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Altered myeloid inflammation and lymphopenia are hallmarks of severe infections. We identified the upregulated EN-RAGE gene program in airway and blood myeloid cells from patients with acute lung injury from SARS-CoV-2 or other causes across 7 cohorts. This program was associated with greater clinical severity and predicted future mechanical ventilation and death. EN-RAGEhi myeloid cells express features consistent with suppressor cell functionality, including low HLA-DR and high PD-L1. Sustained EN-RAGE program expression in airway and blood myeloid cells correlated with clinical severity and increasing expression of T cell dysfunction markers. IL-6 upregulated many EN-RAGE program genes in monocytes in vitro. IL-6 signaling blockade by tocilizumab in a placebo-controlled clinical trial led to rapid normalization of EN-RAGE and T cell gene expression. This identifies IL-6 as a key driver of myeloid dysregulation associated with worse clinical outcomes in COVID-19 patients and provides insights into shared pathophysiological mechanisms in non-COVID-19 ARDS.

Angiopoietin-2 (Ang-2) is associated with vascular endothelial injury and permeability in the acute respiratory distress syndrome (ARDS) and sepsis. Elevated circulating Ang-2 levels may identify critically ill patients with distinct pathobiology amenable to targeted therapy. We hypothesized that plasma Ang-2 measured shortly after hospitalization among patients with sepsis would be associated with the development of ARDS and poor clinical outcomes. To test this hypothesis, we measured plasma Ang-2 in a cohort of 757 patients with sepsis, including 267 with ARDS, enrolled in the emergency department or early in their ICU course before the COVID-19 pandemic. Multivariable models were used to test the association of Ang-2 with the development of ARDS and 30-day morality. We found that early plasma Ang-2 in sepsis was associated with higher baseline severity of illness, the development of ARDS, and mortality risk. The association between Ang-2 and mortality was strongest among patients with ARDS and sepsis as compared to those with sepsis alone (OR 1.81 vs. 1.52 per log Ang-2 increase). These findings might inform models testing patient risk prediction and strengthen the evidence for Ang-2 as an appealing biomarker for patient selection for novel therapeutic agents to target vascular injury in sepsis and ARDS.

Severe asthma patients with low type 2 inflammation derive less clinical benefit from therapies targeting type 2 cytokines and represent an unmet need. We show that mast cell tryptase is elevated in severe asthma patients independent of type 2 biomarker status. Active β-tryptase allele count correlates with blood tryptase levels, and asthma patients carrying more active alleles benefit less from anti-IgE treatment. We generated a noncompetitive inhibitory antibody against human β-tryptase, which dissociates active tetramers into inactive monomers. A 2.15 Å crystal structure of a β-tryptase/antibody complex coupled with biochemical studies reveal the molecular basis for allosteric destabilization of small and large interfaces required for tetramerization. This anti-tryptase antibody potently blocks tryptase enzymatic activity in a humanized mouse model, reducing IgE-mediated systemic anaphylaxis, and inhibits airway tryptase in Ascaris-sensitized cynomolgus monkeys with favorable pharmacokinetics. These data provide a foundation for developing anti-tryptase as a clinical therapy for severe asthma.

RationaleQuantification of type 2 inflammation provided a molecular basis for heterogeneity in asthma. Non-type 2 pathways that contribute to asthma pathogenesis are not well understood.ObjectivesTo identify dysregulated pathways beyond type 2 inflammation.MethodsWe applied RNA sequencing to airway epithelial brushings obtained from subjects with stable mild asthma not on corticosteroids (n = 19) and healthy control subjects (n = 16). Sequencing reads were mapped to human and viral genomes. In the same cohort, and in a separate group with severe asthma (n = 301), we profiled blood gene expression with microarrays.Measurements and main resultsIn airway brushings from mild asthma on inhaled corticosteroids, RNA sequencing yielded 1,379 differentially expressed genes (false discovery rate

BackgroundAsthma is heterogeneous, and airway dysbiosis is associated with clinical features in patients with mild-to-moderate asthma. Whether similar relationships exist among patients with severe asthma is unknown.ObjectiveWe sought to evaluate relationships between the bronchial microbiome and features of severe asthma.MethodsBronchial brushings from 40 participants in the Bronchoscopic Exploratory Research Study of Biomarkers in Corticosteroid-refractory Asthma (BOBCAT) study were evaluated by using 16S ribosomal RNA-based methods. Relationships to clinical and inflammatory features were analyzed among microbiome-profiled subjects. Secondarily, bacterial compositional profiles were compared between patients with severe asthma and previously studied healthy control subjects (n = 7) and patients with mild-to-moderate asthma (n = 41).ResultsIn patients with severe asthma, bronchial bacterial composition was associated with several disease-related features, including body mass index (P < .05, Bray-Curtis distance-based permutational multivariate analysis of variance; PERMANOVA), changes in Asthma Control Questionnaire (ACQ) scores (P < .01), sputum total leukocyte values (P = .06), and bronchial biopsy eosinophil values (per square millimeter, P = .07). Bacterial communities associated with worsening ACQ scores and sputum total leukocyte values (predominantly Proteobacteria) differed markedly from those associated with body mass index (Bacteroidetes/Firmicutes). In contrast, improving/stable ACQ scores and bronchial epithelial gene expression of FK506 binding protein (FKBP5), an indicator of steroid responsiveness, correlated with Actinobacteria. Mostly negative correlations were observed between biopsy eosinophil values and Proteobacteria. No taxa were associated with a TH2-related epithelial gene expression signature, but expression of TH17-related genes was associated with Proteobacteria. Patients with severe asthma compared with healthy control subjects or patients with mild-to-moderate asthma were significantly enriched in Actinobacteria, although the largest differences observed involved a Klebsiella genus member (7.8-fold increase in patients with severe asthma, adjusted P < .001).ConclusionsSpecific microbiota are associated with and may modulate inflammatory processes in patients with severe asthma and related phenotypes. Airway dysbiosis in patients with severe asthma appears to differ from that observed in those with milder asthma in the setting of inhaled corticosteroid use.

BackgroundEosinophilic airway inflammation is heterogeneous in asthmatic patients. We recently described a distinct subtype of asthma defined by the expression of genes inducible by T(H)2 cytokines in bronchial epithelium. This gene signature, which includes periostin, is present in approximately half of asthmatic patients and correlates with eosinophilic airway inflammation. However, identification of this subtype depends on invasive airway sampling, and hence noninvasive biomarkers of this phenotype are desirable.ObjectiveWe sought to identify systemic biomarkers of eosinophilic airway inflammation in asthmatic patients.MethodsWe measured fraction of exhaled nitric oxide (Feno), peripheral blood eosinophil, periostin, YKL-40, and IgE levels and compared these biomarkers with airway eosinophilia in asthmatic patients.ResultsWe collected sputum, performed bronchoscopy, and matched peripheral blood samples from 67 asthmatic patients who remained symptomatic despite maximal inhaled corticosteroid treatment (mean FEV(1), 60% of predicted value; mean Asthma Control Questionnaire [ACQ] score, 2.7). Serum periostin levels are significantly increased in asthmatic patients with evidence of eosinophilic airway inflammation relative to those with minimal eosinophilic airway inflammation. A logistic regression model, including sex, age, body mass index, IgE levels, blood eosinophil numbers, Feno levels, and serum periostin levels, in 59 patients with severe asthma showed that, of these indices, the serum periostin level was the single best predictor of airway eosinophilia (P = .007).ConclusionPeriostin is a systemic biomarker of airway eosinophilia in asthmatic patients and has potential utility in patient selection for emerging asthma therapeutics targeting T(H)2 inflammation.

Chronic spontaneous urticaria (CSU) is a dermatologic condition characterized by spontaneous, pruritic hives and/or angioedema that persists for 6 weeks or longer with no identifiable trigger. Antihistamines and second-line therapies such as omalizumab are effective for some CSU patients, but others remain symptomatic, with significant impact on quality of life. This variable response to treatment and autoantibody levels across patients highlight clinically heterogeneous subgroups. We aimed to highlight pathways involved in CSU by investigating the genetics of CSU risk and subgroups. We performed a genome-wide association study (GWAS) of 679 CSU patients and 4446 controls and a GWAS of chronic urticaria (CU)-index, which measures IgG autoantibodies levels, by comparing 447 CU index–low to 183 CU index–high patients. We also tested whether polygenic scores for autoimmune-related disorders were associated with CSU risk and CU index. We identified 2 loci significantly associated with disease risk. The strongest association mapped to position 56 of HLA-DQA1 (P = 1.69 × 10−9), where the arginine residue was associated with increased risk (odds ratio = 1.64). The second association signal colocalized with expression-quantitative trait loci for ITPKB in whole blood (P colocalization =.997). The arginine residue at position 56 of HLA-DQA1 was also associated with increased risk of CU index–high (P = 6.15 × 10−5, odds ratio = 1.86), while the ITKPB association was not (P =.64). Polygenic scores for 3 autoimmune-related disorders (hypothyroidism, type 1 diabetes, and vitiligo) were associated with CSU risk and CU index (P < 2.34 × 10−3, odds ratio > 1.72). A GWAS of CSU identified 2 genome-wide significant loci, highlighting the shared genetics between CU index and autoimmune disorders. [ABSTRACT FROM AUTHOR]

Asthma is a complex, heterogeneous disease with a high unmet medical need, despite therapies targeting a multitude of pathways. The ability to quantitatively integrate preclinical and clinical data on these pathways could aid in the development and testing of novel targets and therapeutics. In this work, we develop a computational model of asthma biology, including key cell types and mediators, and create a virtual population capturing clinical heterogeneity. The simulated responses to therapies targeting IL‐13, IL‐4Rα, IL‐5, IgE, and TSLP demonstrate agreement with clinical endpoints and biomarkers of type 2 (T2) inflammation, including blood eosinophils, FEV1, IgE, and FeNO. We use the model to explore the potential benefit of targeting the IL‐33 pathway with anti‐IL‐33 and anti‐ST2. Model predictions are compared with data on blood eosinophils, FeNO, and FEV1 from recent anti‐IL‐33 and anti‐ST2 trials and used to interpret trial results based on pathway biology and pharmacology. Results of sensitivity analyses on the contributions of IL‐33 to the predicted biomarker changes suggest that anti‐ST2 therapy reduces circulating blood eosinophil levels primarily through its impact on eosinophil progenitor maturation and IL‐5‐dependent survival, and induces changes in FeNO and FEV1 through its effect on immune cells involved in T2 cytokine production. Finally, we also investigate the impact of ST2 genetics on the conferred benefit of anti‐ST2. The model includes representation of a wide array of biologic mechanisms and interventions that will provide mechanistic insight and support clinical program design for a wide range of novel therapies during drug development. [ABSTRACT FROM AUTHOR]