Blood markers and genetics reveal distinct subgroups of myositis patients, may improve disease classification and treatment

Researchers at the Karolinska Institutet has made significant strides in understanding and classifying myositis, a group of rare autoimmune diseases characterized by muscle inflammation and various organ involvement. Published in eBioMedicine, this research has the potential to revolutionize myositis diagnosis and treatment.

Myositis is notorious for its diverse manifestations, which complicate the already challenging task of categorizing and managing these conditions effectively. However, the study’s breakthrough revealed that it’s possible to divide myositis into eight distinct patient clusters. The key to this classification lies in combining information from two sources: blood markers, specifically autoantibodies, and genetic data from the major histocompatibility complex (MHC) region in the human genome.

The implications of these findings are profound, hinting at distinct disease mechanisms operating within these subgroups. This innovative approach could pave the way for more precise myositis classification and ultimately better patient care.

The study encompassed a cohort of 1,348 myositis patients from five European countries. Researchers scrutinized the presence of 14 myositis-specific or myositis-associated autoantibodies and analyzed genetic variants within the human leucocyte antigen (HLA) genes in the MHC region. Using autoantibody profiles, they successfully categorized patients and then assessed whether these subgroups displayed differences in genetics and clinical symptoms.

The next phase of research will delve into the clinical significance of these subgroups by examining various outcomes, such as disease severity, treatment response, and mortality rates. Furthermore, researchers will investigate additional genetic variants that could shed light on the underlying mechanisms of these complex diseases. This comprehensive approach promises to refine our understanding of myositis and bring us closer to tailored treatments for affected individuals.

Source: Karolinska Institutet

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