Response to biologic drugs in patients with rheumatoid arthritis and antidrug antibodies

IMPORTANCE There are conflicting data on the association of antidrug antibodies with response tobiologic disease–modifying antirheumatic drugs (bDMARDs) in rheumatoid arthritis (RA).OBJECTIVE To analyze the association of antidrug antibodies with response to treatment for RA.DESIGN, SETTING, AND PARTICIPANTS This cohort study analyzed data from the ABI-RA (Anti-Biopharmaceutical Immunization: Prediction and Analysis of Clinical Relevance to Minimize the Riskof Immunization in Rheumatoid Arthritis Patients) multicentric, open, prospective study of patientswith RA from 27 recruiting centers in 4 European countries (France, Italy, the Netherlands, and theUK). Eligible patients were 18 years or older, had RA diagnosis, and were initiating a new bDMARD.Recruitment spanned from March 3, 2014, to June 21, 2016. The study was completed in June 2018,and data were analyzed in June 2022.EXPOSURES Patients were treated with a new bDMARD: adalimumab, infliximab (grouped as anti–tumor necrosis factor [TNF] monoclonal antibodies [mAbs]), etanercept, tocilizumab, and rituximabaccording to the choice of the treating physician.MAIN OUTCOMES AND MEASURES The primary outcome was the association of antidrug antibodypositivity with EULAR (European Alliance of Associations for Rheumatology; formerly, EuropeanLeague Against Rheumatism) response to treatment at month 12 assessed through univariate logisticregression. The secondary end points were the EULAR response at month 6 and at visits from month6 to months 15 to 18 using generalized estimating equation models. Detection of antidrug antibodyserum levels was performed at months 1, 3, 6, 12, and 15 to 18 using electrochemiluminescence (MesoScale Discovery) and drug concentration for anti-TNF mAbs, and etanercept in the serum wasmeasured using enzyme-linked immunosorbent assay.RESULTS Of the 254 patients recruited, 230 (mean [SD] age, 54.3 [13.7] years; 177 females [77.0%])were analyzed. At month 12, antidrug antibody positivity was 38.2% in patients who were treatedwith anti-TNF mAbs, 6.1% with etanercept, 50.0% with rituximab, and 20.0% with tocilizumab.There was an inverse association between antidrug antibody positivity (odds ratio [OR], 0.19; 95% CI,0.09-0.38; P all the visits starting at month 6 using generalized estimating equation models confirmed the inverseassociation between antidrug antibody positivity and EULAR response (OR, 0.35; 95% CI, 0.18-0.65;P P = .03). In the multivariable analysis, antidrug antibodies, body mass index, and rheumatoid factorwere independently inversely associated with response to treatment. There was a significantly higher drug concentration of anti-TNF mAbs in patients with antidrug antibody–negative vs antidrugantibody–positive status (mean difference, −9.6 [95% CI, −12.4 to −6.9] mg/L; P concentrations of etanercept (mean difference, 0.70 [95% CI, 0.2-1.2] mg/L; P = .005) andadalimumab (mean difference, 1.8 [95% CI, 0.4-3.2] mg/L; P = .01) were lower in nonresponders vsresponders. Methotrexate comedication at baseline was inversely associated with antidrugantibodies (OR, 0.50; 95% CI, 0.25-1.00; P = .05).CONCLUSIONS AND RELEVANCE Results of this prospective cohort study suggest an associationbetween antidrug antibodies and nonresponse to bDMARDs in patients with RA. Monitoring antidrugantibodies could be considered in the treatment of these patients, particularly nonresponders tobiologic RA drugs.Pathophysiology and treatment of rheumatic disease

Clinicogenomic factors of biotherapy immunogenicity in autoimmune disease: a prospective multicohort study of the ABIRISK consortium

BackgroundBiopharmaceutical products (BPs) are widely used to treat autoimmune diseases, but immunogenicity limits their efficacy for an important proportion of patients. Our knowledge of patient-related factors influencing the occurrence of antidrug antibodies (ADAs) is still limited.Methods and findingsThe European consortium ABIRISK (Anti-Biopharmaceutical Immunization: prediction and analysis of clinical relevance to minimize the RISK) conducted a clinical and genomic multicohort prospective study of 560 patients with multiple sclerosis (MS, n = 147), rheumatoid arthritis (RA, n = 229), Crohn's disease (n = 148), or ulcerative colitis (n = 36) treated with 8 different biopharmaceuticals (etanercept, n = 84; infliximab, n = 101; adalimumab, n = 153; interferon [IFN]-beta-1a intramuscularly [IM], n = 38; IFN-beta-1a subcutaneously [SC], n = 68; IFN-beta-1b SC, n = 41; rituximab, n = 31; tocilizumab, n = 44) and followed during the first 12 months of therapy for time to ADA development. From the bioclinical data collected, we explored the relationships between patient-related factors and the occurrence of ADAs. Both baseline and time-dependent factors such as concomitant medications were analyzed using Cox proportional hazard regression models. Mean age and disease duration were 35.1 and 0.85 years, respectively, for MS; 54.2 and 3.17 years for RA; and 36.9 and 3.69 years for inflammatory bowel diseases (IBDs). In a multivariate Cox regression model including each of the clinical and genetic factors mentioned hereafter, among the clinical factors, immunosuppressants (adjusted hazard ratio [aHR] = 0.408 [95% confidence interval (CI) 0.253-0.657], p < 0.001) and antibiotics (aHR = 0.121 [0.0437-0.333], p < 0.0001) were independently negatively associated with time to ADA development, whereas infections during the study (aHR = 2.757 [1.616-4.704], p < 0.001) and tobacco smoking (aHR = 2.150 [1.319-3.503], p < 0.01) were positively associated. 351,824 Single-Nucleotide Polymorphisms (SNPs) and 38 imputed Human Leukocyte Antigen (HLA) alleles were analyzed through a genome-wide association study. We found that the HLA-DQA1*05 allele significantly increased the rate of immunogenicity (aHR = 3.9 [1.923-5.976], p < 0.0001 for the homozygotes). Among the 6 genetic variants selected at a 20% false discovery rate (FDR) threshold, the minor allele of rs10508884, which is situated in an intron of the CXCL12 gene, increased the rate of immunogenicity (aHR = 3.804 [2.139-6.764], p < 1 x 10(-5) for patients homozygous for the minor allele) and was chosen for validation through a CXCL12 protein enzyme-linked immunosorbent assay (ELISA) on patient serum at baseline before therapy start. CXCL12 protein levels were higher for patients homozygous for the minor allele carrying higher ADA risk (mean: 2,693 pg/ml) than for the other genotypes (mean: 2,317 pg/ml; p = 0.014), and patients with CXCL12 levels above the median in serum were more prone to develop ADAs (aHR = 2.329 [1.106-4.90], p = 0.026). A limitation of the study is the lack of replication; therefore, other studies are required to confirm our findings.ConclusionIn our study, we found that immunosuppressants and antibiotics were associated with decreased risk of ADA development, whereas tobacco smoking and infections during the study were associated with increased risk. We found that the HLA-DQA1*05 allele was associated with an increased rate of immunogenicity.Moreover, our results suggest a relationship between CXCL12 production and ADA development independent of the disease, which is consistent with its known function in affinity maturation of antibodies and plasma cell survival. Our findings may help physicians in the management of patients receiving biotherapies.Author summaryWhy was this study done?Biopharmaceutical products such as monoclonal antibodies are widely used to treat autoimmune diseases.Biopharmaceutical products may induce the development of antidrug antibodies, which often lead to therapy failure.Patient-related factors that influence the development of antidrug antibodies need to be characterized.What did the researchers do and find?We set up a European multicohort prospective study on 4 autoimmune diseases (multiple sclerosis, rheumatoid arthritis, Crohn's disease, and ulcerative colitis) treated with 8 different biopharmaceutical products.We collected demographic and clinical data and tested antidrug antibodies in longitudinal serum samples from 560 patients. For 457 patients who gave consent, we also collected genetic data.We identified antibiotics and immunosuppressants as negatively associated risk factors and heavy smoking, infections during the study, the allele and a minor variant in the chemokine gene associated with increased protein expression as risk factors of antidrug antibody development.What do these findings mean?Our findings suggest that the combination of immunosuppressant and biopharmaceutical therapy could be associated with decreased risk of antidrug antibody occurrence, which has implications for rheumatoid arthritis and inflammatory bowel diseases, for which immunosuppressants are often, but not always, given together with biopharmaceuticals.Patients heterozygotes or homozygotes for the HLA-DQA1*05 allele may have an increased risk of antidrug antibody occurrence associated with biopharmaceutical therapy.The small study size warrants a validation through independent studies, in particular for the genetic findings

Содержание. Секция 07 - Оптика и спектроскопия

The remarkable complexity of soil and its importance to a wide range of ecosystem services presents major challenges to the modeling of soil processes. Although major progress in soil models has occurred in the last decades, models of soil processes remain disjointed between disciplines or ecosystem services, with considerable uncertainty remaining in the quality of predictions and several challenges that remain yet to be addressed. First, there is a need to improve exchange of knowledge and experience among the different disciplines in soil science and to reach out to other Earth science communities. Second, the community needs to develop a new generation of soil models based on a systemic approach comprising relevant physical, chemical, and biological processes to address critical knowledge gaps in our understanding of soil processes and their interactions. Overcoming these challenges will facilitate exchanges between soil modeling and climate, plant, and social science modeling communities. It will allow us to contribute to preserve and improve our assessment of ecosystem services and advance our understanding of climate-change feedback mechanisms, among others, thereby facilitating and strengthening communication among scientific disciplines and society. We review the role of modeling soil processes in quantifying key soil processes that shape ecosystem services, with a focus on provisioning and regulating services. We then identify key challenges in modeling soil processes, including the systematic incorporation of heterogeneity and uncertainty, the integration of data and models, and strategies for effective integration of knowledge on physical, chemical, and biological soil processes. We discuss how the soil modeling community could best interface with modern modeling activities in other disciplines, such as climate, ecology, and plant research, and how to weave novel observation and measurement techniques into soil models. We propose the establishment of an international soil modeling consortium to coherently advance soil modeling activities and foster communication with other Earth science disciplines. Such a consortium should promote soil modeling platforms and data repository for model development, calibration and intercomparison essential for addressing contemporary challenges