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This review provides an overview of evidence supporting the existence of distinct homeostatic and inflammatory eosinophil subpopulations in health and disease. Particular emphasis is placed on describing the phenotypic and functional roles of these eosinophil subtypes in asthma, as well as the phenotypic changes induced by clinical therapy with the anti-IL-5 biologic agent, mepolizumab. Improved understanding of distinct eosinophil phenotypes may enable targeting of select subpopulations in the treatment of patients with type 2 inflammatory diseases such as asthma. [ABSTRACT FROM AUTHOR]

The angiogenic growth factor angiopoietin 2 (Ang2) destabilizes blood vessels, enhances vascular leak and induces vascular regression and endothelial cell apoptosis. We considered that Ang2 might be important in hyperoxic acute lung injury (ALI). Here we have characterized the responses in lungs induced by hyperoxia in wild-type and Ang2[sup.-/-] mice or those given either recombinant Ang2 or short interfering RNA (siRNA) targeted to Ang2. During hyperoxia Ang2 expression is induced in lung epithelial cells, while hyperoxia-induced oxidant injury, cell death, inflammation, permeability alterations and mortality are ameliorated in Ang2[sup.-/-] and siRNA-treated mice. Hyperoxia induces and activates the extrinsic and mitochondrial cell death pathways and activates initiator and effector caspases through Ang2-dependent pathways in vivo. Ang2 increases inflammation and cell death during hyperoxia in vivo and stimulates epithelial necrosis in hyperoxia in vitro. Ang2 in plasma and alveolar edema fluid is increased in adults with ALI and pulmonary edema. Tracheal Ang2 is also increased in neonates that develop bronchopulmonary dysplasia. Ang2 is thus a mediator of epithelial necrosis with an important role in hyperoxic ALI and pulmonary edema., Author(s): Vineet Bhandari [1]; Rayman Choo-Wing [1]; Chun G Lee [2]; Zhou Zhu [2]; Jonathan H Nedrelow [1]; Geoffrey L Chupp [2]; Xucher Zhang [2]; Michael A Matthay [3]; Lorraine [...]

Distance based unsupervised clustering of gene expression data is commonly used to identify heterogeneity in biologic samples. However, high noise levels in gene expression data and relatively high correlation between genes are often encountered, so traditional distances such as Euclidean distance may not be effective at discriminating the biological differences between samples. An alternative method to examine disease phenotypes is to use pre-defined biological pathways. These pathways have been shown to be perturbed in different ways in different subjects who have similar clinical features. We hypothesize that differences in the expressions of genes in a given pathway are more predictive of differences in biological differences compared to standard approaches and if integrated into clustering analysis will enhance the robustness and accuracy of the clustering method. To examine this hypothesis, we developed a novel computational method to assess the biological differences between samples using gene expression data by assuming that ontologically defined biological pathways in biologically similar samples have similar behavior. Results: Pre-defined biological pathways were downloaded and genes in each pathway were used to cluster samples using the Gaussian mixture model. The clustering results across different pathways were then summarized to calculate the pathway-based distance score between samples. This method was applied to both simulated and real data sets and compared to the traditional Euclidean distance and another pathway-based clustering method, Pathifier. The results show that the pathway-based distance score performs significantly better than the Euclidean distance, especially when the heterogeneity is low and genes in the same pathways are correlated. Compared to Pathifier, we demonstrated that our approach achieves higher accuracy and robustness for small pathways. When the pathway size is large, by downsampling the pathways into smaller pathways, our approach was able to achieve comparable performance. Conclusions: We have developed a novel distance score that represents the biological differences between samples using gene expression data and pre-defined biological pathway information. Application of this distance score results in more accurate, robust, and biologically meaningful clustering results in both simulated data and real data when compared to traditional methods. It also has comparable or better performance compared to Pathifier. [ABSTRACT FROM AUTHOR]

Microsporidia are obligate intracellular protozoa that parasitize both vertebrates and invertebrates and are now recognized as important pathogens in individuals infected with human immunodeficiency virus type 1 (HIV-1). We describe the clinical and morphological features of a case of pleistophora (microsporidian) myositis in a patient with AIDS and delineate the stages of the microsporidian life cycle, as visualized by light and electron microscopy. We discuss significant aspects of microsporidian infections in humans and of myopathy attributable to other causes in HIV-1-infected individuals. As far as we know, ours is only the second reported case of microsporidian myositis and the first reported case in a patient with documented HIV-1 infection. [ABSTRACT FROM PUBLISHER]

Rationale: Asthma is a complex, heterogeneous disease strongly associated with type 2 inflammation, and blood eosinophil counts guide therapeutic interventions in moderate and severe asthma. Eosinophils are leukocytes involved in type 2 immune responses. Despite these critical associations between asthma and blood eosinophil counts, the shared genetic architecture of these two traits remains unknown. The objective of the present study was to characterise the genetic architecture of blood eosinophil counts and asthma in the UK Biobank., Methods: We performed genome-wide association studies (GWAS) of doctor-diagnosed asthma, blood eosinophil, neutrophil, lymphocyte and monocyte counts in the UK Biobank. Genetic correlation analysis was performed on GWAS results and validated in the Trans-National Asthma Genetic Consortium (TAGC) study of asthma., Results: GWAS of doctor-diagnosed asthma and blood eosinophil counts in the UK Biobank identified 585 and 3429 significant variants, respectively. STAT6 , a transcription factor involved in interleukin-4 signalling, was a key shared pathway between asthma and blood eosinophil counts. Genetic correlation analysis demonstrated a positive correlation between doctor-diagnosed asthma and blood eosinophil counts (r=0.38±0.10, correlation±se; p=4.7×10 -11 ). As a validation of this association, we found a similar correlation between TAGC and blood eosinophil counts in the UK Biobank (0.37±0.08, correlation±se; p=1.2×10 -6 )., Conclusions: These findings define the shared genetic architecture between blood eosinophil counts and asthma risk in subjects of European ancestry and point to a genetic link to the STAT6 signalling pathway in these two traits., Competing Interests: Conflict of interest: B. Li has nothing to disclose. Conflict of interest: Y. Wang has nothing to disclose. Conflict of interest: Z. Wang has nothing to disclose. Conflict of interest: X. Li has nothing to disclose. Conflict of interest: S. Kay has nothing to disclose. Conflict of interest: G.L. Chupp reports grants and personal fees from GSK, AstraZeneca, Genentech and Teva, personal fees from BI, and grants and personal fees from Sanofi and Regeneron, outside the submitted work. Conflict of interest: H. Zhao has nothing to disclose. Conflict of interest: J.L. Gomez has nothing to disclose., (Copyright ©The authors 2023.)