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Differentiating idiopathic inflammatory myopathies by automated morphometric analysis of MHC-1, MHC-2 and ICAM-1 in muscle tissue

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Neuropathol Appl Neurobiol. 2024 Aug;50(4):e12998. doi: 10.1111/nan.12998.

ABSTRACT

AIMS: Diagnosis of idiopathic inflammatory myopathies (IIM) is based on morphological characteristics and the evaluation of disease-related proteins. However, although broadly applied, substantial bias is imposed by the respective methods, observers and individual staining approaches. We aimed to quantify the protein levels of major histocompatibility complex (MHC)-1, (MHC)-2 and intercellular adhesion molecule (ICAM)-1 using an automated morphometric method to mitigate bias.

METHODS: Double immunofluorescence staining was performed on whole muscle sections to study differences in protein expression in myofibre and endomysial vessels. We analysed all IIM subtypes including dermatomyositis (DM), anti-synthetase syndrome (ASyS), inclusion body myositis (IBM), immune-mediated-necrotising myopathy (IMNM), dysferlinopathy (DYSF), SARS-CoV-2 infection and vaccination-associated myopathy. Biopsies with neurogenic atrophy (NA) and normal morphology served as controls. Bulk RNA-Sequencing (RNA-Seq) was performed on a subset of samples.

RESULTS: Our study highlights the significance of MHC-1, MHC-2 and ICAM-1 in diagnosing IIM subtypes and reveals distinct immunological profiles. RNASeq confirmed the precision of our method and identified specific gene pathways in the disease subtypes. Notably, ASyS, DM and SARS-CoV-2-associated myopathy showed increased ICAM-1 expression in the endomysial capillaries, indicating ICAM-1-associated vascular activation in these conditions. In addition, ICAM-1 showed high discrimination between different subgroups with high sensitivity and specificity.

CONCLUSIONS: Automated morphometric analysis provides precise quantitative data on immune-associated proteins that can be integrated into our pathophysiological understanding of IIM. Further, ICAM-1 holds diagnostic value for the detection of IIM pathology.

PMID:39030945 | DOI:10.1111/nan.12998

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