E.M. Hensor

Effect of bisphosphonate use in patients with symptomatic and radiographic knee osteoarthritis: data from the Osteoarthritis Initiative

Objectives Bisphosphonates have some reported beneficial effects in treating osteoarthritis (OA). This study examined the effects of bisphosphonate use on symptoms and structural progression of knee OA in participants from the NIH Osteoarthritis Initiative cohort. Methods People with typical OA trial entry criteria (KL2/3, minimum joint space width 2.5–5.0 mm and pain ≥4 on a numeric rating scale) were classified as bisphosphonate users (≥3 of the 5 years; n=55) or non-users (no use in the preceding 5 years or during follow-up; n=268). Annual data over 4 years were analysed using linear mixed modelling and generalised estimating equations. Results Bisphosphonate compliance was 85% at year 1, reducing to 76% by year 4. Numeric rating scale pain scores were significantly reduced among bisphosphonate users at years 2 and 3 (year 3, −0.9 vs −2.2, p=0.004), though not year 4, after adjustment for baseline pain and analgesic use. Differences in Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain and disability scores did not reach statistical significance at any time point. There was a trend to less joint space narrowing in bisphosphonate users over time (year 4, 0.51 vs 0.29 mm; p=0.06). Conclusions Significant reduction in numeric rating scale pain was observed in the first 3 years with bisphosphonate use; diminution of effects by year 4 may reflect reduced compliance. Differences in results obtained using numeric rating scale and WOMAC may reflect different constructs measured by these tools. The beneficial trend on structural progression should be considered in terms of the sample size.

Abnormal T cell differentiation persists in patients with rheumatoid arthritis in clinical remission and predicts relapse

Objectives: An abnormal CD4+ T cell subset related to inflammation exposure (inflammation-related cells, IRC) has been identified in rheumatoid arthritis (RA). Patients with inflammatory and non-inflammatory diseases were used to examine the relationship between inflammation and this T cell subset in vivo. Methods: Blood was collected from healthy controls and patients with RA (active disease or in clinical remission), Crohn’s disease and osteoarthritis. IRC and chemokine receptors were quantified by flow cytometry. Thymic activity and apoptotic factors were measured by real-time polymerase chain reaction. Circulating cytokines were measured by enzyme-linked immunosorbent assay. CXCR4 and SDF1 in synovial biopsies were measured using immunohistochemistry. Results: IRC were identified in patients with RA (p<0.0001) and Crohn’s disease (p = 0.005), but not in those with osteoarthritis. In RA in remission, IRC persisted (p<0.001). In remission, hyperproliferation of IRC was lost, chemokine receptor expression was significantly lowered (p<0.007), Bax expression dropped significantly (p<0.001) and was inversely correlated with IRC (rho = −0.755, p = 0.03). High IRC frequency in remission was associated with relapse within 18 months (OR = 6.4, p<0.001) and a regression model predicted 72% of relapse. Conclusions: These results suggest a model in which, despite the lack of systemic inflammation, IRC persist in remission, indicating that IRC are an acquired feature of RA. They have, however, lost their hyper-responsiveness, acquired a potential for survival, and no longer express chemokine receptors. IRC persistence in remission confirms their important role in chronic inflammation as circulating precursors of pathogenic cells. This was further demonstrated by much higher incidence of relapse in patients with high IRC frequency in remission.

A novel two-score system for interferon status segregates autoimmune diseases and correlates with clinical features

Measurement of type I interferon (IFN-I) has potential to diagnose and stratify autoimmune diseases, but existing results have been inconsistent. Interferon-stimulated-gene (ISG) based methods may be affected by the modularity of the ISG transcriptome, cell-specific expression, response to IFN-subtypes and bimodality of expression. We developed and clinically validated a 2-score system (IFN-Score-A and -B) using Factor Analysis of 31 ISGs measured by TaqMan selected from 3-IFN-annotated modules. We evaluated these scores using in-vitro IFN stimulation as well as in sorted cells then clinically validated in a cohort of 328 autoimmune disease patients and healthy controls. ISGs varied in response to IFN-subtypes and both scores varied between cell subsets. IFN-Score-A differentiated Systemic Lupus Erythematosus (SLE) from both Rheumatoid Arthritis (RA) and Healthy Controls (HC) (both p < 0.001), while IFN-Score-B differentiated SLE and RA from HC (both p < 0.001). In SLE, both scores were associated with cutaneous and hematological (all p < 0.05) but not musculoskeletal disease activity. Comparing with bimodal (IFN-high/low) classification, significant differences in IFN-scores were found between diagnostic groups within the IFN-high group. Our continuous 2-score system is more clinically relevant than a simple bimodal classification of IFN status. This system should allow improvement in diagnosis, stratification, and therapy in IFN-mediated autoimmunity.

A9.06 Analysis of cell-specific interferon response in systemic lupus erythematosus using a novel flow cytometric assay

Background and objectives Type I interferons (IFN-I) have diverse effects on immune cell populations in SLE, Measuring IFN-I using whole blood interferon-stimulated gene (ISG) expression does not completely explain clinical features of SLE. Objective: develop a cell-specific assay using a surface protein encoded by an ISG (BST2). This would allow convenient analysis of IFN response in individual populations to improve immunophenotyping of SLE patients. Materials and methods PBMCs from 133 SLE patientsand 19 healthy controls (HC) were analysed by flow cytometry for cell surface BST2 protein on each immune cell subset. Cells were FACS-sorted into naïve and memory B-cells, plasmablasts, CD3+ T-cells, NK-cells and monocytes in 12 SLE patients and 16 healthy controls. Expression of BST2, as well as 32 other ISGs, were measured using qPCR. Results Analysis of sorted cells confirmed that surface BST2 is a valid cell-specific IFN assay. BST2 expression correlated with BST2 surface protein within each immune subset: naïve B-cells (r = 0.63, p = 0.009); memory B-cells (r = 0.78, p < 0.001); plasmablasts (r = 0.58, p = 0.018);NK cells (0.63, p = 0.008);T-cells (r = 0.61, p = 0.012); monocytes (r = 0.47, p = 0.064). We next used surface BST2 to compare IFN activity of each subset with clinical features in 133 patients. A significant correlation between the PBMC 33-gene IFN score and surface BST2 for each cell subset (all p < 0.001) confirmed validity of BST2 biomarker in this larger population as a measure of overall IFN status. BST2 was significantly higher in SLE than HC on naïve and memory B-cells (p = 0.004, p = 0.003), plasmablasts (p = 0.047), T cells (p = 0.043), but not different on monocytes (p = 0.406). Association of disease activity (total BILAG) with BST2 on naïve and memory B-cells (Tau-a = 0.23 and 0.22 respectively) was substantive and approximately twice as strong as monocytes and T-cells (Tau-a = 0.12 and 0.14). A similar pattern was seen for anti-dsDNA titre, with no association with monocyte BST-2 (Tau-a = 0.07) but a substantive association for memory B cell BST-2 (Tau-a = 0.18). Conclusion IFN-I response differs in cell subsets. This can be measured in a fast, cost-effective, convenient assay using flow cytometric analysis of surface BST2. Our results show that IFN activity measured on B cells is more clinically relevant than on other cell populations.

OP0297 Three-Dimensional Magnetic Resonance Imaging Knee Bone Shape Predicts Total Knee Replacement: Data from the Osteoarthritis Initiative

Background MRI provides more accurate image biomarkers of structural progression than conventional radiography. Active appearance modelling (AAM) enables accurate, 3D quantification of MRIs. Changes in 3D subchondral bone shape are integral to structural progression of knee osteoarthritis (OA) and are predictive of incident radiographic knee OA. However, the association of 3D subchondral bone shape with total knee replacement (TKR) is unknown. Objectives To determine the relationship between scalar 3D bone shape and TKR. Methods This is a nested case-control analysis, within the osteoarthritis initiative (OAI) cohort. Case knees that underwent TKR were matched 1:1 with controls that “survived” the 6 years of follow up, using stratification (propensity) score matching based upon baseline age, gender, BMI category (<24.9, 25-34.9, >35), ipsilateral knee pain severity numeric rating scale, knee side and recruiting centre. Active appearance modelling of the femur, tibia and patella and linear discriminant analyses identified vectors that were best at classifying knees as having OA vs. no OA, scaled such that -1 and +1 represented the mean non-OA and mean OA shapes, respectively. Vector values were compared within matched case-control pairs using paired t-tests and the odds of TKR associated with baseline 3D bone shape were obtained using conditional logistic regression. Results Case-control pairs (n=311) of knees were well matched in terms of propensity scores. In cases of TKR the mean baseline 3D bone shape vector was more positive relative to controls, indicating more advanced OA, for the femur [mean 0.98 vs. -0.16; difference (95% CI) 1.14 (0.92,1.37)], tibia [mean 0.86 vs. -0.05; difference (95% CI) 0.90 (0.69,1.12)] and patella [mean 0.95 vs. -0.07; difference (95% CI) 1.02 (0.74,1.31)]. Unadjusted conditional odds ratios (95% CI) for the femur, tibia and patella revealed increased odds of TKR with increasingly positive 3D bone shape vector values (increasing OA structural severity) (Table 1). After adjusting for Kellgren Lawrence (KL) grade in a multivariable analysis, the femur 3D shape vector was independently associated with TKR [OR 1.21 (1.01, 1.45)] with a slight improvement in model fit (AIC) compared with KL grade.Table 1. Associations between 3D bone shape vectors or KL grade with TKR Imaging variable Univariable (unadjusted) Multivariable* OR 95% CI p value AIC OR 95% CI AIC Femur vector 1.79 1.54, 2.09 <0.001 309.51 1.21 1.01, 1.45 228.33 Tibia vector 1.64 1.42, 1.90 <0.001 334.86 1.02 0.84, 1.24 232.66 Patella vector 1.40 1.26, 1.56 <0.001 346.33 1.09 0.95, 1.26 231.24 KL grade (ref=KL zero)  1 2.42 0.75, 7.82 0.14  2 9.08 3.36,24.49 <0.001  3 31.55 11.23,88.63 <0.001  4 72.77 22.62,234.07 <0.001 230.70 * Adjusted for KL grade. Conclusions 3D bone shape predicts TKR. Femur shape has the greatest association with TKR. This provides evidence of predictive validity of 3D bone shape and its potential utility in trials of prospective disease modifying OA drugs. Disclosure of Interest None declared

FRI0552 Why Does Joint Pain “Spread”? Knee Pain Predicts Later Shoulder Pain, Due to Muscle Weakness. Data from the Osteoarthritis Initiative

Background Joint pain is common in older adults; typically multiple joints are involved. Pain in multiple sites is associated with more intense pain in affected joints, poorer physical functioning, and worse quality of life. However, little is known about the pattern of multi-site joint pain development. Objectives To assess whether number of painful joints increases over time, whether pain in certain joints precedes pain in others, and to assess whether the association is mediated by weakness in a cohort of older adults with painful knee osteoarthritis or at risk of knee osteoarthritis in the NIH Osteoarthritis Initiative (OAI). Methods Participants were categorised as having no knee pain (neither knee painful at baseline and years 1-3), or persistent pain in one or two knees (pain at baseline and on two or more occasions in the same knee over years 1-3). Number of painful joints (neck, back, shoulders, elbows, wrists, hands, hips, knees, ankles, feet) was calculated at each visit. Changes in the number of joints were assessed using mixed effects Poisson regression. Associations between persistent knee pain and incident shoulder pain at year 4 were assessed using log multinomial modelling, adjusted for age, sex, BMI, and CES-D depression score (baseline, change at 4 years) (models 1-3), other lower limb pain (models 2 & 3) and leg weakness, defined as difficulty standing from a sitting position at baseline (WOMAC function subscale 3) (model 3). Results Number of painful joints increased yearly, by 2.4% (95% CI -0.5%, 5.5%), 1.6% (-1.4%, 4.5%), 3.5% (0.6%, 6.6%) and 5.2% (2.2%, 8.3%) at years 1-4 compared to baseline. In participants with persistent pain in knees only at baseline, who later developed pain in another single joint (n=70), this did not occur randomly across joint types (p<0.001) with incidence greatest in shoulders (28.5%). Participants reporting weakness, higher depression scores and pain in additional lower limb joints at baseline were more likely to develop shoulder pain at year 4 (all p<0.001). Persistent pain in 1 or 2 knees was associated with increased risk of bilateral shoulder pain at year 4 after adjustment for demographic factors (model 1: Table 1). Associations attenuated slightly after further adjustment for lower limb pain (model 2). The association between knee pain and the development of shoulder pain was mediated by leg weakness (model 3), as knee pain was associated with weakness (1 knee: β=1.16; 95% CI 1.08, 1.24; 2 knees: β=1.21; 95% CI 1.11, 1.30) and weakness with incident shoulder pain (1 shoulder: relative risk (RR) 1.21; 95% CI 1.06, 1.36; 2 shoulders: RR 1.46, 95% CI 1.25, 1.71). Conclusions Spread of joint pain over time is not random, with shoulders the most common painful joint following knees. Associations between persistent knee pain and new shoulder pain is mediated by functional leg muscle weakness; therefore muscle weakness appears key to the spread of joint pain. Disclosure of Interest None declared

FRI0119 Improvement in some, but not all, surrogate measures of cardiovascular disease following intensive treatment of early rheumatoid arthritis

Background Patients with rheumatoid arthritis (RA) have an elevated risk of cardiovascular disease (CVD), predominantly ischaemic heart disease (IHD). Systemic inflammation is thought to be a key contributor to this risk and it is hoped early therapeutic suppression of inflammation will reduce cardiovascular (CV) events in the long term. Insulin resistance, associated with metabolic syndrome, N-terminal pro-brain natriuretic peptide (NT-proBNP) and atherogenic lipid profiles have been proposed as potential surrogate measures of atherosclerosis in RA. Each has been shown to correlate with systemic inflammation, but their utility in RA above measurement of the acute phase response remains unknown. Objectives To determine whether suppression of inflammation in early RA influences surrogate measures of atherosclerosis, including the homeostasis model assessment of insulin resistance (HOMA-IR), NT-proBNP and dyslipidaemia. Methods CRP, fasting glucose and lipids, and in a sub-group, NT-proBNP and fasting insulin, were measured at baseline and week 26 in DMARD naïve RA patients, with 3-12 months symptoms, recruited into the Infliximab as Induction therapy for Early rheumatoid Arthritis (IDEA) multicentre double-blind randomised controlled trial. Patients met the 1987 ACR criteria. Treatment was randomised to IFX +MTX or MTX with 250mg IV methylprednisolone as induction therapy. 120mg IM methylprednisolone was given if DAS>2.4 at 3 time points within the first 26 weeks. HOMA-IR was calculated at each time point. Descriptive statistics, Wilcoxon and paired t-test, and Spearman’s correlation were performed. Results Data from 112 patients (69% female, mean age 53 years, 55% RF and 70% anti-CCP positive) were analysed. At baseline, 9% were on a statin and 14% an anti-hypertensive agent. 4 patients had known IHD and were excluded from the subsequent analysis. The median (range) CRP was 13mg/l (0-30) with CRP normal (<5.0mg/l) in 33%. Baseline CRP negatively correlated with HDL (rho -2.78, p=0.024) and total cholesterol (TC) (rho -2.33, p=0.026). 15%, 30%, 39%, and 25% had at risk levels for HDL, LDL, TC and triglyceride (TG), respectively1. In the subgroup of 79 patients with data on NT-proBNP and fasting insulin, 17% and 38% of patients had raised levels of NT-proBNP and HOMA-IR, respectively. Comparing week 26 to baseline, there was a significant fall in CRP (p<0.001; normal levels in 64%) and HOMA-IR (p=0.008; abnormal in 19%), but not NT-proBNP (p=0.132; elevated in 17%). With respect to the dyslipidaemia, HDL and TC rose (p<0.001 and p<0.001 respectively), but there was no significant change in LDL or TG. 5%, 46%, 61%, and 20% had at risk levels for HDL, LDL, TC and TG, respectively. Conclusions In this study, suppression of inflammation was associated with improvement in insulin resistance and increased HDL, but no significant change in NT-proBNP, TG or LDL following 26 weeks intensive RA treatment. Further analyses of biomarkers at week 78 and drug specific effects are underway. Long term follow up is being performed to determine if those patients with persistently abnormal CV biomarkers develop subclinical or overt CVD in the future despite intensive early treatment for RA. References JAMA. 2001;285(19):2486-97 Disclosure of Interest L.-A. Bissell: None Declared, S. Mackie: None Declared, L. Kozera: None Declared, J. Nam: None Declared, A. Burska: None Declared, E. Hensor: None Declared, H. Keen: None Declared, E. Villeneuve: None Declared, H. Donica: None Declared, P. Conaghan: None Declared, J. Andrews: None Declared, P. Emery: None Declared, A. Morgan Grant/Research support from: Supported in part by a research grant from Investigator-Initiated Studies Program of Merck Sharp & Dohme Limited. The opinions expressed in this paper are those of the authors and do not necessarily represent those of Merck Sharp & Dohme Limited

A1.33 Predicting the evolution of inflammatory arthritis in ACPA-positive individuals: can T-cell subsets help?

Background and Objectives ACPA+ individuals with non-specific musculoskeletal symptoms are at high risk of developing rheumatoid arthritis (RA). We previously demonstrated dys-regulation of T-cell subsets with loss of naïve and regulatory T-cells (Treg) in early disease. The aim of the current study is to demonstrate the predictive value of T-cell subset analysis for progression towards symptom onset in ACPA+ individuals. Materials and Methods 84 ACPA+ individuals without clinical synovitis at recruitment were followed. 95 healthy controls (HC) provided a reference group. At baseline T-cell subset analyses were performed using 6-colour flowcytometry for naïve T-cells (CD4+ CD45RB + CD45RA+ CD62L+), Treg (CD4+ CD25highFoxp3 + CD127low) and inflammation related cells (IRC: CD4+ CD45RB + CD45RA+ CD62L-). The relationship between naïve cell frequency and age was established in HC and used to age-correct values in ACPA+ . ROC curve analysis was used to identify 2 T-cell cut-offs predicting progression to IA at any time; one which maximised the Youden index (sensitivity + specificity-1), and one which prioritised specificity over sensitivity. Results 42/84 (50%) of patients developed clinical synovitis within a median follow-up of 6.0 months (range 1 week-46 months). For age-corrected naïve T-cells area under the ROC curve (AUC) was 0.67 (95% CI 0.55, 0.79; n = 84, p = 0.007), for IRC 0.70 (0.59, 0.81; n = 81, p = 0.002) and for Treg 0.67 (0.53, 0.80; n = 65, p = 0.021). For each of the three subsets, the Youden index cut-off correctly classified >65% of patients (Table 1). Cut-offs prioritising specificity were identified which did not greatly reduce overall classification success. The confidence intervals for these estimates remain wide and our sample size may still be limited for running such analysis. Youden index cut-off Specificity priority cut-off Subset Cut-off Sensitivity Specificity % Correct Cut-off Sensitivity Specificity % Correct Naïve ≤-6.4 59.5 (43.3, 74.4) 76.2 (60.5, 87.9) 67.9 ≤-14.0 26.2 (13.9, 42.0) 90.5 (77.4, 97.3) 58.3 IRC ≥2.8 56.4 (39.6, 72.2) 76.2 (60.5, 87.9) 66.7 ≥4.5 30.8 (17.0, 47.6) 90.5 (77.4, 97.3) 61.7 Treg ≤4.15 90.6 (75.0, 98.0) 41.2 (24.6, 98.0) 65.1 ≤1.6 34.4 (18.6, 53.2) 91.2 (76.3, 98.1) 63.7 Abstract A1.33 Table 1 Sensitivity and specificity of T-cell subset frequencies for progression to IA, using two different cut-off values for each subset; one where the Youden index was maximised and another that prioritised specificity over sensitivity. Conclusions T-cell dys-regulation in ACPA+ individuals with non-specific musculoskeletal pain may be useful in predicting progression to inflammatory arthritis. Multivariable modelling in larger cohorts is needed to quantify the utility of T-cell subsets in predicting progression to IA.

Publisher Correction: A novel two-score system for interferon status segregates autoimmune diseases and correlates with clinical features

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AB0047 Expression of ifn type i responsive genes in a cardiovascular disease continuum of rheumatoid arthritis

Background Rheumatoid Arthritis (RA) patients have a prominent increase in cardiovascular disease (CVD) not fully explained by traditional risk factors1. Interferons type 1 (IFN-I) have been associated with premature CVD in SLE2 and are implicated in several aspects of atherosclerosis and acute coronary syndromes3. A subpopulation of RA patients also display a peripheral blood IFN-I signature from 25% to 65%4, associated with clinical response to biologics5. The IFN-I signature association with CVD in RA remains unclear. Objectives To analyse expression of interferon type 1 response genes (ISGs) along a cardiac MRI (CMR) phenotyped CVD continuum in patients with RA. Methods PBMC samples from 94 RA patients and 21 healthy controls (HC) were obtained. RA patients were stratified based on CMR into: RA CMRneg (no CVD-RA, n=13), RA CMRpos (subclinical CVD-RA, n=54), and RA with clinical CVD (defined as history of cerebrovascular disease or ischaemic heart disease) (RA-CVD n=25). qPCR of ISGs was performed using TaqMan Gene Expression Assays on Biomark (Fluidigm) with compatible reagents. Factor analysis of Ct values from 51 genes was used to create scores by calculating median dCt for genes loaded by each factor. Results RA cohort median(IQR) age 63 (13.3)yrs, 69% female, disease duration 148.7 (215.3)mths; HC age 43 (16.5)y, 62% female. Three IFN-I factors (IFN Score 1, 2,3) were present in the dataset and were composed of 19, 21 and 7 genes respectively. The Jonckheere Tepstra test showed significant increases in expression of Score 2 across the 4 groups(p=0.002), consistent with a continuum, and multiplicity-corrected post-hoc analysis identified differences between HC and subclinical CVD (p=0.034), HC and RA-CVD (p=0.004); as well as between no CVD-RA and subclinical CVD-RA (p=0.034); and subclinical CVD-RA with RA-CVD (p=0.029). Scores 1 and 3 did not show consistent directional trends across all studied groups. In no CVD-RA expression of Score 1 and 2 positively correlated with CRP (rho=0.744, p=0.002 and rho=659, p=0.010 recspectively). Score 1 with Low-Density Lipoproteins (rho=0.527, p=0.044), Framingham 10y risk (rho=0.595, p=0.019) and Score 3 with Pulse Wave Velocity (rho=0.584, p=0.022). In subclinical CVD-RA score 3 expression negatively correlated with Left Ventricular mass (rho=−0.381, p=0.005), in RA-CVD score 3 expression positively correlated with Glucose (rho=0.724, p=0.042, Triglycerydes (rho=0.821, p=0.023) and Total Cholesterol/High-Density Lipoprotein ratio (rho=0.505, p=0.039).Abstract AB0047 – Figure 1 Conclusions An IFN-I score (Score 2) emerged as a possible factor characterising progression along a CVD continuum in RA patients, from no CVD to subclinical and clinical CVD; also distinguishing between HC and RA with subclinical and clinical CVD. IFN –I is involved in metabolic disturbancies associated with CVD development in RA. These results warrant further evaluation to confirm the findings in a larger cohort. References [1] Kaplan MJ. Curr. Opin. Rheumatol2006;18(3):289–297. [2] Somers EC, et al. PloS one2012;7(5):e37000. [3] de Winther MPJ. Arterioscler. Thromb. Vasc. Biol2016;36(2):217–218. [4] Rodríguez-Carrio J, et al. Front Immunol2018;8. [5] Thurlings RM, et al. Arthritis Rheum2010;62:3607–3614. Disclosure of Interest None declared