Anorexia nervosa (AN) is a complex and heritable eating disorder characterized by dangerously low body weight. Neither candidate gene studies nor an initial genome wide association study (GWAS) have yielded significant and replicated results. We performed a GWAS in 2,907 cases with AN from 14 countries (15 sites) and 14,860 ancestrally matched controls as part of the Genetic Consortium for AN (GCAN) and the Wellcome Trust Case Control Consortium 3 (WTCCC3). Individual association analyses were conducted in each stratum and meta-analyzed across all 15 discovery datasets. Seventy-six (72 independent) SNPs were taken forward for in silico (two datasets) or de novo (13 datasets) replication genotyping in 2,677 independent AN cases and 8,629 European ancestry controls along with 458 AN cases and 421 controls from Japan. The final global meta-analysis across discovery and replication datasets comprised 5,551 AN cases and 21,080 controls. AN subtype analyses (1,606 AN restricting; 1,445 AN binge-purge) were performed. No findings reached genome-wide significance. Two intronic variants were suggestively associated: rs9839776 (P=3.01×10-7) in SOX2OT and rs17030795 (P=5.84×10-6) in PPP3CA. Two additional signals were specific to Europeans: rs1523921 (P=5.76×10-6) between CUL3 and FAM124B and rs1886797 (P=8.05×10-6) near SPATA13. Comparing discovery to replication results, 76% of the effects were in the same direction, an observation highly unlikely to be due to chance (P=4×10-6), strongly suggesting that true findings exist but that our sample, the largest yet reported, was underpowered for their detection. The accrual of large genotyped AN case-control samples should be an immediate priority for the field.
anorexia nervosa; eating disorders; GWAS; genome-wide association study; body mass index; metabolic
The Fc-glycan profile of IgG1 anti-citrullinated peptide antibodies (ACPA) in rheumatoid arthritis (RA) patients has recently been reported to be different from non-ACPA IgG1, a phenomenon which likely plays a role in RA pathogenesis. Herein we investigate the Fc-glycosylation pattern of all ACPA-IgG isotypes and simultaneously investigate in detail the IgG protein-chain sequence repertoire. IgG from serum or plasma (S/P, n = 14) and synovial fluid (SF, n = 4) from 18 ACPA-positive RA-patients was enriched using Protein G columns followed by ACPA-purification on cyclic citrullinated peptide-2 (CCP2)-coupled columns. Paired ACPA (anti-CCP2 eluted IgG) and IgG flow through (FT) fractions were analyzed by LC-MS/MS-proteomics. IgG peptides, isotypes and corresponding Fc-glycopeptides were quantified and interrogated using uni- and multivariate statistics. The Fc-glycans from the IgG4 peptide EEQFNSTYR was validated using protein A column purification. Relative to FT-IgG4, the ACPA-IgG4 Fc-glycan-profile contained lower amounts (p = 0.002) of the agalacto and asialylated core-fucosylated biantennary form (FA2) and higher content (p = 0.001) of sialylated glycans. Novel differences in the Fc-glycan-profile of ACPA-IgG1 compared to FT-IgG1 were observed in the distribution of bisected forms (n = 5, p = 0.0001, decrease) and mono-antennnary forms (n = 3, p = 0.02, increase). Our study also confirmed higher abundance of FA2 (p = 0.002) and lower abundance of afucosylated forms (n = 4, p = 0.001) in ACPA-IgG1 relative to FT-IgG1 as well as lower content of IgG2 (p = 0.0000001) and elevated content of IgG4 (p = 0.004) in ACPA compared to FT. One λ-variable peptide sequence was significantly increased in ACPA (p = 0.0001). In conclusion, the Fc-glycan profile of both ACPA-IgG1 and ACPA-IgG4 are distinct. Given that IgG1 and IgG4 have different Fc-receptor and complement binding affinities, this phenomenon likely affects ACPA effector- and immune-regulatory functions in an IgG isotype-specific manner. These findings further highlight the importance of antibody characterization in relation to functional in vivo and in vitro studies.
To identify novel genetic risk factors for rheumatoid arthritis (RA), we conducted a genome-wide association study (GWAS) meta-analysis of 5,539 autoantibody positive RA cases and 20,169 controls of European descent, followed by replication in an independent set of 6,768 RA cases and 8,806 controls. Of 34 SNPs selected for replication, 7 novel RA risk alleles were identified at genome-wide significance (P<5×10−8) in analysis of all 41,282 samples. The associated SNPs are near genes of known immune function, including IL6ST, SPRED2, RBPJ, CCR6, IRF5, and PXK. We also refined the risk alleles at two established RA risk loci (IL2RA and CCL21) and confirmed the association at AFF3. These new associations bring the total number of confirmed RA risk loci to 31 among individuals of European ancestry. An additional 11 SNPs replicated at P<0.05, many of which are validated autoimmune risk alleles, suggesting that most represent bona fide RA risk alleles.
Translational medicine is becoming increasingly dependent upon data generated from health care, clinical research, and molecular investigations. This increasing rate of production and diversity in data has brought about several challenges, including the need to integrate fragmented databases, enable secondary use of patient clinical data from health care in clinical research, and to create information systems that clinicians and biomedical researchers can readily use. Our case study effectively integrates requirements from the clinical and biomedical researcher perspectives in a translational medicine setting. Our three principal achievements are (a) a design of a user-friendly web-based system for management and integration of clinical and molecular databases, while adhering to proper de-identification and security measures; (b) providing a real-world test of the system functionalities using clinical cohorts; and (c) system integration with a clinical decision support system to demonstrate system interoperability. We engaged two active clinical cohorts, 747 psoriasis patients and 2001 rheumatoid arthritis patients, to demonstrate efficient query possibilities across the data sources, enable cohort stratification, extract variation in antibody patterns, study biomarker predictors of treatment response in RA patients, and to explore metabolic profiles of psoriasis patients. Finally, we demonstrated system interoperability by enabling integration with an established clinical decision support system in health care. To assure the usefulness and usability of the system, we followed two approaches. First, we created a graphical user interface supporting all user interactions. Secondly we carried out a system performance evaluation study where we measured the average response time in seconds for active users, http errors, and kilobits per second received and sent. The maximum response time was found to be 0.12 seconds; no server or client errors of any kind were detected. In conclusion, the system can readily be used by clinicians and biomedical researchers in a translational medicine setting.
To study genetic factors that influence quantitative anti-cyclic citrullinated peptide (anti-CCP) antibody levels in RA patients.
We carried out a genome wide association study (GWAS) meta-analysis using 1,975 anti-CCP+ RA patients from 3 large cohorts, the Brigham Rheumatoid Arthritis Sequential Study (BRASS), North American Rheumatoid Arthritis Consortium (NARAC), and the Epidemiological Investigation of RA (EIRA). We also carried out a genome-wide complex trait analysis (GCTA) to estimate the heritability of anti-CCP levels.
GWAS-meta analysis showed that anti-CCP levels were most strongly associated with the human leukocyte antigen (HLA) region with a p-value of 2×10−11 for rs1980493. There were 112 SNPs in this region that exceeded the genome-wide significance threshold of 5×10−8, and all were in linkage disequilibrium (LD) with the HLA- DRB1*03 allele with LD r2 in the range of 0.25-0.88. Suggestive novel associations outside of the HLA region were also observed for rs8063248 (near the GP2 gene) with a p-value of 3×10−7. None of the known RA risk alleles (~52 loci) were associated with anti-CCP level. Heritability analysis estimated that 44% of anti-CCP variation was attributable to genetic factors captured by GWAS variants.
Anti-CCP level is a heritable trait. HLA-DR3 and GP2 are associated with lower anti-CCP levels.
RA; GWAS; anti-CCP; heritability
A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological datasets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA)1. Here, we performed a genome-wide association study (GWAS) 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 (SNPs). We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 1012–4. We devised an in-silico pipeline using established bioinformatics methods based on functional annotation5, cis-acting expression quantitative trait loci (cis-eQTL)6, and pathway analyses7–9 – as well as novel methods based on genetic overlap with human primary immunodeficiency (PID), hematological cancer somatic mutations and knock-out 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.
Environmental factors may play a role in the development of rheumatoid arthritis (RA), and we have previously observed increased RA risk among women living closer to major roads (a source of air pollution). We examined whether long-term exposures to specific air pollutants were associated with RA risk among women in the Nurses’ Health Study.
The Nurses’ Health Study (NHS) is a large cohort of U.S. female nurses followed prospectively every two years since 1976. We studied 111,425 NHS participants with information on air pollution exposures as well as data concerning other lifestyle and behavioral exposures and disease outcomes. Outdoor levels of different size fractions of particulate matter (PM10 and PM2.5) and gaseous pollutants (SO2 and NO2) were predicted for all available residential addresses using monitoring data from the USEPA. We examined the association of time-varying exposures, 6 and 10 years before each questionnaire cycle, and cumulative average exposure with the risks of RA, seronegative (rheumatoid factor [RF] and anti–citrullinated peptide antibodies [ACPA]) RA, and seropositive RA.
Over the 3,019,424 years of follow-up, 858 incident RA cases were validated by medical record review by two board-certified rheumatologists. Overall, we found no evidence of increased risks of RA, seronegative or seropositive RA, with exposure to the different pollutants, and little evidence of effect modification by socioeconomic status or smoking status, geographic region, or calendar period.
In this group of socioeconomically-advantaged middle-aged and elderly women, adult exposures to air pollution were not associated with an increased RA risk.
We developed RA risk models based on validated environmental factors (E), genetic risk scores (GRS), and gene-environment interactions (GEI) to identify factors that can improve accuracy and reclassification.
Models including E, GRS, GEI were developed among 317 Caucasian seropositive RA cases and 551 controls from Nurses’ Health Studies (NHS) and validated in 987 Caucasian ACPA positive cases and 958 controls from the Swedish Epidemiologic Investigation of RA (EIRA), stratified by gender. Primary analyses included age, smoking, alcohol, parity, weighted GRS using 31 non-HLA alleles, 8 HLA-DRB1 alleles and HLA X smoking interaction. Expanded models included reproductive, geographic, and occupational factors, and additional GEI terms. Hierarchical models were compared for discriminative accuracy using AUC and reclassification using Integrated Discrimination Improvement (IDI) and continuous Net Reclassification Index.
Mean (SD) age of RA diagnosis was 57 in NHS and 50 in EIRA. Primary models produced an AUC of 0.716 in NHS, 0.728 in EIRA women and 0.756 in EIRA men. Expanded models produced improvements in discrimination with AUCs of 0.738 in NHS, 0.728 in EIRA women and 0.769 in EIRA men. Models including G or G + GEI improved reclassification over E models; the full E+G+GEI model provided the optimal predictive ability by IDI analyses.
We have developed comprehensive RA risk models incorporating epidemiologic and genetic factors and gene-environment interactions that have improved discriminative accuracy for RA. Further work developing and assessing highly specific prediction models in prospective cohorts is still needed to inform primary RA prevention trials.
Environmental factors may play a role in the development of rheumatoid arthritis (RA). We examined whether long-term exposures to air pollution were associated with risk of RA in the Swedish Epidemiological Investigation of Rheumatoid Arthritis (EIRA) Study.
We studied 1,497 incident RA cases and 2,536 controls. Local levels of particulate matter (PM10) and gaseous pollutants (SO2 and NO2,) from traffic and home heating were predicted for all residential addresses. We examined the association of an interquartile range increase (2μg/m3 for PM10, 8μg/m3 for SO2, and 9μg/m3 for NO2) in each pollutant at different time points prior to symptom onset and average exposure with the risk of all RA and the risk of the rheumatoid factor (RF) and anti-citrullinated protein antibody (ACPA) RA phenotypes.
There was no evidence of an increased risk of RA with PM10. Total RA risks were modestly elevated for the gaseous pollutants, but were not statistically significant after adjustment for smoking and education (odds ratio (OR)=1.18 [95%confidence interval (CI): 0.97–1.43] and OR=1.09 [95%CI: 0.99–1.19] for SO2 and NO2 in the 10th year before onset). Stronger elevated risks were observed for individuals with less than a university education and with the ACPA- RA phenotype.
No consistent overall associations between air pollution in the Stockholm area and risk for RA were observed. However, there was a suggestion of increased risks of RA incidence with increases in NO2 from local traffic and SO2 from home heating sources with stronger associations for the ACPA- phenotype.
air pollution; rheumatoid arthritis; traffic pollution; home heating pollution
Rheumatoid arthritis (RA) is a complex disease that is associated with genetic and environmental factors. We have investigated geospatial variation in risk of developing RA within Stockholm County, with respect to established environmental risk factors for RA, as well as serologically-defined subgroups of RA.
Information regarding geographical location for 1432 cases and 2529 controls from the Epidemiological Investigation of Rheumatoid Arthritis (EIRA) study, living in Stockholm County at RA symptom onset, or matched date for controls, was used to estimate geospatial variation in risk. We used Generalized Additive Models (GAM) to create a risk surface, calculate odds ratios and adjust for potential confounding by smoking, educational level and RA within family. We performed a stratified analysis based on presence/absence of antibodies to citrullinated peptides (ACPA).
We found significant spatial variation in the odds of developing RA in Stockholm County. After adjustment for smoking, educational level and family history of RA, this geospatial variation remained. The stratified analysis showed areas with higher odds ratios for ACPA-positive RA and ACPA-negative RA, after adjusting for smoking, educational level and having a family history of RA. Living in the city of Stockholm was associated with decreased risk of RA.
The risk of developing RA in Stockholm County is not evenly distributed and there are areas of increased risk that could not be explained by known factors. Further investigations of local exposures or social factors are warranted.
Rheumatoid Arthritis; Epidemiologic methods; Antibodies; Geography; Risk; Smoking; ACPA; Stockholm
Integrating genetic data from families with highly penetrant forms of disease together with genetic data from outbred populations represents a promising strategy to uncover the complete frequency spectrum of risk alleles for complex traits such as rheumatoid arthritis (RA). Here, we demonstrate that rare, low-frequency and common alleles at one gene locus, phospholipase B1 (PLB1), might contribute to risk of RA in a 4-generation consanguineous pedigree (Middle Eastern ancestry) and also in unrelated individuals from the general population (European ancestry). Through identity-by-descent (IBD) mapping and whole-exome sequencing, we identified a non-synonymous c.2263G>C (p.G755R) mutation at the PLB1 gene on 2q23, which significantly co-segregated with RA in family members with a dominant mode of inheritance (P = 0.009). We further evaluated PLB1 variants and risk of RA using a GWAS meta-analysis of 8,875 RA cases and 29,367 controls of European ancestry. We identified significant contributions of two independent non-coding variants near PLB1 with risk of RA (rs116018341 [MAF = 0.042] and rs116541814 [MAF = 0.021], combined P = 3.2×10−6). Finally, we performed deep exon sequencing of PLB1 in 1,088 RA cases and 1,088 controls (European ancestry), and identified suggestive dispersion of rare protein-coding variant frequencies between cases and controls (P = 0.049 for C-alpha test and P = 0.055 for SKAT). Together, these data suggest that PLB1 is a candidate risk gene for RA. Future studies to characterize the full spectrum of genetic risk in the PLB1 genetic locus are warranted.
Recent work has shown that much of the missing heritability of complex traits can be resolved by estimates of heritability explained by all genotyped SNPs. However, it is currently unknown how much heritability is missing due to poor tagging or additional causal variants at known GWAS loci. Here, we use variance components to quantify the heritability explained by all SNPs at known GWAS loci in nine diseases from WTCCC1 and WTCCC2. After accounting for expectation, we observed all SNPs at known GWAS loci to explain more heritability than GWAS-associated SNPs on average (). For some diseases, this increase was individually significant: for Multiple Sclerosis (MS) () and for Crohn's Disease (CD) (); all analyses of autoimmune diseases excluded the well-studied MHC region. Additionally, we found that GWAS loci from other related traits also explained significant heritability. The union of all autoimmune disease loci explained more MS heritability than known MS SNPs () and more CD heritability than known CD SNPs (), with an analogous increase for all autoimmune diseases analyzed. We also observed significant increases in an analysis of Rheumatoid Arthritis (RA) samples typed on ImmunoChip, with more heritability from all SNPs at GWAS loci () and more heritability from all autoimmune disease loci () compared to known RA SNPs (including those identified in this cohort). Our methods adjust for LD between SNPs, which can bias standard estimates of heritability from SNPs even if all causal variants are typed. By comparing adjusted estimates, we hypothesize that the genome-wide distribution of causal variants is enriched for low-frequency alleles, but that causal variants at known GWAS loci are skewed towards common alleles. These findings have important ramifications for fine-mapping study design and our understanding of complex disease architecture.
Heritable diseases have an unknown underlying “genetic architecture” that defines the distribution of effect-sizes for disease-causing mutations. Understanding this genetic architecture is an important first step in designing disease-mapping studies, and many theories have been developed on the nature of this distribution. Here, we evaluate the hypothesis that additional heritable variation lies at previously known associated loci but is not fully explained by the single most associated marker. We develop methods based on variance-components analysis to quantify this type of “local” heritability, demonstrating that standard strategies can be falsely inflated or deflated due to correlation between neighboring markers and propose a robust adjustment. In analysis of nine common diseases we find a significant average increase of local heritability, consistent with multiple common causal variants at an average locus. Intriguingly, for autoimmune diseases we also observe significant local heritability in loci not associated with the specific disease but with other autoimmune diseases, implying a highly correlated underlying disease architecture. These findings have important implications to the design of future studies and our general understanding of common disease.
Anorexia nervosa (AN) is a complex and heritable eating disorder characterized by dangerously low body weight. Neither candidate gene studies nor an initial genome wide association study (GWAS) have yielded significant and replicated results. We performed a GWAS in 2,907 cases with AN from 14 countries (15 sites) and 14,860 ancestrally matched controls as part of the Genetic Consortium for AN (GCAN) and the Wellcome Trust Case Control Consortium 3 (WTCCC3). Individual association analyses were conducted in each stratum and meta-analyzed across all 15 discovery datasets. Seventy-six (72 independent) SNPs were taken forward for in silico (two datasets) or de novo (13 datasets) replication genotyping in 2,677 independent AN cases and 8,629 European ancestry controls along with 458 AN cases and 421 controls from Japan. The final global meta-analysis across discovery and replication datasets comprised 5,551 AN cases and 21,080 controls. AN subtype analyses (1,606 AN restricting; 1,445 AN binge-purge) were performed. No findings reached genome-wide significance. Two intronic variants were suggestively associated: rs9839776 (P=3.01×10−7) in SOX2OT and rs17030795 (P=5.84×10−6) in PPP3CA. Two additional signals were specific to Europeans: rs1523921 (P=5.76×10−6) between CUL3 and FAM124B and rs1886797 (P=8.05×10−6) near SPATA13. Comparing discovery to replication results, 76% of the effects were in the same direction, an observation highly unlikely to be due to chance (P= 4×10−6), strongly suggesting that true findings exist but that our sample, the largest yet reported, was underpowered for their detection. The accrual of large genotyped AN case-control samples should be an immediate priority for the field.
anorexia nervosa; eating disorders; GWAS; genome-wide association study; body mass index; metabolic
Synovial IgG-expressing B cells from patients with rheumatoid arthritis show specificity for citrullinated autoantigens.
Antibodies targeting citrullinated proteins (ACPAs [anticitrullinated protein antibodies]) are commonly found in patients with rheumatoid arthritis (RA), strongly associate with distinct HLA-DR alleles, and predict a more aggressive disease course as compared with seronegative patients. Still, many features of these antibodies, including their site of production and the extent of MHC class II–driven T cell help, remain unclarified. To address these questions, we have used a single B cell–based cloning technology to isolate and express immunoglobulin (Ig) genes from joint-derived B cells of active RA patients. We found ∼25% of synovial IgG-expressing B cells to be specific for citrullinated autoantigens in the investigated ACPA+ RA patients, whereas such antibodies were not found in ACPA− patients. The citrulline-reactive monoclonal antibodies did not react with the unmodified arginine peptides, yet several reacted with more than one citrullinated antigen. A role for active antigen selection of the citrulline-reactive synovial B cells was supported by the strong bias toward amino acid replacement mutations in ACPA+ antibodies and by their loss of reactivity to citrullinated autoantigens when somatic mutations were reverted to the corresponding germline sequences.
Type II collagen (CII) is a cartilage-specific protein to which a loss of immune tolerance may trigger autoimmune reactions and cause arthritis. The major T cell epitope on CII, aa259-273, can be presented by several HLA-DRB1*04 alleles in its native or posttranslational-glycosylated form. Here, we aimed to functionally explore and compare CII-autoreactive T cells from blood and synovial fluid of patients with rheumatoid arthritis (RA).
Peripheral blood were obtained from HLA-DRB1*04 RA and control subjects (n=10 each), then stimulated in vitro with several variants of the CII259-273 epitope: (a) unmodified, or glycosylated on (b) lysine-264, (c) lysine-270, or (d) both lysine-264 and 270. Upregulation of CD154 was used to identify responding T cells. These cells were further characterized by intracellular staining for IL-17, IFNγ and IL-2 by flow cytometry. For RA patients, synovial T cells were investigated in parallel.
Multifunctional T cell responses towards all examined variants of the CII259-273 peptide could be detected in RA patients and to a lesser extent also in healthy HLA-matched individuals (p<0.001). In RA, a comparison between blood and joint-derived T cell function revealed a significant increase of the proinflammatory cytokine IFNγ (p=0.027) in synovial T cells. Studies of longitudinal samples show that T cell responses were sustained over the course of disease, and even included epitope spreading.
The identification of inflammatory T cell responses to both glycosylated and non-glycosylated variants of the major CII epitope in RA patients suggests that CII autoreactivity may be more common than previously appreciated.
Epigenetic mechanisms integrate genetic and environmental causes of disease. Comprehensive genome-wide analyses of epigenetic modifications have not demonstrated robust association with common diseases. Using Illumina HumanMethylation450 arrays on 354 ACPA positive rheumatoid arthritis (RA) cases and 337 controls, we identified two clusters within the MHC region whose differential methylation potentially mediates genetic risk for RA. To reduce confounding hampering previous epigenome-wide studies, we corrected for cellular heterogeneity by estimating and adjusting for cell-type proportions and used mediation analysis to filter out associations likely consequential to disease. Four CpGs also showed association between genotype and variance of methylation in addition to mean. The associations for both clusters replicated at least one CpG (p<0.01), with the rest showing suggestive association, in monocytes in an independent 12 cases and 12 controls. Thus, DNA methylation is a potential mediator of genetic risk.
Genome-wide association studies have facilitated the identification of over 30 susceptibility loci for rheumatoid arthritis (RA). However, evidence for a number of potential susceptibility genes have not so far reached genome-wide significance in studies of Caucasian RA.
A cohort of 4286 RA patients from across Europe and 5642 population matched controls were genotyped for 25 SNPs, then combined in a meta-analysis with previously published data.
Significant evidence of association was detected for nine SNPs within the European samples. When meta-analysed with previously published data, 21 SNPs were associated with RA susceptibility. Although SNPs in the PTPN2 gene were previously reported to be associated with RA in both Japanese and European populations, we show genome-wide evidence for a different SNP within this gene associated with RA susceptibility in an independent European population (rs7234029, P = 4.4×10−9).
This study provides further genome-wide evidence for the association of the PTPN2 locus (encoding the T cell protein tyrosine phosphastase) with Caucasian RA susceptibility. This finding adds to the growing evidence for PTPN2 being a pan-autoimmune susceptibility gene.
Using the Immunochip custom single nucleotide polymorphism (SNP) array, designed for dense genotyping of 186 genome wide association study (GWAS) confirmed loci we analysed 11,475 rheumatoid arthritis cases of European ancestry and 15,870 controls for 129,464 markers. The data were combined in meta-analysis with GWAS data from additional independent cases (n=2,363) and controls (n=17,872). We identified fourteen novel loci; nine were associated with rheumatoid arthritis overall and 5 specifically in anti-citrillunated peptide antibody positive disease, bringing the number of confirmed European ancestry rheumatoid arthritis loci to 46. We refined the peak of association to a single gene for 19 loci, identified secondary independent effects at six loci and association to low frequency variants (minor allele frequency <0.05) at 4 loci. Bioinformatic analysis of the data generated strong hypotheses for the causal SNP at seven loci. This study illustrates the advantages of dense SNP mapping analysis to inform subsequent functional investigations.
Anti–tumor necrosis factor α (anti-TNF) therapy is a mainstay of treatment in rheumatoid arthritis (RA). The aim of the present study was to test established RA genetic risk factors to determine whether the same alleles also influence the response to anti-TNF therapy.
A total of 1,283 RA patients receiving etanercept, infliximab, or adalimumab therapy were studied from among an international collaborative consortium of 9 different RA cohorts. The primary end point compared RA patients with a good treatment response according to the European League Against Rheumatism (EULAR) response criteria (n = 505) with RA patients considered to be nonresponders (n = 316). The secondary end point was the change from baseline in the level of disease activity according to the Disease Activity Score in 28 joints (ΔDAS28). Clinical factors such as age, sex, and concomitant medications were tested as possible correlates of treatment response. Thirty-one single-nucleotide polymorphisms (SNPs) associated with the risk of RA were genotyped and tested for any association with treatment response, using univariate and multivariate logistic regression models.
Of the 31 RA-associated risk alleles, a SNP at the PTPRC (also known as CD45) gene locus (rs10919563) was associated with the primary end point, a EULAR good response versus no response (odds ratio [OR] 0.55, P = 0.0001 in the multivariate model). Similar results were obtained using the secondary end point, the ΔDAS28 (P = 0.0002). There was suggestive evidence of a stronger association in autoantibody-positive patients with RA (OR 0.55, 95% confidence interval [95% CI] 0.39–0.76) as compared with autoantibody-negative patients (OR 0.90, 95% CI 0.41–1.99).
Statistically significant associations were observed between the response to anti-TNF therapy and an RA risk allele at the PTPRC gene locus. Additional studies will be required to replicate this finding in additional patient collections.
Sequencing of the human genome and the subsequent analyses have produced immense volumes of data. The technological advances have opened new windows into genomics beyond the DNA sequence. In parallel, clinical practice generate large amounts of data. This represents an underused data source that has much greater potential in translational research than is currently realized. This research aims at implementing a translational medicine informatics platform to integrate clinical data (disease diagnosis, diseases activity and treatment) of Rheumatoid Arthritis (RA) patients from Karolinska University Hospital and their research database (biobanks, genotype variants and serology) at the Center for Molecular Medicine, Karolinska Institutet.
Requirements engineering methods were utilized to identify user requirements. Unified Modeling Language and data modeling methods were used to model the universe of discourse and data sources. Oracle11g were used as the database management system, and the clinical development center (CDC) was used as the application interface. Patient data were anonymized, and we employed authorization and security methods to protect the system.
We developed a user requirement matrix, which provided a framework for evaluating three translation informatics systems. The implementation of the CDC successfully integrated biological research database (15172 DNA, serum and synovial samples, 1436 cell samples and 65 SNPs per patient) and clinical database (5652 clinical visit) for the cohort of 379 patients presents three profiles. Basic functionalities provided by the translational medicine platform are research data management, development of bioinformatics workflow and analysis, sub-cohort selection, and re-use of clinical data in research settings. Finally, the system allowed researchers to extract subsets of attributes from cohorts according to specific biological, clinical, or statistical features.
Research and clinical database integration is a real challenge and a road-block in translational research. Through this research we addressed the challenges and demonstrated the usefulness of CDC. We adhered to ethical regulations pertaining to patient data, and we determined that the existing software solutions cannot meet the translational research needs at hand. We used RA as a test case since we have ample data on active and longitudinal cohort.
Swedish Rheumatology Quality Register (SRQ); Translational medicine platform; Secondary use of clinical data; Patient de-identification
The majority of our knowledge regarding disease-related mechanisms of uncontrolled citrullination and anti-citrullinated protein antibody development in rheumatoid arthritis (RA) was investigated in Caucasian populations. However, peptidylarginine deiminase (PADI) type 4 gene polymorphisms are associated with RA in East Asian populations and weak or no association was found in Caucasian populations. This study explores the association between the PADI4 polymorphisms and RA risk in a multiethnic population residing in South East Asia with the goal of elucidating generalizability of association in non-Caucasian populations.
A total of 320 SNPs from the PADI locus (including PADI1, PADI2, PADI3, PADI4 and PADI6 genes) were genotyped in 1,238 RA cases and 1,571 control subjects from the Malaysian Epidemiological Investigation of Rheumatoid Arthritis (MyEIRA) case-control study. Additionally, we conducted meta-analysis of our data together with the previously published studies of RA from East Asian populations.
The overall odds ratio (ORoverall) for the PADI4 (rs2240340) allelic model was 1.11 (95% confidence interval (CI) = 1.00 to 1.23, P = 0.04) and for the genotypic model was 1.20 (95% CI = 1.01 to 1.44, P = 0.04). Haplotype analysis for four selected PADI4 SNPs revealed a significant association of one with susceptibility (P = 0.001) and of another with a protective effect (P = 0.02). The RA susceptibility was further confirmed when combined meta-analysis was performed using these data together with data from five previously published studies from Asia comprising 5,192 RA cases and 4,317 control subjects (ORoverall = 1.23 (95% CI = 1.16 to 1.31, Pheterogeneity = 0.08) and 1.31 (95% CI = 1.20 to 1.44, Pheterogeneity = 0.32) in allele and genotype-based models, respectively). In addition, we also detected a novel association of PADI2 genetic variant rs1005753 with RA (ORoverall = 0.87 (95% CI = 0.77 to 0.99)).
Our study demonstrates an association between PADI4 and RA in the multiethnic population from South East Asia and suggests additional association with a PADI2 gene. The study thus provides further support for the notion that polymorphisms in genes for enzymes responsible for citrullination contribute to RA development in multiple populations of Asian descent.
Autoantibodies directed against citrullinated proteins/peptides (ACPAs) are highly specific and predictive for the development of rheumatoid arthritis (RA). Different subgroups of RA patients, which have different prognoses and may require different treatments, are characterized by different autoantibody profiles. The objective of this study was to develop a microarray for the detection of multiple RA-associated autoantibodies, initially focusing on responses against citrullinated epitopes on candidate autoantigens in RA.
The microarray is based on Phadia's ImmunoCAP ISAC system, with which reactivity to more than 100 antigens can be analyzed simultaneously, by using minute serum volumes (< 10 μl). Twelve citrullinated peptides, and the corresponding native arginine-containing control peptides, were immobilized in an arrayed fashion onto a chemically modified glass slide, allowing a three-dimensional layer with high binding capacity. The assay was optimized concerning serum dilution and glass surface, whereas each individual antigen was optimized concerning coupling chemistry, antigen concentration, and selection of spotting buffer. The performance of each peptide in the ImmunoCAP ISAC system was compared with the performance in enzyme-linked immunosorbent assays (ELISAs). Serum from 927 RA patients and 461 healthy controls from a matched case-control study were applied onto reaction sites on glass slides, followed by fluorescent-labeled anti-human immunoglobulin G (IgG) antibody. Fluorescence intensities were detected with a laser scanner, and the results analyzed by using image-analysis software.
Strong correlations between the ImmunoCAP ISAC system and ELISA results were found for individual citrullinated peptides (Spearman ρ typically between 0.75 and 0.90). Reactivity of RA sera with the peptides was seen mainly in the anticyclic citrullinated peptide 2 (CCP2)-positive subset, but some additional reactivity with single citrullinated peptides was seen in the anti-CCP2-negative subset. Adjusting for reactivity against arginine-containing control peptides did not uniformly change the diagnostic performance for antibodies against the individual citrullinated peptides.
The multiplexed array, for detection of autoantibodies against multiple citrullinated epitopes on candidate RA autoantigens, will be of benefit in studies of RA pathogenesis, diagnosis, and potentially as a guide to individualized treatment.
The genetic association of the major histocompatibility complex (MHC) to rheumatoid arthritis risk has commonly been attributed to HLA-DRB1 alleles. Yet controversy persists about the causal variants in HLA-DRB1 and the presence of independent effects elsewhere in the MHC. Using existing genome-wide SNP data in 5,018 seropositive cases and 14,974 controls, we imputed and tested classical alleles and amino acid polymorphisms for HLA-A, B, C, DPA1, DPB1, DQA1, DQB1, and DRB1 along with 3,117 SNPs across the MHC. Conditional and haplotype analyses reveal that three amino acid positions (11, 71 and 74) in HLA-DRβ1, and single amino acid polymorphisms in HLA-B (position 9) and HLA-DPβ1 (position 9), all located in the peptide-binding grooves, almost completely explain the MHC association to disease risk. This study illustrates how imputation of functional variation from large reference panels can help fine-map association signals in the MHC.
Microsomal PGE synthase 1 (mPGES-1) is the terminal enzyme in the induced state of prostaglandin E2 (PGE2) synthesis and constitutes a therapeutic target for rheumatoid arthritis (RA) treatment. We examined the role of the prostaglandin E synthase (PTGES) gene polymorphism in susceptibility to and severity of RA and related variations in the gene to its function. The PTGES gene polymorphism was analyzed in 3081 RA patients and 1900 controls from two study populations: Swedish Epidemiological Investigation of Rheumatoid Arthritis (EIRA) and the Leiden Early Arthritis Clinic (Leiden EAC). Baseline disease activity score (DAS28) was employed as a disease severity measure. mPGES-1 expression was analyzed in synovial tissue from RA patients with known genotypes using immunohistochemistry. In the Swedish study population, among women a significant association with risk for RA was observed for PTGES single-nucleotide polymorphisms (SNPs) in univariate analysis and for the distinct haplotype. These results were substantiated by meta-analysis of data from EIRA and Leiden EAC studies with overall OR 1.31 (95% confidence interval 1.11–1.56). Several PTGES SNPs were associated with earlier onset of disease or with higher DAS28 in women with RA. Patients with the genotype associated with higher DAS28 exhibited significantly higher mPGES-1 expression in synovial tissue. Our data reveal a possible influence of PTGES polymorphism on the pathogenesis of RA and on disease severity through upregulation of mPGES-1 at the sites of inflammation. Genetically predisposed individuals may develop earlier and more active disease owing to this mechanism.
mPGES-1; gene polymorphism; rheumatoid arthritis; gender