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Focused HLA analysis in Caucasians with myositis identifies significant associations with autoantibody subgroups
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Edité par CCSD ; BMJ Publishing Group -
International audience. Objectives Idiopathic inflammatory myopathies (IIM) are a spectrum of rare autoimmune diseases characterised clinically by muscle weakness and heterogeneous systemic organ involvement. The strongest genetic risk is within the major histocompatibility complex (MHC). Since autoantibody presence defines specific clinical subgroups of IIM, we aimed to correlate serotype and genotype, to identify novel risk variants in the MHC region that co-occur with IIM autoantibodies. Methods We collected available autoantibody data in our cohort of 2582 Caucasian patients with IIM. High resolution human leucocyte antigen (HLA) alleles and corresponding amino acid sequences were imputed using SNP2HLA from existing genotyping data and tested for association with 12 autoantibody subgroups. Results We report associations with eight autoantibodies reaching our study-wide significance level of p<2.9×10 –5 . Associations with the 8.1 ancestral haplotype were found with anti-Jo-1 (HLA-B*08:01, p=2.28×10 –53 and HLA-DRB1*03:01, p=3.25×10 –9 ), anti-PM/Scl (HLA-DQB1*02:01, p=1.47×10 –26 ) and anti-cN1A autoantibodies (HLA-DRB1*03:01, p=1.40×10 –11 ). Associations independent of this haplotype were found with anti-Mi-2 (HLA-DRB1*07:01, p=4.92×10 –13 ) and anti-HMGCR autoantibodies (HLA-DRB1*11, p=5.09×10 –6 ). Amino acid positions may be more strongly associated than classical HLA associations; for example with anti-Jo-1 autoantibodies and position 74 of HLA-DRB1 (p=3.47×10 –64 ) and position 9 of HLA-B (p=7.03×10 –11 ). We report novel genetic associations with HLA-DQB1 anti-TIF1 autoantibodies and identify haplotypes that may differ between adult-onset and juvenile-onset patients with these autoantibodies. Conclusions These findings provide new insights regarding the functional consequences of genetic polymorphisms within the MHC. As autoantibodies in IIM correlate with specific clinical features of disease, understanding genetic risk underlying development of autoantibody profiles has implications for future research.
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