A large international study investigating genetic risk factors in autoantibody-defined subgroups of patients with idiopathic inflammatory myopathy (IIM; also known as myositis) has revealed novel strong associations with amino acid positions within HLA molecules. The research also revealed genetic differences between juvenile-onset and adult-onset disease in patients with the same autoantibody specificity.

Credit: S. Harris/Springer Nature Limited

“Traditionally, the strongest genetic risk factors for IIM autoantibodies have been described with classical HLA alleles,” explains corresponding author Simon Rothwell. “In this study, we have refined these associations by identifying specific amino acid positions within HLA molecules that may confer risk, providing mechanistic insights into IIM.”

Rothwell and colleagues analysed genetic data from 2,582 patients enrolled in the Myogen Genetics Consortium, who were divided into 12 subgroups according to the presence of myositis-relevant antibodies. As expected, strong associations with HLA alleles were found within the autoantibody-defined subgroups. For some autoantibodies, associations with amino acid positions were as strong, or stronger, than the classical HLA associations.

Notably, in patients with anti-TIF1 autoantibodies, associations with HLA-DQB1 alleles differed between those with adult-onset IIM and those with pediatric-onset IIM. “The presence of anti-TIF1 autoantibodies is strongly associated with cancer in adult-onset IIM but not in juvenile-onset IIM,” Rothwell highlights. “The identification of independent genetic risk factors suggests distinct aetiologies and disease mechanisms in these patients.”

associations with HLA-DQB1 alleles differed between those with adult-onset IIM and those with pediatric-onset IIM

The analysis provides new insights into the functional importance of genetic risk factors for IIM. “As autoantibodies in IIM correlate with clinical features of disease, understanding genetic risk underlying the development of certain autoantibody profiles has implications for understanding disease progression and prognosis,” concludes Rothwell.