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Introduction Psoriatic arthritis (PsA) is a chronic inflammatory arthritis associated with psoriasis; in UK populations the prevalence rate of PsA in patients with psoriasis is estimated to be 14%.1 While psoriasis has a serious impact on the patient's quality of life, those suffering from PsA have been found to have a lower quality of life than psoriasis alone.2 PsA is a complex disease with environmental and genetic risk factors contributing to the overall liability. The genetic factors contributing to the susceptibility of PsA are not fully understood, but PsA is estimated to have a larger genetic component than psoriasis.3 This suggests a substantial difference in the genetic architecture of the two diseases with a heavier genetic burden for PsA. Many of the genetic risk loci reported as associated with PsA susceptibility are shared with psoriasis indicating the importance of pleiotropic effects within shared molecular pathways mediated by the presence of cutaneous psoriasis in both phenotypes. Recent studies have identified PsA-specific loci that begin to explain this increased burden; the presence of glutamic acid at the amino acid position 45 in HLA-B has been shown to be a risk factor for PsA in a psoriasis cohort and our recent Immunochip study confirmed the independent HLA-B association.4 In addition, we reported evidence for a PsA-specific risk locus at chromosome 5q31 and distinct PsA variants at the IL23R locus.5

mic acid at the amino acid position 45 in HLA-B has been shown to be a risk factor for PsA in a psoriasis cohort and our recent Immunochip study confirmed the independent HLA-B association.4 In addition, we reported evidence for a PsA-specific risk locus at chromosome 5q31 and distinct PsA variants at the IL23R locus.5 The aim of the current study was to test the loci at suggestive levels of significance in our recent Immunochip analysis to identify novel PsA loci in a large collection of PsA cases and controls collected from the UK, Ireland, Germany, Australia, Sweden and Italy. Methods Samples All samples included in this study were of European ancestry and provided written informed consent. Summary statistics and genotype data were available from the PsA Immunochip study comprising 1962 cases and 8923 controls.5 In addition genotype data was available for the psoriasis Wellcome Trust Case Control Consortium 2 (WTCCC2) study which contained 1784 psoriasis samples following exclusion of known PsA samples and 5175 controls.6 A total of 1352 PsA case and 2164 control DNA samples, independent of those tested as part of the Immunochip study, were available for genotyping collected from Germany (cases=508, controls=920), Sweden (cases=417, controls=1079) and Italy (cases=427, controls=165). A description of clinical characteristics for the three cohorts is provided in online supplementary table S1. Data for a total of 3139 PsA cases and 11 078 controls were available for this study following quality control.

(cases=508, controls=920), Sweden (cases=417, controls=1079) and Italy (cases=427, controls=165). A description of clinical characteristics for the three cohorts is provided in online supplementary table S1. Data for a total of 3139 PsA cases and 11 078 controls were available for this study following quality control. SNP selection and genotyping A total 15 single nucleotide polymorphisms (SNPs) were selected from the Immunochip study based on a significance threshold of p<1×10−4.7 Genotyping was performed using the Life Technologies TaqMan chemistry on the QuantStudio genotyping platform at the University of Erlangen, Germany. Sample and SNPs with low call rates (<0.9) were excluded prior to analysis. All genotype cluster plots were manually reviewed and SNPs were screened for deviation from Hardy-Weinberg equilibrium in control samples (Bonferroni corrected p<3.3×10−3). Statistical analysis Association testing was performed using logistic regression implemented in PLINK and meta-analysis of Immunochip and validation summary statistics was performed, weighting SNPs by inverse-variance and assuming fixed effects, using the software package METAL.

SNP selection and genotyping A total 15 single nucleotide polymorphisms (SNPs) were selected from the Immunochip study based on a significance threshold of p<1×10−4.7 Genotyping was performed using the Life Technologies TaqMan chemistry on the QuantStudio genotyping platform at the University of Erlangen, Germany. Sample and SNPs with low call rates (<0.9) were excluded prior to analysis. All genotype cluster plots were manually reviewed and SNPs were screened for deviation from Hardy-Weinberg equilibrium in control samples (Bonferroni corrected p<3.3×10−3). Statistical analysis Association testing was performed using logistic regression implemented in PLINK and meta-analysis of Immunochip and validation summary statistics was performed, weighting SNPs by inverse-variance and assuming fixed effects, using the software package METAL. For loci not previously reported as being associated with psoriasis susceptibility we investigated PsA-specificity using two large psoriasis studies. First, we tested association to psoriasis using genotype data from WTCCC2 and association summary statistics from the largest psoriasis study to date, consisting of 10 588 psoriasis cases and 22 806 controls,8 from ImmunoBase (http://www.immunobase.org). Second, we compared effect estimates in PsA to psoriasis using multinomial logistic regression using genotype data for PsA cases and controls from Immunochip and psoriasis genotype data from WTCCC2 performed in Stata. Finally, we directly compared PsA and psoriasis genotypes, with PsA coded as cases and psoriasis coded as controls. Sex differentiated associations were investigated by analysing men and women separately and comparing differences in effect estimates using Cochrane's Q statistic using Immunochip genotype data.

in Stata. Finally, we directly compared PsA and psoriasis genotypes, with PsA coded as cases and psoriasis coded as controls. Sex differentiated associations were investigated by analysing men and women separately and comparing differences in effect estimates using Cochrane's Q statistic using Immunochip genotype data. To control for phenotype misclassification with rheumatoid arthritis (RA), we included a genetic risk score (GRS) comprised of the 41 non-HLA RA susceptibility SNPs reported in the RA Immunochip study, weighted by odds ratio (OR), as a covariate and recalculated the PsA Immunochip summary statistics.9 10

in Stata. Finally, we directly compared PsA and psoriasis genotypes, with PsA coded as cases and psoriasis coded as controls. Sex differentiated associations were investigated by analysing men and women separately and comparing differences in effect estimates using Cochrane's Q statistic using Immunochip genotype data. To control for phenotype misclassification with rheumatoid arthritis (RA), we included a genetic risk score (GRS) comprised of the 41 non-HLA RA susceptibility SNPs reported in the RA Immunochip study, weighted by odds ratio (OR), as a covariate and recalculated the PsA Immunochip summary statistics.9 10 Results Following quality control of the validation genotype data a total of 13 SNPs for 1177 cases and 2155 controls was available for analysis. Meta-analysis of the validation samples with Immunochip data resulted in a combined data set of 3139 PsA cases and 11 078 controls. We identified genome-wide significance to two loci; NOS2 (rs4795067, p=5.27×10−9) and PTPN22 (rs2476601, p=1.49×10−9) (table 1). Association to NOS2 has previously been reported to psoriasis; however no such association has been made to PTPN22 (figures 1 and 2). Interestingly we observe a higher effect estimate for rs2476601 in men compared with women (1.31 vs 1.22, respectively) as previously reported for this SNP in PsA, however this difference is not statistically significant (Q=0.52). We also observe a much lower minor allele frequency for rs2476601 in the Italian population which is consistent with previous studies demonstrating a North-East to South-West gradient for minor allele frequency (MAF) across continental Europe.11

in PsA, however this difference is not statistically significant (Q=0.52). We also observe a much lower minor allele frequency for rs2476601 in the Italian population which is consistent with previous studies demonstrating a North-East to South-West gradient for minor allele frequency (MAF) across continental Europe.11 Table 1 Summary statistics for Immunochip, validation and meta-analysis of selected SNPs

in PsA, however this difference is not statistically significant (Q=0.52). We also observe a much lower minor allele frequency for rs2476601 in the Italian population which is consistent with previous studies demonstrating a North-East to South-West gradient for minor allele frequency (MAF) across continental Europe.11 Table 1 Summary statistics for Immunochip, validation and meta-analysis of selected SNPs rs chr bp Gene Risk/non-risk Immunochip (cases=1962, controls=8923) Validation (cases=1177, controls=2155) Meta-analysis (cases=3139, controls=11 078) RAF p Value OR p Value OR p Value OR I2 Q rs2476601 1 114 377 568 PTPN22 A/G 0.10 1.29E-05 1.28 1.28E-05 1.44 1.49E-09 1.32 0 0.65 rs4795067 17 26 106 675 NOS2 G/A 0.34 1.94E-07 1.21 7.42E-03 1.25 5.27E-09 1.22 0 0.75 rs984971 2 163 224 521 KCNH7 G/A 0.36 3.62E-06 0.84 0.02 0.87 2.29E-07 0.85 0 0.61 rs1306395 2 61 076 272 LINC01185 C/T 0.43 2.99E-05 0.86 0.04 0.88 3.43E-06 0.87 0 0.85 rs7552167 1 24 518 643 IFNLR1 A/G 0.14 1.53E-05 0.79 0.10 0.88 7.36E-06 0.82 35.6 0.20 rs8106664 19 10 728 030 SLC44A2 G/T 0.23 3.28E-06 0.81 0.13 0.89 1.67E-06 0.83 0 0.52 rs2392581 7 38 573 234 AMPH G/A 0.42 6.90E-05 0.87 0.17 0.93 4.42E-05 0.88 51.7 0.10 rs8103241 19 13 122 612 NFIX G/A 0.46 9.08E-05 0.87 0.19 0.92 5.41E-05 0.88 0 0.52 rs1133071 9 32 455 674 DDX58 C/T 0.30 3.36E-05 1.17 0.20 1.09 2.49E-05 1.15 64.9 0.06 rs6713082 2 62 516 544 B3GNT2 A/C 0.24 4.59E-05 1.18 0.46 1.05 9.44E-05 1.15 71.7 0.03 rs2298428 22 21 982 892 YDJC T/C 0.18 4.38E-05 1.20 0.56 1.04 2.35E-04 1.14 66.8 0.03 rs8016947 14 35 832 666 NFKBIA T/G 0.44 9.65E-05 0.87 0.73 1.02 1.49E-03 0.91 70.1 0.04 rs7895120 10 129 064 193 DOCK1 T/C 0.14 5.29E-05 0.80 0.87 1.01 1.44E-03 0.87 62.9 0.04 bp, base position; chr, chromosome; I2, heterogeneity index for ORs; Q, Cochrane's Q statistic for heterogeneity of ORs; RAF, risk allele frequency;

16947 14 35 832 666 NFKBIA T/G 0.44 9.65E-05 0.87 0.73 1.02 1.49E-03 0.91 70.1 0.04 rs7895120 10 129 064 193 DOCK1 T/C 0.14 5.29E-05 0.80 0.87 1.01 1.44E-03 0.87 62.9 0.04 bp, base position; chr, chromosome; I2, heterogeneity index for ORs; Q, Cochrane's Q statistic for heterogeneity of ORs; RAF, risk allele frequency; Figure 1 Regional association plots for the PTPN22 locus for PsA Immunochip data and meta-analysis of rs2476601. The x-axis represents chromosomal position and gene location. The first y-axis represents –log10 of the observed p value from logistic regression, secondary y-axis represents estimated recombination rates (cM/Mb). Circles represent genotyped single nucleotide polymorphisms (SNPs), colour of the circle represents linkage disequilibrium (r2) with the index SNP (purple circle). kb, kilobase; cM, centimorgan; Mb, megabase. Figure 2 Forest plot of effect estimates for rs2476601 from the Immunochip, validation and meta-analysis. Rows are labelled by study group and include MAF, p values, ORs and 95% CIs. Reported MAF is estimated from control group, for Immunochip cohort this is estimated from UK controls. CI, confidence interval; minor allele frequency; OR, odds ratio.

estimates for rs2476601 from the Immunochip, validation and meta-analysis. Rows are labelled by study group and include MAF, p values, ORs and 95% CIs. Reported MAF is estimated from control group, for Immunochip cohort this is estimated from UK controls. CI, confidence interval; minor allele frequency; OR, odds ratio. As SNPs at the PTPN22 locus have not previously been reported to be associated to psoriasis susceptibility we investigated this further in two large psoriasis data sets. First we analysed genotyped data from the WTCCC2 psoriasis study, excluding known PsA samples (cases n=1784, controls n=5175), for rs2476601 and found no evidence for association (p=0.34). Second we searched summary statistics from the largest psoriasis study to date (cases n=10 588, controls n=22 806) using the ImmunoBase database and again found no evidence for association of rs2476601 to psoriasis susceptibility (p=0.49). Using genotype data from the PsA Immunochip study and WTCCC2 we directly compared the effect estimates for rs2476601 in PsA and psoriasis using multinomial logistic regression and we found the estimates to be significantly different (p=3.2×10−4). A direct comparison of genotypes for PsA (n=1962) and psoriasis (n=1784) found significant association to an increased risk of PsA (p=4.4×10−4, OR=1.3).

ed the effect estimates for rs2476601 in PsA and psoriasis using multinomial logistic regression and we found the estimates to be significantly different (p=3.2×10−4). A direct comparison of genotypes for PsA (n=1962) and psoriasis (n=1784) found significant association to an increased risk of PsA (p=4.4×10−4, OR=1.3). Given that rs2476601 is a genetic risk factor for RA we were concerned that the observed p value in the discovery study was a false positive due to phenotype misclassification caused by the presence of unidentified RA samples in the case cohort. However, we found the association to rs22476601 in the PsA Immunochip data was unaffected by the inclusion of the RA-GRS (p=1.29×10−5 vs PGRS=1.30×10−5).

observed p value in the discovery study was a false positive due to phenotype misclassification caused by the presence of unidentified RA samples in the case cohort. However, we found the association to rs22476601 in the PsA Immunochip data was unaffected by the inclusion of the RA-GRS (p=1.29×10−5 vs PGRS=1.30×10−5). Discussion In this study we present evidence for association of rs2476601 to susceptibility of PsA exceeding the threshold recognised as genome-wide significant (p<5×10−8) for the first time. In addition we used genotype data and summary statistics from two large psoriasis studies to demonstrate that this locus is differentially associated to PsA and not psoriasis per se. We also confirm association of PsA with a previously reported psoriasis locus, NOS2, bringing the total number of confirmed, genome-wide significant, PsA loci to 10 including 4 that are PsA-specific (HLA-B, chromosome 5q31, PsA-specific variants within IL23R and now PTPN22). Studies have shown that PTPN22 is a potent inhibitor of T cell activation and it is possible that the effect may differ between T cell subpopulations.12 For example we have shown that CD8+ T cells are important for PsA, while this has not been reported in psoriasis.5

PsA-specific variants within IL23R and now PTPN22). Studies have shown that PTPN22 is a potent inhibitor of T cell activation and it is possible that the effect may differ between T cell subpopulations.12 For example we have shown that CD8+ T cells are important for PsA, while this has not been reported in psoriasis.5 Strengths of the current study include the large sample sizes used, which allowed us to confirm association at accepted genome-wide thresholds. Previous studies of this locus in PsA have been limited by small sample size; results have either shown weak evidence for association;13 14 weak association in men only15 or no evidence for association at all.16 Indeed, our previous attempts to investigate rs2476601 and PsA susceptibility failed to find any evidence of association.17 This previous study had approximately 60% power to detect an effect of the size estimated in the current study. The absence of association for rs2476601 in the Italian cohort of this study is attributed to reduced power due to the much lower MAF (figure 2). Previous investigations of the rs2476601 PTPN22 variant with psoriasis have consistently reported no evidence for association,18 19 but some have found association to other variants in the region, for example to rs3789604 (RSBN1) or haplotypes spanning PTPN22.20 21 However, in the largest psoriasis genetic association study performed to date, no association was detected to either rs2476601 or rs3789604 (p=0.49 and p=1.00, respectively).8 Indeed, a direct comparison of psoriasis and PsA confirmed that the rs2476601 association is PsA-specific, making it the fourth such locus to be identified.

the largest psoriasis genetic association study performed to date, no association was detected to either rs2476601 or rs3789604 (p=0.49 and p=1.00, respectively).8 Indeed, a direct comparison of psoriasis and PsA confirmed that the rs2476601 association is PsA-specific, making it the fourth such locus to be identified. In contrast to the previous reports, the study presented here is performed in a large cohort of 3139 cases and 11 078 controls, includes independent validation and, for the first time, reports confirmed association with susceptibility to PsA exceeding genome-wide significance (p=1.49×10−9). The identification of PsA-specific loci is vital in terms of understanding the different pathways involved, which may require different treatments, and for future screening strategies to identify subjects at risk of developing PsA in patients with psoriasis.

lity to PsA exceeding genome-wide significance (p=1.49×10−9). The identification of PsA-specific loci is vital in terms of understanding the different pathways involved, which may require different treatments, and for future screening strategies to identify subjects at risk of developing PsA in patients with psoriasis. The SNP, rs2476601, has been found to be associated with multiple autoimmune diseases including RA, where the association is predominantly found in anti-citrullinated protein antibody (ACPA)-positive subjects, although association in the ACPA-negative subgroup has been reported.22 One possibility, therefore, is that the association with PsA could be due to the inclusion of patients with RA and coincidental psoriasis in the PsA cohort. Unfortunately, ACPA or rheumatoid factor status was not available for many samples. A strength of the current study, however, is that we used a GRS of known RA loci, which has been previously shown to adequately control for potential phenotype misclassification, to explore this possible confounder and found that the association with PsA remained statistically significant even after this adjustment.10 In conclusion we report for the first time genome-wide significant association of the rs2476601 variant in the PTPN22 gene with susceptibility to PsA consistent with reports in many other autoimmune diseases. In addition, we use genotype data from a large psoriasis study to demonstrate that rs2476601 is differentially associated to PsA and not psoriasis.

t time genome-wide significant association of the rs2476601 variant in the PTPN22 gene with susceptibility to PsA consistent with reports in many other autoimmune diseases. In addition, we use genotype data from a large psoriasis study to demonstrate that rs2476601 is differentially associated to PsA and not psoriasis. Supplementary Material Web table The authors acknowledge the assistance given by IT Services and the use of the Computational Shared Facility (CSF) at The University of Manchester. The authors thank Arthritis Research UK for their support (grant ref 20385) and the NIHR Manchester Musculoskeletal Biomedical Research Unit. This report includes independent research funded by the National Institute for Health Research Biomedical Research Unit Funding Scheme. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health. The authors gratefully acknowledge the contribution of patients and staff of the Early Swedish Psoriatic Arthritis Registry (SwePsA). Contributors: AB devised the study concept and design. JB performed statistical analysis. JB and AB wrote the manuscript. SL and UH performed validation genotyping and contributed to statistical analysis. AB-A and SU contributed to the statistical analysis. FB, HB and AR contributed to interpretation of findings. INB, HM-O, PHe, AWR, DK, EK, G-MA, EG, JP, RM, OF, NM, PHo, MAB and MF contributed data to the discovery phase. All authors contributed to and approved the manuscript.

g and contributed to statistical analysis. AB-A and SU contributed to the statistical analysis. FB, HB and AR contributed to interpretation of findings. INB, HM-O, PHe, AWR, DK, EK, G-MA, EG, JP, RM, OF, NM, PHo, MAB and MF contributed data to the discovery phase. All authors contributed to and approved the manuscript. Funding: Frankfurt: the German Federal Ministry of Education and Research ArthroMark (project 4, 01 EC 1009C), the Federal State of Hesse (LOEWE-project: IME Fraunhofer Project Group Translational Medicine & Pharmacology at the Goethe University), HB received funding from Pfizer Pharma, Germany (Forschungsförderpreis Rheumatologie 2012). Support for the Australian component of the study was received from Abbvie. MAB is funded by a National Health and Medical Research Foundation (Australia) Senior Principal Research Fellowship. Competing interests: None declared. Ethics approval: All samples were collected with approval from the respective local ethical committee: the medical faculties of the Universities of Erlangen and Münster, the University of Tor Vergata of Rome and the Umeå University, Sweden. Provenance and peer review: Not commissioned; externally peer reviewed. Data sharing statement: All summary statistics for data generated in this study are presented in table 1. Further information can be obtained by contacting the authors.

A reactivity but with no clinical differences between the studied cohorts, findings that were not replicated here. A very recent study found no differences between 24 cN-1A seropositive and 45 seronegative patients with IBM regarding class II human leukocyte antigen (HLA) alleles and the presence of other antibodies.25 The simultaneous discovery of anti-cN-1A antibodies in 2011 by two independent research groups offers potential insights into the pathogenesis of IBM, and will contribute to the debate about the relative influence of the immune system and degeneration.16 19 23 The presence of anti-cN-1A in other autoimmune diseases such as Sjögren's syndrome is also of interest as it might highlight shared underlying immune mechanisms across these diseases.22 As with most other MSAs, further research is required to establish the mechanisms involved in anti-cN-1A reactivity in IBM.

n.16 19 23 The presence of anti-cN-1A in other autoimmune diseases such as Sjögren's syndrome is also of interest as it might highlight shared underlying immune mechanisms across these diseases.22 As with most other MSAs, further research is required to establish the mechanisms involved in anti-cN-1A reactivity in IBM. Anti-cN-1A antibodies are present in the sera of 29%–52% of patients with IBM (33% in our cohort).16 17 Higher proportions of anti-cN-1A antibody seropositivity in other studies (up to 72%) might be explained by different techniques used in different centres, by different cut-off levels for positivity or by differences in patient selection.18 The current study used very strict cut-off values in ELISA testing.26 In a recent study, anti-cN-1A antibodies were found in 37% of patients with IBM, compared with <5% in PM, DM and other neuromuscular disorders, highlighting a potential utility of using anti-cN-1A antibody testing to differentiate IBM and mimicking diagnoses.22 However, the specificity of testing is limited by a high reactivity in some other autoimmune and connective tissue diseases (in 36% of patients with Sjögren's syndrome and in 20% with systemic lupus erythematosus).22 24

tential utility of using anti-cN-1A antibody testing to differentiate IBM and mimicking diagnoses.22 However, the specificity of testing is limited by a high reactivity in some other autoimmune and connective tissue diseases (in 36% of patients with Sjögren's syndrome and in 20% with systemic lupus erythematosus).22 24 The higher frequency of COX-negative fibres, a feature of mitochondrial dysfunction, indicates possible differences in molecular pathways within the subgroups defined by anti-cN-1A antibody status. The reasons for increased mortality and the suggestion of increased risk of death from respiratory cause are unexplained, but these findings appear to agree with those of Goyal et al18 who also found a more severe respiratory phenotype in the antibody-positive group. The lower frequency of proximal upper limb weakness at presentation in the anti-cN-1A antibody positive compared with antibody-negative group remains unexplained.

Introduction Inclusion body myositis (IBM) is an acquired muscle disease that most commonly affects males aged over 45 years. Along with polymyositis (PM) and dermatomyositis (DM), IBM is usually classified as one of the idiopathic inflammatory myopathies. However, IBM differs in comparison with PM and DM, as sustained responses to immunosuppression are not seen, and histologically it is associated with significant degenerative features.1–3 Clinically, IBM is characterised by asymmetric weakness, notably of finger flexors and knee extensors. Weakness in other muscle groups occurs frequently, including bulbar, facial and axial muscles.4 5 The slowly progressive course leads to cumulative disability, although overall life expectancy is unaffected.6–8 The diagnosis of IBM relies upon a combination of clinical and laboratory findings as defined in various diagnostic criteria (eg, Medical Research Council (MRC), Griggs et al and the European Neuromuscular Centre (ENMC) criteria).9–11 However, certain histopathological findings may only become detectable as the disease progresses, and therefore patients with early disease may not fulfil definite diagnostic criteria and can be excluded from clinical trials.12 The average delay between disease onset and diagnosis is around 5 years, and IBM is frequently misdiagnosed initially as PM, resulting in the unnecessary use of potentially harmful treatments, such as high-dose glucocorticoids.8 13–15

y not fulfil definite diagnostic criteria and can be excluded from clinical trials.12 The average delay between disease onset and diagnosis is around 5 years, and IBM is frequently misdiagnosed initially as PM, resulting in the unnecessary use of potentially harmful treatments, such as high-dose glucocorticoids.8 13–15 In IBM, autoantibodies directed against cytosolic 5′-nucleotidase 1A (cN-1A) have recently been identified. It is suggested that these may support the diagnostic process, as well as potentially providing clues as to disease pathogenesis.16 17 However, uncertainties regarding the usefulness of anti-cN-1A autoantibody testing in clinical practice remain. This is particularly true with regard to patient stratification and prognosis, where the few studies that have compared clinical and histopathological features of antibody-positive versus antibody-negative patients with IBM have produced conflicting results in some cases.18 19 In order to explore further the usefulness of anti-cN-1A antibody testing to facilitate IBM subgroup classification, we conducted a retrospective Europe-wide study correlating clinical, serological and histopathological features in a large cohort of patients with IBM stratified by anti-cN-1A antibody status. Patients and methods Study cohort Pooled IBM case data from four European countries were used. Researchers based in Nijmegen, The Netherlands, coordinated data collection from The Netherlands, France and Sweden. Data collection in the UK was coordinated by researchers based in Manchester, UK.

In IBM, autoantibodies directed against cytosolic 5′-nucleotidase 1A (cN-1A) have recently been identified. It is suggested that these may support the diagnostic process, as well as potentially providing clues as to disease pathogenesis.16 17 However, uncertainties regarding the usefulness of anti-cN-1A autoantibody testing in clinical practice remain. This is particularly true with regard to patient stratification and prognosis, where the few studies that have compared clinical and histopathological features of antibody-positive versus antibody-negative patients with IBM have produced conflicting results in some cases.18 19 In order to explore further the usefulness of anti-cN-1A antibody testing to facilitate IBM subgroup classification, we conducted a retrospective Europe-wide study correlating clinical, serological and histopathological features in a large cohort of patients with IBM stratified by anti-cN-1A antibody status. Patients and methods Study cohort Pooled IBM case data from four European countries were used. Researchers based in Nijmegen, The Netherlands, coordinated data collection from The Netherlands, France and Sweden. Data collection in the UK was coordinated by researchers based in Manchester, UK. Study inclusion criteria Included cases met either the MRC (‘pathologically defined’, ‘clinically defined’ or ‘possible’), Griggs et al (‘definite’ or ‘possible’) or ENMC (‘clinicopathologically defined’, ‘clinically defined’ or ‘probable’) diagnostic criteria for IBM and had sera available for anti-cN-1A antibody testing.9 11

clusion criteria Included cases met either the MRC (‘pathologically defined’, ‘clinically defined’ or ‘possible’), Griggs et al (‘definite’ or ‘possible’) or ENMC (‘clinicopathologically defined’, ‘clinically defined’ or ‘probable’) diagnostic criteria for IBM and had sera available for anti-cN-1A antibody testing.9 11 Data collection methodology Swedish, French and Dutch (‘non-UK’) patients were identified from clinical databases. Researchers blinded to anti-cN-1A antibody status (AR, MTJP, KRG, KM) reviewed the medical records and retrospectively completed a standardised data collection pro forma. UK patients were identified from six centres contributing to the UKMYONET research study, coordinated by The University of Manchester. As part of this study, data are captured using a standardised pro forma at the time of study recruitment (ie, before serological test results are available).20 21 Those recruiting patients are asked to record clinical features present at disease onset and features present at the time of recruitment. Some additional fields (to match data from the non-UK cohort) and missing data were collected retrospectively. Copies of pro forma used are contained in online supplementary appendix 1. The datasets were merged and cleaned by a researcher blinded to anti-cN-1A status (JBL). 10.1136/annrheumdis-2016-210282.supp1supplementary appendix

Data collection methodology Swedish, French and Dutch (‘non-UK’) patients were identified from clinical databases. Researchers blinded to anti-cN-1A antibody status (AR, MTJP, KRG, KM) reviewed the medical records and retrospectively completed a standardised data collection pro forma. UK patients were identified from six centres contributing to the UKMYONET research study, coordinated by The University of Manchester. As part of this study, data are captured using a standardised pro forma at the time of study recruitment (ie, before serological test results are available).20 21 Those recruiting patients are asked to record clinical features present at disease onset and features present at the time of recruitment. Some additional fields (to match data from the non-UK cohort) and missing data were collected retrospectively. Copies of pro forma used are contained in online supplementary appendix 1. The datasets were merged and cleaned by a researcher blinded to anti-cN-1A status (JBL). 10.1136/annrheumdis-2016-210282.supp1supplementary appendix Clinical data Data collected included demographic, clinical (eg, distribution of weakness, presence of dysphagia, comorbidities), laboratory findings (creatine kinase (CK) levels, muscle biopsy features, serological testing), comorbidity, mobility aid usage and mortality. In most cases, data were available regarding features present at disease onset and at the time of last patient review (or recruitment to the UKMYONET study in the case of the UK cohort). In all cases, ‘disease onset’ refers to the initial date that symptoms of IBM were noted, as reported by the patient. ‘Disease duration’ is defined as the period between disease onset and the date of anti-cN-1A antibody testing. Regarding mortality, in the non-UK cohort, the primary cause of death was categorised by review of the patient's medical records as either ‘respiratory’, ‘cardiac’, ‘cerebrovascular’, ‘malignancy’ or ‘other’. In the UK cohort, additional mortality and comorbidity statistics were obtained from the UK Health and Social Care Information Centre, including coded data regarding the cause of death where applicable. The cause of death in these cases was assessed and assigned to the same categories as the non-UK cohort.

or ‘other’. In the UK cohort, additional mortality and comorbidity statistics were obtained from the UK Health and Social Care Information Centre, including coded data regarding the cause of death where applicable. The cause of death in these cases was assessed and assigned to the same categories as the non-UK cohort. Histopathology For all cases, the histopathology biopsy report performed at initial diagnostic interrogation was reviewed, and the presence of certain specific features determined from the report text. The reporting histopathologists were blinded to the anti-cN-1A antibody status of each patient at the time of reporting. Cytochrome oxidase (COX) deficient fibres in the biopsy sample were recorded as ‘excessive’ if the reporting histopathologist indicated that numbers were adjudged higher than expected, according to the patient’s age. In some cases, the date that the biopsy was performed was not available. In such instances, this was assumed to be the same as the date of diagnosis. cN-1A analysis All sera were analysed at the Department of Biomolecular Chemistry in Nijmegen by ELISA, with the three synthetic peptides containing cN-1A autoepitopes previously identified by overlapping peptide microarray analyses.16 Signals were quantified by determining optical densities at 450 nm (OD450) using methods previously described and defined as seropositive if the OD450 value was greater than or equal to the established cut-off value for the corresponding peptide.22

pes previously identified by overlapping peptide microarray analyses.16 Signals were quantified by determining optical densities at 450 nm (OD450) using methods previously described and defined as seropositive if the OD450 value was greater than or equal to the established cut-off value for the corresponding peptide.22 Other serological testing Data regarding the presence of myositis-specific antibodies (MSAs) and myositis-associated antibodies (MAAs) were collected where available. For the non-UK patients, data were obtained from results available in the medical records, and methodology of testing was unique to each centre. MSAs and MAAs in the whole UK cohort were screened by immunoprecipitation at the University of Bath (Bath, UK) using previously described standardised methodology.23 ‘Weak positive’ results were assumed to be negative for the purpose of this study.

medical records, and methodology of testing was unique to each centre. MSAs and MAAs in the whole UK cohort were screened by immunoprecipitation at the University of Bath (Bath, UK) using previously described standardised methodology.23 ‘Weak positive’ results were assumed to be negative for the purpose of this study. Statistical analysis The per-subject sum of all recorded comorbidities (of autoimmune disease, cardiovascular disease (including hypertension) and malignancy) was calculated. Current or previous smoking was also treated as a comorbidity for the purposes of this analysis. According to the number of these factors present, each patient was then assigned a comorbidity score of 0, 1 or 2 or more for use in regression. Differences in demographic features, comorbidities, clinical features, autoantibody status and muscle biopsy features between anti-cN-1A antibody positive and negative patients were assessed using logistic regression. In order to test the effect of potential confounders, adjusted (multivariable) logistic regression models were produced when unadjusted analysis had suggested a significant difference (defined as p<0.05).

biopsy features between anti-cN-1A antibody positive and negative patients were assessed using logistic regression. In order to test the effect of potential confounders, adjusted (multivariable) logistic regression models were produced when unadjusted analysis had suggested a significant difference (defined as p<0.05). The impact of anti-cN-1A antibody status on survival and mobility aid requirement was assessed using Kaplan-Meier curves, log-rank testing and Cox proportional hazards regression modelling. In both cases, the start of the surveillance period was the date of disease onset. For the mobility aid analysis, subjects exited the model at the time of mobility aid requirement or at the time they were last known to have not required one. For the survival analysis, subjects exited the model at the time of death or at the time they were last known to have been alive. Each Cox regression model included adjustment for age of disease onset, gender and comorbidities. Other variables were added to the models if there was an a priori assumption that a relationship between anti-cN-1A antibody status and the outcome variable was likely to exist. For example, a higher incidence of anti-cN-1A antibodies in those with Sjögren's syndrome is reported, a more prominent bulbar involvement in anti-cN-1A positive patients with IBM has been described and a correlation between COX deficiency and more advanced age at biopsy could exist.18 22 24 Therefore, models with additional adjustment for such variables were created.

bodies in those with Sjögren's syndrome is reported, a more prominent bulbar involvement in anti-cN-1A positive patients with IBM has been described and a correlation between COX deficiency and more advanced age at biopsy could exist.18 22 24 Therefore, models with additional adjustment for such variables were created. The analysis plan specifically omitted correction for multiple testing due to the highly conservative nature of such methods which would risk elimination of potentially useful information which was sought to be retained, given the exploratory nature of this study. Data were processed and analysed using Stata for Windows V.13.0 (College Station, Texas, USA). Kaplan-Meier curves were generated using GraphPad Prism V.6 (GraphPad Software).

hods which would risk elimination of potentially useful information which was sought to be retained, given the exploratory nature of this study. Data were processed and analysed using Stata for Windows V.13.0 (College Station, Texas, USA). Kaplan-Meier curves were generated using GraphPad Prism V.6 (GraphPad Software). Results After screening databases in the four involved countries, 311 patients meeting the study inclusion criteria were selected for further analysis (45% from the UK, 55% non-UK). Overall, 33% (102/311) were positive for the anti-cN-1A antibody. Table 1 shows the IBM diagnostic criteria met according to anti-cN-1A antibody status. No relationship between a diagnostic classification of ‘possible’ IBM versus ‘definite’ (for Griggs et al criteria) or ‘pathologically/clinically defined’ (for MRC criteria) IBM and anti-cN-1A antibody status was found (for MRC criteria, OR 0.85, 95% CI 0.48 to 1.49, p=0.565; for Griggs et al criteria, OR 0.70, 95% CI 0.36 to 1.36, p=0.292; analysis not performed for ENMC criteria as all anti-cN-1A antibody positive patients met the definition of ‘definite’ IBM). No difference was found in the interval between disease onset and the time of antibody testing between seropositive and seronegative groups (8.29 years (IQR 4.96–11.95) in the seropositive group vs 7.57 years (IQR 4.94–11.18) in the seronegative group, OR 1.01, 95% CI 0.97 to 1.06, p=0.604). Table 1 Summary of diagnostic criteria met in patients included for analysis

Results After screening databases in the four involved countries, 311 patients meeting the study inclusion criteria were selected for further analysis (45% from the UK, 55% non-UK). Overall, 33% (102/311) were positive for the anti-cN-1A antibody. Table 1 shows the IBM diagnostic criteria met according to anti-cN-1A antibody status. No relationship between a diagnostic classification of ‘possible’ IBM versus ‘definite’ (for Griggs et al criteria) or ‘pathologically/clinically defined’ (for MRC criteria) IBM and anti-cN-1A antibody status was found (for MRC criteria, OR 0.85, 95% CI 0.48 to 1.49, p=0.565; for Griggs et al criteria, OR 0.70, 95% CI 0.36 to 1.36, p=0.292; analysis not performed for ENMC criteria as all anti-cN-1A antibody positive patients met the definition of ‘definite’ IBM). No difference was found in the interval between disease onset and the time of antibody testing between seropositive and seronegative groups (8.29 years (IQR 4.96–11.95) in the seropositive group vs 7.57 years (IQR 4.94–11.18) in the seronegative group, OR 1.01, 95% CI 0.97 to 1.06, p=0.604). Table 1 Summary of diagnostic criteria met in patients included for analysis Diagnostic criteria met Anti-cN-1A positive (%) Total (all patients) Medical Research Council Criteria 201010 Pathologically defined IBM 13 (31.7) 41 Clinically defined IBM 39 (39.4) 99 Possible IBM 28 (33.3) 84 Griggs et al9 Criteria Definite IBM 19 (40.4) 47 Possible IBM 61 (32.3) 189 European Neuromuscular Centre Criteria 199711 Definite IBM 7 (31.8) 22 Probable IBM 0 (0.0) 2 Total unique patients* 102 (32.8) 311 *Some patients fulfilled multiple diagnostic criteria. Not all patients were assessed by each criterion. Of the total, 152 patients met only one criterion, 143 patients met two criteria and 16 patients met all three criteria.

a 199711 Definite IBM 7 (31.8) 22 Probable IBM 0 (0.0) 2 Total unique patients* 102 (32.8) 311 *Some patients fulfilled multiple diagnostic criteria. Not all patients were assessed by each criterion. Of the total, 152 patients met only one criterion, 143 patients met two criteria and 16 patients met all three criteria. Anti-cN-1A, anticytosolic 5′-nucleotidase 1A; IBM, inclusion body myositis. Demographics and comorbidities No statistically significant differences were identified in demographic characteristics (including gender, age at disease onset and age at diagnosis), CK levels, smoking history or comorbidities between the anti-cN-1A antibody positive and negative groups (table 2). Non-significant trends were observed in age at disease onset and age at diagnosis (which appeared lower in the antibody-negative group) or the presence of other autoimmune diseases (which appeared more common in the antibody-positive group). Table 2 Summary of demographic features, CK levels and comorbidities stratified by anti-cN-1A antibody status

Demographics and comorbidities No statistically significant differences were identified in demographic characteristics (including gender, age at disease onset and age at diagnosis), CK levels, smoking history or comorbidities between the anti-cN-1A antibody positive and negative groups (table 2). Non-significant trends were observed in age at disease onset and age at diagnosis (which appeared lower in the antibody-negative group) or the presence of other autoimmune diseases (which appeared more common in the antibody-positive group). Table 2 Summary of demographic features, CK levels and comorbidities stratified by anti-cN-1A antibody status Anti-cN-1A positive Anti-cN-1A negative OR (95% CI) p Value Gender (n=311) Female (%) 42/102 (41.2) 84/209 (40.2) Referent – Male (%) 60/102 (58.8) 125/209 (59.8) 0.96 (0.59 to 1.55) 0.868 Ethnicity (n=307) White (%) 97/101 (96.0) 199/206 (96.6) Referent – Black (%) 2/101 (2.0) 4/206 (1.9) 1.03 (0.19 to 5.70) 0.977 Asian (%) 2/101 (2.0) 3/206 (1.5) 1.37 (0.23 to 8.32) 0.734 Other features Mean age in years at disease onset (SD) (n=301) 61.6 (9.7) 59.8 (9.5) 1.02 (0.99 to 1.05) 0.130 Mean age in years at diagnosis (SD) (n=305) 67.2 (9.3) 65.3 (9.5) 1.02 (1.00 to 1.05) 0.089 Disease duration in years at antibody testing (n=301) Median 8.3 (IQR 5.0–12.0) Mean 9.0 (SD 5.5) Median 7.6 (IQR 4.9–11.2) Mean 8.6 (SD 5.2) 1.01 (0.97 to 1.06) 0.604 Highest CK level recorded (n=223) Median 629.0 (IQR 392–850) Mean 774.8 (SD 563.4) Median 600.0 (IQR 400–1012) Mean 1097.2 (SD 2583.4) 1.00 (1.00 to 1.00) 0.318 Current or previous smoker (%) (n=189) 21/52 (40.4) 55/137 (40.2) 1.01 (0.53 to 1.94) 0.976 Comorbidities Autoimmune disease (including Sjögren's syndrome) (%) (n=244) 38/85 (44.7) 54/159 (34.0) 1.57 (0.92 to 2.70) 0.100 Of which, Sjögren's syndrome (%) (n=81) 6/33 (18.2) 8/48 (16.7) 1.11 (0.35 to 3.57) 0.859 Malignancy (%) (n=275) 12/85 (14.1) 33/190 (17.4) 0.78 (0.38 to 1.60) 0.501 Cardiovascular disease (%) (n=284) 31/91 (34.1) 64/193 (33.2) 1.04 (0.62 to 1.76) 0.880 Hypertension (%) (n=181) 29/60 (48.3) 54/121 (44.6) 1.16 (0.62 to 2.16) 0.638 ‘Disease duration in years at antibody testing’ refers to the time period between disease onset and the date of anti-cN-1A antibody testing. n represents data available for analysis per variable (of a total of 311). p Value is derived from logistic regression.

n=181) 29/60 (48.3) 54/121 (44.6) 1.16 (0.62 to 2.16) 0.638 ‘Disease duration in years at antibody testing’ refers to the time period between disease onset and the date of anti-cN-1A antibody testing. n represents data available for analysis per variable (of a total of 311). p Value is derived from logistic regression. Anti-cN-1A, anticytosolic 5′-nucleotidase 1A; CK, creatine kinase. Survival Of the whole cohort of 311 patients, 70 deaths were recorded (31/102 (30%) in the anti-cN-1A antibody positive group and 39/209 (19%) in the negative group). The mean age of death overall was 77.8 years (SD=8.2), with no significant difference detected according to anti-cN-1A antibody status (77.0 years (SD=7.7) in the seropositive group vs 78.4 years (SD=8.6) in the seronegative group, OR 0.98, 95% CI 0.92 to 1.04, p=0.482). The cause of death was known in 63% (44 of 70) of cases. An excess of deaths as a result of respiratory disease was evident in the anti-cN-1A antibody positive group (16/25 (64%) in the anti-cN-1A antibody positive group and 9/25 (36%) in the negative group, OR 4.23, 95% CI 1.79 to 9.97, p=0.001). Adjusted analysis was not performed here due to the low numbers available for analysis. Death from other causes (cardiac, cerebrovascular, malignancy and other causes) did not differ between anti-cN-1A antibody positive and negative groups.

p and 9/25 (36%) in the negative group, OR 4.23, 95% CI 1.79 to 9.97, p=0.001). Adjusted analysis was not performed here due to the low numbers available for analysis. Death from other causes (cardiac, cerebrovascular, malignancy and other causes) did not differ between anti-cN-1A antibody positive and negative groups. Data from 300 patients, where the date of disease onset and date of last follow-up (or date of death) were known, were available for further analysis. This included 66 of those that had died (66/70, 94%) and comprised a total of 3550 patient-years of follow-up. The median survival in the anti-cN-1A antibody positive group was 17.6 years compared with 24.2 years in the antibody-negative group, and the Kaplan-Meier curves were significantly different (log-rank p=0.045, figure 1). Figure 1 Kaplan-Meier survival curves stratified by anti-cN-1A antibody status. X-axis truncated at 25 years from disease onset. In unadjusted analysis, compared with the antibody-negative group, anti-cN-1A antibody positive patients had a 65% increased risk of death (HR 1.65, 95% CI 1.01 to 2.70, p=0.047). After adjustment for age at disease onset, gender and comorbidities, the HR was 1.95 (95% CI 1.17 to 3.27, p=0.011). Furthermore, adding the presence of dysphagia to the model confirmed an independent association (HR 1.89, 95% CI 1.11 to 3.21, p=0.019).

% increased risk of death (HR 1.65, 95% CI 1.01 to 2.70, p=0.047). After adjustment for age at disease onset, gender and comorbidities, the HR was 1.95 (95% CI 1.17 to 3.27, p=0.011). Furthermore, adding the presence of dysphagia to the model confirmed an independent association (HR 1.89, 95% CI 1.11 to 3.21, p=0.019). Mobility Data from 188 patients were available for this analysis. A total of 130 instances of mobility aid uptake were recorded, 81% (52/64) in the anti-cN-1A seropositive group and 63% (78/124) in the seronegative group. The overall median time between disease onset and use of a mobility aid was 8.0 years (IQR 4.6–11.0), with no significant difference between seropositive and seronegative groups (8.0 years (IQR 4.8–10.9), and 6.9 years (IQR 4.4–11.7), respectively; OR 1.01, 95% CI 0.94 to 1.08, p=0.883). Kaplan-Meier curves were not significantly different (log-rank p=0.090), so not shown. In unadjusted analysis, the HR for mobility aid requirement in the antibody-positive group was 1.35 (95% CI 0.95 to 1.93, p=0.097). After adjustment for age at disease onset, gender and comorbidities, the HR for mobility aid requirement was just outside the significance threshold (HR 1.42, 95% CI 0.99 to 2.04, p=0.056).

n unadjusted analysis, the HR for mobility aid requirement in the antibody-positive group was 1.35 (95% CI 0.95 to 1.93, p=0.097). After adjustment for age at disease onset, gender and comorbidities, the HR for mobility aid requirement was just outside the significance threshold (HR 1.42, 95% CI 0.99 to 2.04, p=0.056). Clinical features Table 3 demonstrates the clinical characteristics at disease onset and at last clinical review, stratified by anti-cN-1A antibody status. A significant association between the presence of proximal upper limb weakness at disease onset (not a typical feature of IBM) and being anti-cN-1A antibody negative was identified (OR 0.30 95% CI 0.13 to 0.71, p=0.006). This remained significant after adjustment for age at onset, gender and comorbidities (OR 0.29, 95% CI 0.12 to 0.68, p=0.005), thus potentially defining a more classical and homogenous IBM cohort in the anti-cN-1A antibody positive group. Data regarding the presence of facial weakness were less complete (n=90). Despite this, a significantly increased incidence of facial weakness was identified in the anti-cN-1A antibody positive group at last review (OR 2.60, 95% CI 1.07 to 6.29, p=0.034), which persisted after adjustment for age at onset, gender and comorbidities (OR 3.03, 95% CI 1.20 to 7.67, p=0.019). Table 3 Clinical characteristics at disease onset and at last clinical review stratified by anti-cN-1A antibody status

Clinical features Table 3 demonstrates the clinical characteristics at disease onset and at last clinical review, stratified by anti-cN-1A antibody status. A significant association between the presence of proximal upper limb weakness at disease onset (not a typical feature of IBM) and being anti-cN-1A antibody negative was identified (OR 0.30 95% CI 0.13 to 0.71, p=0.006). This remained significant after adjustment for age at onset, gender and comorbidities (OR 0.29, 95% CI 0.12 to 0.68, p=0.005), thus potentially defining a more classical and homogenous IBM cohort in the anti-cN-1A antibody positive group. Data regarding the presence of facial weakness were less complete (n=90). Despite this, a significantly increased incidence of facial weakness was identified in the anti-cN-1A antibody positive group at last review (OR 2.60, 95% CI 1.07 to 6.29, p=0.034), which persisted after adjustment for age at onset, gender and comorbidities (OR 3.03, 95% CI 1.20 to 7.67, p=0.019). Table 3 Clinical characteristics at disease onset and at last clinical review stratified by anti-cN-1A antibody status Clinical feature Anti-cN-1A positive (%) Anti-cN-1A negative (%) OR (95% CI) p Value At disease onset Proximal upper limb weakness (n=252) 7/84 (8.3) 39/168 (23.2) 0.30 (0.13 to 0.71) 0.006* Proximal lower limb weakness (n=253) 65/85 (76.5) 122/168 (72.6) 1.23 (0.67 to 2.24) 0.510 Distal upper limb weakness (n=251) 22/83 (26.5) 40/168 (23.8) 1.15 (0.63 to 2.11) 0.641 Distal lower limb weakness (n=250) 7/83 (8.4) 20/167 (12.0) 0.68 (0.27 to 1.67) 0.398 Dysphagia (n=119) 15/36 (41.7) 23/83 (27.7) 1.86 (0.82 to 4.22) 0.136 Axial involvement (n=102) 0/30 (0.0) 3/72 (4.2) 1 – Symmetrical weakness (n=97) 25/37 (67.6) 32/60 (53.3) 1.82 (0.78 to 4.29) 0.169 At last review Proximal lower limb weakness (n=137) 35/40 (87.5) 80/97 (82.5) 1.49 (0.51 to 4.35) 0.468 Distal upper limb weakness (n=135) 40/41 (97.6) 89/94 (94.7) 2.25 (0.25 to 19.86) 0.466 Distal lower limb weakness (n=125) 23/43 (53.5) 36/82 (43.9) 1.47 (0.70 to 3.08) 0.309 Dysphagia (n=303) 63/100 (63.0) 113/203 (55.7) 1.36 (0.83 to 2.22) 0.224 Facial weakness (n=90) 18/33 (54.6) 18/57 (31.6) 2.60 (1.07 to 6.29) 0.034† Axial involvement (n=84) 9/26 (34.6) 10/58 (17.2) 2.54 (0.88 to 7.31) 0.084 Clinical evidence of polyneuropathy (n=103) 13/38 (34.2) 31/65 (47.7) 0.57 (0.25 to 1.31) 0.184 Figures in brackets represent within antibody group percentages. n represents data available for analysis per variable (of a total of 311). p Value is derived from logistic regression. Data regarding certain variables (proximal upper limb weakness, facial weakness, symmetrical weakness and clinical evidence of polyneuropathy) were only available at either disease onset or at last review.

resents data available for analysis per variable (of a total of 311). p Value is derived from logistic regression. Data regarding certain variables (proximal upper limb weakness, facial weakness, symmetrical weakness and clinical evidence of polyneuropathy) were only available at either disease onset or at last review. *Adjusted (for age at disease onset, gender and comorbidities) OR 0.29, 95% CI 0.12 to 0.68, p=0.005. †Adjusted (for age at disease onset, gender and comorbidities) OR 3.03, 95% CI 1.20 to 7.67, p=0.019. Anti-cN-1A, anticytosolic 5′-nucleotidase 1A. Autoantibody associations A significant association between seropositivity for anti-SSB (La) antibodies and anti-cN-1A antibodies was identified (OR 3.28, 95% CI 1.33 to 8.07, p=0.010) (table 4). However, adjusted analysis (for anti-SSA antibodies, presence of autoimmune disorders, age at onset, gender and comorbidities) did not confirm that this association was independent (OR 2.12, 95% CI 0.52 to 8.67, p=0.297). Table 4 Autoantibody profile stratified by anti-cN-1A antibody status

Autoantibody associations A significant association between seropositivity for anti-SSB (La) antibodies and anti-cN-1A antibodies was identified (OR 3.28, 95% CI 1.33 to 8.07, p=0.010) (table 4). However, adjusted analysis (for anti-SSA antibodies, presence of autoimmune disorders, age at onset, gender and comorbidities) did not confirm that this association was independent (OR 2.12, 95% CI 0.52 to 8.67, p=0.297). Table 4 Autoantibody profile stratified by anti-cN-1A antibody status Antibody Anti-cN-1A positive (%) Anti-cN-1A negative (%) OR (95% CI) p Value Antinuclear antibodies (n=132) 1/47 (2.1) 1/85 (1.2) 1.83 (0.11 to 29.88) 0.673 Anti-DNA antibodies (n=119) 3/42 (7.1) 1/77 (1.3) 5.85 (0.59 to 58.07) 0.132 Anti-Sm antibodies (n=97) 0/33 (0.0) 1/64 (1.6) 1 – Antineutrophil cytoplasmic antibodies (n=96) 0/32 (0.0) 0/64 (0.0) – – Antimitochondrial antibodies (n=128) 0/41 (0.0) 0/87 (0.0) – – Antiextractable nuclear antigens antibodies (n=102) 4/34 (11.8) 5/68 (7.4) 1.68 (0.42 to 6.71) 0.463 Anti-SSA (Ro) (n=228) 19/76 (25.0) 22/152 (14.5) 1.97 (0.99 to 3.92) 0.054 Anti-SSB (La) (n=228) 13/76 (17.1) 9/152 (5.9) 3.28 (1.33 to 8.07) 0.010* (U1)RNP antibodies (n=223) 1/74 (1.4) 0/149 (0.0) 1 – Antitopoisomerase I (Scl70) (n=222) 0/72 (0.0) 0/150 (0.0) – – Anti-Jo1 (n=228) 1/76 (1.3) 0/152 (0.0) 1 – Other myositis-specific antibody (OMSA)† (n=193) 0/60 (0.0) 1/133 (0.8) 1 – Other myositis-associated antibody (OMAA) (n=128) 0/41 (0.0) 0/87 (0.0) – – Figures in brackets represent within antibody group percentages. n represents data available for analysis per variable (of a total of 311). p Value is derived from logistic regression.

pecific antibody (OMSA)† (n=193) 0/60 (0.0) 1/133 (0.8) 1 – Other myositis-associated antibody (OMAA) (n=128) 0/41 (0.0) 0/87 (0.0) – – Figures in brackets represent within antibody group percentages. n represents data available for analysis per variable (of a total of 311). p Value is derived from logistic regression. *Adjusted (for anti-SSA antibodies, presence of autoimmune disorders, age at disease onset, gender and comorbidities) OR 2.11, 95% CI 0.52 to 8.67, p=0.297. †One patient found positive for anti-SRP antibodies. In this case, no relevant clinical correlation was identified, and the relevance of this finding is uncertain. Anti-cN-1A, anticytosolic 5′-nucleotidase 1A; OMAA, anti-Ku, anti-RNA polymerase I/II/III, anti-PM/SCL, anti-NOR90; OMSA, anti-TIF1 complex, anti-SAE, anti-NXP2, anti-MDA5, anti-SRP, anti-Mi-2, anti-PL12, anti-PL7, anti-EJ, anti-KS, anti-OJ, anti-Zo. Biopsy features We identified a significant association between an excess of COX-deficient fibres on muscle biopsy and the presence of anti-cN-1A antibodies (OR 2.61, 95% CI 1.13 to 6.03, p=0.025) (table 5). In adjusted analysis (for age at disease onset, gender, comorbidities and age at biopsy), a significant independent association was confirmed (OR 2.80, 95% CI 1.17 to 6.66, p=0.020). Table 5 Summary of muscle biopsy features stratified by anti-cN1-A antibody status

Biopsy features We identified a significant association between an excess of COX-deficient fibres on muscle biopsy and the presence of anti-cN-1A antibodies (OR 2.61, 95% CI 1.13 to 6.03, p=0.025) (table 5). In adjusted analysis (for age at disease onset, gender, comorbidities and age at biopsy), a significant independent association was confirmed (OR 2.80, 95% CI 1.17 to 6.66, p=0.020). Table 5 Summary of muscle biopsy features stratified by anti-cN1-A antibody status Biopsy feature Anti-cN-1A positive (%) Anti-cN-1A negative (%) OR (95% CI) p Value Excess COX-deficient fibres (n=185) 53/61 (86.9) 89/124 (71.8) 2.61 (1.13 to 6.03) 0.025* Ragged red fibres (n=164) 30/55 (54.6) 54/109 (49.5) 1.22 (0.64 to 2.34) 0.545 Atrophic fibres (n=176) 59/69 (85.5) 98/107 (91.6) 0.54 (0.21 to 1.41) 0.209 Inflammation (n=290) 94/96 (97.9) 193/194 (99.5) 0.24 (0.02 to 2.72) 0.251 MHC I upregulation (n=198) 67/69 (97.1) 124/129 (96.1) 1.35 (0.26 to 7.15) 0.724 Necrosis (n=136) 40/50 (80.0) 61/86 (70.9) 1.64 (0.71 to 3.78) 0.246 Mononuclear infiltrate (n=224) 72/74 (97.3) 143/150 (95.3) 1.76 (0.36 to 8.70) 0.487 Invasion of non-necrotic fibres (‘partial invasion’) (n=95) 21/30 (70.0) 48/65 (73.9) 0.83 (0.32 to 2.15) 0.696 Rimmed vacuoles (n=257) 77/88 (87.5) 143/169 (84.6) 1.27 (0.60 to 2.72) 0.533 Protein deposits† (n=128) 24/44 (54.6) 53/84 (63.1) 0.70 (0.34 to 1.47) 0.349 Microfilaments‡ (n=81) 9/24 (37.5) 24/57 (42.1) 0.83 (0.31 to 2.20) 0.700 Figures in brackets represent within antibody group percentages. n represents data available for analysis per variable (of a total of 311). p Value is derived from logistic regression.

† (n=128) 24/44 (54.6) 53/84 (63.1) 0.70 (0.34 to 1.47) 0.349 Microfilaments‡ (n=81) 9/24 (37.5) 24/57 (42.1) 0.83 (0.31 to 2.20) 0.700 Figures in brackets represent within antibody group percentages. n represents data available for analysis per variable (of a total of 311). p Value is derived from logistic regression. *Adjusted (for age at disease onset, gender and comorbidities) OR 2.60, 95% CI 1.11 to 6.12, p=0.028. Adjusted (additionally for age at biopsy) OR 2.80, 95% CI 1.17 to 6.66, p=0.020. †Includes amyloid (Congo Red or immunofluorescence), p62 (immunofluorescence) and TDP-43 (immunofluorescence). ‡15–21 nm tubulofilaments identified by electron microscopy. Anti-cN-1A, anticytosolic 5′-nucleotidase 1A; COX, cytochrome oxidase; MHC, major histocompatibility complex.

*Adjusted (for age at disease onset, gender and comorbidities) OR 2.60, 95% CI 1.11 to 6.12, p=0.028. Adjusted (additionally for age at biopsy) OR 2.80, 95% CI 1.17 to 6.66, p=0.020. †Includes amyloid (Congo Red or immunofluorescence), p62 (immunofluorescence) and TDP-43 (immunofluorescence). ‡15–21 nm tubulofilaments identified by electron microscopy. Anti-cN-1A, anticytosolic 5′-nucleotidase 1A; COX, cytochrome oxidase; MHC, major histocompatibility complex. Discussion This multinational exploratory study represents the first of its kind to combine analysis of clinical, histopathological, other serological and mortality data in a large cohort of patients with IBM stratified according to anti-cN-1A antibody status. Our results will guide future confirmatory studies and highlight potential disease mechanisms warranting further evaluation. We found that the anti-cN-1A antibody positive group had a significantly increased mortality risk independent of age, gender, comorbidities and the presence of dysphagia. We also found a smaller proportion with proximal upper limb weakness at disease onset and an excess of COX-deficient fibres on muscle biopsy in the anti-cN-1A antibody positive group. An increased likelihood of having facial weakness and an association between antibody positivity and death from a respiratory cause was also observed, although the numbers assessed here were small. As in other studies, we did not find a relationship between disease duration and the likelihood of identifying anti-cN-1A antibodies.18 19

elihood of having facial weakness and an association between antibody positivity and death from a respiratory cause was also observed, although the numbers assessed here were small. As in other studies, we did not find a relationship between disease duration and the likelihood of identifying anti-cN-1A antibodies.18 19 There are limited reports in the literature comparing the characteristics of patients with IBM with and without anti-cN-1A antibodies, amounting to 258 patients in four separate studies.18 19 24 25 A small proportion of the cases analysed here was included in a previous analysis which did not focus on differences on clinical characteristics according to serotype.22 Some authors identified no significant differences in the characteristics between cohorts, whereas others have suggested that the anti-cN-1A antibody positive group exhibits a more severe phenotype.18 19 Lloyd et al24 identified a lower incidence of rimmed vacuoles on biopsy in those without anti-cN-1A reactivity but with no clinical differences between the studied cohorts, findings that were not replicated here. A very recent study found no differences between 24 cN-1A seropositive and 45 seronegative patients with IBM regarding class II human leukocyte antigen (HLA) alleles and the presence of other antibodies.25

nexplained, but these findings appear to agree with those of Goyal et al18 who also found a more severe respiratory phenotype in the antibody-positive group. The lower frequency of proximal upper limb weakness at presentation in the anti-cN-1A antibody positive compared with antibody-negative group remains unexplained. This study represents the largest cohort of patients with IBM and has only been achieved by an international collaborative effort. Established IBM diagnostic criteria were used to include patients for the analysis, a predefined set of clinical data was retrieved in each patient and all anti-cN-1A testing was performed in one laboratory. However, there remain a number of limitations. The study was retrospective and relied on the identification and recording of clinical characteristics by the treating physicians. In the UK cohort, the recruiting physician (the patient's treating consultant neurologist or rheumatologist) was asked to recall the symptoms that were present at the time of disease onset when completing the pro forma at the time of recruitment, and as such these details may be subject to recall bias. While efforts to minimise missing data were made, data were not complete for all study parameters in all cases, although there was no evidence to suggest that this occurred in a systematic way. Analysis involved pooling of data from different cohorts. There is potential for differences in data collection methodology between cohorts (see online supplementary appendix 1) to reduce the reliability of our findings. However, a comparison of features between UK and non-UK cohorts where pooled data were analysed has revealed largely comparable findings (see online supplementary table S1). Overall, we feel that our pooled analysis has increased statistical power and reduced the likelihood of statistical errors occurring. Objective measurements of muscle strength (eg, dynamometry of the finger flexors) could have improved sensitivity of detection of weakness, but such methods were not available. Also, this study did not perform a reanalysis of muscle biopsy tissue. The cause of death was difficult to establish in some patients in the non-UK cohort, due to missing information in the medical records, and in the UK cohort due to an inability to match some patients to the nationally stored mortality data held by the UK Health and Social Care Information Centre.

muscle biopsy tissue. The cause of death was difficult to establish in some patients in the non-UK cohort, due to missing information in the medical records, and in the UK cohort due to an inability to match some patients to the nationally stored mortality data held by the UK Health and Social Care Information Centre. 10.1136/annrheumdis-2016-210282.supp2supplementary table In the future, anti-cN-1A autoantibody testing and anti-cN-1A autoantibody status could be used in the diagnostic workup of potential IBM cases, and there remains the opportunity to use anti-cN-1A antibody status in the construction of future diagnostic criteria for IBM. However, the results of the current study also suggest that distinct IBM subtypes may be identified according to anti-cN1-A antibody status. Therefore, serum anti-cN-1A testing might also be of use in the stratification of patients with IBM (eg, for clinical trials), rather than purely as a diagnostic biomarker. A large prospective study with a sufficient duration of follow-up might offer potential to further investigate the overall utility of anti-cN-1A antibody testing in the clinical and research settings. Conclusion In this exploratory study, comparison of patients with IBM with and without anti-cN-1A autoantibody reactivity identified differences in their mortality risk, clinical characteristics and histopathological findings. The largest study of its kind has demonstrated that anti-cN-1A antibody testing may, and over and above its diagnostic value, be clinically useful to define distinct IBM subtypes.

anti-cN-1A autoantibody reactivity identified differences in their mortality risk, clinical characteristics and histopathological findings. The largest study of its kind has demonstrated that anti-cN-1A antibody testing may, and over and above its diagnostic value, be clinically useful to define distinct IBM subtypes. The authors thank Hazel Platt (Centre for Integrated Genomic Medical Research, University of Manchester) and Paul New (Salford Royal NHS Foundation Trust). The authors thank all of the patients and their families who contributed to this study. Twitter: Follow Hector Chinoy at @drhectorchinoy Contributors: Initiation and design of this research: Non-UK––CGJS, BGMvE and GJMP; UK––RGC, HC and JAL. Clinical data collection and processing: AR, JBL, MTJP, KM and KRG. Facilitation of clinical data collection, establishment of the cohorts, contribution of cases: UAB, OB, IEL, SS, HC, RGC, JALM, MGH, PMM, MJP, BRFL, CB, DH-J and MER. Establishment of the antibody detection method and laboratory analysis: MKH, BGMvE and GJMP. Statistical analysis: JBL and SRP. Draft manuscript preparation: AR and JBL. All authors were involved with the review of the manuscript and approved the final version.

SS, HC, RGC, JALM, MGH, PMM, MJP, BRFL, CB, DH-J and MER. Establishment of the antibody detection method and laboratory analysis: MKH, BGMvE and GJMP. Statistical analysis: JBL and SRP. Draft manuscript preparation: AR and JBL. All authors were involved with the review of the manuscript and approved the final version. Funding: This study was supported in part by: the Prinses Beatrix Spierfonds (W.OR 12–15); Myositis UK; Arthritis Research UK (18474); Association Française Contre Les Myopathies; The European Union Sixth Framework Programme (project AutoCure; LSH-018661); European Science Foundation in the framework of the Research Networking Programme European Myositis Network; The Swedish Research Council. PMM was supported by a National Institute for Health Research (NIHR) Rare Diseases Translational Research Collaboration Fellowship. This report includes independent research supported by the NIHR Biomedical Research Unit cFunding Scheme. The views expressed in this publication are those of the authors and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health. The UKMYONET project is supported by the Manchester Academic Health Sciences Centre (MAHSC). Competing interests: GJMP and BGMvE are inventors of a patent (EP20120740236) licensed to Euroimmun, and GJMP receives financial support from Euroimmun for his research programme. Leiden University Medical Center receives financial compensation from Novartis for the BYM338 clinical trials in IBM in which UAB is the principal investigator.

GJMP and BGMvE are inventors of a patent (EP20120740236) licensed to Euroimmun, and GJMP receives financial support from Euroimmun for his research programme. Leiden University Medical Center receives financial compensation from Novartis for the BYM338 clinical trials in IBM in which UAB is the principal investigator. Ethics approval: Local ethics committee of each of the participating centres. Provenance and peer review: Not commissioned; externally peer reviewed.

Introduction Rheumatoid arthritis (RA) is a chronic, erosive inflammatory arthritis thought to affect approximately 1% of the UK adult population.1 Recently it has been shown that aggressive early treatment can prevent much of the long term damage associated with the RA.2 The 1987 American College of Rheumatology (ACR) classification criteria, widely used as entry criteria to clinical trials and observational studies, were developed in a cohort of patients with established, longstanding disease3 and are known to perform poorly in patients presenting with recent onset inflammatory arthritis,4 who may benefit most from early intensive treatment. The 2010 ACR/European League Against Rheumatism (EULAR) classification criteria for RA5 aim to have improved sensitivity compared with the 1987 criteria. In particular, the 2010 criteria were designed to better identify RA in patients presenting soon after the development of signs and symptoms of the disease.

reatment. The 2010 ACR/European League Against Rheumatism (EULAR) classification criteria for RA5 aim to have improved sensitivity compared with the 1987 criteria. In particular, the 2010 criteria were designed to better identify RA in patients presenting soon after the development of signs and symptoms of the disease. The developers of the new criteria describe them as ‘defining a new paradigm of RA’. If this is the case, previous estimates of disease incidence and prevalence may no longer be accurate. Measuring prevalence in a relapsing remitting disease, or disease in which signs and symptoms resolve with treatment such as RA, presents additional challenges, as patients on treatment may be completely asymptomatic and have no signs of disease; therefore may be missed by population surveys. Measuring incidence requires an inception cohort with complete capture of all new cases of disease within a stable, defined background population. To date, no studies have estimated incidence of RA using the 2010 criteria. The objectives of this study were (i) to estimate age and sex-specific incidence of RA using the 2010 criteria in Norfolk, UK and (ii) to compare these incidence rates (IR) with those using the previous criteria set, at initial presentation and cumulatively over 5 years.

timated incidence of RA using the 2010 criteria. The objectives of this study were (i) to estimate age and sex-specific incidence of RA using the 2010 criteria in Norfolk, UK and (ii) to compare these incidence rates (IR) with those using the previous criteria set, at initial presentation and cumulatively over 5 years. Patients and methods Setting The Norfolk Arthritis register (NOAR) is a primary care inception cohort of patients aged ≥16 years presenting with ≥2 swollen joints for at least 4 weeks to either primary or secondary care within the former Norwich Health Authority. A detailed description of NOAR is available in previous publications.6 Briefly, patients undergo standardised assessment by a research nurse including details of symptom onset, 51 swollen and tender joint counts and examination for nodules, as well as consent to medical records review. Assessments (including joint counts and examination for nodules) are repeated annually for the first 3 years and at 5 years. Blood is taken at baseline and after 5 years for C reactive protein (CRP) and rheumatoid factor (RF) (latex test) and the remaining sera stored frozen; this was subsequently used to measure anti-citrullinated protein antibody status (ACPA) (Axis-Shield Diastat Anti-CCP kit, Dundee, Scotland). Patients included in this current analysis were all those who had symptom onset of joint pain or swelling between January and December 1990, and were notified to NOAR within 5 years of symptom onset. This time period was selected as we can only be reasonably sure that all new cases of inflammatory oligo- and polyarthritis (IP) presenting to primary care were identified in 1990–1994 and we have previously reported on the incidence using the 1987 criteria for patients with a symptom onset in 1990.6 7 It should be noted that a group of patients from NOAR were used in the development of the 2010 criteria.5 However, those patients were recruited since 2000 and none of the patients included in the present study formed part of the criteria development cohort.

e 1987 criteria for patients with a symptom onset in 1990.6 7 It should be noted that a group of patients from NOAR were used in the development of the 2010 criteria.5 However, those patients were recruited since 2000 and none of the patients included in the present study formed part of the criteria development cohort. Application of classification criteria For the 2010 criteria, joint counts and duration of symptoms were obtained from the nurse assessments and weighted scores assigned as detailed in the criteria (figure 1). In order to obtain as complete a dataset as possible, the medical records of those patients included in this analysis who did not provide a blood sample were searched to identify acute phase reactant (CRP or erythrocyte sedimentation rate (ESR)) and RF results taken near to the time of symptom onset. CRP and ESR were considered elevated if >5 mg/l and >10 mm/h respectively, according to local laboratory reference ranges. The 2010 criteria divide values of RF and ACPA into the following groups for scoring: negative: defined as ≤ upper limit of normal (ULN) for the laboratory and assay; low positive: >ULN but ≤3 times ULN; and high positive: >3 times ULN. In this study these cut offs were 40 and 120 International Units (IU) respectively for RF; for ACPA they were 5 and 15 IU respectively. Figure 1 Classification criteria for RA.

Application of classification criteria For the 2010 criteria, joint counts and duration of symptoms were obtained from the nurse assessments and weighted scores assigned as detailed in the criteria (figure 1). In order to obtain as complete a dataset as possible, the medical records of those patients included in this analysis who did not provide a blood sample were searched to identify acute phase reactant (CRP or erythrocyte sedimentation rate (ESR)) and RF results taken near to the time of symptom onset. CRP and ESR were considered elevated if >5 mg/l and >10 mm/h respectively, according to local laboratory reference ranges. The 2010 criteria divide values of RF and ACPA into the following groups for scoring: negative: defined as ≤ upper limit of normal (ULN) for the laboratory and assay; low positive: >ULN but ≤3 times ULN; and high positive: >3 times ULN. In this study these cut offs were 40 and 120 International Units (IU) respectively for RF; for ACPA they were 5 and 15 IU respectively. Figure 1 Classification criteria for RA. The 1987 criteria exist in two formats: list (figure 1) and tree.3 The list format includes radiographic erosions, which can be substituted with clinical data in the tree format. At baseline assessment, radiographs were not taken, thus the tree format was applied; at 5 years all patients underwent radiographic examination of hands and feet and patients were said to have met the 1987 criteria if they satisfied the tree or list format.

ich can be substituted with clinical data in the tree format. At baseline assessment, radiographs were not taken, thus the tree format was applied; at 5 years all patients underwent radiographic examination of hands and feet and patients were said to have met the 1987 criteria if they satisfied the tree or list format. For both criteria sets, if data were missing on any variables, total scores were calculated with the missing variable value taken as zero, and patients said to have met the criteria if they reached the defined cut-offs: ≥6/10 for the 2010 criteria and ≥4/7 for the 1987 criteria. Incidence rates The denominator population was provided by the former Norfolk Health Service Authority.6 Both criteria sets were applied to calculate age and sex-specific IRs at the baseline assessment. Using the 2010 criteria, 5 year cumulative incidence was estimated by taking the highest score for each parameter (joint count, serology, acute phase reactants and symptom duration) at any assessment over the 5 years follow up period. For the 1987 criteria, 5 years cumulative incidence was estimated in the following manner: if a patient satisfied a particular criterion at an individual assessment, it was then carried forward to all future assessments. CIs around the IRs were calculated using the Poisson distribution. NOAR is approved by the Norwich Local Research Ethics Committee and all patients gave written consent. All data were analysed using STATA V.10 software package (Stata, College Station, Texas, USA).

Incidence rates The denominator population was provided by the former Norfolk Health Service Authority.6 Both criteria sets were applied to calculate age and sex-specific IRs at the baseline assessment. Using the 2010 criteria, 5 year cumulative incidence was estimated by taking the highest score for each parameter (joint count, serology, acute phase reactants and symptom duration) at any assessment over the 5 years follow up period. For the 1987 criteria, 5 years cumulative incidence was estimated in the following manner: if a patient satisfied a particular criterion at an individual assessment, it was then carried forward to all future assessments. CIs around the IRs were calculated using the Poisson distribution. NOAR is approved by the Norwich Local Research Ethics Committee and all patients gave written consent. All data were analysed using STATA V.10 software package (Stata, College Station, Texas, USA). Results A total of 283 patients were registered with NOAR who had symptom onset in 1990. Of these, 23 patients were diagnosed with other rheumatological disorders by their treating rheumatologist and were therefore excluded. Table 1 shows baseline demographic data of the cohort and the proportion of missing data. Thirty-six patients declined to provide a blood sample at baseline. Despite medical record review, 31 of these patients had no result for acute phase reactants and 12 patients had no autoantibody results at baseline. five patients continued to decline blood sampling throughout follow up and therefore had no results available for the acute phase reactant or either autoantibody parameters. After 5 years, 25 patients had died, 22 patients declined follow up after baseline assessment and 16 patients were lost to follow up, thus a total of 197 patients remained under active follow up. For the cumulative analysis, patients who did not complete 5 years follow up were classified cumulatively up to their last assessment.

ars, 25 patients had died, 22 patients declined follow up after baseline assessment and 16 patients were lost to follow up, thus a total of 197 patients remained under active follow up. For the cumulative analysis, patients who did not complete 5 years follow up were classified cumulatively up to their last assessment. Table 1 Baseline demographics and criteria variables Demographic Frequency Missing n (%) Age at symptom onset (mean (SD)) 54 (16.2) 0 Female (n (%)) 173 (69) 0 Symptom duration in weeks (median (IQR)) 29.6 (4.3–71.9) 0 RF low positive (n (%)) 25 (11) 28 (11)† High positive (n (%)) 47 (20) ACPA low positive (n (%)) 6 (3) 77 (30)† High positive (n (%)) 38 (20) Joint involvement* (n (%)) 0 1 large joint 9 (3) 2–10 large joints 9 (3) 1–3 small joints 41 (16) 4–10 small joints 52 (20) >10 joints 149 (57) Acute phase reactant positive (n (%)) 120 (52) 27 (10) CRP 116 (48) ESR 9 (64) CRP (mean (std dev)) 19 (35) ESR (mean (std dev)) 30 (34) Morning stiffness ≥60 min (n (%)) 172 (66) 0 Arthritis of ≥3 joints areas (n (%)) 172 (66) 0 Arthritis of hand joints (n (%)) 215 (83) 0 Symmetric arthritis (n (%)) 183 (70) 0 Rheumatoid nodules (n (%)) 19 (7) 0 *Large joints were defined as shoulders, elbows, hips, knees and ankles. Small joints are defined as metocarpophalangeal joints, proximal interphalageal joints, second through fifth metatarsophalangeal joints, thumb interphalangeal joints and wrists. Distal interphalangeal joints, first carpometacarpal joints and first metatarsophalangeal joints were excluded as per the 2012 criteria.5

les. Small joints are defined as metocarpophalangeal joints, proximal interphalageal joints, second through fifth metatarsophalangeal joints, thumb interphalangeal joints and wrists. Distal interphalangeal joints, first carpometacarpal joints and first metatarsophalangeal joints were excluded as per the 2012 criteria.5 †Missing data quoted are for individual autoantibodies. 8 (2%) patients had no results for ACPA or RF. ACPA, anti-citrullinated protein antibody, CRP, C reactive protein; ESR, erythrocyte sedimentation rate; RF, rheumatoid factor. The overall IR when applying the 2010 criteria at baseline was 40/100 000; 54/100 000 for women and 25/100 000 for men. These rates were higher than when applying the 1987 criteria at baseline (32/100 000 overall, 45/100 000 for women and 18/100 000 for men). Age and sex-specific IRs using the 2010 classification criteria at baseline showed marked similarities to cumulative IRs applying the 1987 criteria up to 5 years (table 2). In women the peak age of incidence was younger than in men for both criteria sets, with highest rates between ages 45–74. In men incidence appeared to increase with age with highest rates in men over 65 years old. Table 2 Age and sex specific incidence rates (IR/100 000 population)

The overall IR when applying the 2010 criteria at baseline was 40/100 000; 54/100 000 for women and 25/100 000 for men. These rates were higher than when applying the 1987 criteria at baseline (32/100 000 overall, 45/100 000 for women and 18/100 000 for men). Age and sex-specific IRs using the 2010 classification criteria at baseline showed marked similarities to cumulative IRs applying the 1987 criteria up to 5 years (table 2). In women the peak age of incidence was younger than in men for both criteria sets, with highest rates between ages 45–74. In men incidence appeared to increase with age with highest rates in men over 65 years old. Table 2 Age and sex specific incidence rates (IR/100 000 population) Female patients Male patients Age band No. of patients with  inflammatory oligo- and polyarthritis 2010 criteria at baseline 1987 criteria cumulative to 5 years follow up 2010 criteria at baseline 1987 crtieria cumulative to 5 years follow up IR (95% CI) IR (95% CI) IR (95% CI) IR (95% CI) 15–24 17 18.6 (6.8 to 40.6) 15.5 (5.0 to 36.3) 0 (0 to 11.1) 6 (0.7 to 21.7) 25–34 23 20.3 (8.2 to 41.8) 31.9 (15.9 to 57.0) 5.6 (0.7 to 20.3) 8.4 (1.7 to 24.6) 35–44 34 56.6 (34.1 to 88.4) 56.6 (34.1 to 88.4) 12.1 (3.3 to 30.9) 12.1 (3.3 to 30.9) 45–54 53 85.6 (56.4 to 124.6) 98.3 (66.8 to 139.5) 34.5 (17.2 to 61.7) 31.4 (15.0 to 57.7) 55–64 58 91.8 (59.4 to 135.5) 91.8 (59.4 to 135.5) 42.1 (21.0 to 75.3) 42.1 (21.0 to 75.3) 65–74 53 87.1 (55.8 to 129.6) 94.4 (61.7 to 138.3) 58.3 (31.9 to 97.8) 66.6 (38.1 to 108.2) 75+ 22 26.1 (10.5 to 53.7) 29.8 (12.9 to 58.7) 44.3 (17.8 to 91.3) 57.0 (26.1 to 108.1) Total 260 53.9 (44.5 to 64.7) 58.5 (48.7 to 69.8) 24.5 (18.1 to 32.4) 27.5 (20.7 to 35.8) Applying the 2010 criteria cumulatively over 5 years follow up gave an estimated IR of 48/100 000; for the 1987 criteria this was 44/100 000. A further 34 patients satisfied the 2010 criteria when applied cumulatively over 5 years; applying the 1987 criteria cumulatively for 5 years classified 49 additional patients as RA. Results applying both criteria sets cumulatively converged after approximately 3 years follow up (figure 2 and table 3); nevertheless there remained some discordance between the criteria (table 4). After 5 years follow up, 50 (19%) patients satisfied neither criteria set, cumulatively or cross-sectionally. All five patients who had no blood results throughout the follow up period met at least one criteria set at baseline.

2 and table 3); nevertheless there remained some discordance between the criteria (table 4). After 5 years follow up, 50 (19%) patients satisfied neither criteria set, cumulatively or cross-sectionally. All five patients who had no blood results throughout the follow up period met at least one criteria set at baseline. Figure 2 Cumulative incidence of RA in patients satisfying both criteria sets after 5 years (n=170). Table 3 Patients satisfying rheumatoid arthritis criteria cumulatively over time Satisfy 1987 criteria cumulatively Satisfy 2010 criteria cumulatively Satisfy both criteria sets cumulatively Satisfy 1987 criteria cumulatively if satisfy both by 5 years Satisfy 2010 criteria cumulatively if satisfy both by 5 years Baseline 131/260 166/260 119/260 125/170 145/170 1 year 163/260 186/260 150/260 154/170 161/170 2 years 174/260 193/260 159/260 164/170 164/170 3 years 177/260 197/260 165/260 167/170 168/170 5 years 180/260 200/260 170/260 170/170 170/170 Table 4 Number of patients satisfying each criteria set after 5 years follow up

Baseline 131/260 166/260 119/260 125/170 145/170 1 year 163/260 186/260 150/260 154/170 161/170 2 years 174/260 193/260 159/260 164/170 164/170 3 years 177/260 197/260 165/260 167/170 168/170 5 years 180/260 200/260 170/260 170/170 170/170 Table 4 Number of patients satisfying each criteria set after 5 years follow up Patients satisfying 1987 criteria cumulatively n (%) Patients not satisfying 1987 criteria cumulatively n (%) Total Patients satisfying 2010 criteria cumulatively 170 (65) 30 (12) 200 Patients not satisfying 2010 criteria cumulatively 10 (4) 50 (19) 60 Total 180 80 260 Discussion The 2010 ACR/EULAR classification criteria for RA have provided a new definition for the disease entity ‘RA’. This is the first study to estimate the incidence of RA using the 2010 criteria. We have shown, in a cohort of patients with early IP, that the incidence of RA according to the 2010 criteria is higher at baseline assessment than the incidence of RA according to the 1987 criteria. The 2010 criteria appear to identify at baseline similar rates of RA as the 1987 criteria identify cumulatively over 5 years. We have shown previously that cumulative application of the 1987 criteria over 5 years increases incidence estimates by up to 93%.7 However, this requires long term follow up of all patients presenting with undifferentiated inflammatory arthritis. Today, with improved treatment strategies, some patients who are given a clinical diagnosis of RA by their treating physicians may never satisfy them. Our results show that application of the 2010 criteria in early disease may therefore negate the need for such long term follow up to confirm classification, and may in part address concerns that some patients, whose disease is suppressed by appropriate treatment, may be inappropriately classified as not having RA.

em. Our results show that application of the 2010 criteria in early disease may therefore negate the need for such long term follow up to confirm classification, and may in part address concerns that some patients, whose disease is suppressed by appropriate treatment, may be inappropriately classified as not having RA. Incidence of RA has been estimated in a variety of populations, with considerable variation in the results.8 In the USA, the incidence of RA in Olmsted County, Minnesota has been tracked since 1955 using the Rochester Epidemiology Project medical record linkage system.9 They, and others, have shown a decline of the incidence of RA in the second half of the 20th century.10 11 Interestingly, this trend may have slowed or even reversed in the past 10 years and their latest published IR was 41/100 000 population,12 which is higher than our estimate using the 1987 criteria. It will be interesting to assess whether these long term trends in incidence will continue given the re-definition of disease in the 2010 criteria. Another recent estimation of RA incidence based on the 1987 criteria was undertaken in Spain, where cases were identified from primary care during the establishment of a nationwide programme of early arthritis units.13 They estimated an IR of 8/100 000, significantly lower than ours applying the same criteria set. This may be due to the reported lower incidence of RA in Southern Europe compared to Northern Europe (8). Where inception cohorts are not available, other methods have been used to estimate incidence. In the UK, a combination of diagnostic codes and disease modifying drug prescriptions recorded within the General Practice Research Database (GPRD)14 were used to identify new cases; in Finland insurance claim forms have been used.11 In both cases, data were collected retrospectively, and, in particular with the GPRD, the definition of incident RA is vulnerable to misclassification.

g drug prescriptions recorded within the General Practice Research Database (GPRD)14 were used to identify new cases; in Finland insurance claim forms have been used.11 In both cases, data were collected retrospectively, and, in particular with the GPRD, the definition of incident RA is vulnerable to misclassification. Studies assessing the 2010 criteria to date have mainly focused on their sensitivity and specificity to predict surrogates of an RA diagnosis (for which there is no gold standard) such as initiation of disease modifying anti-rheumatic drug therapy,15 16 physician opinion17 and absence of drug free remission.18 These studies have shown that the 2010 criteria classify more patients as RA earlier in the disease course compared to the 1987 criteria, with a general improvement in sensitivity at the cost of specificity. Our findings support this hypothesis, that the 2010 criteria are better at classifying early RA; in addition we have demonstrated that this earlier classification identifies similar rates of disease. However, the lack of gold standard is also a limitation in our study, as without this it is not possible to measure true incidence.

s support this hypothesis, that the 2010 criteria are better at classifying early RA; in addition we have demonstrated that this earlier classification identifies similar rates of disease. However, the lack of gold standard is also a limitation in our study, as without this it is not possible to measure true incidence. This study highlights certain subgroups of patients who may be of particular interest for further investigation. The first is those patients who only met one criteria set over the 5 years follow up period. The characteristics of these patients reflect the criteria themselves: patients satisfying only the 1987 criteria were more likely to have prolonged morning joint stiffness, they also had more symmetrical and more hand joint involvement. By contrast, patients satisfying only the 2010 criteria had greater number of joints involved at each assessment (reflecting the inclusion of tender as well as swollen joints). The most notable difference is seen in the frequency of autoantibodies. The majority of patients in our cohort who never satisfied the 2010 criteria but did satisfy the 1987 criteria were autoantibody negative; this difference was most marked at baseline assessment. This pattern has been noted in other cohorts,19 20 and it has been postulated that the two criteria sets may be describing different clinical entities.21 However, the striking similarity in IRs over time in our patients argues against this. It may be that the two criteria sets represent different aspects of the same disease construct; the 2010 criteria describe an acute inflammatory arthritis, whereas the 1987 criteria describe the long term damage that occurs as a consequence. Another subgroup of interest is those patients who never satisfy either criteria set. For patients remaining in this study 5 years after symptom onset, this group comprised 50 patients (19%), which is a substantial proportion. There were missing data in our cohort, particularly relating to serological markers, and this may have led to some patients being misclassified as non-RA. However, none of the patients who could not be classified by either criteria set over 5 years had missing data on all serological variables at all time points. Investigating the long term outcomes of the patients who satisfy neither criteria set will be important to assess the validity of the 2010 criteria.

as non-RA. However, none of the patients who could not be classified by either criteria set over 5 years had missing data on all serological variables at all time points. Investigating the long term outcomes of the patients who satisfy neither criteria set will be important to assess the validity of the 2010 criteria. In the publication describing the development of the 2010 criteria,5 and in subsequent editorials22 the authors suggest they may be used in clinical practice to allow access to disease modifying anti-rheumatic drug or biologic therapy. Although we have shown that these criteria classify more patients early in the disease course than the previous criteria set (which were never used in this context), our results suggest they are not sufficiently sensitive for this purpose. In particular, the fact that some patients fulfil the previous criteria set without fulfilling the new criteria, even after 5 years follow up, indicate caution should be taken considering this application. Further work is needed to elucidate the long term outcomes of patients not fulfilling the new criteria to answer this question. If these are universally good for all patients not fulfilling the criteria, their use as a gateway to treatment may be appropriate. There are a number of strengths in the present study due to unique features of NOAR in the UK: Norfolk has a stable population with little migration, there is a balanced mix of rural and urban populations (thus is representative of both) and a central referral system for musculoskeletal patients to a single secondary care provider, Norwich and Norfolk University Hospital. Significant efforts were made to ensure all patients with IP newly presenting to primary care were reported to NOAR when it was first established in 1989, with visits to GP practices, advertising and a small incentive. We therefore selected the year 1990 to estimate incidence in this study as the year with near complete capture of all patients presenting with early IP. Nevertheless, the IRs reported here are likely to be an underestimate for a number of reasons. Some patients only had RF or ACPA measured; a high positive result in the other autoantibody may have increased the number of patients classified as RA. However, the 2010 criteria only require testing of either RF or ACPA, therefore our data represent a valid estimate of incidence.

nderestimate for a number of reasons. Some patients only had RF or ACPA measured; a high positive result in the other autoantibody may have increased the number of patients classified as RA. However, the 2010 criteria only require testing of either RF or ACPA, therefore our data represent a valid estimate of incidence. NOAR was established when the 1987 criteria were the standard for classification, and elements of its design may make classification by the 1987 criteria easier than by the 2010 criteria, potentially reducing the IRs using the 2010 criteria. This highlights difficulties that occur when applying criteria retrospectively to an historic cohort. In addition, there may have been cases which were not captured, including patients who did not seek healthcare advice at the time of symptom onset. To allow for this delay and to obtain as true an estimate of incidence in that year as possible, the age and sex-specific IRs reported at baseline included patients who had presented to NOAR up to 5 years after symptom onset. However, this meant that a small number of patients had been symptomatic of their disease for a number of years at the time of initial assessment. If IRs were calculated based on initial assessments of only those patients who presented within 2 years of symptom onset, the overall IR using the 2010 criteria was 35/100 000 population; for 1987 criteria it was 27/100 000 at baseline presentation but increased to 36/100 000 cumulatively 5 years after symptom onset.

. If IRs were calculated based on initial assessments of only those patients who presented within 2 years of symptom onset, the overall IR using the 2010 criteria was 35/100 000 population; for 1987 criteria it was 27/100 000 at baseline presentation but increased to 36/100 000 cumulatively 5 years after symptom onset. A further limitation relates to erosive disease. The 2010 criteria include an amendment which states that any patient with radiological evidence of erosion typical of RA should automatically be classified as having RA, without the need to fulfil any other aspect of the criteria. As radiographs were not performed at baseline in this cohort, and because there is no clear definition of ‘typical RA erosion’, this was not applied in the present analysis. x-Rays were performed on all patients after 5 years follow up; if the presence of any erosion (although not specifically a ‘typical RA’ erosion) was applied at that point, four further patients (three women and one man) could be classified as having RA according to the 2010 criteria. In conclusion, we have reported the first IR estimates of RA applying the 2010 ACR/EULAR classification criteria. We have shown that the incidence of RA, as estimated by the 2010 classification criteria at baseline, is very similar to the estimates using the 1987 criteria cumulatively over 5 years. These results indicate that the 2010 criteria may identify RA patients earlier in the disease course and will be important in order to plan timely, cost-effective and efficacious management of patients presenting with inflammatory arthritis.

ry similar to the estimates using the 1987 criteria cumulatively over 5 years. These results indicate that the 2010 criteria may identify RA patients earlier in the disease course and will be important in order to plan timely, cost-effective and efficacious management of patients presenting with inflammatory arthritis. The authors gratefully acknowledge the support of clinical staff at the Norfolk and Norwich University Hospital, local primary care physicians and all of the Norfolk Arthritis Register research nurses. Data management by the team in Manchester is also appreciated. Contributors: All authors were involved in drafting the article or critically reviewing and revising it, and all authors approved the final version to be published. Study concept and design: JHH, KLH, DPMS; acquisition of data: JRC, TM; analysis and interpretation of the data: JHH, SMMV, KLH, DPMS. Funding: NOAR is funded by Arthritis Research UK (grant reference 17552). JHH is funded by an Arthritis Research UK Clinical fellowship (grant reference 19743). The authors have received no other financial support or other benefits from commercial sources for the work reported in the manuscript. Competing interests: None. Ethics approval: Norwich Local Research Ethics Committee. Provenance and peer review: Not commissioned; externally peer reviewed.