Clinicogenomic factors of biotherapy immunogenicity in autoimmune disease: A prospective multicohort study of the ABIRISK consortium - Pass P3S - Publications - Génomique
Article Dans Une Revue PLoS Medicine Année : 2020

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

Signe Hässler (1, 2, 3) , Delphine Bachelet (1, 4) , Julianne Duhazé (1, 5) , Natacha Szely (6) , Aude Gleizes (6, 7) , Salima Hacein-Bey Abina (7, 8) , Orhan Aktas (9) , Michael Auer (10) , Jérôme Avouac (11, 12) , Mary Birchler (13) , Yoram Bouhnik (14, 15) , Olivier Brocq (16) , Dorothea Buck-Martin (17) , Guillaume Cadiot (15, 18) , Franck Carbonnel (15, 19) , Yehuda Chowers (20) , Manuel Comabella (21) , Tobias Derfuss (22, 23) , Niek de Vries (24) , Naoimh Donnellan (25) , Abiba Doukani (26) , Michael Guger (27) , Hans-Peter Hartung (9) , Eva Kubala Havrdova (28, 29) , Bernhard Hemmer (17, 30) , Tom Huizinga (31) , Kathleen Ingenhoven (9) , Poul Erik Hyldgaard-Jensen (32) , Elizabeth Jury (33) , Michael Khalil (34) , Bernd Kieseier (9) , Anna Laurén (35) , Raija Lindberg (22, 23) , Amy Loercher (13) , Enrico Maggi (36, 37) , Jessica Manson (38) , Claudia Mauri (33) , Badreddine Mohand Oumoussa (26) , Xavier Montalban (21, 39, 40) , Maria Nachury (15, 41) , Petra Nytrova (28, 29) , Christophe Richez (42, 43) , Malin Ryner (44) , Finn Sellebjerg (32) , Claudia Sievers-Stober (22, 23) , Dan Sikkema (13) , Martin Soubrier (45) , Sophie Tourdot (6) , Caroline Trang-Poisson (15, 46) , Alessandra Vultaggio (36) , Clemens Warnke (9, 47) , Sebastian Spindeldreher (48, 49) , Pierre Dönnes (50) , Timothy Hickling (51) , Agnès Hincelin Mery (52) , Matthieu Allez (53, 15) , Florian Deisenhammer (10) , Anna Fogdell-Hahn (44) , Xavier Mariette (54) , Marc Pallardy (6) , Philippe Broët (1, 5, 55)
1 CESP - Centre de recherche en épidémiologie et santé des populations
2 I3 - Immunologie - Immunopathologie - Immunothérapie [CHU Pitié Salpêtrière]
3 CIC-BTi - Centre d'investigation clinique Biothérapie [CHU Pitié-Salpêtrière]
4 IMEA - Institut de médecine et d'épidémiologie appliquée [AP-HP Hôpital Bichat-Claude Bernard]
5 Centre de recherche du CHU Sainte-Justine / Research Center of the Sainte-Justine University Hospital [Montreal, Canada]
6 MI2 - Inflammation, microbiome, immunosurveillance
7 Service de Médecine interne - Immunologie clinique [Kremlin-Bicêtre]
8 UTCBS - UM 4 (UMR 8258 / U1267) - Unité de Technologies Chimiques et Biologiques pour la Santé
9 Heinrich Heine Universität Düsseldorf = Heinrich Heine University [Düsseldorf]
10 IMU - Innsbruck Medical University = Medizinische Universität Innsbruck
11 IC UM3 (UMR 8104 / U1016) - Institut Cochin
12 Service de rhumatologie [CHU Cochin]
13 GlaxoSmithKline
14 Hôpital Beaujon [AP-HP]
15 GETAID - Groupe d’Étude Thérapeutique des Affections Inflammatoires du Tube Digestif
16 Hôpital Princesse Grace [Monaco]
17 TUM - Technische Universität Munchen - Technical University Munich - Université Technique de Munich
18 CHU Reims - Hôpital universitaire Robert Debré [Reims]
19 Service d'Hépato-gastro-entérologie [APHP Kremlin-Bicêtre]
20 University of Haifa [Haifa]
21 CemCat - Centre d'Esclerosi Múltiple de Catalunya
22 University Hospital Basel [Basel]
23 Unibas - Université de Bâle = University of Basel = Basel Universität
24 VU University Medical Center [Amsterdam]
25 Royal Berkshire Hospital
26 PASS-P3S - Plateforme Post-génomique de la Pitié-Salpêtrière
27 Kepler University Hospital
28 UK - Univerzita Karlova [Praha, Česká republika] = Charles University [Prague, Czech Republic]
29 First Faculty of Medicine Charles University
30 SyNergy - Munich Cluster for systems neurology [Munich]
31 LUMC - Leiden University Medical Center
32 Danish Multiple Sclerosis Research Centre
33 UCL - University College of London [London]
34 Medical University of Graz = Medizinische Universität Graz
35 Malmö Högskola = Malmö University
36 UniFI - Università degli Studi di Firenze = University of Florence = Université de Florence
37 Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS
38 UCLH - University College London Hospitals
39 St. Michael's Hospital
40 University of Toronto
41 Service des Maladies de l'Appareil Digestif et de la Nutrition [CHRU Lille]
42 Service de Rhumatologie [CHU Pellegrin]
43 CIRID - Composantes innées de la réponse immunitaire et différenciation
44 Department of Clinical Neuroscience [Sotckholm]
45 Service Rhumatologie [CHU Clermont-Ferrand]
46 Institut des Maladies de l'Appareil Digestif
47 Uniklinik Köln - Universitätsklinikum Köln
48 NIBR - Novartis Institutes for BioMedical Research
49 Integrated Biologix GmbH [Basel]
50 SciCross AB
51 Pfizer
52 Sanofi Aventis R&D [Chilly-Mazarin]
53 AP-HP - Hopital Saint-Louis [AP-HP]
54 Centre de recherche en Immunologie des Infections virales et des maladies auto-immunes
55 Hôpital Paul Brousse
Mary Birchler
  • Fonction : Auteur
Niek de Vries
Michael Guger
  • Fonction : Auteur
  • PersonId : 1224982
Amy Loercher
  • Fonction : Auteur
Claudia Mauri
Dan Sikkema
  • Fonction : Auteur
Pierre Dönnes
Timothy Hickling
  • Fonction : Auteur
Marc Pallardy

Résumé

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.
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hal-03979090 , version 1 (06-06-2023)

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Signe Hässler, Delphine Bachelet, Julianne Duhazé, Natacha Szely, Aude Gleizes, et al.. Clinicogenomic factors of biotherapy immunogenicity in autoimmune disease: A prospective multicohort study of the ABIRISK consortium. PLoS Medicine, 2020, 17 (10), pp.e1003348. ⟨10.1371/journal.pmed.1003348⟩. ⟨hal-03979090⟩
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