Porphyromonas gingivalis peptidylarginine deiminase as a risk factor for the response to cytokine targeted therapy in patients with rheumatoid arthritis

Background:Idiopathic juvenile arthritis (JIA) is a heterogeneous group of pathologies whose origin remains unknown at present (1). They are characterised by a systemic inflammatory and joint disease affecting children under 16 years of age. The current classification groups the different forms of JIA into 7 distinct entities (systemic forms, polyarticular forms with or without rheumatoid factors, oligoarticular forms, inflammatory arthritis associated with enthesopathies (ERA), arthritis associated with psoriasis and unclassifiable arthritis). Exact etiology of JIA is still unknown. To date, the various hypotheses put forward on the occurrence of JIAs integrate the genetic and environmental framework.The link between periodontal disease and rheumatoid arthritis (RA) is largely reported. Recently, Porphyromonas gingivalis (P. gingivalis) infection explained the occurrence of arthritis in rodent and in RA (2). Several studies mention the beneficial effect of P. gingivalis treatment on disease activity.Currently, there are very few studies on the prevalence of P. gingivalis in patients with JIA and the possible involvement of the germ in the development of inflammatory joint diseases in the pediatric population(3)(4).Objectives:The objective of our study is to determine presence of high IgG antibodies against P. gingivalis and Prevotella Intermedia in a cohort of patients with JIA compared to a control population and to determine variation of level according to sub-classes of JIA.Methods:Sera were obtained from 101 patients satisfying the ILAR classification criteria for JIA and in 25 patients with two other dysimmune disorders (type 1 diabetes and juvenile inflammatory bowel disease). Level of IgG antibodies against P. gingivalis and Prevotella Intermedia were obtained by homemade ELISA already used previously (5).Results:In the JIA group, major children were oligarthritis (47.5%), polyarthritis represents 31.7% of JIAs, ERA and systemic forms of JIA are respectively 9 and 11%. For the control group, 10 (40%) children had diabetes and 15 (60%) had IBD.Levels of anti-P. gingivalis anti-Prevotella Intermedia antibodies were higher in AJI group compared at control groups (P<0.01, P<0.05). Theses difference are mainly related to oligoarthritis and ERA subsets for both P. gingivalis and Prevotella Intermedia.Figure 1.Relative titer of antibodies to P. gingivalis and anti Prevotella intermedia. *: P<0.05; **: P<0.01; ***: P<0.001. P. gingivalis (control vs oligoarthritis p= 0.0032. control vs ERA p= 0.0092). Prevotella intermedia (control vs oligoarthritis p= 0.0194. control vs ERA p= 0.0039).Conclusion:We confirmed high level of anti-P. gingivalis and anti-Prevotella intermedia antibodies in JIA compared to other inflammatory disorders. For the first time, we observed that this high level was mainly in oligoarthritis and ERA. Further investigations are required to investigate involvement of oral dysbiosis in AJI pathogenesis. As observed in RA, it could be a new way to integrate in JIA therapy management.References:[1]Thatayatikom A, De Leucio A. Juvenile Idiopathic Arthritis (JIA). StatPearls Publishing; 2020[2]Cheng Z, Meade J, Mankia K, Emery P, Devine DA. Periodontal disease and periodontal bacteria as triggers for rheumatoid arthritis. Best Pract Res Clin Rheumatol. 2017;31(1):19–30.[3]Romero-Sánchez C, Malagón C, Vargas C, Fernanda Torres M, Moreno LC, Rodríguez C, et al. Porphyromonas Gingivalis and IgG1 and IgG2 Subclass Antibodies in Patients with Juvenile Idiopathic Arthritis. J Dent Child Chic Ill. 2017 May 15;84(2):72–9.[4]Lange L, Thiele GM, McCracken C, Wang G, Ponder LA, Angeles-Han ST, et al. Symptoms of periodontitis and antibody responses to Porphyromonas gingivalis in juvenile idiopathic arthritis. Pediatr Rheumatol Online J. 2016 Feb 9[5]Rinaudo-Gaujous M, Blasco-Baque V, Miossec P, Gaudin P, Farge P, Roblin X, et al. Infliximab Induced a Dissociated Response of Severe Periodontal Biomarkers in Rheumatoid Arthritis Patients. J Clin Med. 2019 May 26;8(5).Disclosure of Interests:None declared.

Download Full-text

Is periodontitis a risk factor for rheumatoid arthritis?

BDJ ◽

10.1038/s41415-021-2965-4 ◽

2021 ◽

Vol 230 (8) ◽

pp. 532-532

Author(s):

Reena Wadia

Keyword(s):

Rheumatoid Arthritis ◽

Risk Factor

Download Full-text

AB0138 A MOLECULAR SIGNATURE RESPONSE CLASSIFIER STRATIFIES SEROPOSITIVE RHEUMATOID ARTHRITIS PATIENTS BASED ON THEIR LIKELIHOOD OF INADEQUATE RESPONSE TO TNF INHIBITOR THERAPIES

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2021-eular.3307 ◽

2021 ◽

Vol 80 (Suppl 1) ◽

pp. 1096.3-1097

Author(s):

S. Cohen ◽

V. Strand ◽

E. Connolly-Strong ◽

J. Withers ◽

L. Zhang ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Targeted Therapy ◽

Tumor Necrosis Factor ◽

Tumor Necrosis ◽

Molecular Signature ◽

Inadequate Response ◽

Tnf Inhibitor ◽

Odds Ratios ◽

Selection For ◽

Necrosis Factor

Background:There is an urgent need for precision medicine in targeted therapy selection for the treatment of rheumatoid arthritis (RA). TNF inhibitor (TNFi) therapies are the most prescribed targeted therapy for RA patients, yet the majority of patients fail to achieve a clinically meaningful response using this medication class. A blood-based molecular signature test evaluates RNA and clinical metrics to stratify RA patients based on their likelihood of having an inadequate response to TNFi therapies.1 Patients unlikely to respond to TNFi therapies can be directed to a different treatment option such as a JAK inhibitor, thus reducing the time needed to identify an effective therapy, improving confidence in and adherence to treatment, and increasing the patients’ chance of reaching treat-to-target goals.Objectives:High-titers of anti-cyclic citrillunated protein (anti-CCP) have been independently associated with reduced response to TNFi therapy;2 thus, we evaluated the ability of a blood-based molecular signature response classifier (MSRC) test to stratify RA patients by their likelihood of inadequate response to TNFi therapies – regardless of their positive or negative anti-CCP status.Methods:A subset of patients enrolled in the Network-04 prospective observational trial evaluating the ability of a molecular signature response classifier to stratify patients were subdivided into two groups based upon whether they were positive (N = 72) or negative (N = 74) for anti-CCP. The odds of inadequate response to TNFi therapies were calculated based on whether or not a patient had a molecular signature of non-response to TNFi therapy at baseline before the start of treatment. Odds ratios and confidence intervals were calculated3,4 to represent the strength of association between detecting the molecular signature of non-response and the patient’s failure to achieve ACR50 at 6 months.Results:The odds that a patient with a molecular signature of non-response failed to meet ACR50 criteria at 6 months was approximately three times greater than among those patients who lacked the signal (Table 1). No significant difference in odds ratios was observed between patients who were positive or negative for anti-CCP.Table 1.The odds of patients with a molecular signature of non-response failing to achieve an ACR50 response 6 months after TNF inhibitor therapy initiationOdds ratio (95% confidence interval)Anti-CCP positive3.5 (1.3-9.7)Anti-CCP negative3.1 (1.2-8.3)Conclusion:The MSRC test evaluates RA disease biology and accurately stratifies patients based on their likelihood of having an inadequate response to TNFi therapies, regardless of being negative or positive for anti-CCP autoantibodies. Rheumatologists can use the results of the MSRC test to inform targeted therapy selection for RA patients, instead of their anti-CCP serostatus, eliminating the variability inherent to the anti-CCP measurement and its inability to consistently predict TNFi therapy incompatibility. With the MSRC test, providers can rely on a more predictable and accurate assessment of TNFi therapy success or failure when coordinating patient management.References:[1]Mellors, T. et al. Clinical Validation of a Blood-Based Predictive Test for Stratification of Response to Tumor Necrosis Factor Inhibitor Therapies in Rheumatoid Arthritis Patients. Network and Systems Medicine3, 91-104, doi:10.1089/nsm.2020.0007 (2020).[2]Braun-Moscovici, Y. et al. Anti-cyclic citrullinated protein antibodies as a predictor of response to anti-tumor necrosis factor-alpha therapy in patients with rheumatoid arthritis. J Rheumatol33, 497-500 (2006).[3]Szumilas, M. Explaining odds ratios. J Can Acad Child Adolesc Psychiatry19, 227-229 (2010).[4]Sperandei, S. Understanding logistic regression analysis. Biochem Med (Zagreb) 24, 12-18, doi:10.11613/BM.2014.003 (2014).Disclosure of Interests:Stanley Cohen: None declared, Vibeke Strand Consultant of: Abbvie, Amgen, Arena, BMS, Boehringer Ingelheim, Celltrion, Galapagos, Genentech/Roche, Gilead, GSK, Ichnos, Inmedix, Janssen,Kiniksa, Lilly,Merck, Novartis, Pfizer, Regeneron, Samsung, Sandoz, Sanofi, Setpoint, UCB, Erin Connolly-Strong Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation, Johanna Withers Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation, Lixia Zhang Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation, Ted Mellors Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation, Viatcheslav Akmaev Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation

Download Full-text

SAT0077 CARDIOVASCULAR RISK ASSESSMENT WITH CAROTID ULTRASONOGRAPHY IN ADDITION TO THE TRADITIONAL CARDIOVASCULAR RISK FACTORS IN RHEUMATOID ARTHRITIS PATIENTS: A CASE CONTROL STUDY

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2020-eular.6420 ◽

2020 ◽

Vol 79 (Suppl 1) ◽

pp. 973-973

Author(s):

R. Gonzalez Mazario ◽

J. J. Fragio-Gil ◽

P. Martinez Calabuig ◽

E. Grau García ◽

M. De la Rubia Navarro ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Risk Factors ◽

Risk Factor ◽

Cardiovascular Risk ◽

Disease Duration ◽

Case Control Study ◽

Case Control ◽

Healthy Controls ◽

Carotid Ultrasonography ◽

Control Study

Background:Cardiovascular disease (CV) is the most frequent cause of death in rheumatoid arthritis (RA) patients. It is well known that RA acts as an independent cardiovascular risk factor.Objectives:To assess the CV risk in RA patients using carotid ultrasonography (US) additionally to the traditional CV risk factors.Methods:A prospective transversal case control study was performed, including adult RA patients who fulfilled ACR/EULAR 2010 criteria and healthy controls matched according to CV risk factors. Population over 75 years old, patients with established CV disease and/or chronic kidney failure (from III stage) were excluded. The US evaluator was blinded to the case/control condition and evaluated the presence of plaques and the intima-media thickness. Statistical analysis was performed with R (3.6.1 version) and included a multivariate variance analysis (MANOVA) and a negative binomial regression adjusted by confounding factors (age, sex and CV risk factors).Results:A total of 200 cases and 111 healthy controls were included in the study. Demographical, clinical and US data are exposed in table 1. Not any difference was detected in terms of CV risk factors between the cases and controls. In both groups a relationship between age, BMI and high blood pressure was detected (p<0.001).Table 1.Table 2.RA basal characteristicsDisease duration (years)16,98 (11,38)Erosions (X-Ray of hands/feet)163 (81,5%)Seropositive (RF/anti-CCP)146 (73%)Extra-articular symptoms44 (22%)Intersticial difusse lung disease10 (5%)Rheumatoid nodules14 (7%)Prednisone use103 (51,5%)Median dose of Prednisone last year (mg)2,34 (2,84)sDMARDsMethotrexate104 (52%)Leflunomide29 (14,5%)Hydroxycloroquine9 (4,5%)bDMARDs89 (44,5%) TNFi41 (20,5%) Abatacept15 (7,5%) IL6i22 (11%) RTX11 (5,5%)JAKi26 (13%) Baricitinib11 (5,5%) Tofacitinib15 (7,5%)DAS 28-ESR3,1 (2,3, 3,9)SDAI7,85 (4,04, 13,41)HAQ0,88 (0,22, 1,5)RF (U/mL)51 (15, 164,25)Anti-CCP (U/mL)173 (22, 340)Patients showed higher intima-media (both right and left) thickness compared to controls (p<0.006). Moreover it was also related to the disease duration and DAS28 score (p<0.001). A higher plaque account was noted in cases(p<0.004) and it was also related to the disease duration (p<0.001).Conclusion:RA implies a higher CV risk. Traditional CV risk factors explains only partially the global risk. These findings support that RA acts as an independent cardiovascular risk factor.Disclosure of Interests:None declared

Download Full-text

FRI0443 CLINICAL CHARACTERISTICS AND RELATED FACTORS OF COMMON RHEUMATIC DISEASES COMPLICATED WITH TUBERCULOSIS INFECTION

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2020-eular.3717 ◽

2020 ◽

Vol 79 (Suppl 1) ◽

pp. 819.1-819

Author(s):

L. Long ◽

G. Tang ◽

Y. Han ◽

Q. Peng ◽

J. Liu ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Weight Loss ◽

Risk Factor ◽

High Risk ◽

Rheumatic Diseases ◽

Clinical Characteristics ◽

Control Group ◽

Average Dose ◽

Systemic Lupus ◽

Infection Group

Background:Rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and syndrome(SS) are common rheumatic diseases with high incidence. Patients with those rheumatic diseases are at high risk of tuberculosis (TB) infection. However, manifestations can be atypical and easily confused with those of rheumatic disease itself. For those patients, diagnosis is usually much more difficult and further make treatment delayed. Sometimes it may lead to mistreatment. Therefore, it is important to recognize the clinical characteristics of those patients.Objectives:To explore the clinical characteristics and high risk factors of common systemic rheumatism complicated with tuberculosis infection.Methods:A total of 3,906 cases of RA, SLE, and SS common systemic rheumatism diagnosed in the People’s Hospital of Sichuan Province from January 2007 to January 2017 were collected with carefully exclusion with other infectious diseases and neoplastic disease. One hundred and five patients with TB were included as infection group, including 42 cases of RA, 41 cases of SLE, and 22 cases of SS. In the control group, 84 patients with RA, 82 patients with SLE, and 44 patients with SS were randomly selected from the corresponding rheumatoid non-infected patients hospitalized during the same period.Results:Fever was the most common symptom among 42 cases of RA, 41 cases of SLE, and 22 cases of SS with TB, accounting for 83.3%, 92.7%, and 68.2%, respectively. Cough, weight loss or fatigue was less common. For 41 cases of SLE and 22 cases of SS with TB, the proportion of pulmonary was 46.3%, 59.01%, respectively.In TB infection group, 27 cases of RA, 21 cases of SLE, and 13 cases of SS with TB had two or more chest CT findings, accounting for 59%, 57%, 62%, respectively. Lesions located in the posterior or posterior segment which TB usually affected were 9 cases(33.3%),9cases(42.9%),6cases(27.2%),respectively.The daily average dose of hormones within 1 year in TB infection group was higher than that in the control group (P<0.05). For SLE patients, lower counts of CD4+TL were found in TB infection group (P<0.05), while no such differences were found in RA and SS group.Conclusion:Patients with RA who have TB infection are mainly pulmonary TB. For SLE and SS patients, the chance of pulmonary tuberculosis and extra-pulmonary tuberculosis is similar.Symptoms of RA, SLE, SS with TB, such as fever, cough, weight loss, fatigue, are similar with the primary disease or other infection. Chest imaging is diversity. It is difficult to diagnose.Daily average dose of hormone within one year may be a common risk factor for RA, SLE and SS patients with TB. Decreased CD4+TL may also be a risk factor for SLE patients with TB.References:[1]Cantini F, Nannini C, Niccoli L, et al. Risk of Tuberculosis Reactivation in Patients with Rheumatoid Arthritis, Ankylosing Spondylitis, and Psoriatic Arthritis Receiving Non-Anti-TNF-Targeted Biologics[J]. Mediators of Inflammation, 2017, 2017(6):1-15.[2]Ruangnapa K, Dissaneewate P, Vachvanichsanong P. Tuberculosis in SLE patients: rare diagnosis, risky treatment.[J]. Clinical & Experimental Medicine, 2015, 15(3):429-432.[3]Manuela D F, Bruno L, Martina S, et al. Lung Infections in Systemic Rheumatic Disease: Focus on Opportunistic Infections[J]. International Journal of Molecular Sciences, 2017, 18(2):293-315.[4]Disseminated tuberculosis masquerading as a presentation of systemic lupus erythematosus.Li JC, Fong W, Wijaya L, Leung YY.Int J Rheum Dis. 2017 Oct 2. doi: 10.1111/1756-185X.13195.[5]Handa R, Upadhyaya S, Kapoor S, et al. Tuberculosis and biologics in rheumatology: India – A special situation[J]. International Journal of Rheumatic Diseases, 2017, 51(2):115.Disclosure of Interests:None declared

Download Full-text