Myositis-specific autoantibodies in clinical practice: Improving the performance of the immunodot.

Idiopathic inflammatory myopathies (IIM) diagnosis and sub-classification can be improved by detection of myositis specific antibodies (MSA) as a first step in diagnosis. However, when using semi-quantitative immunodots for MSA detection, clinical assay performance needs to be improved. A retrospective study was done for the "myositis" and "synthetase" immunodots (SRP, NXP2, TIF1gamma, SAE1/2, Mi2, MDA5, Jo1, PL7, PL12, EJ, OJ, KS, ZO and HA) from D-Tek used for 270 patients who had tested positive for MSA in a tertiary laboratory hospital. Results from this analysis revealed: (i) none of the 60 healthy controls presented MSA; (ii) a low assay specificity among patients who tested positive for MSA, 128/270 (47%) were labeled IIM based on the manufacturer's recommended threshold; (iii) in non-IIM patients (53%), the MSA spectrum overlaps predominantly with other autoimmune diseases or idiopathic interstitial lung disease; and (iv) use of a clinical cut-off improves assay specificity for anti-SRP, anti-NXP2, anti-MDA5, anti-Jo1 and anti-PL7 Abs. Determining the clinical threshold of the semi-quantitative immunodot assay for MSA is effective for improving its capacity to discriminate IIM from non-IIM and, when IIM diagnosis is excluded, another autoimmune disease or an idiopathic interstitial lung disease should be considered in front of a positive MSA.

Bories E ，Fortenfant F ，Pugnet G ，Renaudineau Y ，Bost C ... -  《-》

Autoantigenic properties of the aminoacyl tRNA synthetase family in idiopathic inflammatory myopathies.

Preger C ，Notarnicola A ，Hellström C ，Wigren E ，Fernandes-Cerqueira C ，Kvarnström M ，Wahren-Herlenius M ，Idborg H ，Lundberg IE ，Persson H ，Gräslund S ，Jakobsson PJ ... -  《-》

Integrated analysis of plasma and urine reveals unique metabolomic profiles in idiopathic inflammatory myopathies subtypes.

Idiopathic inflammatory myopathies (IIM) are a class of autoimmune diseases with high heterogeneity that can be divided into different subtypes based on clinical manifestations and myositis-specific autoantibodies (MSAs). However, even in each IIM subtype, the clinical symptoms and prognoses of patients are very different. Thus, the identification of more potential biomarkers associated with IIM classification, clinical symptoms, and prognosis is urgently needed. Plasma and urine samples from 79 newly diagnosed IIM patients (mean disease duration 4 months) and 52 normal control (NC) samples were analysed by high-performance liquid chromatography of quadrupole time-of-flight mass spectrometry (HPLC-Q-TOF-MS)/MS-based untargeted metabolomics. Orthogonal partial least-squares discriminate analysis (OPLS-DA) were performed to measure the significance of metabolites. Pathway enrichment analysis was conducted based on the KEGG human metabolic pathways. Ten machine learning (ML) algorithms [linear support vector machine (SVM), radial basis function SVM, random forest, nearest neighbour, Gaussian processes, decision trees, neural networks, adaptive boosting (AdaBoost), Gaussian naive Bayes and quadratic discriminant analysis] were used to classify each IIM subtype and select the most important metabolites as potential biomarkers. OPLS-DA showed a clear separation between NC and IIM subtypes in plasma and urine metabolic profiles. KEGG pathway enrichment analysis revealed multiple unique and shared disturbed metabolic pathways in IIM main [dermatomyositis (DM), anti-synthetase syndrome (ASS), and immune-mediated necrotizing myopathy (IMNM)] and MSA-defined subtypes (anti-Mi2+, anti-MDA5+, anti-TIF1γ+, anti-Jo1+, anti-PL7+, anti-PL12+, anti-EJ+, and anti-SRP+), such that fatty acid biosynthesis was significantly altered in both plasma and urine in all main IIM subtypes (enrichment ratio > 1). Random forest and AdaBoost performed best in classifying each IIM subtype among the 10 ML models. Using the feature selection methods in ML models, we identified 9 plasma and 10 urine metabolites that contributed most to separate IIM main subtypes and MSA-defined subtypes, such as plasma creatine (fold change = 3.344, P = 0.024) in IMNM subtype and urine tiglylcarnitine (fold change = 0.351, P = 0.037) in anti-EJ+ ASS subtype. Sixteen common metabolites were found in both the plasma and urine samples of IIM subtypes. Among them, some were correlated with clinical features, such as plasma hypogeic acid (r = -0.416, P = 0.005) and urine malonyl carnitine (r = -0.374, P = 0.042), which were negatively correlated with the prevalence of interstitial lung disease. In both plasma and urine samples, IIM main and MSA-defined subtypes have specific metabolic signatures and pathways. This study provides useful clues for understanding the molecular mechanisms, searching potential diagnosis biomarkers and therapeutic targets for IIM.

Liu D ，Zhao L ，Jiang Y ，Li L ，Guo M ，Mu Y ，Zhu H ... -  《-》

Evaluating the diagnostic utility of new line immunoassays for myositis antibodies in clinical practice: a retrospective study.

Montagnese F ，Babačić H ，Eichhorn P ，Schoser B ... -  《-》

Profiling of Myositis Specific Antibodies and Composite Scores as an Aid in the Differential Diagnosis of Autoimmune Myopathies.

Mahler M ，Malyavantham K ，Seaman A ，Bentow C ，Anunciacion-Llunell A ，Sanz-Martínez MT ，Viñas-Gimenez L ，Selva-O'Callaghan A ... -  《-》