Mammen, Andrew L.

ABSTRACT Autoantibody internalization has been implicated in autoimmune disease pathogenesis, yet its mechanisms, and generality across different diseases, cell types, and affected tissues remain poorly defined. Using bulk RNA sequencing, we identified reproducible, autoantibody-specific transcriptomic signatures consistent with autoantigen dysfunction in muscle biopsies from patients with anti-Mi2 dermatomyositis and anti-PM/Scl scleromyositis across independent cohorts. Electroporation of purified patient IgG into primary cultures of healthy cells was sufficient to induce the corresponding transcriptomic programs in vitro . Direct immunofluorescence demonstrated immunoglobulin internalization into subcellular compartments matching the localization of the autoantigen in different affected tissues. Spatial transcriptomic analyses revealed that antibody-secreting cells translocated cytoplasmic material (i.e., immunoglobulin RNA) into adjacent affected cells expressing autoantibody-specific transcripts. The disease-specific transcripts were present not only in muscle fibers, but also in other cells, including macrophages, endothelial cells, and fibroblasts. Autoantibody-induced transcriptomic programs were associated with cell damage and autoantibody-specific reactive inflammatory programs, including activation of type I interferon and TGF-ß1 signaling in anti-Mi2 dermatomyositis and activation of type II interferon in anti-PM/Scl scleromyositis. Antibody internalization was also observed in different tissues from patients with other autoimmune diseases, including anti-U1RNP mixed connective tissue disease, anti-Ku overlap syndrome, and anti-Scl70 systemic sclerosis. Together, these findings establish autoantibody internalization as a shared pathogenic mechanism across diverse autoimmune diseases, providing a unifying framework for conditions driven by autoantibodies against intracellular antigens.

ABSTRACT Objectives T‐cell large granular lymphocytic leukemia (T‐LGLL), reported in up to 58% of inclusion body myositis (IBM) patients, is a rare leukemia of cytotoxic or less commonly helper T cells. The range of myopathies in T‐LGLL and the impact of coexisting T‐LGLL in IBM are not well understood. Our objectives are to investigate the spectrum of myopathies in patients with T‐LGLL and compare the clinical, serological, pathological, and transcriptomic features of IBM patients with and without T‐LGLL. Methods We reviewed two Mayo Clinic cohorts: (1) T‐LGLL patients evaluated for myopathies (2003–2018), and (2) IBM patients tested for T‐LGLL via T‐cell receptor gene rearrangement or flow cytometry (2016–2022). We also compared transcriptomic profiles of IBM muscle biopsies with and without T‐LGLL. Results Of 447 T‐LGLL patients, 13 (2.9%) had myopathies, IBM being the most common ( n = 7). Of 43 IBM patients, 9 (20.9%) had T‐LGLL, with 5 diagnosed prior to the onset of weakness. Clinical and pathological features were largely similar between IBM patients with and without T‐LGLL, except for milder finger flexor weakness and more frequent neutropenia (55.6% vs. 0%, p < 0.001) in the T‐LGLL group. However, transcriptomic analysis of muscle tissues revealed a more immunologically active profile, with upregulation of T‐cell and macrophage markers, elevated levels of IFN‐γ gene and IFN‐γ–inducible genes, heightened cytokine activity, and enhanced immunoglobulin production in IBM patients with T‐LGLL. Interpretation IBM is the most common myopathy in T‐LGLL patients. While clinico‐sero‐pathological features were largely similar, transcriptomic differences suggest IBM with T‐LGLL may represent a distinct, more immune‐driven subtype.

Abstract Objectives Granulomatous myositis (GM) is defined by focal collections of activated macrophages that fuse to form multinucleated cells that aggregate into granulomas within skeletal muscle. This study aimed to elucidate the pathophysiology of GM by defining its specific transcriptomic profile. Methods Bulk RNA sequencing was performed on 722 muscle biopsies, including 38 from patients with GM, other myopathies and healthy comparators. Spatial transcriptomics and immunohistochemistry assays were used to identify the location of specific transcripts and proteins within the tissue. Results We conducted a systematic analysis of the inflammatory pathways implicated in GM. This analysis revealed that GM muscle biopsies are characterized by elevated levels of IFNγ, IFNγ-inducible genes and proinflammatory cytokine genes including IL1B, TNF and TGFB1. Additionally, we identified a specific gene signature in GM, comprising 1293 genes that were significantly upregulated and 256 significantly downregulated. These genes were strongly correlated with transcriptomic markers of disease activity. Using this gene signature, support vector machine models accurately identified GM, achieving an area under the curve of 99.6% (99.0–99.9%) and an accuracy of 98.6% (98.2–98.9%). Among the identified genes, CHIT1 emerged as the most significantly upregulated gene, with its expression strongly correlating with disease severity. Furthermore, CHIT1 was detected at both the RNA and protein levels in granulomas and giant cells. Conclusion GM is transcriptomically characterized by a strong IFNγ signature and overexpression of proinflammatory cytokines, including IL1B, TNF and TGFB1. Additionally, it exhibits a unique transcriptomic profile, including CHIT1, which correlates with disease activity.

ABSTRACT Aims Sarcoid myopathy (SaM) is characterised by granulomatous myositis (GM) and can overlap with inclusion body myositis (IBM), a late‐onset chronic idiopathic inflammatory myopathy with a still enigmatic pathogenesis. As GM can occur in different clinical contexts, we aimed to examine the histomorphologic features and gene expression profiles in cases of definite SaM that may inform diagnostic and therapeutic considerations. Methods We performed a multidimensional characterisation of muscle biopsy specimens from patients with ‘pure SaM’ (n=17), SaM with concomitant IBM (SaM‐IBM) (n=2), including histopathologic and ultrastructural analysis in addition to quantitative real‐time polymerase chain reaction. Additionally, bulk RNA sequencing was performed on 38 muscle biopsy specimens from patients with SaM (including SaM‐IBM) (n=30) and NGI (n=8). Results Histopathological analysis revealed a pattern of endomysial and perimysial granulomatous inflammation frequently extending to the fascia, endomysial fibrosis, muscle fibre atrophy, variation in muscle fibre size and capillary thickening. Findings from immunohistochemical studies established Chitinase 1 as a pure giant cell marker in SaM. On a subcellular level, ‘pure SaM’ was characterised by focal accumulation of large swollen mitochondria with rare cristae but an absence of irregular cristae. Transcriptomic analysis of patients with SaM confirmed markedly elevated expression of both type 1 and type 2 human leukocyte antigen molecules. Macrophage activity markers were highly elevated. Consistent with histologic findings, CHIT1 was specifically overexpressed in SaM samples but not in ‘pure IBM’ muscle biopsy specimens. Conclusions SaM is characterised by a stereotypical appearance at the histopathologic level and disease‐specific immune dysregulation that involves macrophage function and maturation. SaM‐IBM represents a noteworthy overlap syndrome that shares multiple dysregulated immune pathways with ‘pure SaM’.

Abstract Objective Myositis is a heterogeneous family of inflammatory myopathies. We sought to define the differential expression of cytokines, cytokine receptors and immune checkpoint genes in muscle biopsies from patients with different forms of myositis in order to characterize patterns of inflammation in each. Methods Bulk RNA-sequencing was performed on muscle biopsy samples from 669 patients, including 105 with DM, 80 with immune-mediated necrotizing myopathy (IMNM), 65 with anti-synthetase syndrome, 53 with IBM, 19 with anti-PM/Scl myositis, 310 with other inflammatory or genetic myopathies and 37 controls with normal tissue (NT). Myositis clinical groups and autoantibody subgroups were analysed separately. Expression data were analysed for 338 genes encoding cytokines, cytokine receptors and immune checkpoints. Myositis group-specific genes were identified from this list by finding genes that were specifically differentially expressed in one group compared with all samples and compared with NT (α &lt; 0.001). Results IBM patients had the most differentially overexpressed genes (71) among all clinical groups, including 37 that were IBM-specific. Among the top genes were several involved in type 1 inflammation, including CCL5, CXCR3, CCR5, CXCL9 and IFNG. Anti-Jo1 and anti-PM/Scl patients exhibited differential overexpression of a similar set of genes, while DM patients exhibited differential overexpression of a different set of genes involved in type 1 inflammation. IMNM patients had the least number of differentially overexpressed genes with no predominant inflammatory pattern. Conclusion Each myositis clinical group and autoantibody subgroup had differentially overexpressed inflammatory mediators, including a strong type 1 inflammatory gene signature in IBM.

Abstract Objectives The lack of uniform terminology and abbreviations for anti-synthetase syndrome has led to significant challenges in research and clinical practice. This study aimed to establish an international consensus on a standardized nomenclature and abbreviation among a diverse group of global myositis experts and patient representatives. Methods This qualitative project was approved by the International Myositis Assessment and Clinical Studies Group (IMACS). Based on the outcomes of a literature review and preliminary survey, list of terms for nomenclature and abbreviations was finalized. Subsequently, two rounds of the Delphi survey were conducted among myositis experts and patient participants to ascertain current practices and preferences. Using Nominal Group Technique (NGT), the project steering committee developed a consensus nomenclature and abbreviation. Results A total of 241 and 132 myositis experts from six continents, 35 countries and 9 specialities participated in round 1 and round 2 of the Delphi survey, respectively. The results indicated a preference for the terms anti-synthetase syndrome, antisynthetase syndrome and anti-tRNA synthetase syndrome. The abbreviations ASS, ASyS and ASSD were most used, though ASS received notable disapproval. The steering committee, including twenty-five myositis experts and three patient representatives from diverse backgrounds and geographical locations, reached a consensus on ‘anti-synthetase syndrome’ as the preferred nomenclature and ASyS as the preferred abbreviation, with 100% and 93.1% votes, respectively. Conclusion The terms anti-synthetase syndrome and ASyS should be adopted as the standard nomenclature and abbreviation in both research and clinical practice. This standardization is expected to increase consistency within the literature.

Expanding the US Food and Drug Administration–approved indications for immune checkpoint inhibitors in patients with cancer has resulted in therapeutic success and immune-related adverse events (irAEs). Neurologic irAEs (irAE-Ns) have an incidence of 1%–12% and a high fatality rate relative to other irAEs. Lack of standardized disease definitions and accurate phenotyping leads to syndrome misclassification and impedes development of evidence-based treatments and translational research. The objective of this study was to develop consensus guidance for an approach to irAE-Ns including disease definitions and severity grading. A working group of four neurologists drafted irAE-N consensus guidance and definitions, which were reviewed by the multidisciplinary Neuro irAE Disease Definition Panel including oncologists and irAE experts. A modified Delphi consensus process was used, with two rounds of anonymous ratings by panelists and two meetings to discuss areas of controversy. Panelists rated content for usability, appropriateness and accuracy on 9-point scales in electronic surveys and provided free text comments. Aggregated survey responses were incorporated into revised definitions. Consensus was based on numeric ratings using the RAND/University of California Los Angeles (UCLA) Appropriateness Method with prespecified definitions. 27 panelists from 15 academic medical centers voted on a total of 53 rating scales (6 general guidance, 24 central and 18 peripheral nervous system disease definition components, 3 severity criteria and 2 clinical trial adjudication statements); of these, 77% (41/53) received first round consensus. After revisions, all items received second round consensus. Consensus definitions were achieved for seven core disorders: irMeningitis, irEncephalitis, irDemyelinating disease, irVasculitis, irNeuropathy, irNeuromuscular junction disorders and irMyopathy. For each disorder, six descriptors of diagnostic components are used: disease subtype, diagnostic certainty, severity, autoantibody association, exacerbation of pre-existing disease or de novo presentation, and presence or absence of concurrent irAE(s). These disease definitions standardize irAE-N classification. Diagnostic certainty is not always directly linked to certainty to treat as an irAE-N (ie, one might treat events in the probable or possible category). Given consensus on accuracy and usability from a representative panel group, we anticipate that the definitions will be used broadly across clinical and research settings.

ObjectiveTo develop response criteria for adult dermatomyositis (DM) and polymyositis (PM).MethodsExpert surveys, logistic regression, and conjoint analysis were used to develop 287 definitions using core set measures. Myositis experts rated greater improvement among multiple pairwise scenarios in conjoint analysis surveys, where different levels of improvement in 2 core set measures were presented. The PAPRIKA (Potentially All Pairwise Rankings of All Possible Alternatives) method determined the relative weights of core set measures and conjoint analysis definitions. The performance characteristics of the definitions were evaluated on patient profiles using expert consensus (gold standard) and were validated using data from a clinical trial. The nominal group technique was used to reach consensus.ResultsConsensus was reached for a conjoint analysis–based continuous model using absolute percent change in core set measures (physician, patient, and extramuscular global activity, muscle strength, Health Assessment Questionnaire, and muscle enzyme levels). A total improvement score (range 0–100), determined by summing scores for each core set measure, was based on improvement in and relative weight of each core set measure. Thresholds for minimal, moderate, and major improvement were ≥20, ≥40, and ≥60 points in the total improvement score. The same criteria were chosen for juvenile DM, with different improvement thresholds. Sensitivity and specificity in DM/PM patient cohorts were 85% and 92%, 90% and 96%, and 92% and 98% for minimal, moderate, and major improvement, respectively. Definitions were validated in the clinical trial analysis for differentiating the physician rating of improvement (P < 0.001).ConclusionThe response criteria for adult DM/PM consisted of the conjoint analysis model based on absolute percent change in 6 core set measures, with thresholds for minimal, moderate, and major improvement.