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. 2025 Aug:118:105873.
doi: 10.1016/j.ebiom.2025.105873. Epub 2025 Jul 31.

HLA-A∗03:01 as predictive genetic biomarker for glatiramer acetate treatment response in multiple sclerosis: a retrospective cohort analysis

Brian C Zhang  1 , Tilman Schneider-Hohendorf  2 , Rebecca Elyanow  1 , Beatrice Pignolet  3 , Simon Falk  2 , Christian Wünsch  2 , Marie Deffner  2 , Erik Yusko  1 , Damon May  1 , Daniel Mattox  1 , Eva Dawin  2 , Lisa Ann Gerdes  4 , Florence Bucciarelli  3 , Lisa Revie  2 , Gisela Antony  5 , Sven Jarius  6 , Christiane Seidel  7 , Makbule Senel  8 , Stefan Bittner  9 , Felix Luessi  9 , Joachim Havla  10 , Matthias Knop  11 , Manuel A Friese  12 , Susanne Rothacher  13 , Anke Salmen  14 , Fumie Hayashi  15 , Roland Henry  15 , Stacy Caillier  15 , Adam Santaniello  15 ; University of California San Francisco MS-EPIC Team  15 ; German Competence Network Multiple Sclerosis (KKNMS); Maria Seipelt  16 , Christoph Heesen  12 , Sandra Nischwitz  11 , Antonios Bayas  13 , Hayrettin Tumani  8 , Florian Then Bergh  7 , Gerd Meyer Zu Hörste  2 , Tania Kümpfel  10 , Catharina C Gross  2 , Brigitte Wildemann  6 , Martin Kerschensteiner  4 , Ralf Gold  14 , Sven G Meuth  17 , Frauke Zipp  9 , Bruce A C Cree  15 , Jorge Oksenberg  15 , Michael R Wilson  15 , Stephen L Hauser  15 , Scott S Zamvil  15 , Luisa Klotz  2 , Roland Liblau  3 , Harlan Robins  1 , Joseph J Sabatino Jr  15 , Heinz Wiendl  18 , Nicholas Schwab  19
Collaborators, Affiliations

HLA-A∗03:01 as predictive genetic biomarker for glatiramer acetate treatment response in multiple sclerosis: a retrospective cohort analysis

Brian C Zhang et al. EBioMedicine. 2025 Aug.

Abstract

Background: Glatiramer acetate (GA) is a well-tolerated treatment for multiple sclerosis (MS) and comparable in its efficacy to high-dose interferon beta (IFN). As a lack of validated treatment response biomarkers for MS hampers progress in personalised treatment, the study goal was to search for biomarkers of a successful treatment response utilising the known observation of T-cell expansions after GA treatment.

Methods: T-cell receptor beta chain (TRB) sequencing was performed in 3021 patients with MS: a discovery cohort of 1627 patients with MS, 204 of whom had previously been treated with GA, and then validated in 1394 patients with MS, 424 of whom had previously been treated with GA. Clinical data from 1987 patients with MS treated with GA or IFN and available HLA information from the NationMS, ACP, EPIC, BIONAT, and CombiRx trial cohorts were used for a subsequent analysis.

Findings: Common GA-associated TRB expansions were exclusively detected in HLA-A∗03:01 or in HLA-DRB1∗15:01 backgrounds, within CD8+ effector- or CD4+ central-memory T cells. Both sets of common sequences clonally expanded after GA treatment in a first validation cohort and predicted GA exposure in two further validation cohorts. To evaluate whether restriction of public TRBs to only two HLA alleles is also associated with GA's clinical efficacy, we analysed five cohorts of patients with MS for a potential benefit of the two HLAs concerning the GA response compared to IFN. We consistently found positive interactions with HLA-A∗03:01. This included a relative reduction in relapse risk compared to IFN in HLA-A∗03:01 carriers of 33% (CombiRx: GA + IFN arm: HR 0.67 [95% CI: 0.47-0.96], p = 0.0269) and 34% (CombiRx: GA arm: HR 0.66 [95% CI: 0.45-0.98], p = 0.0377), and in risk to first relapse of 63% (NationMS: HR 0.37 [95% CI: 0.16-0.88], p = 0.0246), but no positive association with DRB1∗15:01.

Interpretation: HLA-A∗03:01 carrying patients with MS specifically benefit from GA treatment and GA significantly outperforms IFN in these patients. Therefore, determining HLA-A∗03:01 status before choosing a platform treatment for MS, would allow for a personalised treatment decision between GA and IFN.

Funding: German Research Foundation, National Institutes of Health, National Multiple Sclerosis Society, Valhalla Foundation, Westridge Foundation, Mayer Foundation, German Federal Ministry of Education and Research.

Keywords: Biomarker; Genetics; Glatiramer acetate; HLA; Multiple sclerosis; Treatment response.

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Conflict of interest statement

Declaration of interests BCZ: is an employee of Adaptive Biotechnologies and receives salary, stock, and options as part of their employment compensation outside of the submitted work. TSH: reports travel support from Roche and Biogen, research support from Novartis Pharma and is co-inventor on patents outside of this study. RE: is an employee of Adaptive Biotechnologies and receives salary, stock, and options as part of their employment compensation outside of the submitted work. BP: nothing to disclose. SF: nothing to disclose. CW: nothing to disclose. MD: nothing to disclose. EY: is an employee of Adaptive Biotechnologies and receives salary, stock, and options as part of their employment compensation outside of the submitted work. DM: is an employee of Adaptive Biotechnologies and receives salary, stock, and options as part of their employment compensation outside of the submitted work. DMX: is an employee of Adaptive Biotechnologies and receives salary, stock, options and patent participation as part of their employment compensation, outside of the submitted work. ED: nothing to disclose. LAG: received research funding from Hertie Foundation (funding of MS TWIN STUDY + personal funding), from DMSG national and Bavarian section (funding of MS TWIN STUDY), and from the DFG for the SyNergy Cluster (funding of MS TWIN STUDY + personal funding). FB: nothing to disclose. LR: nothing to disclose. GA: nothing to disclose. SJ: nothing to disclose. CS: nothing to disclose. MS: reported consulting fees from Alexion, Amgen/Horizon, Bayer, Biogen, Bristol-Myers-Squibb/Celgene, Merck, Roche, and Sanofi Genzyme, honoraria from Alexion, Janssen, Amgen/Horizon, Biotest, Roche, Sanofi Genzyme, and UCB, travel support from Alexion, Celgene, Janssen, Amgen/Horizon, Roche, and Sanofi Genzyme, and participation on advisory boards for Alexion, Amgen/Horizon, Bayer, Biogen, Bristol-Myers-Squibb, Merck, Roche, and Sanofi Genzyme. SB: received honoraria from Biogen, Bristol Myers Squibb, Hexal, Merck Healthcare, Novartis, Roche, Sanofi and Teva. He is supported by the Deutsche Forschungsgemeinschaft (DFG, SFB CRC TRR 355–480846870), Novartis and the Hermann- and Lilly-Schilling Foundation. FL: received consultancy fees from Roche and support with travel cost from Teva Pharma. JH: reported grants for OCT research from the Sumaira Foundation, Horizon/Amgen, Roche and Merck, personal consulting fees and honoraria from Alexion, Amgen, Merck, Novartis, Neuraxpharm, Johnson&Johnson, Rewind Therapeutics and Roche and nonfinancial support of the Sumaira-Foundation and Guthy-Jackson Charitable Foundation, all outside the submitted work. MKN: nothing to disclose. MF: nothing to disclose. SR: nothing to disclose. AS: received speaker honoraria from Bristol Myers Squibb, Merck, Neuraxpharm, Novartis, consulting fees from Neuraxpharm, and research support by the Medical Faculty of the University of Bern, the Swiss MS Society and the regional association of North Rhine-Westphalia of the German MS Society (DMSG Landesverband NRW) and Novartis, all not related to this work. FH: received grants or contracts from Japan Society for the Promotion of Science (JSPS, Overseas Research Fellowship, 2023-present), the Uehara Memorial Foundation (Overseas Research Fellowship, 2022–2023), and the Japanese Society of Neurology (Overseas Training Program, 2022–2023), outside this study. RH: his institution received grants from Roche/Genentech and he received consulting fees from Roche, Sanofi and Novartis, lecture honoraria from Sanofi, and compensation for participation on advisory boards from Roche, Novartis and Sanofi. SC: nothing to disclose. ASANT: nothing to disclose. MSEIP: reported speaker honoraria from Merck, Novartis and Roche as well as travel support from AB Science, Alkermes, Baxalta, Bayer, Biogen, CSL Behring, Genzyme, Griffols, Merck, Novartis, Octapharma, Receptoc, Roche, Sanofi Aventis, Teva, UCB Biopharma. CH: nothing to disclose. SN: received lecture honoraria from Roche, Novartis, and Sanofi, travel support from Sanofi, and received compensation for serving on a scientific advisory board of Roche, Neuraxpharm, Bristol –Myers Squibb and Merck. AB: received consulting fees from Roche, Merck, Novartis, Sandoz/HEXAL, lecture honoraria from Merck, Biogen, Novartis, TEVA, Roche, Sanofi/Genzyme, Bristol Myers Squibb, Jannsen, and Sandoz/HEXAL, and received travel support from Biogen, TEVA, Novartis, Sanofi/Genzyme, Merck, Celgene and Jannsen. HAT: reported unpaid roles in DGLN, DGN, DMSG, AMSEL, KKNMS, DGG, Pflegebrücke, Albert-Einstein-Discovery centre e.V., personal consulting fees or lecture honoraria from Alexion, Bayer, Biogen, Bristol-Myers Squibb, Fresenius, Fujirebio, Hexal, Horizon, Janssen, Johnson&Johnson, Merck, Novartis, Roche, Sanofi, Teva, Viatris, and grants from DMSG, Ministerium für Wissenschaft und Forschung BW, Novartis, Sanofi, Faber-Stiftung, Chemische Fabrik Karl Bucher GmbH to his institution outside the submitted work. FTB: received grants or contracts from German Science Fund (DFG), German Federal Ministry of Education and Science (BMBF), Diamed and Fresenius, consulting fees from Amgen-Horizon, Biogen, Merck, Novartis, Roche, Sanofi-Genzyme and lecture honoraria from Alexion, Amgen-Horizon, Fresenius, Merck, Novartis, Roche, Takeda, travel support from Fresenius, Merck, Neuraxpharm, Roche, Sanofi-Genzyme and Teva. GMZH: was supported by grants from the Deutsche Forschungsgemeinschaft (DFG) (ME4050/12–1, ME4050/13–1), a grant from the Bundesministerium für Bildung und Forschung (BMBF) ‘Lipid Immune Neuropathy Consortium’ grants from Roche and from Novartis. GMzH has received speaker honoraria/travel support from Alexion, LFB Pharma, Argenx, Janssen. He has received reimbursement for serving on AdBoards/Trial Steering Comittees from LFB Pharma, Roche, Immunovant, Argenx. He has received project-related research funding from Merck KGaA, Biogen, Roche and material support from Novartis. TK: received speaker honoraria and/or personal fees for advisory boards from Novartis Pharma, Roche Pharma, Alexion/Astra Zeneca, Horizon Therapeutics/Amgen, Merck, Chugai Pharma and Biogen. The Institution she works for has received compensation for serving as a member of a steering committee from Roche. TK is a site principal investigator in several randomised clinical trials (Novartis Pharma, Roche Pharma, BMS and Sanofi Genzyme) and in a randomized clinical trials supported by the BMBf (funding code: 01GM1908E) and her institution has received compensation for clinical trials all outside the present work. TK is Part of the managing board of the German TK Part of the managing board of the German “krankheitsbezogenes Kompetenznetz Multiple Sklerose” (KKNMS) and of the German Neuromyelitis Optica Study Group (NEMOS) – both unpaid. CCG: received grants from European Joint Programme on Rare Diseases (EJP RD), Horizon 2020 ReSToRE, Biogen, Roche, Sanofi, licence fees for European patent No. 4314829, lecture honoraria from the DIU Dresden International University GmbH. She issued a patent with the number EP22199707.5 and is unpaid extended board member and member of the Education Commission of the DGLN e.V., member of the Advisory Board of the DAkkS and board member of EUSAC e.V. BW: reported grants from the Deutsche Forschungsgemeinschaft, German Ministry of Education and research, Baden-Württemberg Ministry for Science, Research and Art, Dietmar Hopp Foundation, Klaus Tschira Foundation, grants and personal fees from Merck, ArgenX, Novartis, and personal fees from Alexion, INSTAND, Roche. MK: received speaker honoraria and/or personal fees for advisory boards from Biogen, Janssen-Cilag, Merck, Novartis, Sanofi, Roche and Teva as well as grant support from Sanofi and Roche. RG: received research support from Teva Pharmaceutical Industries, Biogen Idec, Bayer Schering Pharma, Genzyme, Merck Serono, and Novartis, speaker honoraria from Biogen Idec, Teva Pharmaceutical Industries, Bayer Schering Pharma, and Novartis and participated on scientific advisory boards for Teva Pharmaceutical Industries, Biogen Idec, Bayer Schering Pharma, Kyverna, and Novartis. RG is an editorial board member of Therapeutic Advances in Neurological Diseases and Experimental Neurology and The Journal of Neuroimmunology. SGM: received honoraria for lecturing, travel expenses and for attending meetings from Academy 2, Argenx, Alexion, Almirall, Amicus Therapeutics Germany, AstraZeneca, Bayer Health Care, Biogen, BioNtech, BMS, Celgene, Datamed, Demecan, Desitin, Diamed, Diaplan, DIU Dresden, DPmed, Gen Medicine and Healthcare products, Genzyme, Hexal AG, IGES, Impulze GmbH, Janssen Cilag, KW Medipoint, MedDay Pharmaceuticals, Medmile, Merck Serono, MICE, Mylan, Neuraxpharm, Neuropoint, Novartis, Novo Nordisk, ONO Pharma, Oxford PharmaGenesis, QuintilesIMS, Roche, Sanofi, Springer Medizin Verlag, STADA, Chugai Pharma, Teva, UCB, Viatris, Wings for Life international and Xcenda. His research is funded by the German Ministry for Education and Research (BMBF), German Federal Institute for Risk Assessment (BfR), German Research Foundation (DFG), Else Kröner Fresenius Foundation, Gemeinsamer Bundesausschuss (G-BA), German Academic Exchange Service, Hertie Foundation, Interdisciplinary Centre for Clinical Studies (IZKF) Muenster, German Foundation Neurology, Ministry of Culture and Science of the State of North Rhine-Westphalia, The Daimler and Benz Foundation, Multiple Sclerosis Society North Rhine-Westphalia Regional Association (dmsg), Peek & Cloppenburg Düsseldorf Foundation, Hempel Foundation for Science, Art and Welfare, German Alzheimer Society e.V. Dementia self-help and Alexion, Almirall, Amicus Therapeutics Germany, Argenx, Bayer Vital GmbH, BGP Products Operations (Viatris Company), Biogen, BMS, Demecan, Diamed, DGM e. v., Fresenius Medical Care, Genzyme, Gesellschaft von Freunden und Förderern der Heinrich-Heine-Universität Düsseldorf e.V., HERZ Burgdorf, Hexal, Janssen, Merck Serono, Novartis, Novo Nordisk Pharma, ONO Pharma, Roche and Teva. FZ: received consultation funds from: Amgen, Biogen, Max Planck Society (MPG), Bristol-Meyers-Squibb, Celgene, Hexal, Horizon, Janssen, Merck Serono, Novartis, Roche, Sanofi Genzyme, Sandoz, TEVA. Her research is funded by the DFG (CRC 1292 – 318346496) and BMBF VIP + CheckAut. BC: reported grants or contracts from Genentech and Kyverna to UCSF, consulting fees from Alexion, Alumis, Avotres, Biogen, Boston Pharma, EMD Serono, Hexal/Sandoz, Horizon, Immunic AG, Kyverna, Neuron23, Novartis, Sanofi, Siemens and TG Therapeutics, participation on a data safety monitoring board or advisory board from IDMC – vidofludimus calcium in MS (Immunic AG). JO: nothing to disclose. MRW: received unrelated research grant funding from Roche/Genentech and Kyverna Therapeutics, previously received unrelated research grant funding from Novartis, has received licencing fees from CDI Labs and consulting fees and stock from Delve Bio, where he is also a board member. SLH: currently serves on the scientific advisory boards of Accure, Alector, Hinge Bio; previously consulted for BD, Gilead, Moderna, NGM Bio, Nurix Therapeutics, Pheno Therapeutics; previously served on the Board of Directors of Neurona and currently serves as an advisor. Dr. Hauser also has received nonfinancial support (travel reimbursement and writing support for anti-CD20-therapy-related meetings and presentations) from F. Hoffmann-La Roche and Novartis AG; SZ: nothing to disclose. LK: received compensation for participation on data safety monitoring or advisory boards from Alexion, Biogen, Bristol-Myers Squibb, Hexal, Horizon, Janssen, Merck Serono, Novartis, Roche, Sandoz, Sanofi, Teva and Viatris, and research grants from Amgen, Argenx, Bayer, Biogen, Bristol-Myers Squibb, Grifols, Horizon, Merck Serono, Novartis, Roche, Sanofi, Santhera and Teva, as well as from the German Research Foundation, IZKF Münster, IMF Münster, all outside the submitted work. RL: reported grants from Roche, PopulationBio and COUR-Pharma, consulting fees and materials from Novartis, and speaker honoraria from Biogen, Sanofi-Genzyme, Merck-Serono and Hikma, all outside the submitted work. HR: is an employee of Adaptive Biotechnologies and receives salary, stock, and options as part of their employment compensation outside of the submitted work. JJS: has previously received research grant funding from Roche/Genentech and Novartis and advisory board honoraria from IgM Biosciences and TG Therapeutics. HW: reported consulting fees from Biogen, Merck, Novartis, Sanofi, Genzyme, UCB, Roche, Samsung, Bristol-Myers Squibb, Alexien, Argenx, Immunic, Janssen, LTS, Lundbeck, Medix Europa, Muna Therapeutics, Myrobalan Therapeutics, Peervoice, PSL Group Services, Red Nucleus, Sangamo, Syneos, Toleranzia, Viatris, Teladoc, Swiss Multiple Sclerosis Society, travel support from Biogen, Merck, Sanofi, Novartis, Teva, Springer, Streamed Up, EPG Health, WebMD Health, Ology Medical Education, participation on advisory boards for Biogen, Roche, Novartis, Merck, Genzyme, Argenx, Galapagos, UniQURE, Sandoz, Janssen Pharmaceuticals and serves as expert advisor for Biogen, Roche, Novartis, Merck, Genzyme, Argenx, Galapagos, UniQURE, Sandoz, Janssen Pharmaceuticals, all outside of the submitted work. NS: reported grants from DFG and Roche during the conduct of the study.

Figures

Fig. 1
Fig. 1
Treatment with glatiramer acetate expands HLA-A∗03:01-associated CD8+ T cells and HLA-DRB1∗15:01-associated CD4+ T cells with shared TRB sequences and motifs. a: Number and HLA restriction of common GA-associated TRB sequences identified from bulk TRB sequencing of GA-treated vs. non-GA-treated patients with MS. b: Variable beta chain gene usage of GA-associated TRB sequences. c: 1-Hamming clustering of GA-associated TRB sequences with resulting highlighted motifs. d and e: Validation of HLA-A∗03:01-associated (d, n(HLA-A∗03:01 negative) = 55, p = 0.82, n(HLA-A∗03:01 positive) = 17, p = 0.00011) and HLA-DRB1∗15:01-associated (e, n(HLA-DRB1∗15:01 negative) = 44, p = 0.16, n(HLA-DRB1∗15:01 positive) = 28, p < 0.0001) GA-associated TRB sequence patterns in TRB repertoires before (Naive) and after treatment (Treated) with GA in the EPIC cohort by quantification of GA-associated TRB clonal breadth per 106 unique rearrangements. Significance was assessed by paired t-test. f and g: AUC curves predicting history of GA treatment in HLA-A∗03:01 positive patients (f) and HLA-DRB1∗15:01 positive patients (g) from validation cohorts (BIONAT (n = 1255), MS twin (n = 67)). h: Uniform manifold approximation and projection (UMAP) plot showing CD3+ sorted T cells expressing GA-associated TRB sequences from three HLA-A∗03:01 positive and HLA-DRB1∗15:01 positive GA-treated patients with MS, annotated by Seurat and aCSF clustering (aCSF annotations in brackets, TRB sequence HLA association in square brackets). As shorthand, A03 and DR15 are used to refer to HLA-A∗03:01 and HLA-DRB1∗15:01. Significance was assessed by a paired Wilcoxon rank-sum test. The asterisks indicate a p-value of <0.001(∗∗∗).
Fig. 2
Fig. 2
Clinical efficacy of GA treatment is mediated by HLA-A∗03:01. a: Annualised relapse rate in HLA-A∗03 negative (left, n(IFN) = 112, n(GA) = 112, n(IFN + GA) = 258) and HLA-A∗03 positive patients (right, n(IFN) = 56, n(GA) = 60, n(IFN + GA) = 95) of the CombiRx cohort; Error bars indicate 95% CI from a Poisson model. Statistical assessment was performed using a Cox regression model of relapse data with Andersen-Gill modification, subset to the two compared groups. HLA-A∗03 negative: p(IFN vs. GA) = 0.15, p(IFN vs. IFN + GA) = 0.00065, p(GA vs. IFN + GA) = 0.12. HLA-A∗03 positive: p(IFN vs. GA) = 0.00018, p(IFN vs. IFN + GA) < 0.0001, p(GA vs. IFN + GA) = 0.38. b: Modelling relapse data from panel a by a Cox regression with Andersen-Gill modification with the covariates normalised age, sex, disease duration, GA treatment, GA + IFN treatment, HLA-A∗03, HLA-DRB1∗15:01, and the interactions of treatment and HLA covariates yields a p-value of 0.0377 for the HLA-A∗03 GA interaction and a p-value of 0.0269 for the HLA-A∗03 IFN + GA interaction. c: Kaplan–Meier curves with proportions of relapse-free patients vs. observation period in days of the NationMS cohort; Left panel indicates HLA-A∗03:01 negative patients (n(IFN) = 165, n(GA) = 64), right panel HLA-A∗03:01 positive patients (n(IFN) = 74, n(GA) = 32). d: Modelling data from panel c with a Cox regression and the covariates normalised age, sex, normalised disease duration, GA treatment, HLA-A∗03:01, HLA-DRB1∗15:01, and the interactions of treatment and HLA covariates yields a p-value of 0.0246 for the HLA-A∗03:01 GA interaction. e: MSSS scores at study start of matched patients from the BIONAT cohort; Left panel indicates HLA-A∗03:01 negative patients (n(no prior GA treatment) = 301, n(prior GA treatment) = 178, p = 0.42), right panel indicates HLA-A∗03:01 positive patients (n(no prior GA treatment) = 65, n(prior GA treatment) = 56, p = 0.0026). Significance was assessed using a Wilcoxon rank-sum test. f: Modelling the data from panel e with a linear regression and the covariates normalised age, sex, prior treatment, HLA-A∗03:01, HLA-DRB1∗15:01, and the interactions of treatment and HLA covariates yields a p-value of 0.0072 for the HLA-A∗03:01 GA interaction. g: Annual change in EDSS scores of the EPIC cohort; Left panel indicates HLA-A∗03:01 negative patients (n(IFN) = 24, n(GA) = 55, p = 0.62), right panel indicates HLA-A∗03:01 positive patients (n(IFN) = 17, n(GA) = 21, p = 0.0096). Significance was assessed using a Wilcoxon rank-sum test. h: Modelling the data from panel g with a linear regression and the covariates normalised age, sex, normalised disease duration, treatment, HLA-A∗03:01, HLA-DRB1∗15:01, and the interactions of treatment and HLA covariates yields a p-value of 0.0137 for the HLA-A∗03:01 GA interaction. i: Difference in brain lesions of the ACP cohort; Left boxes indicate HLA-A∗03:01 negative patients (n(IFN) = 61, n(GA) = 39), right boxes indicate HLA-A∗03:01 positive patients (n(IFN) = 33, n(GA) = 15). Significance was assessed using a Wilcoxon rank-sum test. p(HLA-A∗03:01 negative; IFN vs. GA) = 0.069, p(HLA-A∗03:01 positive; IFN vs. GA) = 0.022, p(IFN; HLA-A∗03:01 negative vs. -positive) = 0.45, p(GA; HLA-A∗03:01 negative vs. -positive) = 0.00052. j: Modelling the data from panel i with a linear regression and the covariates normalised age, sex, normalised disease duration, treatment, HLA-A∗03:01, HLA-DRB1∗15:01, and the interactions of treatment and HLA covariates yields a p-value of 0.0031 for the HLA-A∗03:01 GA interaction. As shorthand, A∗03, A∗03:01 and DRB1∗15:01 are used to refer to HLA-A∗03, HLA-A∗03:01 and HLA-DRB1∗15:01. Green bars, boxes and lines indicate IFN treatment, magenta bars, boxes and lines GA treatment, and light blue bars indicate IFN + GA treatment; Boxes indicate the 25% and 75% percentile and median, whiskers indicate 1.5× inter-quartile range, + indicates the mean. The asterisks indicate a p-value of <0.05 (∗), <0.01 (∗∗), or <0.001(∗∗∗).
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