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

BACKGROUND: Biopharmaceutical 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 FINDINGS: The 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 × 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. CONCLUSION: In 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

Low Percentage of Signal Regulatory Protein α/β+ Memory B Cells in Blood Predicts Development of Anti-drug Antibodies (ADA) in Adalimumab-Treated Rheumatoid Arthritis Patients

An important goal for personalized treatment is predicting response to a particular therapeutic. A drawback of biological treatment is immunogenicity and the development of antibodies directed against the drug [anti-drug antibodies (ADA)], which are associated with a poorer clinical outcome. Here we set out to identify a predictive biomarker that discriminates rheumatoid arthritis (RA) patients who are more likely to develop ADA in response to adalimumab, a human monoclonal antibody against tumor necrosis factor (TNF)α. By taking advantage of an immune-phenotyping platform, LEGENDScreen™, we measured the expression of 332 cell surface markers on B and T cells in a cross-sectional adalimumab-treated RA patient cohort with a defined ADA response. The analysis revealed seven differentially expressed markers (DEMs) between the ADA+ and ADA− patients. Validation of the DEMs in an independent prospective European cohort of adalimumab treated RA patients, revealed a significant and consistent reduced frequency of signal regulatory protein (SIRP)α/β-expressing memory B cells in ADA+ vs. ADA− RA patients. We also assessed the predictive value of SIRPα/β expression in a longitudinal RA cohort prior to the initiation of adalimumab treatment. We show that a frequency of &lt; 9.4% of SIRPα/β-expressing memory B cells predicts patients that will develop ADA, and consequentially fail to respond to treatment, with a receiver operating characteristic (ROC) area under the curve (AUC) score of 0.92. Thus, measuring the frequency of SIRPα/β-expressing memory B cells in patients prior to adalimumab treatment may be clinically useful to identify a subgroup of active RA subjects who are going to develop an ADA response and not gain substantial clinical benefit from this treatment

Standardizing terms, definitions and concepts for describing and interpreting unwanted immunogenicity of biopharmaceuticals: Recommendations of the innovative medicines initiative ABIRISK consortium

Biopharmaceuticals (BPs) represent a rapidly growing class of approved and investigational drug therapies that is contributing significantly to advancing treatment in multiple disease areas, including inflammatory and autoimmune diseases, genetic deficiencies, and cancer. Unfortunately, unwanted immunogenic responses to BPs, in particular those affecting clinical safety or efficacy, remain among the most common negative effects associated with this important class of drugs. To manage and reduce risk of unwanted immunogenicity, diverse communities of clinicians, pharmaceutical industry, and academic scientists are involved in: interpretation and management of clinical and biological outcomes of BP immunogenicity, improvement of methods for describing, predicting and mitigating immunogenicity risk, and elucidation of underlying causes. Collaboration and alignment of efforts across these communities is made difficult due to lack of agreement on concepts, practices, and standardized terms and definitions related to immunogenicity. The Innovative Medicines Initiative (IMI; www.imi-europe.org), ABIRISK consortium (Anti-Biopharmaceutical [BP] Immunization Prediction and Clinical Relevance to Reduce the Risk; www.abirisk.eu), was formed by leading clinicians, academic scientists, and EFPIA (European Federation of Pharmaceutical Industries and Associations) members to elucidate underlying causes, improve methods for immunogenicity prediction and mitigation, and establish common definitions around terms and concepts related to immunogenicity. These efforts are expected to facilitate broader collaborations and lead to new guidelines for managing immunogenicity. To support alignment, an overview of concepts behind the set of key terms and definitions adopted to date by ABIRISK is provided herein along with a link to access and download the ABIRISK terms and definitions and provide comments (http://www.abirisk.eu/index_t_and_d.asp). This article is protected by copyright. All rights reserved

A comparison of the ability of the human IgG1 allotypes Gm1(3) and Gm1(1,17) to stimulate T-cells responses from allotype matched and mismatched donors

The immunogenicity of clinically administered antibodies has clinical implications for the patients receiving them, ranging from mild consequences, such as increased clearance of the drug from the circulation, to life threatening effects. The emergence of methods to engineer variable regions resulting in the generation of humanised and fully human antibodies as therapeutics has reduced the potential for adverse immunogenicity. However, due to differences in sequence referred to as allotypic variation, antibody constant regions are not homogeneous within the human population, even within sub-classes of the same immunoglobulin isotype. For therapeutically administered antibodies, the potential exists for an immune response from the patient to the antibody if the allotype of patient and antibody do not match. Allotypic distribution in the human population varies within and across ethnic groups making the choice of allotype for a therapeutic antibody difficult. This study investigated the potential of human IgG1 allotypes to stimulate responses in human CD4+ T-cells from donors matched for homologous and heterologous IgG1 allotypes. Allotypic variants of the therapeutic monoclonal antibody trastuzumab were administered to genetically defined allotypic matched and mismatched donor T-cells. No significant responses were observed in the mismatched T-cells. To investigate the lack of T-cell responses in relation to mismatched allotypes, HLA-DR agretopes were identified via MHC associated peptide proteomics (MAPPs). As expected, many HLA-DR restricted peptides were presented. However, there were no peptides presented from the sequence regions containing the allotypic variations. Together the results from the T cell assay and MAPPs assay indicate that the allotypic differences in human IgG1 do not represent a significant risk for induction of immunogenicity

Aggregation of Human Recombinant Monoclonal Antibodies Influences the Capacity of Dendritic Cells to Stimulate Adaptive T-cell Responses In Vitro

Subvisible proteinaceous particles which are present in all therapeutic protein formulations are in the focus of intense discussions between health authorities, academics and biopharmaceutical companies in the context of concerns that such particles could promote unwanted immunogenicity via anti-drug antibody formation. In order to provide further understanding of the subject, this study closely examines the specific biological effects proteinaceous particles may exert on dendritic cells (DCs) as the most efficient antigen-presenting cell population crucial for the initiation of the adaptive immune response. Two different model IgG antibodies were subjected to three different types of exaggerated physical stress to generate subvisible particles in far greater concentrations than the ones typical for the currently marketed biotherapeutical antibodies. The aggregated samples were used in in vitro biological assays in order to interrogate the early DC-driven events that initiate CD4 T-cell dependent humoral adaptive immune responses – peptide presentation capacity and co-stimulatory activity of DCs. Most importantly, antigen presentation was addressed with a unique approach called MHC-associated peptide proteomics (MAPPs), which allows for identifying the sequences of HLA-DR associated peptides directly from human dendritic cells [1]. The experiments demonstrated that highly aggregated solutions of two model mAbs generated under controlled conditions can induce activation of human monocyte-derived DCs as indicated by upregulation of typical maturation markers including co-stimulatory molecules necessary for CD4 T-cell activation. Additional data suggest that highly aggregated proteins could induce in vitro T-cell responses. Intriguingly, strong aggregation-mediated changes in the pattern and quantity of antigen-derived HLA-DR associated peptides presented on DCs were observed, indicating a change in protein processing and presentation. Increasing the amounts of subvisible proteinaceous particles correlated very well with the pronounced increase in the peptide number and clusters presented in the context of class II HLA-DR molecules, suggesting a major involvement of a mass-action mechanism of altering the presentation

Longitudinal analysis of anti-drug antibody development in multiple sclerosis patients treated with interferon beta-1a (Rebif™) using B cell receptor repertoire analysis

A significant proportion of multiple sclerosis (MS) patients treated with interferon beta-1a (Rebif™) develop anti-drug antibodies (ADA) with a negative impact on treatment efficacy. We hypothesized that high-throughput B-cell receptor (BCR) repertoire analysis could be used to predict and monitor ADA development. To study this we analyzed 228 peripheral blood samples from 68 longitudinally followed patients starting on interferon beta-1a. Our results show that whole blood BCR analysis does not reflect, and does not predict ADA development in MS patients treated with interferon beta-1a. We propose that BCR analysis of phenotypically selected cell subsets or tissues might be more informative

Correlation of HLA-DR associated peptides and peptide clusters measured by MAPPs to the amount of protein present in subvisible particles.

<p>Linear regression analyses of the increase of the HLA-DR associated peptides and clusters as functions of the calculated amount of protein present in the subvisible particles. Left up: HLA-DR associated peptides of mAb1 vs protein amount in subvisible particles (r² = 0.994), left down: HLA-DR associated peptide clusters of mAb1 vs protein amount in subvisible particles (r² = 0.993), right up: HLA-DR associated peptides of mAb2 vs protein amount in subvisible particles (r² = 0.86), right down: HLA-DR associated peptide clusters of mAb2 vs protein amount in subvisible particles (r² = 0.943). HS: aggregates generated by heat and shake stress; FT: aggregates generated by freeze and thaw stress, S: aggregates generated by shear stress mAb1: monoclonal antibody 1, mAb2: monoclonal antibody 2, 1: stress level 1, 2: stress level 2. For further details, please, see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0086322#s4" target="_blank">Materials and Methods</a>.</p