Search

Background:TNF inhibitors (TNFi) represent an extraordinary advance in the management of Rheumatoid Arthritis (RA). Despite their benefits, there is a percentage of patients (20–40%) that do not achieve clinical improvement. Therefore, it is necessary to search for new and easily accessible biomarkers predictive of therapeutic response that might guide precision medicine.Objectives:1. To explore changes in the molecular profile of RA patients following TNFi therapy in serum samples. 2. To search for new and reliable biomarkers predictive of TNFi response, based on clinical and molecular profiles of RA patients, by using machine learning algorithms.Methods:In a prospective multicenter study, 79 RA patients undergoing TNFi and 29 healthy donors (HD) were enrolled. Twenty-two RA patients were further included as a validation cohort. Serum samples were obtained before and after 6 months of treatment, and therapeutic efficacy was evaluated. Patients’ response was determined following EULAR response criteria. Serum inflammatory profile was analyzed by a multiplex immunoassay, along with oxidative and NETotic profiles, evaluated by commercial kits. A circulating miRNA array was also performed by next-generation sequencing. Clustering analysis was carried out to identify groups of patients with distinctive molecular signatures. Then, clinical and molecular changes induced by TNFi were delineated after 6 months of therapy. Finally, integrative clinical and molecular signatures as predictors of response were assessed at baseline by supervised machine learning methods, using regularized logistic regressions.Results:Inflammatory, oxidative stress and NETosis-derived biomolecules were found altered in RA patients versus HD, closely interconnected and associated with several deregulated miRNAs. This altered molecular profile at baseline allowed the unsupervised division of three clusters of RA patients with distinctive clinical phenotypes, further linked to TNFi effectiveness. Cluster 1 included RA patients with low levels of pro-inflammatory cytokines, associated with a medium-low disease activity score and good clinical response. Clusters 2-3 comprised patients with high levels of pro-inflammatory cytokines, associated with a high disease activity and a non-response rate of 30%.After 6 months of therapy the molecular profile found altered in RA patients was reversed in responder patients, who achieved a molecular phenotype similar to HDs. However, non-responder patients’ molecular profile remained significantly deregulated, including alterations in inflammatory mediators (IL-6, L-8, TNFα, VEGF, IL-1RA, IL-5, IL-15, GMCSF, GCSF, FGFb), oxidative stress markers (LPO) and NETosis-derived products (Elastase), along with specific miRNAs (miR-199a-5p). These molecular changes further correlated with changes in disease activity score. Machine-learning algorithms identified clinical (Creatinine, IgM, Vitamin D, Swollen Joints, C4, Disease Duration and Tryglicerides) and molecular (Nucleosomes, IL-10, miR-106a-5p, IL-13, IL-12p70, IL-15 and LPO) signatures as potential predictors of response to TNFi treatment with high accuracy. Furthermore, the integration of both features in a combined model increased the predictive value of these signatures (AUC: 0.91). These results were further confirmed in an independent validation cohort.Conclusion:1. RA patients display distinctive altered molecular profiles directly linked to their clinical status and associated with TNFi effectiveness. 2. Clinical response was associated with a specific modulation of the inflammatory profile, the reestablishment of the altered oxidative status, the reduction of NETosis and the reversion of related altered miRNAs. 3. The integrative analysis of the clinical and molecular profiles using machine learning allows the identification of novel signatures as potential predictors of therapeutic response to TNFi therapy.Disclosure of Interests:None declared

Background:Factors associated with the development of chronic heart failure (CHF) in systemic lupus erythematosus (SLE) have received little attention. On the other hand, recent data from the use of hydroxychloroquine in the treatment of SARS-CoV-2 infection during the COVID19 pandemic have cast some doubts on its cardiological safety.Objectives:To identify factors associated to CHF in SLE.Methods:Retrospective cross-sectional study, including all patients with SLE (≥4 ACR-1997 criteria) recruited in RELESSER registry. The objectives and methodology of the registry have been described previously (1). CHF was defined according to the Charlson index item. Patients with CHF before diagnosis of SLE were excluded. Cumulative damage was measured with the SLICC/ACR index, excluding cardiovascular (CV) items (mSDI). Multivariate analysis exploring factors associated with CHF was carried out.Results:117 patients (3% of the entire cohort) with SLE and CHF and 3,506 controls with SLE without CHF were included. 90% were women. Disease duration: mean (SD), 120.2 (87.7) months. CHF appeared after a median (P25-P75) of 9.40 (4.2-18.3) years from SLE diagnosis. Patients with CHF were older (59.8 ± 18.2 vs. 46.2 ± 4.3). In the bivariate analysis, the association of CHF with greater severity [Katz severity index: median (IQR): 4 (3-5) vs. 2 (1-3)], damage [mSDI: 3 (2-4) vs 0 (0-1)], comorbidity [modified Charlson- excluding CV items: 4 (3-6) vs 1(1-3)] and both CV (37.5% vs 6.7%) and overall mortality (43.2% vs 4.7%) (pTable 1.Congestive heart failure associated factors (multivariable analysis)Odds Ratio95% CIP-valueSex (female)0.460.25 - 0.880.0147Ischaemic cardiopathy7.964.01 - 15.48Cardiac arrhythmia7.384.00 - 13.42Pulmonary hypertension3.711.84 - 7.250.0002Cardiac valvulopathy6.333.41 - 11.62Hospitalization (due to SLE)3.741.81 - 8.650.0008Calcium or vitamin D5.292.07 - 16.860.0015Antimalarials0.280.17 - 0.45mSDI *1.291.16 - 1.44*mSDI = modified SLICC/ACR damage index (without cardiovascular items)Conclusion:- CHF is a rather late complication of SLE.- Patients with SLE and CHF have more severe SLE, with greater refractoriness to SLE treatments and higher overall mortality.- Treatment with antimalarials, as routinely used in SLE patients, is not only safe to heart, but even appears to have a cardioprotective effect.References:[1]Rúa-Figueroa I, López-Longo FJ, Calvo-Alén J, et al. National registry of patients with systemic lupus erythematosus of the Spanish Society of Rheumatology: objectives and methodology. Reumatol Clin. 2014;10(1):17-24.Acknowledgements:Research Unit of Spanish Society of RheumatologyDisclosure of Interests:None declared

Background:Data on disease activity status and health status (HS) in clinical practice in Spain for patients with ankylosing spondylitis (AS) are scarce. The MIDAS study assessed the disease activity and the relationship with the reported HS in patients with AS treated in clinical practice in Spain.Objectives:This is a sub-analysis to evaluate the differences in disease activity and HS by gender of the patients with AS included in the MIDAS study.Methods:MIDAS is an observational, non-interventional, cross-sectional, multicenter study. Patients included were ≥18 years old with ≥6 months since diagnosis, were classified by ASAS and modified New York criteria; undergoing treatment ≥3 months. The primary variable was the disease control assessed by the percentage of patients in remission and low disease activity (measured by BASDAI and ASDAS-CRP)1-2.Results:We analyzed 313 AS patients; 237 (75.7%) were male and 76 (24.3%) female (Table 1). Disease control: According to BASDAI Table 1.Baseline demographic and clinical characteristics of the AS patients analysed.Total(n=313)Male(n=237)Female(n=76)Age (years), mean (SD)50.4 (12.0)50.1 (12.2)51.2 (11.5)Years since diagnosis, mean (SD)15.5 (11.6)16.8 (12.2)11.4 (8.5)Years since the symptoms’ onset to the study visit, mean (SD)20.5 (12.7)22.2 (13.0)15.2 (9.9)Years since the symptoms’ onset to diagnosis, mean (SD)5.0 (7.2)5.4 (7.7)3.9 (5.6)BMI (kg/m2), mean (SD)27.0 (4.9)27.5 (4.6)25.5 (5.6)Obesity (BMI>30), n (%)67 (23.0%)53 (23.7%)14 (20.9%)Smoking habitCurrent smoker, n (%)75 (24.0%)61 (25.7%)14 (18.4%)Ex-smoker (>6 months), n (%)81 (25.9%)68 (28.7%)13 (17.1%)Non-smoker, n (%)137 (43.8%)96 (40.5%)41 (53.9%)Family history of AS, n (%)66 (21.1%)48 (20.3%)18 (23.7%)Presence of HLA-B27, n (%)245 (78.5%)187 (79.2%)58 (76.3%)Patients previously treated with bDMARD99 (31.6%)77 (32.5%)22 (28.9%)Active disease, n (%)*BASDAI ≥4111 (35.5%)73 (30.8%)38 (50.0%) ASDAS-CRP ≥2.1133 (42.4%)99 (41.8%)34 (44.7%)CRP levels (mg/l), mean (SD)5.1 (8.2)5.7 (9.0)3.3 (4.3)PASS, n (%)270 (86.3%)208 (87.8%)62 (81.6%)ASAS-HI, mean (SD)5.8 (4.4)5.5 (4.4)6.8 (4.2)*Refers to the percentage of patients with active disease according to BASDAI≥4 and ASDAS-CRP ≥2.1.AS, ankylosing spondylitis; ASAS-HI, Assessment of Spondyloarthritis International Society - Health index; ASDAS, Ankylosing Spondylitis Disease Activity Score; BASDAI, Bath Ankylosing Spondylitis Disease Activity Index; bDMARD: biologic disease modifying anti-rheumatic drug; BMI, body mass index; CRP, C-reactive protein; HLA-B27, human leukocyte antigen B27; PASS, patient acceptable symptom state; SD, standard deviation.Conclusion:Our analysis showed a higher proportion of females with active disease when using the BASDAI definition. However, when using the ASDAS-CRP definition, these differences by gender seem to be less pronounced. Also, the impact of disease activity on the HS seems to be higher in females than males. As far as we know, this is the first Spanish study to evaluate gender in this patient population.References:[1]Smolen JS et al. Ann Rheum Dis 2018;77:3-17[2]Gratacós J et al. Reumatol Clin 2018;14:320-33Figure 1.Disease status by sex A)Disease control according to BASDAI B)Disease status according to ASDAS-CRPASDAS-CRP, Ankylosing Spondylitis Disease Activity Score- C-reactive protein; BASDAI, Bath Ankylosing Spondylitis Disease Activity Index.Acknowledgements:We thank to MIDAS group investigators and patients included in the study.Disclosure of Interests:Cristina Fernández-Carballido Speakers bureau: I have received lectures fees from Abbvie, Celgene, Janssen, Lilly, MSD, Novartis, Pfizer, Roche and UCB., Consultant of: I have worked as a paid consultant for Abbvie, Celgene, Janssen, Lilly, Novartis, Pfizer and UCB., Jordi Gratacos-Masmitja Speakers bureau: MSD, Pfizer, AbbVie, Janssen Cilag, Novartis, Lilly and Amgen., Consultant of: MSD, Pfizer, AbbVie, Janssen Cilag, Novartis, Lilly and Amgen., Grant/research support from: During the course of the year I have received a private grand from Pfizer.I have not received any private influence in the elaboration of the contents of this talk., Eugenio de Miguel Speakers bureau: AbbVie, Novartis, Pfizer, MSD, BMS, UCB, Roche, Grunental, Janssen, Sanofi., Paid instructor for: Janssen, Novartis, Roche, Consultant of: AbbVie, Novartis, Pfizer, Galapagos, Grant/research support from: Abbvie, Novartis, Pfizer, Pilar Susana Del Río Martínez Speakers bureau: Novartis, Pfizer, Janssen, Sanofi., Paid instructor for: Lilly, Consultant of: Lilly, Sanofi Aventis, Olga Martínez González Speakers bureau: Novartis, Antonio Fernandez-Nebro Speakers bureau: MSD, Pfizer, AbbVie, Janssen Cilag, Novartis, Celgene, GSK, and Lilly, Consultant of: MSD, Pfizer, AbbVie, Janssen Cilag, Novartis, Celgene, GSK, and Lilly, Paloma Vela-Casasempere Speakers bureau: Astra-Zeneca, AbbVie, Boehringer, GSK, Novartis, UCB, Fresenius-Kabi, Sobi and Lilly, Consultant of: Astra-Zeneca, AbbVie, Boehringer, GSK, Novartis, UCB, Fresenius-Kabi, Sobi and Lilly, Grant/research support from: My unit has received also research support from Roche, MSD, Novartis, Lilly, BMS, and Fresenius-Kabi., Cristina Sanabra Employee of: Novartis employee, Carlos Sastré Employee of: Novartis employee.

Objectives:To describe the prevalence of subclinical atherosclerosis measured as carotid intima-media thickness (cIMT) in patients with rheumatoid arthritis (RA) and to analyze the associated factors.Methods:We performed an observational study of 60 patients with RA and 60 sex and age-matched controls. Patients with dyslipidemia were excluded. The main variable was the cIMT measured by ultrasound. The maximum cIMT was measured and atheromatous plaque was defined as focal thickening of the arterial wall protruding toward the lumen and measuring >0.5 mm or more than 50% of the neighboring cIMT. The other variables included were clinical and laboratory values, lipid metabolism, the 28-joint Disease Activity Score (DAS28), International Physical Activity Questionnaire (METs) and Adherence to a Mediterranean diet (MEDAS). Descriptive, bivariate and two multivariate models were constructed to identify factors associated with pathologic cIMT in all subjects and other in RA patients.Results:The baseline characteristics of both groups are shown in Table 1. The RA patients did not have differences in the mean (SD) of maximum cIMT in relation to the controls (0.77 [0.1] vs 0.75 [0.1]; p = 0.392), nor in the number of plaques (16 [26.7%] vs 10 [16.7]; p = 0.184). The factors associated with maximum cIMT in the total sample were male sex (ß= 0.182; p = 0.039), age (ß = 0.010; p Table 1.Baseline characteristics of 60 patients with RA and 60 controls.VariablePatients n=60Controls n=60p-valueAge in years, mean (SD)54.0 (11.1)54.2 (110.4)0.943Female sex; n (%)53 (88.3)51 (85.0)0.591Smoking0.300 Never smoked, n (%)27 (45.8)30 (54.5) Exsmoker, n (%)23 (39.0)14 (25.5) Active smoker, n (%)9 (15.3)11 (20,0)BMI (kg/m2), mean (SD)28.0 (5.5)27.3 (4.9)0.540MET-minute, median (IQR)533.2 (605.1)809 (716.9)0.028MEDAS, median (IQR)9.4 (1.8)9.1 (2.1)0.349Progression of RA, months, mean (SD)119.7 (84.1-170.5)--Diagnostic delay, months, median (IQR)5.7 (5.1-14.4)--Erosions, n (%)25 (43.1)--RF >10, n (%)45 (75.0)0 (0.0)ACPA >20, n (%)48 (80.0)0 (0,0)High-sensitivity CRP (mg/dl), median (IQR)8.1 (4.2)2.0 (4.5)0.009ESR (mm/h), median (IQR)21.1 (16.6)13.9 (12.3)0.008DAS28 at protocol, mean (SD)3.1 (2.2-4.2)--Synthetic DMARDs, n (%)52 (88.1)-- Methotrexate, n (%)36 (61.0)-- Leflunomide, n (%)6 (10.2)-- Sulfasalazine, n (%)7 (11.9)-- Hydroxychloroquine, n (%)4 (6.8)Biologic DMARDs, n (%)32 (54.2)-- Anti TNF-α, n (%)23 (39.0)-- Jak inhibitor, n (%)1 (1.7)-- Anti-IL-6, n (%)6 (10.2)-- Abatacept, n (%)1 (1.7)--Abbreviations: RA, rheumatoid arthritis; ACPA, anti-citrullinated peptide antibodies; RF, rheumatoid factor; SD, standard deviation; MEDAS: Mediterranean Diet Adherence Survey; DAS28, 28-joint Disease Activity Score; CRP, C-reactive protein; ESR, erythrocyte sedimentation rate; DMARD, disease-modifying antirheumatic drug; IL-6, interleukin 6; Anti TNF, anti–tumor necrosis factor.Conclusion:In patients with well-controlled established RA, subclinical atherosclerosis is associated, in addition to sex, age, and mediterranean diet, with inflammatory activity and ACPA value.Acknowledgements:Grant for Medical Researchers from “Fundación Española de Reumatología” 2019Grant from “Fundación Española de Reumatología” 2018 for non-funded projects.Disclosure of Interests:None declared

Background:IgA vasculitis (IgAV) and IgA nephropathy (IgAN) are inflammatory conditions that share pathogenic and molecular mechanisms [1] and may represent different outcomes of a continuous spectrum of disease [2]. Interleukin (IL)17A has been identified as a common genetic risk locus for several immune-mediated diseases [3, 4].Objectives:To determine whether IgAV and IgAN exhibit a different IL17A association pattern.Methods:Five IL17A tag polymorphisms (rs4711998, rs8193036, rs3819024, rs2275913 and rs7747909) were genotyped in 388 Caucasian patients with IgAV, 99 patients with IgAN and 1,003 sex and ethnically matched healthy controls.Results:No statistically significant differences between patients with IgAV and healthy controls and between patients with IgAN and healthy controls were observed when each IL17A genetic variant was analyzed independently (Table 1). Similarly, IgAV patients exhibited similar genotype and allele IL17A frequencies than those with IgAN (Table 1). Moreover, no genotype or allele differences between IgAV patients who developed nephritis and patients with IgAN were detected. Furthermore, haplotype frequencies were similar in patients with IgAV, IgAV and nephritis and those with IgAN.Table 1.Genotype and allele frequencies of IL17A gene in patients with IgA vasculitis, patients with IgA nephropathy and healthy controls.PolymorphismChangeData set1/11/22/212rs4711998G/AIgAV53.4 (207)38.9 (151)7.7 (30)72.8 (565)27.2 (211)IgAN49.0 (48)42.9 (42)8.2 (8)70.4 (138)29.6 (58)Controls52.7 (529)41.2 (413)6.1 (61)73.3 (1471)26.7 (535)rs8193036T/CIgAV57.0 (221)38.4 (149)4.6 (18)76.2 (591)23.8 (185)IgAN64.3 (63)31.6 (31)4.1 (4)80.1 (157)19.9 (39)Controls60.3 (605)35.2 (353)4.5 (45)77.9 (1563)22.1 (443)rs3819024A/GIgAV44.1 (171)43.3 (168)12.6 (49)65.7 (510)34.3 (266)IgAN39.4 (39)54.5 (54)6.1 (6)66.7 (132)33.3 (66)Controls45.6 (457)44.6 (447)9.9 (99)67.8 (1361)32.2 (645)rs2275913G/AIgAV44.6 (172)43.3 (167)12.2 (47)66.2 (511)33.8 (261)IgAN39.8 (39)53.1 (52)7.1 (7)66.3 (130)33.7 (66)Controls44.8 (449)44.2 (443)11.1 (111)66.8 (1341)33.2 (665)rs7747909G/AIgAV53.9 (209)39.4 (153)6.7 (26)73.6 (571)26.4 (205)IgAN41.1 (39)54.7 (52)4.2 (4)68.4 (130)31.6 (60)Controls53.0 (532)39.4 (395)7.6 (76)72.7 (1459)27.3 (547)Conclusion:Our results revealed that IgAV and IgAN share a similar IL17A association pattern.References:[1]N Engl J Med 2013;368:2402-14.[2]Am J Kidney Dis 1988;12:373-7.[3]Ann Rheum Dis 2014;73:1742-5.[4]Mediators Inflamm 2018;2018:1395823.Acknowledgements:This study was supported by European Union FEDER funds and “Fondo de Investigaciones Sanitarias” (grant PI18/00042) from ‘Instituto de Salud Carlos III’ (ISCIII, Health Ministry, Spain). DP-P is a recipient of a Río Hortega programme fellowship from the ISCIII, co-funded by the European Social Fund (ESF, `Investing in your future´) [grant number CM20/00006]; SR-M is supported by funds of the RETICS Program co-funded by the European Regional Development Fund (ERDF) [grant number RD16/0012/0009]; VP-C is supported by a pre-doctoral grant from IDIVAL [grant number PREVAL 18/01]; BA-M is a recipient of a `López Albo´ Post-Residency Programme funded by Servicio Cántabro de Salud; LL-G is supported by funds of IDIVAL [grant number INNVAL20/06]; RL-M is a recipient of a Miguel Servet type I programme fellowship from the ISCIII, co-funded by the European Social Fund (ESF, `Investing in your future´) [grant number CP16/00033].Disclosure of Interests:Diana Prieto-Peña: None declared, Fernanda Genre: None declared, Sara Remuzgo Martinez: None declared, Verónica Pulito-Cueto: None declared, Belén Atienza-Mateo: None declared, Belén Sevilla: None declared, Javier Llorca: None declared, Norberto Ortego: None declared, Leticia Lera-Gómez: None declared, Maite Leonardo: None declared, Ana Peñalba: None declared, Luis Martín-Penagos: None declared, Jose Alberto Miranda-Filloy: None declared, J. Narváez: None declared, LUIS CAMINAL MONTERO: None declared, PAZ COLLADO: None declared, Antonio Fernandez-Nebro: None declared, Gisela Díaz-Cordoves: None declared, Secundino Cigarrán: None declared, Jesús Calviño: None declared, Carmen Cobelo: None declared, Javier Sanchez Perez: None declared, Diego de Argila: None declared, Esteban Rubio-Romero: None declared, MANUEL LEON LUQUE: None declared, Juan María Blanco-Madrigal: None declared, E. Galindez: None declared, Javier Martin Ibanez: None declared, Santos Castañeda: None declared, Ricardo Blanco Speakers bureau: Abbvie, Pfizer, Roche, Bristol-Myers, Janssen and MSD, Consultant of: Abbvie, Pfizer, Roche, Bristol-Myers, Janssen and MSD, Grant/research support from: Abbvie, MSD and Roche, Miguel A González-Gay Speakers bureau: Pfizer, Abbvie, MSD, Grant/research support from: Pfizer, Abbvie, MSD, Raquel López-Mejías: None declared

Objectives:To analyze the effect of disease-modifying antirheumatic drugs (DMARDs) and identify risk factors associated with disease progression and mortality in patients with rheumatoid arthritis associated with interstitial lung disease (RA-ILD).Methods:We performed a multicenter, prospective, observational study of patients with RA-ILD receiving DMARDs between 2015 and 2020. The patients were assessed using high-resolution computed tomography and pulmonary function tests at baseline and at 60 months. The main outcome measure at 60 months was worsening of FVC >10% or DLCO >15% and radiological progression or death. We recorded demographic and clinical characteristics, lung function, and the incidence of adverse events. A Cox regression analysis was performed to identify factors associated with worsening of ILD.Results:After 60 months, lung disease had stabilized in 66 patients (56.9%), improved in 9 (7.8%), and worsened in 23 (19.8%). Eighteen patients (15.5%) died, with a mean survival of 71.8 (1.9) months. Baseline characteristics of 116 with RA-ILD treated with DMARDs is in table 1.The Cox multivariate analysis revealed the independent predictors of worsening of RA-ILD to be usual interstitial pneumonia (HR, 2.6 [95%CI, 1.0-6.7]), forced vital capacity (%) (HR, 3.8 [95%CI, 1.5-6.7]), anticitrullinated protein antibody titers (HR, 2.8 [95%CI, 1.1-6.8]), smoking (HR, 2.5 [95%CI, 1.1-6.2]), and treatment with abatacept, tocilizumab, or rituximab (HR, 0.4 [95%CI, 0.2-0.8]). During follow-up, 79 patients (68%) experienced an adverse event, mostly infection (61%).Conclusion:Lung function is stable in most patients with RA-ILD receiving treatment with DMARDs, although one third of patients die. Identifying factors of worsening in RA-ILD is important for clinical management.Table 1.Baseline characteristics of 116 with RA-ILD treated with DMARDsVariableTotal=116Epidemiological characteristicsFemale sex, n (%)63 (54.3)Age, years, mean (SD)68.3 (9.9)Clinical and analytical characteristicsCurrent smokerNonsmoker, n (%)57 (49.1)Smoker, n (%)23 (19.8)Exsmoker, n (%)36 (31.0)Time since diagnosis of RA, months, median (p25-p75)148.5 (71.5-217.8)Diagnostic delay, months, median (p25-p75)8.5 (4.9-16.8)Time since diagnosis of ILD, months, median (p25-p75)27.5 (9.8-60.0)Positive rheumatoid factor (>10), n (%)111 (95.7)Positive ACPA titer (>20), n (%)100 (86.2)Erosive disease, n (%)76 (65.5)Treatment Synthetic DMARD100 (86.2) Methotrexate, n (%)51 (44.0) Leflunomide, n (%)30 (25.9) Sulfasalazine, n (%)9 (7.8) Hydroxychloroquine, n (%)21 (18.1)Biologic DMARD50 (43.1) Infliximab, n (%)1 (0.9) Etanercept, n (%)6 (5.2) Adalimumab, n (%)3 (2.6) Golimumab, n (%)3 (2.6) Certolizumab, n (%)3 (2.6) Tocilizumab, n (%)6 (5.2) Abatacept, n (%)15 (12.9) Rituximab, n (%)13 (11.2) Immunosuppressants11 (9.5) Mycophenolate, n (%)7 (6.0) Azathioprine, n (%)4 (3.4) Antifibrotic agents, nintedanib, n (%)1 (0.9) Baseline corticosteroids, n (%)69 (60.0) Dose of baseline corticosteroids, median (p25-p75)5.0 (0.0-7.5)Abbreviations. RA: rheumatoid arthritis; ILD: interstitial lung disease; ACPA: anticyclic citrullinated protein antibody; DMARD: disease-modifying antirheumatic drug; SD: standard deviation.Acknowledgements:Grant for Medical Researchers of the “Fundación Española de Reumatología” 2019. declare.Disclosure of Interests:None declared

Background:Metotrexate (MTX) is the first-line treatment for rheumatoid arthritis (RA) both in monotherapy and in combination with biologic disease-modifying antirheumatic drugs (bDMARDs), it usually well tolerated but AEs may appear that causing toxicity that requires suspension of the treatmentObjectives:Determine the prevalence of certain polymorphisms among patients that receive bDMARD in monotherapy or in combination with MTX to confirm its relevance as biomarkers of intolerance. Evaluate the influence of certain polymorphisms in the effectiveness of monotherapy or combined treatment in patients, through“Disease Activity Score 28”(DAS28), SDAI Simple disease activity index (SDAI), Clinical disease activity index (CDAI) and each one of its componentsMethods:Retrospective observational multicentric study (University Hospital Complex, Granada, Carlos de Haya Hospital, Malaga and University Hospital Reina Sofia, Cordoba), of cases-control of 227 patients with RA (criteria ACR/EULAR), of which 120 received MTX and bDMARD combined therapy (cases) and other with only bDMARD (controls). All of them had been or were currently treated with MTX, remained with stable doses of bDMARD, and had a DNA sample stored before the inclusion in the studyDNA was isolated from total peripheral blood and by fluorescent probe HybProbe and/ or Taqman, 10 polymorphisms of 10 protein coding genes were determined involved in the metabolism and toxicity of MTX according to current evidenceBesides the type of polymorphism, data on the activity of the disease were analysed (DAS28VSG, DAS28PCR, SDAI, CDAI, at the start of the MTX income, of the BT, and in the inclusion visitA descriptive and comparative study was carried out on all that and afterwards an assessment was made through a multiple logistic regression analysis (MLR) on the risk of intolerance to MTXResults:An analysis was carried out on 227 patients (120 cases and 107 controls) with an average age of 60 (12,1) being women 78,4%, with a time of evolution since diagnosis of 14,84 (7,78) years48,9% registered adverse events (AE) MTX related, mainly gastrointestinal, hepatobiliary and skin-subcutaneous tissue. The percentage of AE appearance was superior in the monotherapy group than in the group with combined therapyThe most prevalent polymorphism (84,6% (IC95%: 84,09%-85,11%) and in cases (86,0% (IC95%: 79,43%-92,57%) washomozygous CC (ITPase-c94a); in controlshomozygous GG (GGH-T401C) (87,5% (IC95%:81,58%-93,42%)There were no significant differences in the parameters of activity between groups, in both, patients were best basally controlled than at the start of the MTX income and/or bDMARDBeinghomozygous-AA for the DHFR genewas significantly associated (pIn MLR,homozygous GG(ref. heterozygous AG) in polymorphismGGH-T401C,beinghomozygous CC(ref. heterozygous TC) in polymorphismABCC2-C24TandPCR (mg/dL) at the start of bDMARDresulted independent predictive factors of MTX intoleranceConclusion:Polymorphisms T401C for the GGH gene and C24T for the ABCC2 gene and PCR at the start of the bDMARD resulted independent predictive factors of MTX intolerance. Polymorphismhomozygous AAforDHFR genewas related to significant protection against appearance of AEDisclosure of Interests:Alejandro Escudero Contreras: None declared, Rafaela Ortega Castro: None declared, Jerusalem Calvo Gutierrez: None declared, Natalia Mena-Vázquez: None declared, Rafael Cáliz Cáliz: None declared, Eduardo Collantes Estevez Grant/research support from: ROCHE and Pfizer, Speakers bureau: ROCHE, Lilly, Bristol and Celgene, Antonio Fernandez-Nebro: None declared, Maria del Carmen Abalos-Aguilera: None declared, Chary Lopez-Pedrera Grant/research support from: ROCHE and Pfizer., Mª Teresa Ruiz Jimenez Employee of: Roche Farma, SPAIN, Font Ugalde Pilar: None declared

Background:Objectives:To study the frequency of polyautoinmunity and multiple autoinmune syndrome (MAS) in patients with rheumatoid arthritis (RA) and systemic lupus erithematosus (SLE).Methods:Study design: We performed a cross-sectional study in patients with RA and SLE, and compared them with healthy subjects. Cases: RA patients classified by ACR/EULAR 2010 criteria and SLE patients classified by ACR/EULAR 2019 criteria. SLE and RA patients were compiled consecutively from a rheumatology clinic of the Regional University hospital of Malaga. Controls: subjects without rheumatologic autoimmune disease (AD) from the same population area. Protocol: All subjects filled out a predesigned questionnaire for the collection of polyautoimmunity data on the cut-off date. Main variables: polyautoimmunity was defined as co-occurrence of SLE or RA and other AD. Secondary variables: Rheumatologic, cutaneous, endocrine, digestive and neurological AD. MAS was defined as presence of three or more AD. Family history of SLE, RA and other autoimmune diseases were also collected. Statistic analysis: descriptive analysis, bivariate analysis and multivariable analysis were done. (Dependent variable: Polyautoimmunity).Results:We recruited 109 patients with RA, 105 with SLE and 88 controls. Fifteen patients with RA (13.8%), 43 with SLE (41%) and 2 controls (2.2%) reported polyautoimmunity. Table 1 describes the epidemiological characteristics, comorbidities and polyautoimmunity in study population. The most frequent AD associated with RA was Sjögren’s syndrome (SS) (53.3%) and SS (55.8%) followed by the antiphospholipid syndrome (30.2%) were associated with SLE. Hashimoto’s thyroiditis and psoriasis were the next most frequent AD. According to family history, 5 patients with RA (33.3%) and 12 with SLE (27.9%) had a family history of first degree of other AD. Obesity was associated with polyautoimmunity in RA (OR = 3,362, p = 0.034). In SLE, joint damage (OR = 2.282, p = 0.038) and anti-RNP antibodies (OR = 5.095, p = 0.028) were factors associated with polyautoimmunity and taking hydroxychloroquine was a protective factor (OR = 0.190, p = 0.004).Conclusion:Polyautoimmunity in RA and especially in SLE is frequent. It was associated with obesity in RA and in SLE with joint damage and anti-RNP antibodies. The hydroxychloroquine appeared as a protective factor.VariablesRA(N=109)SLE(N=105)Controls(N=88)P valueEpidemiological characteristicsSex: female, n (%)85 (78.0)99 (94.3)68 (77.3)0.001Age, mean (SD), years56.5 (10.8)50.8 (13.2)57.1 (10.6)0.133Caucasic race, n (%)107 (98.2)105 (100)88 (100)0.168ComorbiditiesSmoking0.001 No smoking, n (%)55 (50.5)78 (74.3)56 (63.6) Smoking history, n (%)54 (49.5)27 (25.7)32 (36.4)Obesity, n (%)38 (34.9)21 (20.0)22 (25.0)0.044Dyslipidemia, n (%)24 (22.0)22 (21.2)17 (19.3)0.896Hypertension, n (%)27 (24.8)28 (26.7)23 (26.1)0.746Diabetes mellitus, n (%)7 (6.4)1 (1.0)1 (1.1)0.031Polyautoimmunity, n (%)15 (13.8)43 (41)2 (2.2)MAS, n (%)1 (0.9)9 (8,6)0 (0.0)FH polyautoimmunity, n (%)19 (17.6)26 (24.8)15 (17.0)0.060RA: rheumatoid arthritis; SLE: systemic lupus erithematosus; SD: standard desviation; MAS: multiple autoinmune syndrome; FH:Family historyDisclosure of Interests:None declared

Background:Climatological conditions and ethnicity impact on the course of the disease in systemic lupus erythematosus patients.Objectives:We carry out a study to analyze cutaneous manifestations in SLE patients from Argentina and Spain.Methods:Patients data from Spanish Rheumatology Society Lupus Registry (RELESSER) and Argentina Rheumatology Society Lupus Registry (RELESSAR) were retrospectively analyzed for presence of cutaneous lesions (alopecia, photosensitivity, malar rash, discoid lesions, oral ulcers and subacute lesions). RELESSER-T and RELESSAR-T are multicenter, hospital-based registries, with retrospective cross-sectional collection of data about patients with SLE attending Spanish and Argentinian rheumatology services from the public national health system. Data about climatological conditions throughout the Spanish and Argentinian geography were provided by the Spanish Meteorological Agency and Argentine Meteorological Services.Results:A total of 5604 patients were included, median age 44.6 ± 15.3, 90.4 % female. Current smokers were 28,9%. Other climatological, geographical, biological and clinical data are shown in table 1. In the multivariable model, the presence of cutaneous lesion were significantly associated with temperature OR 1.116 (95% CI:1.042-1.196 p=0,002), altitude OR 1.001 (95% CI:1.000-1.001, p=0.012), hemolytic anemia OR 1.401 (95% CI:1.017-1.931 p=0.039) and serositis OR 1.509 (95% CI:1.215-1.875 p=0.000). Negative associations were observed between females OR 0.392 (95% CI:0.297-0.518, p=0.000), latitude OR 0.994 (95% CI:0.988-0.999, p=0.000), oceanic climate OR 0.566 (95% CI:0.381-0.842, p=0.005), leukopenia OR 0.790 (95% CI:0.643-0.970, p=0.025), renal disorder OR 0.761 (95% CI:0.600-0.966, p=0.025), glucocorticoids treatment OR 0.571 (95% CI:0.456-0.715, p=0.000) and antimalarial drugs OR 0.439 (95% CI:0.342-0.563, p=0.000).Table 1.Geographical, climatological and clinical/laboratory variables.No cutaneous manifestationsCutaneous manifestationspLatitude, median (interqualite range)40.47 (38.35-41.63)40.37 (-31.41-41.34)0.001Altitude, median (interqualite range)192.0 (37.0-698.0)156.0 (25.0-609.0)0.000Temperature, mean monthly ± SD15.2 ± 3.515.3 ± 3.60.000Humidity, mean monthly ± SD66.9 ± 7.267.4 ± 7.10.108Oceanic climate, n (%)307 (11)2406 (89)0.000Subhumid/altitude climate, n (%)17 (7)240 (93)0.002Mediterranean climate, n (%)292 (17)1434 (83)0.000Arthritis, n (%)523 (12)3722 (88)0,003Serositis, n (%)254 (16)1368 (84)0,000Renal disorder, ever, n (%)206 (11)1576 (89)0.015Hemolytic anemia, n (%)90 (17)426 (83)0,002Leukopenia, n (%)345 (11)2669 (89)0.000Thrombocytopenia, n (%)170 (15)986 (85)0.076Antiphospholipid antibodies, n (%)293 (15)1606 (85)0.000Anti DNA, n (%)522 (14)3279 (86)0.044Anti-Ro/SSA, n (%)189 (11)1563 (89)0.000Hypocomplementemia, n (%)510 (12)3736 (88)0.000Glucocorticoids mucocutaneous cause, ever, n (%)499 (11)3928 (89)0.000Antimalarial drug: ever, n (%)500 (11)4034 (89)0.000Conclusion:In the current analysis, taking RELESSAR and RELESSER data together, we observe positive association between higher temperature and skin lesion and negative association with living in southern hemisphere latitudes.References:Influence of Solar Radiation in Cutaneous Manifestations of Lupus: Data from the Gladel Cohort [abstract]. Arthritis Rheumatol. 2016; 68 (suppl 10).Disclosure of Interests:Raúl Menor-Almagro: None declared, Mercedes Argentina García: None declared, Iñigo Rua-Figueroa: None declared, Guillermo Pons Estel: None declared, Maria Auxiliadora Martin-Martinez: None declared, Alejandro Muñoz Jimenez.: None declared, María Galindo-Izquierdo: None declared, Jaime Calvo-Alen: None declared, Antonio Fernandez-Nebro: None declared, Alejandro Olive: None declared, Bernardo Pons-Estel Grant/research support from: GSK, Janssen, Consultant of: GSK, Janssen, Speakers bureau: GSK, Janssen, Jose M Pego-Reigosa: None declared

Background:Objectives:To analyze the diagnostic utility of lung ultrasound (US) to detect interstitial lung disease (ILD) in Rheumatoid arthritis (RA) patients comparing with high-resolution computed tomography (HRCT).Methods:Study design: We performed a cross-sectional, observational study in patients with RA-ILD (cases) controlled with a gruop of RA patients without ILD (controls) paired by sex, age and time of disease evolution.Protocol: Patients were selected between May and September 2019. Patients were interwied by two rheumathologist for the protocolized collection of clinical data. The patients were assessed using HRCT, Pulmonary Function Test (PFT) and lung US.. The rheumatology who performed the lung US were blinded to patients clinical data. Variables: (1) B-lines number; (2) evaluation of the lung- ultrasound score already described: L. Gargani, Gutiérrez comprehensivo, Gutiérrez reducido and Mohhammadi;(3)pleural irregularities; (4) A pattern US lost;(5). Other variables included demographic, clinical-analytical, therapeutic and ILD-type description. Statistical analysis: descriptive, bivariant analysis. We applied Pearson’s correlation coefficient between B-lines, PFT and clinical variable.Furthermore, to establish the cut-off point of the US B-lines number for detecting the presence of significant AR-ILD in relation to HRCT, we used the receiver operating characteristic (ROC) curve analysis. A logistic regression analysis was performed to identify the intercostal spaces (IV: B-lines number in each space) wich wereindependently associated with ILD (DV: ILD in HRCT).Results:71 patients were included, 37 (52,1%) with ILD-RA and 34 (47,95) RA controls. The main characteristics are shown in Table 1. RA-ILD presented more B-lines number than control without ILD (median ICR] 91.0 [31.0-149.0] vs 6.5 [1.5-30.5]; p=Sensitivity of 75.7%, Specifity=79.4%, PPV= 80% and NPV=75%,whilst in reduced score of 10 intercostal spaces, the detection of 5.5 B-lines had a sensivity= 62.2%,Specifity= 91.3%, PPV=88.4%, NPV=69.5%. In multivariate analysis, the intercostal spaces which showed independent association with ILD were 3rdright anterior axillary space(OR [IC 95%] 19.0 [1.3-27.5]), 8thright posterior axillary space (OR [IC 95%] 0.04 [0.0-0.6]), 8thright subescapular space (OR [IC 95%] 16.5 [1.8-45.5]),9thright paravertebral space (OR [IC 95%] 7.11 [1.0-37.1]) and 2ndleft clavicular middle space(OR [IC 95%] 21.9 [1,26-37.8]).Conclusion:Lung Ultrasoud could be a useful tool for interstitial lung disease diagnosis associated with Rheumatoid Artrithis. A 10 space reduced score showed a similar total predictive capacity than 72-space scoreReferences:Disclosure of Interests:None declared

Background:Objectives:To describe the impact of the disease on patients with rheumatoid arthritis (RA), systemic lupus erythematosus (SLE) or ankylosing spondylitis (EA) on the social health of people who suffer from it.Methods:Cross section of a consecutive sampling of patients with AS, RA or SLE. Selection criteria: age ≥18 years with AS (ASAS criteria), AR (EULAR / ACR 2010 criteria) and SLE (ACR-EULAR criteria) able to understand and willing to perform the questionnaires. Protocol: All patients who attended a consultation between October and December 2019 were offered to participate in the study. After their approval and verification of the inclusion criteria, they conducted a battery of PROMIS platform questionnaires focused on assessing their social health. Likewise, data on their disease, comorbidities and socio-labor profile were collected. All participants signed an informed consent and the study was approved by the CEIC of the referral hospital.Main outcomes:The variables collected by the questionnaires evaluate social health in several areas: mobility, depression, satisfaction with social relationships, social isolation, company, ability to participate in social activities, emotional support, instrumental support and support through information. Statistical analysis: Descriptive, bivariate analysis using t-student, ANOVA and χ2;, followed by multivariate linear regression (RLM) (Vd: ability to participate in continuous social activities 7-35).Results:151 patients participated: 50 with RA (90% women, mean age 55.12 ± 13.64 years), 51 with AS (51% women, 52.59 ± 12.15 years) and 50 patients with SLE (96 % women, mean age 47.14 ± 11.3 years). The most frequent comorbidities were: arthritis, visual impairment, anxiety and depression (table 1). These results present a greater tendency to depression and anxiety patients of SLE. No significant differences were observed in most of the social questionnaires analyzed between groups (table 2), except in a worse mobility in patients with RA and AD compared to SLE (p = 0.017). About half of the patients in all groups had depression (43%) and reduced mobility (63.6%). All groups are satisfied with their social role 128 (85.3%), have the capacity to participate in social activities 140 (94%) and feel accompanied 147 (97.4%). On the contrary, the social isolation figure is 42 (28%). Social isolation implies an affectation of the serious social role in patients who claim to be accompanied, so it is not secondary to loneliness or lack of family support.In the multivariate analysis it was observed that the independent variables that were associated with the ability to participate in social activities were satisfaction with social relations (β = 0.349 [p = Conclusion:The predictors of the ability to participate in social activities in patients with RA, AD and SLE were: depression, mobility deficit, social isolation and satisfaction with social activities. Patients with RA, AD and SLE present similar data, so there are no differences due to pathologies in the social role, highlighting that they have a good social support and despite this there is social isolation being able to be associated with the deficit in mobility and high rates of depression.Disclosure of Interests:None declared

Background:In Rheumatoid arthritis (RA), between 20% and 40% of patients do not achieve a 20% improvement in American College of Rheumatology (ACR) criteria, another similar percentage loses response over time or experience adverse events that forces them to the suspension of treatment. Those patients who have failed one or more therapeutic strategies, are more refractory patients and the response to successive targets is usually lower than naive patients, with 50% ACR20 response percentages.Objectives:To describe the clinical-analytical characteristics and response to the last treatment, in rheumatoid arthritis (RA) refractory to biological disease modifying anti-rheumatic drugs (bDMARDs) and targeted synthetic DMARDs (tsDMARDs). To identify possible factors related to refractoriness to bDMARDs and tsDMARDs.Methods:Retrospective multicentre, controlled study of patients with RA refractory to bDMARDs and tsDMARDs. Control group was formed by patients with non-refractory RA; matched by gender, age and diseaseduration. Refractoriness was defined as failure to more than 2 different targets of bDMARDs or tsDMARDs. Demographic, clinical-analytical data and rates of disease activity and physical function were collected. A descriptive analysis, a bivariate analysis and a binary logistic regression were performed to see the variables associated with refractoriness.Results:A total of 94 patients were selected from HRUM and HCUVV: 47 with refractory RA and 47 with non-refractory RA. The clinical-epidemiological characteristics of both groups are classified in Table 1. The majority were women with a mean age of 57 years. There was a greater proportion of patients with multimorbidity and cardiovascular risk factors among the refractory to FAMEb. All patients affected a significant improvement with the new treatment in activity and physical function at 6 months compared to baseline. Refractoriness is associated with a higher body mass index [OR(IC95%), 7.73 (1.56-8.42); p=0.012], and depression [OR(IC95%), 1.11 (1.24-1.83); p=0.035].Table 1.Clinical-epidemiological characteristics of patients.VariableRefractory RA (N=47)Non-refractory RA(N=47)p-valueSex (female), n (%)38 (80,9)38 (80,9)1,000Age, means (SD)57,1 (10,8)57,4 (10,8)0,896Caucasian race, n (%)45 (95,7)44 (93,6)0,646Body mass index, means (SD)30,4 (6,8)26,5 (3,8)0,002Non-smoker, n (%)26 (55,3)28 (59,6)Former smoker>6 months, n (%)16 (34,0)7 (14,9)Smoker, n (%)5 (10,6)12 (25,5)Rheumatoid Factor, n (%)40 (85,1)42 (89,4)0,536Anti-cyclic citrullinated peptide, n (%)37 (78,7)38 (80,9)0,797Erosions, n (%)33 (70,2)28 (59,6)0,280Hypertension, n (%)24 (51,1)20 (42,6)0,408Obesity, n (%)19 (40,4)9 (19,1)0,024Diabetes Mellitus, n (%)10 (21,3)6 (12,8)0,272Dyslipidemia, n (%)20 (42,6)15 (31,9)0,286Neoplasia, n (%)2 (4,3)0 (0,0)0,153Fibromyalgia, n (%)4 (8,5)1 (2,1)0,168Depression, n (%)18 (38,3)4 /8,5)0,001Multicomorbidity, n (%)17 (36,2)6 (12,8)0,008Comorbidities number, median (IQR)2,0 (1,0-3,0)1,0 (0,0-2,0)0,002Conclusion:Patients with refractory RA have an adequate response to subsequent treatment lines. These patients have a remarkable percentage of associated comorbidities.Disclosure of Interests:None declared

Background:Blocking Tumor Necrosis Factor (TNF) activity is a successful therapeutic approach for approximately 60% of patients with rheumatoid arthritis (RA). To date, however, the biological basis of the lack of efficacy of anti-TNF agents is unknown.Objectives:The objective of present study was to characterize the biological basis of anti-TNF lack of efficacy in RA using an epigenomic data approach in two steps: first, to assess the differential methylation changes between responders and non-responders and second, to use this differential methylation profile in a systems biology approach to infer differential methylated biological modules according to anti-TNF response.Methods:A total of n=68 patients diagnosed with RA according to the ACR-EULAR criteria belonging to 16 Hospitals across Spain were recruited. All patients were >18 years old, with more than 6 months of disease evolution and a baseline disease activity of DAS28 > 3.2. Treatment response was defined according to the EULAR criteria at week 12. Good and moderate responders were aggregated into a single responder group. Genomic DNA was collected at baseline and the methylation profile was assessed using the Illumina Infinium EPIC array, which interrogates 850,000 methylation CpG sites across the genome. Differential Methylation analysis, biological pathway association and the systems Biology approach using Protein-Protein Interaction Networks, were conducted using the R statistical language and the Bioconductor libraries.Results:From 68 anti-TNF treated patients, n=27 (39.7%) were good responders, n=26 (38.2%) moderate responders and n=15 (22.05%) non-responders at week 12 of treatment. Differential methylation analysis identified two distinctive biological profiles associated with the clinical response: responders were associated to interleukin and cytokine production, and non-responders were associated with biological pathways associated to TGF-Beta production and T cell regulation. Using these differentially methylated profiles, epigenetic modules with differentially methylated hotspots between responders and non-responders were also found. Two epigenetic modules with significant enrichment in inflammatory and interleukin production and immune regulatory processes were validated in an independent patient cohort.Conclusion:The epigenetic analysis of whole blood from RA patients using a module-based approach shows reproducible biological mechanisms associated with the response to anti-TNF therapy.Acknowledgments:We would like to thank the clinical researchers and patients participating in the IMID Consortium for their collaborationDisclosure of Interests:Antonio Julià: None declared, Antonio Gómez: None declared, Antonio Fernández Nebro: None declared, Francisco J. Blanco Grant/research support from: Sanofi-Aventis, Lilly, Bristol MS, Amgen, Pfizer, Abbvie, TRB Chemedica International, Glaxo SmithKline, Archigen Biotech Limited, Novartis, Nichi-iko pharmaceutical Co, Genentech, Jannsen Research & Development, UCB Biopharma, Centrexion Theurapeutics, Celgene, Roche, Regeneron Pharmaceuticals Inc, Biohope, Corbus Pharmaceutical, Tedec Meiji Pharma, Kiniksa Pharmaceuticals, Ltd, Gilead Sciences Inc, Consultant of: Lilly, Bristol MS, Pfizer, Alba Erra: None declared, Simon Sánchez Fernandez: None declared, Jordi Monfort: None declared, Mercedes Alperi-López: None declared, Isidoro González-Álvaro Grant/research support from: Roche Laboratories, Consultant of: Lilly, Sanofi, Paid instructor for: Lilly, Speakers bureau: Abbvie, MSD, Roche, Lilly, Rosario Garcia de Vicuna Grant/research support from: BMS, Lilly, MSD, Novartis, Roche, Consultant of: Abbvie, Biogen, BMS, Celltrion, Gebro, Lilly, Mylan, Pfizer, Sandoz, Sanofi, Paid instructor for: Lilly, Speakers bureau: BMS, Lilly, Pfizer, Sandoz, Sanofi, Raimón Sanmartí Speakers bureau: Abbvie, Eli Lilly, BMS, Roche and Pfizer, Cesar Diaz Torne: None declared, Carlos Marras Fernandez Cid: None declared, Jesús Tornero Molina: None declared, Núria Palau: None declared, Raquel M Lastra: None declared, Jordi Lladós: None declared, Sara Marsal: None declared

Background:Blocking of the Tumor Necrosis Factor (TNF) activity is a successful therapeutic approach for 2 out of 3 Rheumatoid Arthritis patients. Identifying the patients that will not respond to this therapeutic approach is a major translational goal in RA. Association of seropositivity to rheumatoid factor (RF) or anti-cyclic-citrullinated antibodies (anti-CCP) with anti-TNF response has proven inconclusive, suggesting that other yet unexplored biomarkers could be more informative for this goal.Objectives:We tested the association of two recently introduced biomarkers in RA: anti-carbamylated protein antibodies (anti-CarP) and anti-peptidylarginine deiminase type 4 (anti-PAD4).Methods:A prospective cohort of n=80 RA patients starting anti-TNF therapy was recruited and levels for all four autoantibodies -RF, anti-CCP, anti-CarP and anti-PAD4- were measured at baseline. The change in DAS28 score between baseline and week 12 of therapy was used as the clinical endpoint.Results:Single marker-analysis showed no significant association with drug response. However, when testing for interactions between autoantibodies, we found highly significant associations with drug response. Anti-CCP and RF showed a positive interaction with the response to anti-TNF therapy (P=0.00068), and anti-PAD4 and antiCarP titers showed a negative interaction with the clinical response at week 12 (P=0.0062). Using an independent retrospective sample (n=199 patients), we validated the interaction between anti-CCP and RF with the clinical response to anti-TNF agents. (P=0.044).Conclusion:The results of this study show that interactions between antibodies are important in the response to anti-TNF therapy and suggest potential pathogenic relationships.Acknowledgments :We would like to thank the clinical researchers and patients participating in the IMID Consortium for their collaborationDisclosure of Interests:Antonio Julià: None declared, Maria Lopez Lasanta: None declared, Francisco Blanco: None declared, Antonio Gómez: None declared, Isabel Haro: None declared, Antonio Juan Mas: None declared, Alba Erra: None declared, Mª Luz García Vivar: None declared, Jordi Monfort: None declared, Simon Sánchez Fernandez: None declared, Isidoro González-Álvaro Grant/research support from: Roche Laboratories, Consultant of: Lilly, Sanofi, Paid instructor for: Lilly, Speakers bureau: Abbvie, MSD, Roche, Lilly, Mercedes Alperi-López: None declared, Raúl Castellanos: None declared, Antonio Fernandez-Nebro: None declared, Cesar Diaz Torne: None declared, Núria Palau: None declared, Raquel M Lastra: None declared, Jordi Lladós: None declared, Raimon Sanmarti: None declared, Sara Marsal: None declared

Objectives:To evaluate the changes promoted in levels of circulating inflammatory mediators in RA patients in response to TNF-α inhibitors (TNFi) and anti-CD20 therapies, in order to identify biomarkers of clinical efficacy and potential predictors of therapeutic response to these drugs.Methods:In a prospective RA cohort multicenter study, we collected serum from RA patients with moderate or high disease activity prior and after 6 months of treatment with TNFi or rituximab (RTX), and analyzed levels of 27 proteins that constitute a multi-biomarker test of the inflammatory profile of these samples, using a multiplex immunoassay. Patients’ response was determined according to the EULAR response criteria (good/moderate/no). We compared basal levels of inflammatory molecules between the differential response patient groups and analyzed their discriminative ability. Logistic prediction models were created to assess the added value of potential inflammatory predictors.Results:Among 111 total RA patients, 50 of 85 (59%) patients in the TNFi group and 18 of 26 patients in the RTX group (69%) responded to the biologic treatment. High DAS28 or SDAI scores, or titers of auto-antibodies (RF or ACPA) at baseline were not predictive of response to any treatment. Instead, smoking habit and hyperlipidemia at baseline were predictors of a worse response to any of these bDMARDs.Of the molecules analyzed by the multiplex assay, 14 inflammatory mediators showed a significant downregulation on patients’ responders to TNFi therapy. Moreover, the decline on 7 biomolecules was related to reduced DAS28. After RTX treatment, 15 inflammatory mediators were reduced in patients with good clinical response; downregulation in 4 of those biomolecules correlated with reduced DAS28.In the search for predictors of response to each bDMARD, by using the MetaboAnalyst software, we could classify patients with distinctive therapeutic response based on the baseline levels of the inflammatory molecules analyzed. Receiver operating characteristic (ROC) analyses for those multiple biomarkers allowed us to further identify specific signatures of inflammatory biomolecules that may serve as predictors of response to each bDMARD therapy with high sensitivity and specificity. Thus, a signature of five molecules was identified as potential predictor of TNFi response [Vascular endothelial growth factor (VEGF), Eotaxin, RANTES, IL7 and IL-17]. Indeed, a signature including three highly expressed cytokines/chemokines in RA serum were identified as predictors of RTX response [interferon-inducible protein 10 (IP10), Eotaxin and monocyte chemotactic protein 1 (MCP-1)].Conclusion:The extensive analysis of serum inflammatory profile allowed to identify specific and distinctive signatures of biomolecules that, in coordination with known clinical and serological profiles, might predict the response of RA patients to TNFi or RTX treatments.Acknowledgments :Funded by Junta de Andalucía (PI-0285-2017), ISCIII, (PI18/00837 and RIER RD16/0012/0015) co-funded with FEDERDisclosure of Interests:María Luque-Tévar: None declared, Carlos Perez-Sanchez: None declared, Font Ugalde Pilar: None declared, Montserrat Romero-Gómez: None declared, Alejandra M. Patiño-Trives: None declared, Desiree Ruiz: None declared, Iván Arias de la Rosa: None declared, Maria del Carmen Abalos-Aguilera: None declared, Rafaela Ortega Castro: None declared, Alejandro Escudero Contreras: None declared, Carlos Rodríguez-Escalera Speakers bureau: Lilly, GSK, Novartis and Sanofi, José Javier Pérez Venegas: None declared, María Dolores Ruiz Montesinos: None declared, Carmen Dominguez: None declared, Carmen Romero Barco: None declared, Antonio Fernandez-Nebro: None declared, Natalia Mena-Vázquez: None declared, Jose Luis Marenco Speakers bureau: ABbvie, Pfzer, lilly, Julia Uceda: None declared, Mª Dolores Toledo-Coello: None declared, Nuria Barbarroja Puerto Grant/research support from: ROCHE and Pfizer., Speakers bureau: ROCHE and Celgene., Maria A Aguirre: None declared, Chary Lopez-Pedrera Grant/research support from: ROCHE and Pfizer., Eduardo Collantes-Estévez Grant/research support from: ROCHE and Pfizer., Speakers bureau: ROCHE, Lilly, Bristol and Celgene.

Background:Objectives:To analyze the effect of disease-modifying antirheumatic drugs (DMARDs) on the outcome of interstitial lung disease secondary to rheumatoid arthritis (ILD-RA).Methods:We performed a multicenter, prospective, observational study of patients with ILD-RA receiving DMARDs between 2015 and 2017. The patients were assessed using high-resolution computed tomography and lung function tests at baseline and at 24 months. The radiological assessment was centralized. The main outcome measure at 24 months was change in lung function (improvement, non-progression, progression, or death). We recorded the 28-joint Disease Activity Score 28 (DAS28) and adverse events. A logistic regression analysis was performed to identify factors associated with progression of ILD.Results:We included 70 patients with ILD-RA treated with DMARDs. The main baseline characteristics are shown in Table 1. After 24 months, lung disease did not progress in 40 patients (57.1%), improved in 8 (11.4%), and progressed in 21 (30.0%). One patient (1.4%) died. The factors associated with progression of ILD in the multivariate analysis were treatment with abatacept, tocilizumab, or rituximab (OR, 0.102 [95%CI, 0.015-0.686]), DAS28 (OR, 1.969 [95%CI, 1.005-3.857]), and smoking (OR, 6.937 [95%CI, 1.378-4.900]). During follow-up, 30 patients (42.9%) experienced an adverse event, which was severe in 12 cases (17.1%).Conclusion:Lung function is stable and inflammatory activity well controlled in most patients with ILD-RA receiving treatment with DMARDs. Non–anti-TNF DMARDs reduce the risk of progression of lung disease in 90% of patients, whereas the inflammatory activity of RA and smoking are associated with progression.Table:VariablePatients=70Epidemiological characteristicsFemale sex, n (%)39 (55.7)Age, y, mean (SD)68.8 (7.8)Clinical-laboratory characteristicsSmoking historyNever smoked, n (%)23 (32.9)Smoked, n (%)47 (67.1)Time since diagnosis of RA,(months),mean (SD)161.0 (125.9)Diagnostic delay,(months),median (IQR)12.0 (5.9-24.0)Time since diagnosis of ILD,(months),mean (SD)42.3 (48.3)Positive rheumatoid factor (>10), n (%)65 (92.0)Anticitrullinated protein antibody (>20), n (%)58 (82.9)Synthetic DMARDs64 (91.4)Methotrexate, n (%)30 (42.9)Leflunomide, n (%)16 (22.9)Sulfasalazine, n (%)8 (11.4)Hydroxychloroquine, n (%)10 (14.3)Biologic DMARDs27 (38.1)Infliximab, n (%)1 (1.4)Etanercept, n (%)4 (5.7)Adalimumab, n (%)1 (1.4)Golimumab, n (%)1 (1.4)Certolizumab, n (%)0 (0.0)Tocilizumab, n (%)5 (6.2)Abatacept, n (%)5 (6.2)Rituximab, n (%)10 (14.3)Other immunosuppressantsMycophenolate, n (%)4 (5.7)Azathioprine, n (%)1 (1.4)Disclosure of Interests:None declared

Background:The mortality in Systemic Lupus Erythematosus (SLE) varies largely across different countries most probably due to social, healthcare and ethnic differences.Objectives:To analyze the causes and identify predictive factors of mortality of SLE in Spain in the present century.Methods:We performed a cross-sectional and retrospective study analyzing data from the RELESSER cohort (Spanish Registry of Systemic Lupus Erythematosus of the Spanish Society of Rheumatology). We included all patients diagnosed with SLE since the year 2000 and recorded sociodemographic, clinical and serological variables, comorbidities and treatments, as well as indicators of disease activity, damage and severity. The characteristics of the deceased patients were compared with those of the survivors, and variables with clinical significance or statistical significance were grouped into multivariate models to determine which ones were independently associated with the outcome of the disease.Results:A total of 2004 patients were included, 88.6% female, the mean age at diagnosis was 38.3 (± 15.3) years, with a mean delay in diagnosis of 28.9 (± 52.6) months. Up to 2.84% of the individuals had died. The leading cause of death was SLE activity (n=16), followed by infections (n=14), vascular events (n=7) and cancer (n=6). The mean age of death was 54.68 (± 20.13) years, and neither age, sex nor delay in diagnosis was independently associated with mortality. The presence of nephritis, depression, severe infections, organ damage (SLICC/ACR DI) or disease activity (SLEDAI), as well as the use of cyclophosphamide, rituximab or high doses of corticosteroids, were predictors of mortality in our cohort. Antimalarial treatment and skin manifestations were linked to improved survival.Conclusion:In the RELESSER cohort, clinical factors, co-morbidities, as well as therapeutic attitudes were associated with a significant increase in mortality in SLE. Interestingly, depression was independently associated to mortality. The activity of the disease and infections continue to be the main causes of death at the beginning of the 21st century amongst our patients.Disclosure of Interests:Clara Moriano: None declared, Jaime Calvo Grant/research support from: Lilly, UCB, Consultant of: Abbvie, Jansen, Celgene, Iñigo Rua-Figueroa: None declared, Elvira Diez Alvarez: None declared, Cristina Bermúdez: None declared, Francisco J López-Longo Grant/research support from: AbbVie and GSK, Speakers bureau: AbbVie, Actelion, Bristol Myers Squibb, GSK, MSD, Pfizer, Roche, and UCB Pharma, María Galindo-Izquierdo: None declared, Alejandro Olive: None declared, Eva Tomero Muriel: None declared, Antonio Fernandez-Nebro: None declared, Mercedes Freire González: None declared, Olaia Fernández- Berrizbeitia: None declared, Ana Pérez Gómez: None declared, Esther Uriarte Isacelaya: None declared, Carlos Marras Fernandez Cid: None declared, Carlos A. Montilla-Morales: None declared, Gregorio Santos Soler: None declared, Ricardo Blanco Grant/research support from: AbbVie, MSD, and Roche, Speakers bureau: AbbVie, Pfizer, Roche, Bristol-Myers, Janssen, and MSD, M. Rodíguez-Gómez: None declared, Paloma Vela-Casasempere: None declared, Alina Boteanu: None declared, J. Narváez: None declared, Victor Martinez Taboada: None declared, Blanca Hernández-Cruz Speakers bureau: Abbvie, Lilly, Sanofi, BMS, STADA, José Luis Andreu: None declared, José A Hernandez Beriain: None declared, Lorena Expósito: None declared, Raúl Menor-Almagro: None declared, Mónica Ibañez Barceló: None declared, Ivan Castellví Consultant of: Boehringer Ingelheim, Actelion, Kern Pharma, Speakers bureau: Boehringer Ingelheim, Actelion, Bristol-Myers Squibb, Roche, Carles Galisteo: None declared, Enrique Raya: None declared, Víctor Quevedo Vila: None declared, Tomas Vazquez Rodriguez: None declared, Jesus Ibañez: None declared, Jose M Pego-Reigosa: None declared

Contains fulltext : 88471.pdf (Publisher’s version ) (Closed access) OBJECTIVE: To investigate the possible association of the BANK1 gene with genetic susceptibility to systemic sclerosis (SSc) and its subphenotypes. METHODS: A large multicentre case-control association study including 2380 patients with SSc and 3270 healthy controls from six independent case-control sets of Caucasian ancestry (American, Spanish, Dutch, German, Swedish and Italian) was conducted. Three putative functional BANK1 polymorphisms (rs17266594 T/C, rs10516487 G/A, rs3733197 G/A) were selected as genetic markers and genotyped by Taqman 5 allelic discrimination assay. RESULTS: A significant association of the rs10516487 G and rs17266594 T alleles with SSc susceptibility was observed (pooled OR=1.12, 95% CI 1.03 to 1.22; p=0.01 and pooled OR=1.14, 95% CI 1.05 to 1.25; p=0.003, respectively), whereas the rs3733197 genetic variant showed no statistically significant deviation. Stratification for cutaneous SSc phenotype showed that the BANK1 rs10516487 G, rs17266594 T and rs3733197 G alleles were strongly associated with susceptibility to diffuse SSc (dcSSc) (pooled OR=1.20, 95% CI 1.05 to 1.37, p=0.005; pooled OR=1.23, 95% CI 1.08 to 1.41, p=0.001; pooled OR=1.15, 95% CI 1.02 to 1.31, p=0.02, respectively). Similarly, stratification for specific SSc autoantibodies showed that the association of BANK1 rs10516487, rs17266594 and rs3733197 polymorphisms was restricted to the subgroup of patients carrying anti-topoisomerase I antibodies (pooled OR=1.20, 95% CI 1.02 to 1.41, p=0.03; pooled OR=1.24, 95% CI 1.05 to 1.46, p=0.01; pooled OR=1.26, 95% CI 1.07 to 1.47, p=0.004, respectively). CONCLUSION: The results suggest that the BANK1 gene confers susceptibility to SSc in general, and specifically to the dcSSc and anti-topoisomerase I antibody subsets. 01 april 2010

Objectives To know the usefulness of follow-up call legalized at the beginning of biologic therapy and patient contact with consultation of nursing after the start of treatment. Methods Observational study cross.Patients: We collected 120 patients who began treatment with biologic therapy, intravenous or subcutaneous from December 2013 to November 2015. Protocol: Protocol is education for self-management of subcutaneous biological therapy at the beginning of the treatment. This Protocol includes a follow-up call from the consultation of nursing that matches the first administration of the treatment at home or within 3–5 days after the first infusion. This call is made in the case of the biological subcutaneous as per guideline: etanercept (7 days), adalimumab (14 days), golimumab (28 days), tocilizumab (7days), certolizumab (14 days), abatacept (7days) either guideline prescribed in case of dose reduction. Offers the possibility of contact (telephone and e-mail) with the consultation of nurses in case of doubt or incidence during treatment and is analytical control to the month of the beginning of nurse telephone consultation. Statistical analysis: a descriptive analysis of the main variables. Results 120 patients with RA initiated treatments were: etanercept 33,3% (n40), adalimumab 8,3% (10), tocilizumab sc 20% (24), abatacept sc 12,5% (15), golimumab 13,3% (16), rituximab 6,7% (8), certolizumab pegol 3,3% (4), biosimilar 2,5% (3). In terms of the associated FAME: none 38,3% (46), methotrexate 49,2% (59), Leflunomide 8.3% (10), sulfasalazine 1,7% (2), hydroxychloroquine 2,5% (3).They were detected in the Protocol call patients with incidences 14,16% (17): local reaction3.3% (4), pruritus 5.8% (7), upset general 0.8% (1), diarrhea 0.8% (1), constipation 0.8% (1), headache 1.7% (2). The patients called the nursing consultation to communicate incidences 10.83% (13): anemia 0.8% (1), hypertransaminasemia 1,7% (2), implant dental 0.8% (1), bruising 0,8% (1), inefficiency 6.7% (8). Also communicated to the consultation of nursing infections during 16.6% (20): urinary tract infection 5,8% (7), upper respiratory tract infection 1,7% (2), upper respiratory tract infection+herpes simplex 0,8% (1), lower respiratory tract infection 3,3% (4), surgical wound infection 0.8% (1), dental infection 0,8% (1), herpes simplex 0,8% (1), gastroenteritis 0,8% (1), not frightening infection 1,7% (2).Patients who started biologic therapy in the period studied only 8.3% (10) changed treatment.The emergence of new comorbidities were detected during treatment with biologic therapy 4,16% (5): hypertension 0,8% (1), hypertension + diabetes mellitus II 1,7% (2), nonspecific Interstitial pneumonia 0,8% (1), psoriasis 0,8% (1). Conclusions The follow-up call is a useful tool for the control of security of the new beginnings of biological agents. It could foster adherence to treatment monitoring at home and offering the possibility to communicate with the nursing. Disclosure of Interest None declared

Background Reliable data regarding the prevalence of specific medical comorbidities among patients with PrimarySjogren9s Syndrome (pSS) remain sparse and there are not comparative studies among patients with pSS and patients with Systemic Lupus Erythematosus (SLE). Objectives To compare the prevalence of the main comorbidities of two large cohorts of patients with pSS and SLE, with focus in cardiovascular (CV) diseases. Methods Cross-sectional multicenter study comparing cumulative prevalence of the most relevant comorbidities, with identical definition in both cohorts. Patients on follow-up from SJOGRENSER (Spanish Register of pSS) and RELESSER (Spanish Register of SLE), fulfilling AECG-2002 and ACR-97 classification criteria, were included. Binomial logistic regression analysis was carried out to explore potential differences, adjusting for age, sex and disease duration with further specific adjustments for each variable, including CV risk factors and treatments, when it was considered convenient. Results 437 pSS (95.2% female) and 2,960 SLE (89.5% female) patients were included. Mean age: 58.6 (p55-p75: 50.0–69.9) and 46.4years (22.4–41.6) respectively (p Patients with pSS were hospitalized by the disease activity lesser than SLE: 17% vs 53%, p The following comorbidities were less prevalent in pSS: Smoking [25.3% vs 48.2%, p Conclusions pSS patients have consistently less serious comorbidity burden compared with SLE patients, namely less CV diseases and less infections. In contrast, the risk of lymphoma exceeds that seen in SLE patients. The higher prevalence of CV events in SLE does not seem to be explained only by traditional CV risk factors, suggesting that SLE derived factors could be involved. Acknowledgement Systemic Autoimmune Diseases Group of Spanish Society of Rheumatology (EAS-SER) and SER Research Unit Disclosure of Interest None declared

Background Genome-wide association studies (GWAS) in Psoriatic Arthritis (PsA)patients and controls have allowed the identification of multiple variants associated with disease risk. To date, however, no GWAS for PsA phenotypes has been reported. Objectives The main objective of this study was to identify new genetic variation associated with clinical phenotypes in PsA. Methods A total of n=835 patients diagnosed with PsA using CASPAR criteria were recruited in the discovery stage and genotyped for >600,000 single nucleotide polymorphisms. GWAS were performed for clinical and biological phenotypes associated with joint and skin disease. After allelic association analysis, those SNPs with highest level of significance were analyzed in an independent cohort of n=414 PsA patients. Results In the GWAS stage, several genomic regions showing high evidence of association with different PsA phenotypes (P Conclusions Usign a GWAS approach, new loci associated with axial and peripheral disease in PsA have been identified. Disclosure of Interest None declared

Objectives To study the adherence to biologic therapy (BT) in patients with RA. Methods Design :Cross-sectional study. Patients: Consecutive sampling stratified by route of administration in the biological therapy unit (UTB). Protocol: Patients with sc BT are alternately reviewed every 3 months in general and specific (only BT pts) outpatient clinic. Iv BT patients are checked each time the drug is infused. Both groups of pts are reviewed according to a predetermined protocol of data collection. At the start of BT all subjects are interviewed by a nurse who explains the mode of application of drugs and emphasizing the importance of adherence to the effectiveness and safety of BT. Outcome variables: (1) level of adherence evaluated by Morisky-Green Test (MGT) and withdrawal drug in hospital pharmacy or drugstore (medication possession ratio [MPR]). Good adherence was considered when 4 responses indicative of adherence were given in MGT and a MPR>80%. The attendance rate to infusions was handled as equivalent to the medication possession ratio. Other variables: Demographics, comorbidities, clinical-analytical and synthetic DMARDs reclaim in the drugstores using “XXI electronic prescription”(a software used to control the dispensations in the public health system in Andalusia) in the last 6 months. Statistical analysis: Bivariate analyses were performed using T student test, Mann Whitney U test and Ji square test, followed by binary logistic regression (BLR). Results The main characteristics of the patients (n=178) are shown in the table. One hundred and twelve (63%) were with sc BT, 66 (37%) with iv BT and 49 patients (27.5%) were in monotherapy. 123/178 (69%) showed good adherence to BT and 67/129 (52%) took correctly concomitant synthetic DMARDs. Good adherence to BT was associated in the bivariate analyses with better control of the disease measured by DAS28 (p Conclusions Adherence to BT of patients with RA in a specific unit is moderate (69.1%) and adherence to the concomitant synthetic DMARDs is bad (52.7%).Patients with moderate or high activity in the previous 6 months, have 4.5 odds of having a bad adherence to FAMEb compared to those who are in remission or have low activity. Likewise, patients who do not take in proper manner associated biological DMARDs are 5.4 times more likely to have bad adherence to FAMEb. Disclosure of Interest None declared

Background Systemic lupus erythematosus (SLE) is a genetically complex rheumatic disease with heterogeneous clinical manifestations. Recent studies have suggested the existence of a genetic basis for the diverse SLE clinical phenotypes. Also, there is increasing evidence indicating that a substantial part of the genetic variation associated with complex diseases is explained by small-effect genes from common genetic pathways. Objectives The objective of the present study was to identify new genetic variation associated with SLE phenotypes using a genome-wide association study at the pathway level. Methods A total of 598,258 SNPs were genotyped in a discovery cohort of n=482 SLE patients of southern European ancestry using the Illumina platform Quad610. After quality control analysis, including ancestry estimation using principal-component analysis, genome-wide pathway analysis was performed. A total of 14 clinically relevant SLE phenotypes were tested for association with n>700 reference genetic pathways. Significantly associated pathways (corrected P-value in silico analysis on cell types of relevance in SLE pathogenesis. Results In the discovery stage, two genetic pathways were significantly associated with the presence of oral ulcers and antinuclear antibodies in SLE ( P FDR VEGF ) genetic pathway ( P =1.3e-2). Analyzing the transcriptional effect of the topical immunotherapies used for the treatment of oral ulcers in SLE, we found a significant differential expression of VEGF pathway genes ( P Conclusions In this work we have performed the first genome-wide association study for clinically relevant SLE phenotype using a pathway-based approach. With this new approach, we have identified and validated the association of VEGF genetic pathway with oral ulcers in SLE. These findings represent an important step towards the characterization of the genetic basis of phenotype heterogeneity in SLE. Disclosure of Interest None declared

Background Since insomnia is a chronic problem in patients with chronic diseases, factors that are associated with it are varied. Objectives To study the variables associated with the severity of insomnia according to the questionnaire of Oviedo9s dream (QOD) in patients with spondylarthritis (AE) and psoriatic arthritis (PsA), including the activity of the disease as measured by restriction, BASDAI and DAS28. Methods Design. Descriptive cross-sectional study. Patients: Were selected by sampling consecutive patients with AE or PsA in follow-up by our unit of biologic therapy. Inclusion criteria: adults (≥16 years old) with AE (ASAS criteria) or PsA (CASPAR criteria) capable of understanding and willing to make the questionnaires. Exclusion criteria: other rheumatic diseases, age Results 120 patients participated: 60 patients with ad (36.7% women, 45, 1±10, 6 years) and 60 patients with APs (58.6% women, 49, 9±9, 2 years). The most common comorbidities were: anxiety, depression, and disc disease. Women had more multimorbidity (p=0, 047) and osteoporosis (p Conclusions The insomnia and hypersomnia are 2 health problems strongly linked to pain and fatigue in patients with AE ans PsA but not with the activity of the disease. It would be necessary to work in nursing consultation the improvement in the management of sleep in these patients in a structured way to decrease the impact of insomnia and hypersomnia. Disclosure of Interest None declared

Background Rheumatoid arthritis (RA) is a complex disease of unknown etiology, involving both genetic and environmental factors. Objectives The aim of this study was to analyze the more relevant epidemiological characteristics in a large cohort of patients with RA and controls in the Spanish population. Methods A cross-sectional,comparative,multicenter study of patients with RA and hypernormal healthy subjects for IMID diseases was performed.All patients were recruited through the Immune-Mediated Inflammatory Diseases Consortium (IMIDC).The IMIDC is a network of Spanish biomedical researchers focused in the study of the molecular basis of IMID diseases.All patients included in the present study were selected from the outpatient clinics of 12 Rheumatology Departments at different Spanish university hospitals.An epidemiological questionnaire developed by experts at DNA National Bank was applied to obtain all data. Results 2,366 RA patients and 1,558 healthy subjects were included.77% of RA patients and 40% of controls were female.The mean age of patients with RA was 60±13 years and controls 49±7 years.The height and weight of controls was significantly higher than in patients with RA.The level of statistical significance was decreased by introducing gender and age as covariates.In our cohort,65% of patients with RA had no education or only primary education.Control subjects mostly had secondary or higher education.The physical exercise was significantly more frequent in controls.The gender and age affect the assessment of physical activity performed by both groups of patients.Regarding employment status,most patients with RA were housewives (43%) whereas in controls were external employers (44%).RA patients most frequently used public transportation (39%) while controls use their cars (52%).The mean consumption of tobacco, alcohol and coffee was higher in controls but the significance level decreased in multivariate analysis,confirming the influence of gender and age on these variables.The average number of children in RA patients was higher than controls,a difference that was not confirmed by including confounding factors. Conclusions In this large comparative study we describe for the first time the general epidemiological characteristics in patients with RA and healthy subjects representative of the Spanish population.RA patients are older as compared with controls and most of them are housewives with no education or primary education.The influence of gender confirms the significance level of physical activity,alcohol consumption, smoking, coffee intake, weight, height and average number of children. Disclosure of Interest None declared

Background The recent advances in metabolomics have allowed the study of the regulatory processes linked to metabolism. The holistic analysis of the metabolites in biological samples can provide new insights to identify pathological processes and to develop new biomarkers. The present study represents the first high-throughput metabolomics analysis of immune-mediated inflammatory diseases (IMIDs). Objectives Identification and validation of diagnostic and activity biomarkers through the analysis of the urine metabolome within two independent cohorts of >2,500 individuals including healthy controls and IMID patients. Methods The metabolomics analysis was performed using nuclear magnetic resonance on 2 independent cohorts. The discovery cohort included 100 controls and 200 patients per IMID: rheumatoid arthritis (RA), psoriatic arthritis (PsA), psoriasis (Ps), ulcerative colitis (UC), Crohn9s disease (CD), and systemic lupus erythematosus (SLE). The validation cohort included 200 controls and 200 patients per IMID. The patients of each IMID were selected to define 2 groups: low and high disease activity patients. n=37 metabolites were accurately quantified. The association analyses were performed at 3 levels: diagnostic -comparing each IMID vs controls-, differential -comparing similar IMIDs between them-, and activity -comparing low and high activity patients of each IMID-. The statistical analysis was performed using linear regression adjusted by epidemiological variables. Results The diagnostic analysis identified n=41 disease-metabolite associations, from which n=37 were replicated in the validation cohort. These associations involved n=15 different metabolites from which n=6 were jointly associated to ≥3 IMIDs (Figure). When analyzing differences between IMIDs, we validated n=6 associations: n=5 when comparing CD vs UC, and n=1 when comparing RA vs PsA. We also validated at the nominal level 2 more associations related with CD vs UC and RA vs PsA. The analysis of disease activity identified and validated n=3 associations related with disease activity in CD patients. We also validated at the nominal level n=2 associations in UC and n=1 association in PsA, SLE and CD. Conclusions We have identified and validated significant differences in metabolite concentrations when comparing IMID patients vs healthy controls. CD, UC and RA gathered the largest number of metabolic associations. Importantly, n=6 metabolites were associated to ≥3 IMIDs. These metabolites are then candidate proxies for the physiopathological processes shared by these diseases. Regarding to the discrimination between related IMIDs, the urine metabolome has shown significant differences when comparing CD vs UC and RA vs PsA. The disease activity analysis also identified significant associations but with a lower impact than that from the diagnostic analysis. Disclosure of Interest None declared