A large-scale rheumatoid arthritis genetic study identifies association at chromosome 9q33.2

Role of Selected Genetic Polymorphisms in the Development of Rheumatoid Arthritis in a British White Population

BACKGROUND

Rheumatoid arthritis (RA) is a complex autoimmune disease that negatively affects synovial joints, leading to the deterioration of movement and mobility of patients. This chronic disease is considered to have a strong genetic inheritance, with genome-wide association studies (GWAS) highlighting many genetic loci associated with the disease. Moreover, numerous confounding and non-genetic factors also contribute to the risk of the disease.

AIMS

This study investigates the association of selected genetic polymorphisms with rheumatoid arthritis risk and develops a polygenic risk score (PRS) based on selected genes.

METHODS

A case-control study recruited fully consenting participants from the East Midlands region of the UK. DNA samples were genotyped for a range of polymorphisms and genetic associations were calculated under several inheritance models. PRS was calculated at crude (unweighted) and weighted levels, and its associations with clinical parameters were determined.

RESULTS

There were significant associations with the risk of RA at six genetic markers and their associated risk alleles (TNRF2*G, TRAF1*A, PTPN22*T, HLA-DRB1*G, TNFα*A, and IL4-590*T). The TTG haplotype at the VDR locus increased the risk of RA with an OR of 3.05 (CI 1.33-6.98, p = 0.009). The GA haplotype of HLADRB1-TNFα-308 was a significant contributor to the risk of RA in this population (OR = 2.77, CI 1.23-6.28, p = 0.01), although linkage disequilibrium was low. The polygenic risk score was significantly higher in cases over controls in both unweighted (mean difference = 1.48, t285 = 5.387, p < 0.001) and weighted (mean difference = 2.75, t285 = 6.437, p < 0.001) results.

CONCLUSION

Several genetic loci contribute to the increased risk of RA in the British White sample. The PRS is significantly higher in those with RA and can be used for clinical applications and personalised prevention of disease.

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.

A genome-wide cross-trait analysis identifies genomic correlation, pleiotropic loci, and causal relationship between sex hormone-binding globulin and rheumatoid arthritis

BACKGROUND

Our study aims to investigate an intrinsic link underlying sex hormone-binding globulin (SHBG) and rheumatoid arthritis (RA), which remains inconclusive in observational settings.

METHODS

Summary statistics were collected from the largest GWAS(s) on SHBG adjusted for BMI (SHBGadjBMI; Noverall = 368,929; Nmen = 180,094; Nwomen = 188,908), crude SHBG (Noverall = 370,125; Nmen = 180,726; Nwomen = 189,473), and RA (Ncase = 22,350; Ncontrol = 74,823). A genome-wide cross-trait design was performed to quantify global and local genetic correlation, identify pleiotropic loci, and infer a causal relationship.

RESULTS

Among the overall population, a significant global genetic correlation was observed for SHBGadjBMI and RA ([Formula: see text] = 0.11, P = 1.0 × 10-4) which was further supported by local signal (1q25.2). A total of 18 independent pleiotropic SNPs were identified, of which three were highly likely causal variants and four were found to have effects on both traits through gene expression mediation. A putative causal association of SHBGadjBMI on RA was demonstrated (OR = 1.20, 95% CI = 1.01-1.43) without evidence of reverse causality (OR = 0.999, 95% CI = 0.997-1.000). Sex-specific analyses revealed distinct shared genetic regions (men: 1q32.1-q32.2 and 5p13.1; women: 1q25.2 and 22q11.21-q11.22) and diverse pleiotropic SNPs (16 in men and 18 in women, nearly half were sex-specific) underlying SHBGadjBMI and RA, demonstrating biological disparities between sexes. Replacing SHBGadjBMI with crude SHBG, a largely similar yet less significant pattern of results was observed.

CONCLUSION

Our cross-trait analysis suggests an intrinsic, as well as a sex-specific, link underlying SHBG and RA, providing novel insights into disease etiology.

Insights into high-risk multiple myeloma from an analysis of the role of PHF19 in cancer

Despite  improvements in outcome, 15-25% of newly diagnosed multiple myeloma (MM) patients have treatment resistant high-risk (HR) disease with a poor survival. The lack of a genetic basis for HR has focused attention on the role played by epigenetic changes. Aberrant expression and somatic mutations affecting genes involved in the regulation of tri-methylation of the lysine (K) 27 on histone 3 H3 (H3K27me3) are common in cancer. H3K27me3 is catalyzed by EZH2, the catalytic subunit of the Polycomb Repressive Complex 2 (PRC2). The deregulation of H3K27me3 has been shown to be involved in oncogenic transformation and tumor progression in a variety of hematological malignancies including MM. Recently we have shown that aberrant overexpression of the PRC2 subunit PHD Finger Protein 19 (PHF19) is the most significant overall contributor to HR status further focusing attention on the role played by epigenetic change in MM. By modulating both the PRC2/EZH2 catalytic activity and recruitment, PHF19 regulates the expression of key genes involved in cell growth and differentiation. Here we review the expression, regulation and function of PHF19 both in normal and the pathological contexts of solid cancers and MM. We present evidence that strongly implicates PHF19 in the regulation of genes important in cell cycle and the genetic stability of MM cells making it highly relevant to HR MM behavior. A detailed understanding of the normal and pathological functions of PHF19 will allow us to design therapeutic strategies able to target aggressive subsets of MM.

C5 Variant rs10985126 is Associated with Mortality in Patients with Symptomatic Coronary Artery Disease

BACKGROUND

Complement component 5a (C5a) is a highly potent anaphylatoxin with a variety of pro-inflammatory effects. C5a contributes to progression of atherosclerosis and inhibition of the receptor (C5aR) might offer a therapeutic strategy in this regard. Single nucleotide polymorphisms (SNPs) of the C5 gene may modify protein expression levels and therefore function of C5a and C5aR. This study aimed to examine associations between clinically relevant C5a SNPs and the prognosis of patients with symptomatic coronary artery disease (CAD). Furthermore, we sought to investigate the influence of C5 SNPs on C5aR platelet surface expression and circulating C5a levels.

METHODS

C5 variants (rs25681, rs17611, rs17216529, rs12237774, rs41258306, and rs10985126) were analyzed in a consecutive cohort of 833 patients suffering from symptomatic coronary artery disease (CAD). Circulating C5a levels were determined in 116 patients whereas C5aR platelet surface expression was measured in 473 CAD patients. Endpoints included all-cause mortality, myocardial infarction (MI), and ischemic stroke (IS). Homozygous carriers (HC) of the minor allele (rs10985126) showed significantly higher all-cause mortality than major allele carriers. While we could not find significant associations between rs10985126 allele frequency and C5aR platelet surfazl ce expression, significantly elevated levels of circulating C5a were found in HC of the minor allele of the respective genotype. rs17216529 allele frequency correlated with the composite combined endpoint and bleeding events. However, since the number of HC of the minor allele of this genotype was low, we cannot draw a robust conclusion about the observed associations.

CONCLUSION

In this study, we provide evidence for the prognostic relevance of rs10985126 in CAD patients. C5 rs10985126 may serve as a prognostic biomarker for risk stratification in high-risk CAD patients and consequently promote tailored therapies.

Inhibitory feedback control of NF-κB signalling in health and disease

Cells must adapt to changes in their environment to maintain cell, tissue and organismal integrity in the face of mechanical, chemical or microbiological stress. Nuclear factor-κB (NF-κB) is one of the most important transcription factors that controls inducible gene expression as cells attempt to restore homeostasis. It plays critical roles in the immune system, from acute inflammation to the development of secondary lymphoid organs, and also has roles in cell survival, proliferation and differentiation. Given its role in such critical processes, NF-κB signalling must be subject to strict spatiotemporal control to ensure measured and context-specific cellular responses. Indeed, deregulation of NF-κB signalling can result in debilitating and even lethal inflammation and also underpins some forms of cancer. In this review, we describe the homeostatic feedback mechanisms that limit and ‘re-set’ inducible activation of NF-κB. We first describe the key components of the signalling pathways leading to activation of NF-κB, including the prominent role of protein phosphorylation and protein ubiquitylation, before briefly introducing the key features of feedback control mechanisms. We then describe the array of negative feedback loops targeting different components of the NF-κB signalling cascade including controls at the receptor level, post-receptor signalosome complexes, direct regulation of the critical ‘inhibitor of κB kinases’ (IKKs) and inhibitory feedforward regulation of NF-κB-dependent transcriptional responses. We also review post-transcriptional feedback controls affecting RNA stability and translation. Finally, we describe the deregulation of these feedback controls in human disease and consider how feedback may be a challenge to the efficacy of inhibitors.

Identification of Novel Pleiotropic SNPs Associated with Osteoporosis and Rheumatoid Arthritis

Genome-wide association studies (GWASs) have identified hundreds of genetic loci for osteoporosis (OP) and rheumatoid arthritis (RA), individually, however, a large proportion of the total trait heritability remains unexplained. Previous studies demonstrated that these two diseases may share some common genetic determination and risk factors, but they were generally focused on individual trait and failed to identify the common variants that play key functional roles in the etiology of these two diseases. Here, we performed a conditional false discovery rate (cFDR) analysis to identify novel pleiotropic variants shared between them by integrating two independent GWASs with summary statistics for total body bone mineral density (TB-BMD, a major risk factor for osteoporosis) (n = 66,628) and RA (n = 58,284). A fine-mapping approach was also applied to identify the most probable causal variants with biological effects on both TB-BMD and RA. As a result, we found 47 independent pleiotropic SNPs shared between TB-BMD and RA, and 40 of them were validated in heel ultrasound estimated BMD (eBMD), femoral neck BMD (FN-BMD) or lumbar spine (LS-BMD). We detected one SNP (rs13299616) was novel and not identified by previous BMD or RA-related studies. Combined with fine-mapping and GWAS-eQTL colocalization analyses, our results suggested that locus 1p13.2 (including PTPN22, MAGI3, PHTF1, and RSBN1) was an important region to regulate TB-BMD and RA simultaneously. These findings provide new insights into the shared biological mechanisms and functional genetic determinants between OP and RA, and novel potential targets for treatment development.

TLR expression profiles are a function of disease status in rheumatoid arthritis and experimental arthritis

The role of the innate immune system has been established in the initiation and perpetuation of inflammatory disease, but less attention has been paid to its role in the resolution of inflammation and return to homeostasis. Toll-like receptor (TLR) expression profiles were analysed in tissues with differing disease status in rheumatoid arthritis (RA), ankylosing spondylitis (AS), and in experimental arthritis. TLR gene expression was measured in whole blood and monocytes, before and after TNF blockade. In RA and osteoarthritis synovia, the expression of TLRs was quantified by standard curve qPCR. In addition, four distinct stages of disease were defined and validated in collagen-induced arthritis (CIA), the gold standard animal model for RA - pre-onset, early disease, late disease and immunised mice that were resistant to the development of disease. TLR expression was measured in spleens, lymph nodes, blood cells, liver and the paws (inflamed and unaffected). In RA whole blood, the expression of TLR1, 4 and 6 was significantly reduced by TNF blockade but the differences in TLR expression profiles between responders and non-responders were less pronounced than the differences between RA and AS patients. In RA non-responders, monocytes had greater TLR2 expression prior to therapy compared to responders. The expression of TLR1, 2, 4 and 8 was higher in RA synovium compared to control OA synovium. Circulating cytokine levels in CIA resistant mice were similar to naïve mice, but anti-collagen antibodies were similar to arthritic mice. Distinct profiles of inflammatory gene expression were mapped in paws and organs with differing disease status. TLR expression in arthritic paws tended to be similar in early and late disease, with TLR1 and 2 moderately higher in late disease. TLR expression in unaffected paws varied according to gene and disease status but was generally lower in resistant paws. Disease status-specific profiles of TLR expression were observed in spleens, lymph nodes, blood cells and the liver. Notably, TLR2 expression rose then fell in the transition from naïve to pre-onset to early arthritis. TLR gene expression profiles are strongly associated with disease status. In particular, increased expression in the blood precedes clinical manifestation.

TRAF1 suppresses antifungal immunity through CXCL1-mediated neutrophil recruitment during Candida albicans intradermal infection

Background

Candida albicans is the most common opportunistic human fungal pathogen. The chemokine ligand CXCL1 plays a protective role in fungal infection through the recruitment of neutrophils. TRAF1 (tumor necrosis factor-associated factor 1) can be highly induced by proinflammatory stimuli such as LPS and TNF and has been implicated in septic shock. However, the role of TRAF1 in infection, especially fungal infection, remains elusive. Herein, we reveal that TRAF1 suppresses the antifungal immune response to Candida albicans intradermal infection through the regulation of CXCL1 induction and neutrophil recruitment.

Methods

A mouse model of C. albicans intradermal infection was established. The Traf1^−/− mice and Traf1^−/− immortalized human keratinocytes were generated. The p65 inhibitor triptolide, STAT1 inhibitor fludarabine, neutrophil-depletion antibody Ly6G, and neutralizing antibody for CXCL1 were utilized. The expression of proinflammatory cytokines and chemokines was assessed by real-time PCR and ELISA, and the activation of signaling molecules was analyzed by Western blotting. Hematoxylin and eosin staining and periodic acid Schiff staining were used for histology or fungal detection, respectively. The immunofluorescence and flow cytometry analyses were employed in the assessment of immune cell infiltration. Bone marrow transplantation and adoptive transfer experiments were conducted to establish a role for TRAF1 in the macrophage compartment in fungal skin infection.

Results

TRAF1-deficient mice demonstrated improved control of Candida albicans intradermal infection, and concomitant increase in neutrophil recruitment and reduction in fungal burden. The chemokine CXCL1 was upregulated in the TRAF1-deficient macrophages treated with heat-killed C. albicans. Mechanistically, TRAF1-deficient macrophages showed increased activation of transcription factor NFκB p65. The human CXCL8 was also highly induced in the TRAF1-deficient human keratinocytes upon TNF stimulation through decreasing the activation of transcription factor STAT1. TRAF1-deficient macrophages played a critical role in containing the C. albicans skin infection in vivo.

Conclusion

TRAF1-deficient mice can better control fungal infection in the skin, a process attributable to the CXCL-neutrophil axis. Mechanistically, TRAF1 likely regulates CXCL1 expression in both macrophages and keratinocytes through the transcriptional factor NFκB and STAT1, respectively. Our finding offers new insight into the understanding of the immune regulatory mechanisms in host defense against C. albicans infection.

Graphical abstract

Associations of TRAF1/C5 rs10818488 and rs3761847 polymorphisms with genetic susceptibility to rheumatoid arthritis: a case-control study and updated meta-analysis

The results on associations of tumor necrosis factor (TNF)-receptor associated factor 1/complement component 5 (TRAF1/C5) rs10818488 and rs3761847 polymorphisms with rheumatoid arthritis (RA) are controversial, thus this study was performed to examine whether the aforementioned polymorphisms were associated with RA in a Chinese population. Furthermore, an updated meta-analysis was conducted. The polymorphisms were genotyped in 328 Chinese RA patients and 449 healthy controls. Studies examining the association of TRAF1/C5 rs10818488 and/or rs3761847 polymorphism with RA were exhaustively searched. No significant difference in either genotype or allele distribution between RA patients and controls was found. The updated meta-analysis was conducted based on 19 articles including the present study. A significant association of RA with TRAF1/C5 rs10818488 polymorphism G allele in Europeans (OR = 0.843, 95% CI = 0.730-0.975, p = 0.021) and in Asians (OR = 1.070, 95% CI = 1.009-1.136, p = 0.024) was found. Additionally, a significant association of RA with TRAF1/C5 rs10818488 polymorphism G allele under the recessive model in Asians (OR = 1.129, 95% CI = 1.023-1.246, p = 0.016) and in Africans (OR = 0.657, 95% CI = 0.507-0.851, p = 0.001) was found. Only a borderline significant association of RA with TRAF1/C5 rs3761847 polymorphism A allele was found in Europeans. Non-significant associations of RA with TRAF1/C5 rs10818488 and rs3761847 polymorphisms were found in our study. The updated meta-analysis results demonstrate that TRAF1/C5 rs10818488 polymorphism is associated with RA in Europeans, Asians and Africans, and TRAF1/C5 rs3761847 polymorphism is associated with RA in Europeans with borderline significant evidence.

The genetic pathogenesis, diagnosis and therapeutic insight of rheumatoid arthritis

Rheumatoid arthritis (RA) is a systemic autoimmune disease that causes chronic inflammation of the joints. RA is a heterogeneous disorder caused by an abnormal autoimmune response triggered by the complex interactions of genetic and environmental factors that contribute to RA etiology. However, its underlying pathogenic mechanisms are yet to be fully understood. In this review, I provide an overview of the pathogenesis, diagnosis and therapeutic insight in the clinical management of RA in light of the recent updates to classification criteria and recent discoveries of genetic loci associated with susceptibility for RA.

Studying the effects of haplotype partitioning methods on the RA-associated genomic results from the North American Rheumatoid Arthritis Consortium (NARAC) dataset

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Haplotype blocks methods plays a complementary role to the single-SNP approaches.

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CIT, FGT, SSLD, and single-SNP methods should be applied to discover the markers.

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Selection of the method used for the association has an impact on the biomarkers.

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SSLD method detected more significant SNPs than CIT, FGT, and single-SNP methods.

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The 383 SNPs discovered by all methods are significantly associated with RA.

The human genome, which includes thousands of genes, represents a big data challenge. Rheumatoid arthritis (RA) is a complex autoimmune disease with a genetic basis. Many single-nucleotide polymorphism (SNP) association methods partition a genome into haplotype blocks. The aim of this genome wide association study (GWAS) was to select the most appropriate haplotype block partitioning method for the North American Rheumatoid Arthritis Consortium (NARAC) dataset. The methods used for the NARAC dataset were the individual SNP approach and the following haplotype block methods: the four-gamete test (FGT), confidence interval test (CIT), and solid spine of linkage disequilibrium (SSLD). The measured parameters that reflect the strength of the association between the biomarker and RA were the P-value after Bonferroni correction and other parameters used to compare the output of each haplotype block method. This work presents a comparison among the individual SNP approach and the three haplotype block methods to select the method that can detect all the significant SNPs when applied alone. The GWAS results from the NARAC dataset obtained with the different methods are presented. The individual SNP, CIT, FGT, and SSLD methods detected 541, 1516, 1551, and 1831 RA-associated SNPs respectively, and the individual SNP, FGT, CIT, and SSLD methods detected 65, 156, 159, and 450 significant SNPs respectively, that were not detected by the other methods. Three hundred eighty-three SNPs were discovered by the haplotype block methods and the individual SNP approach, while 1021 SNPs were discovered by all three haplotype block methods. The 383 SNPs detected by all the methods are promising candidates for studying RA susceptibility. A hybrid technique involving all four methods should be applied to detect the significant SNPs associated with RA in the NARAC dataset, but the SSLD method may be preferred because of its advantages when only one method was used.

TRAF1 Signaling in Human Health and Disease

Tumor necrosis factor receptor (TNFR) associated factor 1 (TRAF1) is a signaling adaptor first identified as part of the TNFR2 signaling complex. TRAF1 plays a key role in pro-survival signaling downstream of TNFR superfamily members such as TNFR2, LMP1, 4-1BB, and CD40. Recent studies have uncovered another role for TRAF1, independent of its role in TNFR superfamily signaling, in negatively regulating Toll-like receptor and Nod-like receptor signaling, through sequestering the linear ubiquitin assembly complex, LUBAC. TRAF1 has diverse roles in human disease. TRAF1 is overexpressed in many B cell related cancers and single nucleotide polymorphisms (SNPs) in TRAF1 have been linked to non-Hodgkin's lymphoma. Genome wide association studies have identified an association between SNPs in the 5' untranslated region of the TRAF1 gene with increased incidence and severity of rheumatoid arthritis and other rheumatic diseases. The loss of TRAF1 from chronically stimulated CD8 T cells results in desensitization of the 4-1BB signaling pathway, thereby contributing to T cell exhaustion during chronic infection. These apparently opposing roles of TRAF1 as both a positive and negative regulator of immune signaling have led to some confusion in the literature. Here we review the role of TRAF1 as a positive and negative regulator in different signaling pathways. Then we discuss the role of TRAF1 in human disease, attempting to reconcile seemingly contradictory roles based on current knowledge of TRAF1 signaling and biology. We also discuss avenues for future research to further clarify the impact of TRAF1 in human disease.

Systematic approach demonstrates enrichment of multiple interactions between non-HLA risk variants and HLA-DRB1 risk alleles in rheumatoid arthritis

OBJECTIVE

In anti-citrullinated protein antibody positive rheumatoid arthritis (ACPA-positive RA), a particular subset of HLA-DRB1 alleles, called shared epitope (SE) alleles, is a highly influential genetic risk factor. Here, we investigated whether non-HLA single nucleotide polymorphisms (SNP), conferring low disease risk on their own, interact with SE alleles more frequently than expected by chance and if such genetic interactions influence the HLA-DRB1 SE effect concerning risk to ACPA-positive RA.

METHODS

We computed the attributable proportion (AP) due to additive interaction at genome-wide level for two independent ACPA-positive RA cohorts: the Swedish epidemiological investigation of rheumatoid arthritis (EIRA) and the North American rheumatoid arthritis consortium (NARAC). Then, we tested for differences in the AP p value distributions observed for two groups of SNPs, non-associated and associated with disease. We also evaluated whether the SNPs in interaction with HLA-DRB1 were cis-eQTLs in the SE alleles context in peripheral blood mononuclear cells from patients with ACPA-positive RA (SE-eQTLs).

RESULTS

We found a strong enrichment of significant interactions (AP p<0.05) between the HLA-DRB1 SE alleles and the group of SNPs associated with ACPA-positive RA in both cohorts (Kolmogorov-Smirnov test D=0.35 for EIRA and D=0.25 for NARAC, p<2.2e-16 for both). Interestingly, 564 out of 1492 SNPs in consistent interaction for both cohorts were significant SE-eQTLs. Finally, we observed that the effect size of HLA-DRB1 SE alleles for disease decreases from 5.2 to 2.5 after removal of the risk alleles of the two top interacting SNPs (rs2476601 and rs10739581).

CONCLUSION

Our data demonstrate that there are massive genetic interactions between the HLA-DRB1 SE alleles and non-HLA genetic variants in ACPA-positive RA.

Genetic variants within the TNFRSF1B gene and susceptibility to rheumatoid arthritis and response to anti-TNF drugs: a multicenter study

BACKGROUND

Recent research suggests that genetic variants in the tumor necrosis factor receptor 2 (TNFRSF1B) gene may have an impact on susceptibility to rheumatoid arthritis (RA) and drug response. The present population-based case-control study was carried out to evaluate whether 5 tagging single-nucleotide polymorphisms (SNPs) within the TNFRSF1B gene are associated with the risk of RA and response to antitumor necrosis factor (TNF) drugs.

METHODS

The study population included 1412 RA patients and 1225 healthy controls. A subset of 596 anti-TNF-naive RA patients was selected to assess the association of TNFRSF1B SNPs and drug response according to the EULAR response criteria.

RESULTS

We found that carriers of the TNFRSF1Brs3397C allele had a significantly increased risk of developing RA (P=0.0006). Importantly, this association remained significant after correction for multiple testing. We also confirmed the lack of association of the TNFRSF1Brs1061622 SNP with the risk of RA in the single-SNP analysis (P=0.89), but also through well-powered meta-analyses (PDOM=0.67 and PREC=0.37, respectively). In addition, our study showed that carriers of the TNFRSF1Brs3397C/C, TNFRSF1Brs1061622G/G, and TNFRSF1Brs1061631A/A genotypes had an increased risk of having a worse response to anti-TNF drugs at the level of P less than 0.05 (P=0.014, 0.0085 and 0.028, respectively). We also observed that, according to a log-additive model, carriers of the TNFRSF1Brs3397C or TNFRSF1Brs1061622G alleles showed an increased risk of having worse response to anti-TNF medications (P=0.018 and 0.0059). However, the association of the TNFRSF1Brs1061622 SNP only reached marginal significance after correction for multiple testing according to a log-additive model (P=0.0059) and it was not confirmed through a meta-analysis (PDOM=0.12).

CONCLUSION

Our results suggest that the TNFRSF1Brs3397 variant may play a role in modulating the risk of RA, but does not provide strong evidence of an impact of TNFRSF1B variants in determining response to anti-TNF drugs.

Transcription factor Phf19 positively regulates germinal center reactions that underlies its role in rheumatoid arthritis

The Polycomb Repressive Complex 2 (PRC2) component PHD Finger Protein 19 (phf19) gene has been identified to be associated with rheumatoid arthritis (RA) risk. Here we show that Phf19 is highly expressed in murine germinal centers (GCs) and RA patients. To investigate the function of Phf19 in lymphocytes, we generated RAG1-deficient mice reconstituted with Phf19 or control-vector transduced bone marrow (BM) cells. Lymphogenesis in primary lymphoid tissues of Phf19-RM is normal, however, Phf19-RM form enlarged GCs and generate more antibody-secreting cells (ASCs). Overexpression of Phf19 promotes proliferation and survival of GC B cells and Tfh cells in vivo. The uncovered Phf19-dependent targets include the genes encoding cyclin D2, the prosurvival factor Bcl-xL and CD40-CD40 ligand axis, their regulation by Phf19 could partially elucidate the advantages observed in Phf19-overexpressing GCs. Our results underscore an unrecognized but critical function for Phf19 in GCs formation and antibody generation, and implicate the potential role of Phf19 in RA pathogenesis.

TRAF molecules in inflammation and inflammatory diseases

Purpose of Review

This review presents an overview of the current knowledge of TRAF molecules in inflammation with an emphasis on available human evidence and direct in vivo evidence of mouse models that demonstrate the contribution of TRAF molecules in the pathogenesis of inflammatory diseases.

Recent Findings

The tumor necrosis factor receptor (TNF-R)-associated factor (TRAF) family of cytoplasmic proteins was initially identified as signaling adaptors that bind directly to the intracellular domains of receptors of the TNF-R superfamily. It is now appreciated that TRAF molecules are widely employed in signaling by a variety of adaptive and innate immune receptors as well as cytokine receptors. TRAF-dependent signaling pathways typically lead to the activation of nuclear factor-κBs (NF-κBs), mitogen-activated protein kinases (MAPKs), or interferon-regulatory factors (IRFs). Most of these signaling pathways have been linked to inflammation, and therefore TRAF molecules were expected to regulate inflammation and inflammatory responses since their discovery in 1990s. However, direct in vivo evidence of TRAFs in inflammation and especially in inflammatory diseases had been lacking for many years, partly due to the difficulty imposed by early lethality of TRAF2^-/-, TRAF3^-/-, and TRAF6^-/- mice. With the creation of conditional knockout and lineage-specific transgenic mice of different TRAF molecules, our understanding about TRAFs in inflammation and inflammatory responses has rapidly advanced during the past decade.

Summary

Increasing evidence indicates that TRAF molecules are versatile and indispensable regulators of inflammation and inflammatory responses and that aberrant expression or function of TRAFs contributes to the pathogenesis of inflammatory diseases.

T cell activation Rho GTPase activating protein (TAGAP) is upregulated in clinical and experimental arthritis

Genome-wide association studies have identified various susceptibility variants and loci associated with incidence of rheumatoid arthritis (RA) in different populations. One of these is T cell activation Rho GTPase activating protein (TAGAP). The present study sought to measure the expression of TAGAP in RA patients, CD4⁺ T cells subsets from healthy humans and in mice with collagen-induced arthritis. Peripheral blood mononuclear cells (PBMC) from RA patients and tissues of arthritic mice at different stages of the disease were used for the evaluation of TAGAP mRNA expression. Increased TAGAP expression was observed in RA patients compared to healthy controls, and there were differences in the expression level of TAGAP in the tissues of mice with experimental arthritis. Gene expression in CD4⁺ T cells from healthy humans was greatest 4 h after activation and protein expression was greatest after 24 h. The expression of TAGAP was not correlated with CD4⁺ lymphocyte subsets which were enriched for functionally defined subsets (Th17, Treg, Th1), further indicating its utility as an indicator of lymphocyte activation. These findings indicate that increased TAGAP expression is a distinguishing feature of inflammatory disease and further highlight the role of TAGAP in RA susceptibility.

The Decay of Disease Association with Declining Linkage Disequilibrium: A Fine Mapping Theorem

Several important and fundamental aspects of disease genetics models have yet to be described. One such property is the relationship of disease association statistics at a marker site closely linked to a disease causing site. A complete description of this two-locus system is of particular importance to experimental efforts to fine map association signals for complex diseases. Here, we present a simple relationship between disease association statistics and the decline of linkage disequilibrium from a causal site. Specifically, the ratio of Chi-square disease association statistics at a marker site and causal site is equivalent to the standard measure of pairwise linkage disequilibrium, r². A complete derivation of this relationship from a general disease model is shown. Quite interestingly, this relationship holds across all modes of inheritance. Extensive Monte Carlo simulations using a disease genetics model applied to chromosomes subjected to a standard model of recombination are employed to better understand the variation around this fine mapping theorem due to sampling effects. We also use this relationship to provide a framework for estimating properties of a non-interrogated causal site using data at closely linked markers. Lastly, we apply this way of examining association data from high-density genotyping in a large, publicly-available data set investigating extreme BMI. We anticipate that understanding the patterns of disease association decay with declining linkage disequilibrium from a causal site will enable more powerful fine mapping methods and provide new avenues for identifying causal sites/genes from fine-mapping studies.

The signaling adaptor TRAF1 negatively regulates Toll-like receptor signaling and this underlies its role in rheumatic disease

TRAF1 is a signaling adaptor known for its role in tumor necrosis factor receptor-induced cell survival. Here we show that monocytes from healthy human subjects with a rheumatoid arthritis-associated single-nucleotide polymorphism (SNP) in the TRAF1 gene express less TRAF1 protein but greater amounts of inflammatory cytokines in response to lipopolysaccharide (LPS). The TRAF1 MATH domain binds directly to three components of the linear ubiquitination (LUBAC) complex, SHARPIN, HOIP and HOIL-1, to interfere with the recruitment and linear ubiquitination of NEMO. This results in decreased NF-κB activation and cytokine production, independently of tumor necrosis factor. Consistent with this, Traf1^-/- mice show increased susceptibility to LPS-induced septic shock. These findings reveal an unexpected role for TRAF1 in negatively regulating Toll-like receptor signaling, providing a mechanistic explanation for the increased inflammation seen with a disease-associated TRAF1 SNP.

TcoF-DB v2: update of the database of human and mouse transcription co-factors and transcription factor interactions

Transcription factors (TFs) play a pivotal role in transcriptional regulation, making them crucial for cell survival and important biological functions. For the regulation of transcription, interactions of different regulatory proteins known as transcription co-factors (TcoFs) and TFs are essential in forming necessary protein complexes. Although TcoFs themselves do not bind DNA directly, their influence on transcriptional regulation and initiation, although indirect, has been shown to be significant, with the functionality of TFs strongly influenced by the presence of TcoFs. In the TcoF-DB v2 database, we collect information on TcoFs. In this article, we describe updates and improvements implemented in TcoF-DB v2. TcoF-DB v2 provides several new features that enables exploration of the roles of TcoFs. The content of the database has significantly expanded, and is enriched with information from Gene Ontology, biological pathways, diseases and molecular signatures. TcoF-DB v2 now includes many more TFs; has substantially increased the number of human TcoFs to 958, and now includes information on mouse (418 new TcoFs). TcoF-DB v2 enables the exploration of information on TcoFs and allows investigations into their influence on transcriptional regulation in humans and mice. TcoF-DB v2 can be accessed at http://tcofdb.org/.

Association of Complement C5 Gene Polymorphisms with Proliferative Diabetic Retinopathy of Type 2 Diabetes in a Chinese Han Population

Purpose

To investigate the association of C5 SNPs with proliferative diabetic retinopathy (PDR) of type 2 diabetes (T2D).

Methods

A total of four C5 SNPs including rs2269067, rs7040033, rs1017119 and rs7027797 were genotyped in 400 PDR patients with T2D (cases) and 600 non- proliferative diabetic retinopathy PDR (NPDR) with T2D patients (controls) by using PCR-RFLP method. mRNA expression was examined by real-time PCR. Cytokine production was detected by ELISA.

Results

The frequency of GG genotype of C5 rs2269067 was significantly increased in cases compared with controls (Pc = 3.4×10⁻⁵, OR = 1.87). And C5 mRNA expression was significantly increased in rs2269067 GG cases as compared with CG or CC cases (P = 0.003, P = 0.001, respectively). Moreover, the production of IL-6 was significantly increased in rs2269067 GG cases compared to CG cases or CC cases (P = 0.002, P = 0.001, respectively).

Conclusions

C5 rs2269067 GG genotype confers risk for PDR of T2D in Chinese han population and is associated with an elevated C5 mRNA expression and an increased IL-6 production.

Copy number variations and gene polymorphisms of complement components in ocular Behcet's disease and Vogt-Koyanagi-Harada syndrome

Complement is involved in many immune-mediated diseases. However, the association of its copy number variations (CNVs) and polymorphisms with Behcet’s disease (BD) and Vogt-Koyanagi-Harada syndrome (VKH) is unknown. We examined copy number and mRNA expression by real-time PCR. Cytokine production by stimulated peripheral blood mononuclear cells (PBMCs) in genotyped individuals was measured by ELISA. The frequencies of having more than two copies of C3 were significantly increased in BD and VKH, whereas CNV of C5 was only associated with BD. Increased frequencies of the GG genotype of C3 rs408290 and C5 rs2269067 were found in BD. No association was observed between C3 and C5 SNPs and VKH. mRNA expression in the high CNV group and GG cases of C3 and C5 was significantly higher compared to other genotypes. Increased interleukin-17 and IFN-γ was observed in the high CNV group and GG genotype cases of C3. Interleukin-17 but not IFN-γ was increased in the high CNV group and GG genotype cases of C5. No effect of C3 or C5 genetic variants was seen on the production of TNF-α, IL-10, IL-1β, MCP-1, IL-6 and IL-8. Our study thus provides further evidence for a role of complement in the pathogenesis of uveitis.

Genetic-based prediction of disease traits: prediction is very difficult, especially about the future

Translation of results from genetic findings to inform medical practice is a highly anticipated goal of human genetics. The aim of this paper is to review and discuss the role of genetics in medically-relevant prediction. Germline genetics presages disease onset and therefore can contribute prognostic signals that augment laboratory tests and clinical features. As such, the impact of genetic-based predictive models on clinical decisions and therapy choice could be profound. However, given that (i) medical traits result from a complex interplay between genetic and environmental factors, (ii) the underlying genetic architectures for susceptibility to common diseases are not well-understood, and (iii) replicable susceptibility alleles, in combination, account for only a moderate amount of disease heritability, there are substantial challenges to constructing and implementing genetic risk prediction models with high utility. In spite of these challenges, concerted progress has continued in this area with an ongoing accumulation of studies that identify disease predisposing genotypes. Several statistical approaches with the aim of predicting disease have been published. Here we summarize the current state of disease susceptibility mapping and pharmacogenetics efforts for risk prediction, describe methods used to construct and evaluate genetic-based predictive models, and discuss applications.

Associations between TRAF1-C5 gene polymorphisms and rheumatoid arthritis: a meta-analysis

OBJECTIVE

The aim of this study is to determine whether tumor necrosis factor receptor-associated factor 1-complement 5 (TRAF1-C5) polymorphisms are associated with susceptibility to rheumatoid arthritis (RA) in different populations.

METHODS

We conducted a meta-analysis of associations between the TRAF1-C5 polymorphisms and RA susceptibility.

RESULTS

A total of 24 comparative studies were included in this meta-analysis, including 22,682 patients with RA and 23,493 controls. The meta-analysis showed an association between the second allele of rs10818488 and RA in Europeans, but not in Asians (OR 1.229, 95% CI 1.094-1.381, p = 0.001; OR 1.060, 95% CI 0.930-1.335, p = 0.092). The meta-analysis also indicated an association between the second allele of rs3761847 and RA in Europeans, but not in Asians (OR 1.156, 95% CI 1.006-1.327, p = 0.041; OR 1.049, 95% CI 0.952-1.156, p = 0.333). The meta-analysis revealed an association between the second allele of the rs2900180 and rs10760130 polymorphisms and RA risk in Europeans (OR 1.224, 95% CI 1.065-1.405, p = 0.004; OR 1.072, 95% CI 1.002-1.147, p = 0.042).

CONCLUSIONS

This meta-analysis confirms that the TRAF1-C5 rs10818488, rs3761847, rs2900180 and rs10760130 polymorphisms are associated with RA susceptibility in Europeans.

Complement-targeted therapeutics in periodontitis

Periodontitis is a prevalent oral chronic inflammatory disease which, in severe forms, may exert a major impact on systemic health. Clinical and histological observations, as well as experimental animal studies, suggest involvement of the complement system in periodontitis. However, the precise roles of the various complement components and pathways in periodontitis have only recently started to be elucidated. In this chapter, we review recent progress in the field and discuss the potential of complement-targeted therapeutics in the treatment of periodontitis.

NF-κB and Rheumatoid Arthritis: Will Understanding Genetic Risk Lead to a Therapeutic Reward?

NF-κB has long been known to play an important role in autoimmune diseases such as rheumatoid arthritis (RA). Indeed, as our understanding of how NF-κB is utilized has increased, we have been hard put to find a process not associated with this transcription factor family in some way. However, new data originating, in part, from genome-wide association studies have demonstrated that very specific alterations in components of the NF-κB pathway are sufficient to confer increased risk of developing disease. Here we review the data which have identified specific components of the NF-κB pathway, and consider what is known of their mechanisms of action and how these mechanisms might play into the disease process. In addition, the use of genetic information to predict RA is considered.

TRAF1 gene polymorphism correlates with the titre of Gp210 antibody in patients with primary biliary cirrhosis

Background. Polymorphisms of TRAF1 (Tumor necrosis factor receptor-associated factor 1) are associated with rheumatoid arthritis (RA). Whether TRAF1 polymorphisms confer increased risk for primary biliary cirrhosis (PBC), an autoimmune liver disease which can co-exist with RA, is unknown. Aim of the Study. To assess the frequency of the RA-conferring susceptibility TRAF1 polymorphisms rs3761847 and rs2900180 in a cohort of PBC patients. The association of TRAF1 polymorphisms with clinical features and autoantibody markers was also analyzed. Methods. We studied 179 PBC patients and 300 controls. Samples were genotyped for TRAF1 gene polymorphisms by real-time PCR. Autoantibodies were tested by ELISA. Results. The frequency of rs3761847 and rs2900180 polymorphisms did not differ between patients and controls. Laboratory or clinical features were not associated with specific polymorphisms. Gp210 autoantibody titres were conspicuously higher among GG homozygotes of rs3761847 as compared with AA homozygotes (P = 0.02). In contrast, antichromatin titers were higher in AA compared to GG rs3761847 homozygotes (P = 0.04). Rheumatoid factor IgG titres were significantly higher in rs2900180 TT homozygotes than CC homozygotes (P = 0.02). Conclusions. TRAF1 polymorphisms occur with the similar frequency in PBC patients and in the general population, but their presence is probably involved in the regulation of specific PBC-related autoantibodies.

Network-based gene expression biomarkers for cold and heat patterns of rheumatoid arthritis in traditional chinese medicine

In Traditional Chinese Medicine (TCM), patients with Rheumatoid Arthritis (RA) can be classified into two main patterns: cold-pattern and heat-pattern. This paper identified the network-based gene expression biomarkers for both cold- and heat-patterns of RA. Gene expression profilings of CD4+ T cells from cold-pattern RA patients, heat-pattern RA patients, and healthy volunteers were obtained using microarray. The differentially expressed genes and related networks were explored using DAVID, GeneSpring software, and the protein-protein interactions (PPI) method. EIF4A2, CCNT1, and IL7R, which were related to the up-regulation of cell proliferation and the Jak-STAT cascade, were significant gene biomarkers of the TCM cold pattern of RA. PRKAA1, HSPA8, and LSM6, which were related to fatty acid metabolism and the I-κB kinase/NF-κB cascade, were significant biomarkers of the TCM heat-pattern of RA. The network-based gene expression biomarkers for the TCM cold- and heat-patterns may be helpful for the further stratification of RA patients when deciding on interventions or clinical trials.

K. T. Caucasian and Asian specific rheumatoid arthritis risk loci reveal limited replication and apparent allelic heterogeneity in north Indians

Genome-wide association studies and meta-analysis indicate that several genes/loci are consistently associated with rheumatoid arthritis (RA) in European and Asian populations. To evaluate the transferability status of these findings to an ethnically diverse north Indian population, we performed a replication analysis. We investigated the association of 47 single-nucleotide polymorphisms (SNPs) at 43 of these genes/loci with RA in a north Indian cohort comprising 983 RA cases and 1007 age and gender matched controls. Genotyping was done using Infinium human 660w-quad. Association analysis by chi-square test implemented in plink was carried out in two steps. Firstly, association of the index or surrogate SNP (r2>0.8, calculated from reference GIH Hap-Map population) was tested. In the second step, evidence for allelic/locus heterogeneity at aforementioned genes/loci was assessed for by testing additional flanking SNPs in linkage equilibrium with index/surrogate marker.Of the 44 European specific index SNPs, neither index nor surrogate SNPs were present for nine SNPs in the genotyping array. Of the remaining 35, associations were replicated at seven genes namely PTPN22 (rs1217407, p = 3×10(-3)); IL2-21 (rs13119723, p = 0.008); HLA-DRB1 (rs660895, p = 2.56×10(-5); rs6457617, p = 1.6×10(-09); rs13192471, p = 6.7×10(-16)); TNFA1P3 (rs9321637, p = 0.03); CCL21 (rs13293020, p = 0.01); IL2RA (rs2104286, p = 1.9×10(-4)) and ZEB1 (rs2793108, p = 0.006). Of the three Asian specific loci tested, rs2977227 in PADI4 showed modest association (p<0.02). Further, of the 140 SNPs (in LE with index/surrogate variant) tested, association was observed at 11 additional genes: PTPRC, AFF3, CD28, CTLA4, PXK, ANKRD55, TAGAP, CCR6, BLK, CD40 and IL2RB. This study indicates limited replication of European and Asian index SNPs and apparent allelic heterogeneity in RA etiology among north Indians warranting independent GWAS in this population. However, replicated associations of HLA-DRB1, PTPN22 (which confer ∼50% of the heritable risk to RA) and IL2RA suggest that cross-ethnicity fine mapping of such loci is apposite for identification of causal variants.

A network-based analysis of traditional Chinese medicine cold and hot patterns in rheumatoid arthritis

OBJECTIVE

Rheumatoid arthritis (RA) is a heterogeneous disease, and traditional Chinese medicine (TCM) can be used to classify RA into different patterns such as cold and hot based on its clinical manifestations. The aim of this study was to investigate potential network-based biomarkers for RA with either a cold or a hot pattern.

METHOD

Microarray technology was used to reveal gene expression profiles in CD4(+) T cells from 21 RA patients with cold pattern and 12 with hot pattern. A T-test was used to identify significant differences in gene expression among RA patients with either cold or hot pattern. Cytoscape software was used to search the existing literature and databases for protein-protein interaction information for genes of interest that were identified from this analysis. The IPCA algorithm was used to detect highly connected regions for inferring significant complexes or pathways in this protein-protein interaction network. Significant pathways and functions were extracted from these subnetworks by the Biological Network Gene Ontology tool.

RESULT

Four genes were expressed at higher levels in RA patients with cold pattern than in patients with hot pattern, and 21 genes had lower levels of expression. Protein-protein interaction network analysis for these genes showed that there were four highly connected regions. The most relevant functions and pathways extracted from these subnetwork regions were involved in small G protein signaling pathways, oxidation-reduction in fatty acid metabolism and T cell proliferation.

CONCLUSION

Complicated network based pathways appear to play a role in the different pattern manifestations in patients with RA, and our results suggest that network-based pathways might be the scientific basis for TCM pattern classification.

Negative regulation of NF-κB and its involvement in rheumatoid arthritis

The transcription factor NF-κB plays crucial roles in the regulation of inflammation and mmune responses, and inappropriate NF-κB activity has been linked with many autoimmune and inflammatory diseases, including rheumatoid arthritis. Cells employ a multilayered control system to keep NF-κB signalling in check, including a repertoire of negative feedback regulators ensuring termination of NF-κB responses. Here we will review various negative regulatory mechanisms that have evolved to control NF-κB signalling and which have been implicated in the pathogenesis of rheumatoid arthritis.

Causal graph-based analysis of genome-wide association data in rheumatoid arthritis

BACKGROUND

GWAS owe their popularity to the expectation that they will make a major impact on diagnosis, prognosis and management of disease by uncovering genetics underlying clinical phenotypes. The dominant paradigm in GWAS data analysis so far consists of extensive reliance on methods that emphasize contribution of individual SNPs to statistical association with phenotypes. Multivariate methods, however, can extract more information by considering associations of multiple SNPs simultaneously. Recent advances in other genomics domains pinpoint multivariate causal graph-based inference as a promising principled analysis framework for high-throughput data. Designed to discover biomarkers in the local causal pathway of the phenotype, these methods lead to accurate and highly parsimonious multivariate predictive models. In this paper, we investigate the applicability of causal graph-based method TIE* to analysis of GWAS data. To test the utility of TIE*, we focus on anti-CCP positive rheumatoid arthritis (RA) GWAS datasets, where there is a general consensus in the community about the major genetic determinants of the disease.

RESULTS

Application of TIE* to the North American Rheumatoid Arthritis Cohort (NARAC) GWAS data results in six SNPs, mostly from the MHC locus. Using these SNPs we develop two predictive models that can classify cases and disease-free controls with an accuracy of 0.81 area under the ROC curve, as verified in independent testing data from the same cohort. The predictive performance of these models generalizes reasonably well to Swedish subjects from the closely related but not identical Epidemiological Investigation of Rheumatoid Arthritis (EIRA) cohort with 0.71-0.78 area under the ROC curve. Moreover, the SNPs identified by the TIE* method render many other previously known SNP associations conditionally independent of the phenotype.

CONCLUSIONS

Our experiments demonstrate that application of TIE* captures maximum amount of genetic information about RA in the data and recapitulates the major consensus findings about the genetic factors of this disease. In addition, TIE* yields reproducible markers and signatures of RA. This suggests that principled multivariate causal and predictive framework for GWAS analysis empowers the community with a new tool for high-quality and more efficient discovery.

REVIEWERS

This article was reviewed by Prof. Anthony Almudevar, Dr. Eugene V. Koonin, and Prof. Marianthi Markatou.

Single nucleotide polymorphisms at the TRAF1/C5 locus are associated with rheumatoid arthritis in a Han Chinese population

BACKGROUND

Genetic variants in TRAF1C5 and PTPN22 genes have been shown to be significantly associated with arthritis rheumatoid in Caucasian populations. This study investigated the association between single nucleotide polymorphisms (SNPs) in TRAF1/C5 and PTPN22 genes and rheumatoid arthritis (RA) in a Han Chinese population. We genotyped SNPs rs3761847 and rs7021206 at the TRAF1/C5 locus and rs2476601 SNP in the PTPN22 gene in a Han Chinese cohort composed of 576 patients with RA and 689 controls. The concentrations of anti-cyclic citrullinated peptide antibodies (CCP) and rheumatoid factor (RF) were determined for all affected patients. The difference between the cases and the controls was compared using χ2 analysis.

RESULTS

Significant differences in SNPs rs3761847 and rs7021206 at TRAF1/C5 were observed between the case and control groups in this cohort; the allelic p-value was 0.0018 with an odds ratio of 1.28 for rs3761847 and 0.005 with an odds ratio of 1.27 for rs7021206. This significant association between rs3761847 and RA was independent of the concentrations of anti-CCP and RF. No polymorphism of rs2476601 was observed in this cohort.

CONCLUSIONS

We first demonstrated that genetic variants at the TRAF1/C5 locus are significantly associated with RA in Han Chinese, suggesting that TRAF1/C5 may play a role in the development of RA in this population, which expands the pathogenesis role of TRAF1/C5 in a different ethnicity.

Most common single-nucleotide polymorphisms associated with rheumatoid arthritis in persons of European ancestry confer risk of rheumatoid arthritis in African Americans

OBJECTIVE

Large-scale genetic association studies have identified >20 rheumatoid arthritis (RA) risk alleles among individuals of European ancestry. The influence of these risk alleles has not been comprehensively studied in African Americans. We therefore sought to examine whether these validated RA risk alleles are associated with RA risk in an African American population.

METHODS

Twenty-seven candidate single-nucleotide polymorphisms (SNPs) were genotyped in 556 autoantibody-positive African Americans with RA and 791 healthy African American control subjects. Odds ratios (ORs) and 95% confidence intervals (95% CIs) for each SNP were compared with previously published ORs for RA patients of European ancestry. We then calculated a composite genetic risk score (GRS) for each individual based on the sum of all risk alleles.

RESULTS

Overlap of the ORs and 95% CIs between the European and African American populations was observed for 24 of the 27 candidate SNPs. Conversely, 3 of the 27 SNPs (CCR6 rs3093023, TAGAP rs394581, and TNFAIP3 rs6920220) demonstrated ORs in the opposite direction from those reported for RA patients of European ancestry. The GRS analysis indicated a small but highly significant probability that African American patients relative to control subjects were enriched for the risk alleles validated in European RA patients (P = 0.00005).

CONCLUSION

The majority of RA risk alleles previously validated for RA patients of European ancestry showed similar ORs in our population of African Americans with RA. Furthermore, the aggregate GRS supports the hypothesis that these SNPs are risk alleles for RA in the African American population. Future large-scale genetic studies are needed to validate these risk alleles and identify novel RA risk alleles in African Americans.

Genetic predisposition to autoimmunity--what have we learned?

Rapid advances in genetic technologies have led to the identification of more than 85 loci that contribute to susceptibility to autoimmune diseases. These susceptibility genes are distributed throughout the innate and adaptive immune systems, indicating that dysregulations in both immune systems participate in the development of autoimmunity. A significant subset of these susceptibility genes are shared between multiple autoimmune diseases. However, the dysregulation of specific pathways, such as the pathogen recognition receptors of the innate immune system and the TNF supergene family, are significantly involved in some autoimmune diseases. Although these findings dramatically increase the details available concerning the nature of genetic predisposition to autoimmunity, a mechanistic understanding of the processes involved has not been achieved. Future studies must focus on correlating phenotypes with specific genotypes to improve our understanding of the immune processes that are dysregulated during the development of autoimmunity.

Complement: a key system for immune surveillance and homeostasis

Nearly a century after the significance of the human complement system was recognized, we have come to realize that its functions extend far beyond the elimination of microbes. Complement acts as a rapid and efficient immune surveillance system that has distinct effects on healthy and altered host cells and foreign intruders. By eliminating cellular debris and infectious microbes, orchestrating immune responses and sending 'danger' signals, complement contributes substantially to homeostasis, but it can also take action against healthy cells if not properly controlled. This review describes our updated view of the function, structure and dynamics of the complement network, highlights its interconnection with immunity at large and with other endogenous pathways, and illustrates its multiple roles in homeostasis and disease.

Only one independent genetic association with rheumatoid arthritis within the KIAA1109-TENR-IL2-IL21 locus in Caucasian sample sets: confirmation of association of rs6822844 with rheumatoid arthritis at a genome-wide level of significance

INTRODUCTION

The single nucleotide polymorphism (SNP) rs6822844 within the KIAA1109-TENR-IL2-IL21 gene cluster has been associated with rheumatoid arthritis (RA). Other variants within this cluster, including rs17388568 that is not in linkage disequilibrium (LD) with rs6822844, and rs907715 that is in moderate LD with rs6822844 and rs17388568, have been associated with a number of autoimmune phenotypes, including type 1 diabetes (T1D). Here we aimed to: one, confirm at a genome-wide level of significance association of rs6822844 with RA and, two, evaluate whether or not there were effects independent of rs6822844 on RA at the KIAA1109-TENR-IL2-IL21 locus.

METHODS

A total of 842 Australasian RA patients and 1,115 controls of European Caucasian ancestry were genotyped for rs6822844, rs17388568 and rs907715. Meta-analysis of these data with published and publicly-available data was conducted using STATA.

RESULTS

No statistically significant evidence for association was observed in the Australasian sample set for rs6822844 (odds ratio (OR)=0.95 (0.80 to 1.12), P=0.54), or rs17388568 (OR=1.03 (0.90 to 1.19), P=0.65) or rs907715 (OR=0.98 (0.86 to 1.12), P=0.69). When combined in a meta-analysis using data from a total of 9,772 cases and 10,909 controls there was a genome-wide level of significance supporting association of rs6822844 with RA (OR=0.86 (0.82 to 0.91), P=8.8x10(-8), P=2.1x10(-8) including North American Rheumatoid Arthritis Consortium data). Meta-analysis of rs17388568, using a total of 6,585 cases and 7,528 controls, revealed no significant association with RA (OR=1.03, (0.98 to 1.09); P=0.22) and meta-analysis of rs907715 using a total of 2,689 cases and 4,045 controls revealed a trend towards association (OR=0.93 (0.87 to 1.00), P=0.07). However, this trend was not independent of the association at rs6822844.

CONCLUSIONS

The KIAA1109-TENR-IL2-IL21 gene cluster, that encodes an interleukin (IL-21) that plays an important role in Th17 cell biology, is the 20th locus for which there is a genome-wide (P Collapse

Key Words Collapse

MESH Headings

• Aged
• Aged, 80 and over
• Alleles
• Arthritis, Rheumatoid/ethnology
• Arthritis, Rheumatoid/genetics
• Australia
• Case-Control Studies
• Female
• GTPase-Activating Proteins/genetics
• Genetic Predisposition to Disease/genetics
• Genotype
• Humans
• Interleukin-2/genetics
• Interleukins/genetics
• Male
• Microtubule-Associated Proteins/genetics
• Middle Aged
• New Zealand
• Polymorphism, Single Nucleotide/genetics
• White People/ethnology
• White People/genetics

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Grants

• 076113 Wellcome Trust

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Affiliation(s)

Jade E Hollis-Moffatt Department of Biochemistry, 710 Cumberland Street, University of Otago, Dunedin 9054, New Zealand
Michael Chen-Xu Department of Biochemistry, 710 Cumberland Street, University of Otago, Dunedin 9054, New Zealand
Ruth Topless Department of Biochemistry, 710 Cumberland Street, University of Otago, Dunedin 9054, New Zealand
Nicola Dalbeth Department of Medicine, 85 Park Road, University of Auckland, Auckland 1142, New Zealand
Peter J Gow Department of Rheumatology, Middlemore Hospital, Hospital Road, Auckland 1640, New Zealand
Andrew A Harrison Department of Medicine, 23A Mein Street, University of Otago, Wellington 6242, New Zealand
John Highton Department of Medicine, Great King Street, University of Otago, Dunedin 9054, New Zealand
Peter BB Jones Department of Medicine, 85 Park Road, University of Auckland, Auckland 1142, New Zealand
Michael Nissen Department of Medicine, Daws Road, Flinders Medical Centre and Repatriation General Hospital, Adelaide 5041, Australia
Malcolm D Smith Department of Medicine, Daws Road, Flinders Medical Centre and Repatriation General Hospital, Adelaide 5041, Australia
Andre van Rij Department of Surgery, Great King Street, University of Otago, Dunedin 9054, New Zealand
Gregory T Jones Department of Surgery, Great King Street, University of Otago, Dunedin 9054, New Zealand
Lisa K Stamp Department of Medicine, Riccarton Avenue, University of Otago, Christchurch 8140, New Zealand
Tony R Merriman Department of Biochemistry, 710 Cumberland Street, University of Otago, Dunedin 9054, New Zealand

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Gene discovery in rheumatoid arthritis highlights the CD40/NF-kappaB signaling pathway in disease pathogenesis

During the past several years, substantial progress has been made in the identification of genetic variants that predispose to rheumatoid arthritis (RA) and other autoimmune disorders. Progress in this area has been facilitated by the availability of new technology that allows for a much more comprehensive screen of the genome than was possible before, in conjunction with large samples of RA patients with well-characterized disease. Recent RA genetic studies have identified genes with important functions related to intracellular signaling mechanisms, transcription factors, cytokines, membrane receptors, costimulatory molecules, and enzymes. In particular, recent discoveries highlight the importance of the CD40/NF-kappaB signaling pathway in RA, based on genetic association with several genes relevant to this pathway, including CD40, TRAF1, TNFAIP3, and REL. Progress in the identification of genes that contribute to RA is proceeding at a very rapid pace. These genetic discoveries shed light on underlying disease mechanisms in RA and provide targets for the development of novel diagnostic and therapeutic tools for future use in this chronic inflammatory disorder.

Update on the genetic risk factors for rheumatoid arthritis

Rheumatoid arthritis (RA) is a complex disease, meaning that multiple genetic variants, environmental factors and random events interact to trigger pathological pathways. Although many of these etiological factors have not yet been identified, recent groundbreaking advances have expanded our knowledge about the genetic factors that contribute to RA. Here, we review the most recent findings on the genetic risk factors for RA. First, we give an overview of the genetics of RA and briefly describe the susceptibility loci discovered prior to the availability of genome-wide association studies (GWAS). Second, we focus on the newly discovered RA loci that have arisen from GWAS in populations of European ancestry. Through these studies, the number of established RA susceptibility loci has now grown to 13. Third, we discuss several important issues emerging from GWAS, such as ethnic heterogeneity and shared autoimmunity risk loci. Finally, we discuss what still needs to be accomplished before a more complete picture of the genetic risk to RA can be attained.

The TRAF1/C5 locus confers risk for familial and severe alopecia areata

BACKGROUND

Alopecia areata (AA) is a common hair loss disorder with a complex mode of inheritance. Autoimmune mechanisms are presumed to be crucial aetiologically. It is plausible that a number of autoimmune disorders may share a common genetic background. This phenomenon has been demonstrated in previous studies, which have shown an overlap of susceptibility alleles between AA and other autoimmune disorders. Recent studies have shown that genetic variants on the TRAF1/C5 (tumor necrosis factor receptor-associated factor 1, complement component 5) locus confer susceptibility to rheumatoid arthritis (RA).

OBJECTIVES

To examine the role of the TRAF1/C5 locus in the development of AA using a large sample of 1,195 patients with AA and 1280 controls.

METHODS

We genotyped the two most significant single nucleotide polymorphisms (SNPs) (rs10818488, rs2416808) from a former RA candidate gene study. After having obtained evidence for association, we performed a fine-mapping study and genotyped the locus with an additional 27 SNPs.

RESULTS

While no significant result was obtained for the overall sample, rs2416808 showed significant associations in the analysis of the subgroups with severe AA and with a positive family history. The most significant P-value for rs2416808 was in familial cases (P = 0.004, P(corr) = 0.026). The fine mapping revealed significant associations for four additional SNPs in the analysis of subgroups, with rs2416808 remaining the most significant marker.

CONCLUSIONS

Our results point to the involvement of the TRAF1/C5 locus in the aetiology of familial and severe AA, and provide further support for a shared aetiology between AA and other autoimmune disorders.

Detecting significant single-nucleotide polymorphisms in a rheumatoid arthritis study using random forests

Random forest is an efficient approach for investigating not only the effects of individual markers on a trait but also the effect of the interactions among the markers in genetic association studies. This approach is especially appealing for the analysis of genome-wide data, such as those obtained from gene expression/single-nucleotide polymorphism (SNP) array experiments in which the number of candidate genes/SNPs is vast. We applied this approach to the Genetic Analysis Workshop 16 Problem 1 data to identify SNPs that contribute to rheumatoid arthritis. The random forest computed a raw importance score for each SNP marker, where higher importance score suggests higher level of association between the marker and the trait. The significance level of the association was determined empirically by repeatedly reapplying the random forest on randomly generated data under the null hypothesis that no association exists between the markers and the trait. Using random forest, we were able to identify 228 significant SNPs (at the genome-wide significant level of 0.05) across the whole genome, over two-thirds of which are located on chromosome 6, especially clustered in the region of 6p21 containing the human leukocyte antigen (HLA) genes, such as gene HLA-DRB1 and HLA-DRA. Further analysis of this region indicates a strong association to the rheumatoid arthritis status.

Analysis of genome-wide association data by large-scale Bayesian logistic regression

Single-locus analysis is often used to analyze genome-wide association (GWA) data, but such analysis is subject to severe multiple comparisons adjustment. Multivariate logistic regression is proposed to fit a multi-locus model for case-control data. However, when the sample size is much smaller than the number of single-nucleotide polymorphisms (SNPs) or when correlation among SNPs is high, traditional multivariate logistic regression breaks down. To accommodate the scale of data from a GWA while controlling for collinearity and overfitting in a high dimensional predictor space, we propose a variable selection procedure using Bayesian logistic regression. We explored a connection between Bayesian regression with certain priors and L1 and L2 penalized logistic regression. After analyzing large number of SNPs simultaneously in a Bayesian regression, we selected important SNPs for further consideration. With much fewer SNPs of interest, problems of multiple comparisons and collinearity are less severe. We conducted simulation studies to examine probability of correctly selecting disease contributing SNPs and applied developed methods to analyze Genetic Analysis Workshop 16 North American Rheumatoid Arthritis Consortium data.

A new gene-based association test for genome-wide association studies

Genome-wide association studies are widely used today to discover genetic factors that modify the risk of complex diseases. Usually, these methods work in a SNP-by-SNP fashion. We present a gene-based test that can be applied in the context of genome-wide association studies. We compare both strategies, SNP-based and gene-based, in a sample of cases and controls for rheumatoid arthritis.We obtained different results using each strategy. The SNP-based test found the PTPN22 gene while the gene-based test found the PHF19-TRAF1-C5 region. That suggests that no single strategy performs better than another in all cases and that a certain underlying genetic architecture can be delineated more easily with one strategy rather than with another.

Pathway-based analysis of a genome-wide case-control association study of rheumatoid arthritis

Evaluation of the association between single-nucleotide polymorphisms (SNPs) and disease outcomes is widely used to identify genetic risk factors for complex diseases. Although this analysis paradigm has made significant progress in many genetic studies, many challenges remain, such as the requirement of a large sample size to achieve adequate power. Here we use rheumatoid arthritis (RA) as an example and explore a new analysis strategy: pathway-based analysis to search for related genes and SNPs contributing to the disease.

We first propose the application of measure of explained variation to quantify the predictive ability of a given SNP. We then use gene set enrichment analysis to evaluate enrichment of specific pathways, where pathways, are considered enriched if they consist of genes that are associated with the phenotype of interest above and beyond is expected by chance. The results are also compared with score tests for association analysis by adjusting for population stratification.

Our study identified some significantly enriched pathways, such as "cell adhesion molecules," which are known to play a key role in RA. Our results showed that pathway-based analysis may identify other biologically interesting loci (e.g., rs1018361) related to RA: the gene (CTLA4) closest to this marker has previously been shown to be associated with RA and the gene is in the significant pathways we identified, even though the marker has not reached genome-wide significance in univariate single-marker analysis.

Replication of recently identified associated single-nucleotide polymorphisms from six autoimmune diseases in Genetic Analysis Workshop 16 rheumatoid arthritis data

Many autoimmune diseases share similar underlying pathology and have a tendency to cluster within families, giving rise to the concept of shared susceptibility genes among them. In the Genetic Analysis Workshop 16 rheumatoid arthritis (RA) data we sought to replicate the genetic association between single-nucleotide polymorphisms (SNPs) identified in recent genome-wide association studies (GWAS) on RA and five other autoimmune diseases. We identified 164 significantly associated non-HLA SNPs (p < 10^-5) from 16 GWAS and 13 candidate gene studies on six different autoimmune diseases, including RA, systemic lupus erythematosus, type 1 diabetes, Crohn disease, multiple sclerosis, and celiac disease. Using both direct and imputation-based association test, we replicated 16 shared susceptibility regions involving RA and at least one of the other autoimmune diseases. We also identified hidden population structure within cases and controls in Genetic Analysis Workshop 16 RA data and assessed the effect of population structure on the shared autoimmunity regions. Because multiple autoimmune diseases share common genetic origin, these could be areas of immense interest for further genetic and clinical association studies.