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Distinct HLA associations with autoantibody-defined subgroups in idiopathic inflammatory myopathies

Publikace na 1. lékařská fakulta |
2023

Tento text není v aktuálním jazyce dostupný. Zobrazuje se verze "en".Abstrakt

Background: In patients with idiopathic inflammatory myopathies (IIM), autoantibodies are associated with specific clinical phenotypes suggesting a pathogenic role of adaptive immunity. We explored if autoantibody profiles are associated with specific HLA genetic variants and clinical manifestations in IIM.

Methods: We included 1348 IIM patients and determined the occurrence of 14 myositis-specific or-associated autoantibodies. We used unsupervised cluster analysis to identify autoantibody-defined subgroups and logistic regression to estimate associations with clinical manifestations, HLA-DRB1, HLA-DQA1, HLA-DQB1 alleles, and amino acids imputed from genetic information of HLA class II and I molecules.

Findings: We identified eight subgroups with the following dominant autoantibodies: anti-Ro52, -U1RNP, -PM/Scl,-Mi2,-Jo1,-Jo1/Ro52,-TIF1 gamma or negative for all analysed autoantibodies. Associations with HLA-DRB1*11, HLA-DRB1*15, HLA-DQA1*03, and HLA-DQB1*03 were present in the anti-U1RNP-dominated subgroup.

HLA-DRB1*03, HLA-DQA1*05, and HLA-DQB1*02 alleles were overrepresented in the anti-PM/Scl and anti-Jo1/ Ro52-dominated subgroups. HLA-DRB1*16, HLA-DRB1*07 alleles were most frequent in anti-Mi2 and HLA- DRB1*01 and HLA-DRB1*07 alleles in the anti-TIF1 gamma subgroup.

The HLA-DRB1*13, HLA-DQA1*01 and HLA-DQB1*06 alleles were overrepresented in the negative subgroup. Significant signals from variations in class I molecules were detected in the subgroups dominated by anti-Mi2, anti-Jo1/Ro52, anti-TIF1 gamma, and the negative subgroup.

Interpretation: Distinct HLA class II and I associations were observed for almost all autoantibody-defined subgroups. The associations support autoantibody profiles use for classifying IIM which would likely reflect underlying pathogenic mechanisms better than classifications based on clinical symptoms and/or histopathological features.