TNFAIP3, STAT4, and CCR6. Moreover, we briefly examine the potential use of genetic data in clinical practice in RA treatment, which represents a challenge in medical genetics in the post-GWAS era.

Genetics of rheumatoid arthritis contributes to biology and drug discovery.

A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA). Here we performed a genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ∼10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2 - 4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation, cis-acting expression quantitative trait loci and pathway analyses--as well as novel methods based on genetic overlap with human primary immunodeficiency, haematological cancer somatic mutations and knockout mouse phenotypes--to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.

An association analysis of HLA-DRB1 with systemic lupus erythematosus and rheumatoid arthritis in a Japanese population: effects of *09:01 allele on disease phenotypes.

Objective. To re-evaluate the roles of HLA-DRB1 alleles in susceptibility to SLE and RA and their effects on autoantibody status in large-scale Japanese cohorts. Methods. A total of 656 SLE, 2410 RA and 911 control subjects, who were all Japanese, were genotyped for HLA-DRB1 alleles using sequence-specific oligonucleotide probes. The association of alleles with disease susceptibility was tested by logistic regression analysis and by the relative predispositional effect method. The association with autoantibody status was examined by the standard χ(2) test. Results. HLA-DRB1*15:01, *09:01, *08:02 and *04:01 were significantly associated with SLE susceptibility, while shared epitope (SE) alleles and DRB1*09:01 were associated with RA susceptibility. The compound heterozygote of DRB1*09:01/*15:01 conferred an increased risk for SLE compared with the homozygotes for DRB1*09:01 and *15:01 and was associated with earlier onset of disease, whereas the compound effect of DRB1-SE/*09:01 was not clear in RA. DRB1*09:01 was significantly associated with the appearance of anti-Sm antibody in SLE as well as ACPA in RA, while protectively associated with anti-dsDNA antibody in SLE. No significant interaction was observed between DRB1*09:01 and smoking status for the appearance of ACPA, unlike that observed in SE alleles in RA. Conclusion. We identified HLA-DRB1 alleles associated with SLE and RA in a Japanese population and demonstrated a shared susceptibility of DRB1*09:01 between the diseases as well as its effect on autoantibody production.

PLD4 as a novel susceptibility gene for systemic sclerosis in a Japanese population.

OBJECTIVE: Systemic sclerosis (SSc) is an autoimmune disease for which multiple susceptibility genes have been reported. Genome-wide association studies have shown that large numbers of susceptibility genes are shared among autoimmune diseases. Recently, our group identified 9 novel susceptibility genes associated with rheumatoid arthritis (RA) in a Japanese population. The aim of this study was to elucidate whether the 18 genes that displayed associations or suggestive associations for RA in our previous study are associated with SSc in Japanese. METHODS: We performed an association study that included 415 patients with SSc and 16,891 control subjects, followed by a replication study that included 315 patients and 21,054 control subjects. The 18 markers reported to display association with RA were analyzed for their associations with SSc in the first study, and 5 markers were further analyzed in the replication study. The inverse variance method was used to evaluate the associations of these markers with SSc in a combined study. RESULTS: In the phospholipase D4 gene (PLD4), rs2841277 displayed a significant association with SSc in Japanese patients (P = 0.00017). We observed that rs2841280 in exon 2 of PLD4 was in strong linkage disequilibrium with rs2841277 and introduced an amino acid alteration. We also observed associations between SSc and rs6932056 in TNFAIP3 and rs2280381 in IRF8 (P = 0.0000095 and P = 0.0030, respectively), both of which displayed associations with SSc in a European population. CONCLUSION: We determined that PLD4 is a novel susceptibility gene for SSc in Japanese, thus confirming the involvement of PLD4 in autoimmunity. Associations between SSc and TNFAIP3 or IRF8 were also detected in our Japanese population. SSc and RA appear to share relatively large proportions of their genetic backgrounds.

Functional variants in NFKBIE and RTKN2 involved in activation of the NF-κB pathway are associated with rheumatoid arthritis in Japanese.

Rheumatoid arthritis is an autoimmune disease with a complex etiology, leading to inflammation of synovial tissue and joint destruction. Through a genome-wide association study (GWAS) and two replication studies in the Japanese population (7,907 cases and 35,362 controls), we identified two gene loci associated with rheumatoid arthritis susceptibility (NFKBIE at 6p21.1, rs2233434, odds ratio (OR) = 1.20, P = 1.3 × 10(-15); RTKN2 at 10q21.2, rs3125734, OR = 1.20, P = 4.6 × 10(-9)). In addition to two functional non-synonymous SNPs in NFKBIE, we identified candidate causal SNPs with regulatory potential in NFKBIE and RTKN2 gene regions by integrating in silico analysis using public genome databases and subsequent in vitro analysis. Both of these genes are known to regulate the NF-κB pathway, and the risk alleles of the genes were implicated in the enhancement of NF-κB activity in our analyses. These results suggest that the NF-κB pathway plays a role in pathogenesis and would be a rational target for treatment of rheumatoid arthritis.

Use of a multiethnic approach to identify rheumatoid- arthritis-susceptibility loci, 1p36 and 17q12.

We have previously shown that rheumatoid arthritis (RA) risk alleles overlap between different ethnic groups. Here, we utilize a multiethnic approach to show that we can effectively discover RA risk alleles. Thirteen putatively associated SNPs that had not yet exceeded genome-wide significance (p < 5 × 10(-8)) in our previous RA genome-wide association study (GWAS) were analyzed in independent sample sets consisting of 4,366 cases and 17,765 controls of European, African American, and East Asian ancestry. Additionally, we conducted an overall association test across all 65,833 samples (a GWAS meta-analysis plus the replication samples). Of the 13 SNPs investigated, four were significantly below the study-wide Bonferroni corrected p value threshold (p < 0.0038) in the replication samples. Two SNPs (rs3890745 at the 1p36 locus [p = 2.3 × 10(-12)] and rs2872507 at the 17q12 locus [p = 1.7 × 10(-9)]) surpassed genome-wide significance in all 16,659 RA cases and 49,174 controls combined. We used available GWAS data to fine map these two loci in Europeans and East Asians, and we found that the same allele conferred risk in both ethnic groups. A series of bioinformatic analyses identified TNFRSF14-MMEL1 at the 1p36 locus and IKZF3-ORMDL3-GSDMB at the 17q12 locus as the genes most likely associated with RA. These findings demonstrate empirically that a multiethnic approach is an effective strategy for discovering RA risk loci, and they suggest that combining GWASs across ethnic groups represents an efficient strategy for gaining statistical power.

The human AIRE gene at chromosome 21q22 is a genetic determinant for the predisposition to rheumatoid arthritis in Japanese population.

Rheumatoid arthritis (RA) is a typical complex trait and the major cause of chronic inflammation worldwide. Although multiple genetic loci have been shown for their association with the onset of RA, they cover only a part of its genetic components and are largely ethnicity-specific. To identify novel genetic factors related to the predisposition and prognosis of RA in Japanese, we conducted a large-scale genome-wide association (GWA) study. We performed a GWA analysis by scanning the genome of 1247 RA cases and 1486 controls for 277 420 single nucleotide polymorphisms (SNPs), followed by replication analysis using two independent sample sets consisting of 1865 cases and 1623 controls, and 2303 cases and 3380 controls. We identified two SNPs, rs2075876 and rs760426, in intron of the autoimmune regulator AIRE gene at chromosome 21q22 that showed strong associations with the disease (P= 3.6 × 10(-9) and P= 4.4 × 10(-8), respectively). Rs1800250, in exon7 of AIRE, was in strong linkage disequilibrium (r(2)= 0.94) with rs2075876 and introduced an amino acid alteration (S278R) in the SAND domain of the AIRE protein. In silico analysis showed the decreased transcription of AIRE by the risk allele of rs2075876 compared with the alternative allele (P= 6.8 × 10(-5)). No correlation was observed between the rs2075876 genotype and quantitative traits reflecting the progression of RA. As AIRE is a key molecule which regulates the expression and presentation of self-antigens in thymic negative selection, its downregulation by genetic polymorphisms may result in the survival of auto-reactive T cells to trigger auto-inflammation in RA.

PADI4 polymorphism predisposes male smokers to rheumatoid arthritis.

OBJECTIVE: To elucidate the differential role of peptidyl arginine deiminase 4 (PADI4) polymorphism in rheumatoid arthritis (RA) between Asian and European populations, possible gene-environmental interactions among the PADI4 polymorphism, sex and smoking status were analysed. METHODS: Three independent sets of case-control samples were genotyped for single-nucleotide polymorphisms in PADI4; Japanese samples (first set, 1019 RA patients, 907 controls; second set, 999 RA patients, 1128 controls) using TaqMan assays and Dutch samples (635 RA patients, 391 controls) using Sequenom MassARRAY platform. The association of PADI4 with RA susceptibility was evaluated by smoking status and sex in contingency tables and logistic regression models. RESULTS: In the first set of Japanese samples, PADI4 polymorphism (rs1748033) showed a greater risk in men (OR(allele) 1.39; 95% CI 1.10 to 1.76; p(trend)=0.0054) than in women and in ever-smokers (OR(allele) 1.25; 95% CI 1.02 to 1.53; p(trend)=0.032) than in never-smokers. Moreover, the highest risk was seen in male ever-smokers (OR(allele) 1.46; 95% CI 1.12 to 1.90; p(trend)=0.0047). Similar trends were observed in the second set of Japanese samples as well as in Dutch samples. CONCLUSION: PADI4 polymorphism highly predisposes male smokers to RA, and the genetic heterogeneity observed between Asian and European populations may be partly explained by differences in smoking prevalence among men.