Inflammatory myopathies and beyond: The dual role of neutrophils in muscle damage and regeneration

Skeletal muscle is one of the most abundant tissues of the human body and is responsible for the generation of movement. Muscle injuries can lead to severe disability. Skeletal muscle is characterized by an important regeneration capacity, which is possible due to the interaction between the myoblasts and immune cells. Neutrophils are fundamental as inducers of muscle damage and as promoters of the initial inflammatory response which eventually allows the muscle repair. The main functions of the neutrophils are phagocytosis, respiratory burst, degranulation, and the production of neutrophil extracellular traps (NETs). An overactivation of neutrophils after muscle injuries may lead to an expansion of the initial damage and can hamper the successful muscle repair. The importance of neutrophils as inducers of muscle damage extends beyond acute muscle injury and recently, neutrophils have become more relevant as part of the immunopathogenesis of chronic muscle diseases like idiopathic inflammatory myopathies (IIM). This heterogeneous group of systemic autoimmune diseases is characterized by the presence of muscle inflammation with a variable amount of extramuscular features. In IIM, neutrophils have been found to have a role as biomarkers of disease activity, and their expansion in peripheral blood is related to certain clinical features like interstitial lung disease (ILD) and cancer. On the other hand, low density granulocytes (LDG) are a distinctive subtype of neutrophils characterized by an enhanced production of NETs. These cells along with the NETs have also been related to disease activity and certain clinical features like ILD, vasculopathy, calcinosis, dermatosis, and cutaneous ulcers. The role of NETs in the immunopathogenesis of IIM is supported by an enhanced production and deficient degradation of NETs that have been observed in patients with dermatomyositis and anti-synthetase syndrome. Finally, new interest has arisen in the study of other phenotypes of LDG with a phenotype corresponding to myeloid-derived suppressor cells, which were also found to be expanded in patients with IIM and were related to disease activity. In this review, we discuss the role of neutrophils as both orchestrators of muscle repair and inducers of muscle damage, focusing on the immunopathogenesis of IIM

Clinical and laboratory features associated with macrophage activation syndrome in Still's disease: data from the international AIDA Network Still's Disease Registry

: To characterize clinical and laboratory signs of patients with still's disease experiencing macrophage activation syndrome (MAS) and identify factors associated with MAS development. patients with still's disease classified according to internationally accepted criteria were enrolled in the autoInflammatory disease alliance (AIDA) still's disease registry. clinical and laboratory features observed during the inflammatory attack complicated by MAS were included in univariate and multivariate logistic regression analysis to identify factors associated to MAS development. A total of 414 patients with Still's disease were included; 39 (9.4%) of them developed MAS during clinical history. At univariate analyses, the following variables were significantly associated with MAS: classification of arthritis based on the number of joints involved (p = 0.003), liver involvement (p = 0.04), hepatomegaly (p = 0.02), hepatic failure (p = 0.01), axillary lymphadenopathy (p = 0.04), pneumonia (p = 0.03), acute respiratory distress syndrome (p < 0.001), platelet abnormalities (p < 0.001), high serum ferritin levels (p = 0.009), abnormal liver function tests (p = 0.009), hypoalbuminemia (p = 0.002), increased LDH (p = 0.001), and LDH serum levels (p < 0.001). at multivariate analysis, hepatomegaly (OR 8.7, 95% CI 1.9-52.6, p = 0.007) and monoarthritis (OR 15.8, 95% CI 2.9-97.1, p = 0.001), were directly associated with MAS, while the decade of life at Still's disease onset (OR 0.6, 95% CI 0.4-0.9, p = 0.045), a normal platelet count (OR 0.1, 95% CI 0.01-0.8, p = 0.034) or thrombocytosis (OR 0.01, 95% CI 0.0-0.2, p = 0.008) resulted to be protective. clinical and laboratory factors associated with MAS development have been identified in a large cohort of patients based on real-life data

Patient global assessment and inflammatory markers in patients with idiopathic inflammatory myopathies - A longitudinal study.

AIM To explore if patient global assessment (PGA) is associated with inflammation over time and if associations are explained by other measures of disease activity and function in patients with idiopathic inflammatory myopathies (IIM). METHODS PGA and systemic inflammatory markers prospectively collected over five years were retrieved from the International MyoNet registry for 1200 patients with IIM. Associations between PGA, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP) and creatine kinase (CK) were analyzed using mixed models. Mediation analysis was used to test if the association between PGA and inflammatory markers during the first year of observation could be explained by measures of disease activity and function. RESULTS PGA improved, and inflammatory markers decreased during the first year of observation. In the mixed models, high levels of inflammatory markers were associated with worse PGA in both men and women across time points during five years of observation. In men, but not in women, the association between elevated ESR, CRP and poorer PGA was explained by measures of function and disease activity. With a few exceptions, the association between improved PGA and reduced inflammatory markers was partially mediated by improvements in all measures of function and disease activity. CONCLUSION Increased levels of systemic inflammation are associated with poorer PGA in patients with IIM. In addition to known benefits of lowered inflammation, these findings emphasize the need to reduce systemic inflammation to improve subjective health in patients with IIM. Furthermore, the results demonstrate the importance of incorporating PGA as an outcome measure in clinical practice and clinical trials

p-values of Spearman´s correlation analysis in Fig 1B.

(DOCX)</p

Untargeted serum metabolomics of COVID-19 patients.

A. Heatmap and hierarchical clustering analysis of COVID-19 and control individuals with all the metabolites included in the analysis. Different intensities in red and blue colors in the heatmap and scale bar at the right side of the figure, denotes increased or reduced levels, respectively. B. Spearman correlation analysis of serum metabolites in COVID-19 and control groups. H, healthy controls, M, mild/moderate disease; S, severe disease. Blue numbers indicate a positive association. Red numbers indicate a negative association. Asterisks denote statistical significance with p-value S3 Table.</p

Principal component analysis of all patients included in the analysis.

Pooled samples (blue intense) were used as a quality control and shows a compact well-defined cluster, ensuring a good reproducibility of our GC/MS analysis. (DOCX)</p

Metabolites with significant changes between the groups.

Metabolites with significant changes between the groups.</p

Correlation analysis of the metabolites and the clinical tests in the severe group.

A. Spearman correlations analysis of metabolites and clinical tests. SpO2 = Oxygen saturation; LDH = Lactate dehydrogenase; Art pH = Arterial pH; PaO2 = Partial pressure of oxygen; PaCO2 = Partial pressure of CO2; Art HCO3 = Arterial bicarbonate; PaFi = PaO2/FiO2; TB = Total bilirubin; DB = Direct bilirubin; IB = Indirect bilirubin; ALT = Alanine aminotransferase; AST = Aspartate aminotransferase; AP = Alkaline phosphatase; Alb = Albumin; INR = International Normalized Ratio; CRP = C reactive protein; CPK = Creatine phosphokinase. Different intensities in blue and red numbers indicate a positive or negative association, respectively (see also the gradient scale at the right side of the figure). B. Proposed model for the main changes identified in our cohort. The graphs were constructed with normalized values. H, healthy controls; M, mild/moderate disease; S, severe disease. ‡Direct involvement of cystine over glutamic acid levels through xCT antiporting system. †Enzymatic involvement over glutamic levels through proline dehydrogenase activity. Statistical differences were calculated employing Kruskal-Wallis and Dunn tests. P*<0.05 **<0.01, ***<0.001, ****<0.0001.</p

Main demographic features of the patients included in the analysis.

Main demographic features of the patients included in the analysis.</p