fetching data ...

OP0160 (2022)
HLA-DRB1 ASSOCIATIONS WITH AUTOANTIBODY-DEFINED SUBGROUPS IN IDIOPATHIC INFLAMMATORY MYOPATHIES (IIM)
V. Leclair1,2, A. S. Galindo-Feria3,4, S. Rothwell5, O. Kryštůfková6, H. Mann6, L. Pyndt Diederichsen7,8, H. Andersson9, M. Klein6, S. Tansley10, N. Mchugh10, J. Lamb11, J. Vencovský6, H. Chinoy12,13, M. Holmqvist1, L. Padyukov3,4, I. E. Lundberg3,4, L. M. Diaz-Gallo3,4
1Karolinska Institutet and Karolinska University Hospital, Division of Rheumatology and Clinical Epidemiology Division, Department Medicine Solna, Stockholm, Sweden
2Jewish General Hospital Lady Davis Institute, Division of Rheumatology, Montreal, Canada
3Karolinska Institutet and Karolinska University Hospital, Division of Rheumatology, Department Medicine Solna, Stockholm, Sweden
4Karolinska Institutet, Center for Molecular Medicine, Department of Medicine Solna, Stockholm, Sweden
5University of Manchester, Centre for Genetics and Genomics Versus Arthritis, Manchester, United Kingdom
61st Medical Faculty, Charles University, Institute of Rheumatologyand Department of Rheumatology, Prague, Czech Republic
7Copenhagen University Hospital, Rigshospitalet, Center for Rheumatology and Spine Diseases, Copenhagen, Denmark
8Odense University Hospital, Department of Rheumatology, Odense, Denmark
9Oslo University Hospital, Department of Rheumatology, Oslo, Norway
10University of Bath, Department of Pharmacy and Pharmacology, Bath, United Kingdom
11University of Manchester, Epidemiology and Public Health Group, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, Manchester, United Kingdom
12The University of Manchester, National Institute for Health Research Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester, United Kingdom
13Manchester Academic Health Science Centre, Department of Rheumatology, Salford Royal NHS Foundation Trust, Salford, United Kingdom

Background: There is a gap between how IIM patients are classified in practice and current validated classification criteria 1 . Also, different associations with genetic variations in HLA can inform about different T-cell mechanisms involved in disease pathogenesis.


Objectives: We aimed to systematically study associations between HLA-DRB1 alleles, clinical manifestations, and autoantibody-defined IIM subgroups.


Methods: We included 1348 IIM patients from five European countries. An unsupervised cluster analysis was performed using 14 autoantibodies: anti-Jo1, -PL7, -PL12, -EJ, -OJ, -SRP, -U1RNP, -Ro52, -Mi2, -TIF1γ, -MDA5, -PMScl, -SAE1, and -NXP2 to identify patients’ subgroups. Logistic regressions were used to estimate the associations between HLA-DRB1 alleles, clinical manifestations and the identified subgroups.


Results: Eight subgroups were defined by the autoantibody status ( Table 1 ). Three of the subgroups (1, 2 and 6) have overlapping autoantibodies, while four are almost monospecific (3,4,5 and 7), and one (8) has patients negative for tested autoantibodies. Figure 1 represents the significant associations between HLA-DRB1 alleles and the eight subgroups. Heliotrope rash and Gottron’s sign were significantly more frequent in subgroups 3 (OR:2.2 95%CI:[1.1-4.8], OR:2.6 95%CI:[1.3-5.9], respectively), 4 (OR:12 95%CI:[3.6-75], OR:7.8 95%CI:[2.8-33], respectively) and 7 (OR:22 95%CI:[4.5-385], OR:10 95%CI:[3.1-65], respectively), and Raynaud’s phenomenon was significantly more frequent in subgroup 6 (OR:3.3 95%CI:[1.2-11]).

Autoantibody-defined subgroups using an unsupervised cluster analysis.

Subgroups/ Medoids
Variables 1 Ro52 2 U1RNP 3 PMScl 4 Mi2 5 Jo1 6 Jo1/Ro52 7 TIF1 8 None* All
n (% ) 137 (10) 183 (14) 107 (8) 65 (5) 119 (9) 140 (10) 78 (6) 519 (39) 1348 (100)
Female (% ) 93 (68) 116 (63) 79 (74) 45 (69) 76 (64) 96 (69) 64 (82) 313 (60) 882 (65)
Age at diagnosis, median (IQR) 56 (16) 51.5 (23) 51 (25) 57 (22.5) 47.5 (23.25) 52 (19.5) 53.5 (21.75) 58 (22) 55 (23)
Autoantibodies
Anti-Jo1 0 6 (3) 0 1 (2) 119 (100) 140 (100) 0 0 266 (20)
Anti-PL7 7 (5) 13 (7) 0 0 0 0 0 0 20 (1.5)
Anti-PL12 5 (4) 3 (2) 1 (1) 0 1 (1) 0 0 0 10 (0.7)
Anti-EJ 2 (2) 0 0 0 0 0 0 0 2 (0.1)
Anti-OJ 0 7 (4) 0 0 0 0 0 0 7 (0.5)
Anti-TIF1 10 (7) 2 (1) 2 (2) 0 0 0 78 (100) 0 92 (7)
Anti-Mi2 1 (1) 1 (1) 1 (1) 65 (100) 0 2 (1) 0 0 70 (5)
Anti-SAE1 8 (6) 23 (13) 0 0 0 0 0 0 31 (2)
Anti-NXP2 1 (1) 23 (13) 1 (1) 0 0 0 0 0 25 (2)
Anti-MDA5 9 (7) 10 (6) 1 (1) 1 (2) 0 1 (1) 0 0 22 (2)
Anti-SRP 8 (6) 32 (18) 0 0 0 0 0 0 40 (3)
Anti-Ro52 137 (100) 16 (9) 0 0 0 140 (100) 0 0 293 (22)
Anti-PMScl 11 (8) 1 (1) 107 (100) 0 0 0 0 0 119 (9)
Anti-U1RNP 0 79 (43) 0 0 0 3 (2) 0 0 82 (6)

*IIM patients negative for the tested autoantibodies.

Forest plot of significant associations of HLA. *DRB1 alleles with autoantibody-defined subgroups. Scandinavia includes patients from Denmark, Norway, and Sweden.


Conclusion: Our study reveals that certain subgroups of IIM patients are characterized by overlap of myositis -specific and -associated autoantibodies, which in turn are associated with different HLA-DRB1 alleles including potential novel associations. These results point to different disease mechanisms in the subgroups, as well as suggest that IIM classification could be improved by integrating broader serological and genetic data.


REFERENCES:

[1]Parker MJS, Oldroyd A, Roberts ME, et al. The performance of the European League Against Rheumatism/American College of Rheumatology idiopathic inflammatory myopathies classification criteria in an expert-defined 10 year incident cohort. Rheumatology (Oxford). 2019;58(3):468-475.


Acknowledgements: We thank all the patients who participated in the study.


Disclosure of Interests: Valerie Leclair: None declared, Angeles Shunashy Galindo-Feria: None declared, Simon Rothwell: None declared, Olga Kryštůfková: None declared, Heřman Mann: None declared, Louise Pyndt Diederichsen: None declared, helena andersson: None declared, Martin Klein: None declared, Sarah Tansley: None declared, Neil McHugh: None declared, Janine Lamb: None declared, Jiří Vencovský Speakers bureau: Abbvie, Biogen, Boehringer, Eli Lilly, Gilead, MSD, Novartis, Pfizer, Roche, Sanofi, UCB, Werfen, Consultant of: Abbvie, Argenx, Boehringer, Eli Lilly, Gilead, Octapharma, Pfizer, UCB, Grant/research support from: Abbvie, Hector Chinoy: None declared, Marie Holmqvist: None declared, Leonid Padyukov: None declared, Ingrid E. Lundberg Shareholder of: Roche and Novartis, Consultant of: Corbus Pharmaceuticals Inc, Astra Zeneca, Bristol Myer´s Squibb, Corbus Pharmaceutical, EMD Serono Research & Development Institute, Argenx, Octapharma, Kezaar, Orphazyme, and Janssen, Grant/research support from: Astra Zeneca, Lina M. Diaz-Gallo: None declared

Citation: , volume 81, supplement 1, year 2022, page 104
Session: The treatment and outcome of scleroderma (Oral Presentations)