Retinoids and activation of PKC induce tissue-type plasminogen activator expression and storage in human astrocytes

BACKGROUND: Emerging data demonstrate important roles for tissue-type plasminogen activator (t-PA) in the central nervous system (CNS). In contrast to endothelial cells, little is known about the regulation of t-PA gene expression and secretion in astrocytes. OBJECTIVES: The aims of the present study were to investigate whether t-PA gene expression is regulated by retinoids and the protein kinase C (PKC) activator phorbol 12-myristate 13-acetate (PMA) in human astrocytes, and to study whether t-PA is stored and subject to regulated release from these cells, as with endothelial cells. METHODS: Native human astrocytes were treated with RA and/or PMA. mRNA was quantified by real-time RT-PCR and protein secretion determined by ELISA. Intracellular t-PA immunoreactivity in astrocytes was examined by immunocyto- and histochemistry. RESULTS: RA and/or PMA induced a time-dependent increase in t-PA mRNA and protein levels in astrocytes, reaching 10-fold after combined treatment. This was associated with increased amounts of t-PA storage in intracellular granular structures. Both forskolin and histamine induced regulated release of t-PA. The presence of t-PA in reactive astrocytes was confirmed in human brain tissue. CONCLUSIONS: These data show that RA and PKC activation induce a strong up-regulation of t-PA expression in astrocytes, and increased intracellular storage pools. Moreover, a regulated release of t-PA can be induced from these cells. This raises the possibility that astrocytes contribute to the regulation of extracellular t-PA levels in the CNS

Autoantibody Specificities and Type I Interferon Pathway Activation in Idiopathic Inflammatory Myopathies

Myositis is a heterogeneous group of autoimmune diseases, with different pathogenic mechanisms contributing to the different subsets of disease. The aim of this study was to test whether the autoantibody profile in patients with myositis is associated with a type I interferon (IFN) signature, as in patients with systemic lupus erythematous (SLE). Patients with myositis were prospectively enrolled in the study and compared to healthy controls and to patients with SLE. Autoantibody status was analysed using an immunoassay system and immunoprecipitation. Type I IFN activity in whole blood was determined using direct gene expression analysis. Serum IFN-inducing activity was tested using peripheral blood cells from healthy donors. Blocking experiments were performed by neutralizing anti-IFNAR or anti-IFN-α antibodies. Patients were categorized into IFN high and IFN low based on an IFN score. Patients with autoantibodies against RNA-binding proteins had a higher IFN score compared to patients without these antibodies, and the IFN score was related to autoantibody multispecificity. Patients with dermatomyositis (DM) and inclusion body myositis (IBM) had a higher IFN score compared to the other subgroups. Serum type I IFN bioactivity was blocked by neutralizing anti-IFNAR or anti-IFN-α antibodies. To conclude, a high IFN score was not only associated with DM, as previously reported, and IBM, but also with autoantibody monospecificity against several RNA-binding proteins and with autoantibody multispecificity. These studies identify IFN-α in sera as a trigger for activation of the type I IFN pathway in peripheral blood and support IFN-α as a possible target for therapy in these patients. © 2016 The Foundation for the Scandinavian Journal of Immunolog

EULAR/ACR classification criteria for adult and juvenile idiopathic inflammatory myopathies and their major subgroups: A methodology report

Objective T o describe the methodology used to develop new classification criteria for adult and juvenile idiopathic inflammatory myopathies (IIMs) and their major subgroups. Methods A n international, multidisciplinary group of myositis experts produced a set of 93 potentially relevant variables to be tested for inclusion in the criteria. Rheumatology, dermatology, neurology and paediatric clinics worldwide collected data on 976 IIM cases (74% adults, 26% children) and 624 non-IIM comparator cases with mimicking conditions (82% adults, 18% children). The participating clinicians classified each case as IIM or non-IIM. Generally, the classification of any given patient was based on few variables, leaving remaining variables unmeasured. We investigated the strength of the association between all variables and between these and the disease status as determined by the physician. We considered three approaches: (1) a probability-score approach, (2) a sum-ofitems approach criteria and (3) a classification-tree approach. Results T he approaches yielded several candidate models that were scrutinised with respect to statistical performance and clinical relevance. The probabilityscore approach showed superior statistical performance and clinical practicability and was therefore preferred over the others. We developed a classification tree for subclassification of patients with IIM. A calculator for electronic devices, such as computers and smartphones, facilitates the use of the European League Against Rheumatism/American College of Rheumatology (EULAR/ ACR) classification criteria. Conclusions The new EULAR/ACR classification criteria provide a patient's probability of having IIM for use in clinical and research settings. The probability is based on a score obtained by summing the weights associated with a set of criteria items. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted

EULAR/ACR classification criteria for adult and juvenile idiopathic inflammatory myopathies and their major subgroups: A methodology report

Objective T o describe the methodology used to develop new classification criteria for adult and juvenile idiopathic inflammatory myopathies (IIMs) and their major subgroups. Methods A n international, multidisciplinary group of myositis experts produced a set of 93 potentially relevant variables to be tested for inclusion in the criteria. Rheumatology, dermatology, neurology and paediatric clinics worldwide collected data on 976 IIM cases (74% adults, 26% children) and 624 non-IIM comparator cases with mimicking conditions (82% adults, 18% children). The participating clinicians classified each case as IIM or non-IIM. Generally, the classification of any given patient was based on few variables, leaving remaining variables unmeasured. We investigated the strength of the association between all variables and between these and the disease status as determined by the physician. We considered three approaches: (1) a probability-score approach, (2) a sum-ofitems approach criteria and (3) a classification-tree approach. Results T he approaches yielded several candidate models that were scrutinised with respect to statistical performance and clinical relevance. The probabilityscore approach showed superior statistical performance and clinical practicability and was therefore preferred over the others. We developed a classification tree for subclassification of patients with IIM. A calculator for electronic devices, such as computers and smartphones, facilitates the use of the European League Against Rheumatism/American College of Rheumatology (EULAR/ ACR) classification criteria. Conclusions The new EULAR/ACR classification criteria provide a patient's probability of having IIM for use in clinical and research settings. The probability is based on a score obtained by summing the weights associated with a set of criteria items. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted