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Rationale: The past 25 years have seen huge progress in understanding of the pathobiology of type-2 (T2) asthma, identification of measurable biomarkers, and the emergence of novel monoclonal antibody treatments. Although present in a minority of patients with severe asthma, very little is known about the mechanisms underlying T2-low asthma, making it a significant unmet need in asthma research. Objectives: The objective of this study was to explore the differences between study exacerbators and nonexacerbators, to describe physiological changes at exacerbation in those who are T2 HIGH and T2 LOW at the time of exacerbation, and to evaluate the stability of inflammatory phenotypes when stable and at exacerbation. Methods: Exacerbation assessment was a prespecified secondary analysis of data from a 48-week, multicenter, randomized controlled clinical study comparing the use of biomarkers and symptoms to adjust steroid treatment in a T2-low severe asthma-enriched cohort. Participants were phenotyped as T2 LOW (fractional exhaled nitric oxide ⩽ 20 ppb and blood eosinophil count ⩽ 150 cells/µl) or T2 HIGH (fractional exhaled nitric oxide > 20 or blood eosinophil count > 150) at study enrollment and at each exacerbation. Here, we report the findings of the exacerbation analyses, including comparison of exacerbators and nonexacerbators, the physiological changes at exacerbation in those who had evidence of T2 biology at exacerbation versus those that did not, and the stability of inflammatory phenotypes when stable and at exacerbation. Measurements and Main Results: Of the 301 participants, 60.8% (183) had one or more self-reported exacerbations (total of 390). Exacerbators were more likely to be female, have a higher body mass index, and have more exacerbations requiring oral corticosteroid and unscheduled primary care attendances for exacerbations. At enrollment, 23.6% (71) were T2 LOW and 76.4% (230) T2 HIGH . The T2 LOW group had more asthma primary care attendances, were more likely to have a previous admission to HDU (high dependency unit)/ICU and to be receiving maintenance oral corticosteroids. At exacerbation, the T2 LOW events were indistinguishable from T2 HIGH exacerbations in terms of lung function (mean fall in T2 LOW FEV 1, 200 [400] ml vs. T2 HIGH 200 [300] ml; P  = 0.93) and symptom increase (ACQ5: T2 LOW , 1.4 [0.8] vs. T2 HIGH , 1.3 [0.8]; P  = 0.72), with no increase in T2 biomarkers from stable to exacerbation state in the T2 LOW exacerbations. The inflammatory phenotype within individual patients was dynamic; inflammatory phenotype at study entry did not have a significant association with exacerbation phenotype. Conclusions: Asthma exacerbations demonstrating a T2 LOW phenotype were physiologically and symptomatically similar to T2 HIGH exacerbations. T2 LOW asthma was an unstable phenotype, suggesting that exacerbation phenotyping should occur at the time of exacerbation. The clinically significant exacerbations in participants without evidence of T2 biology at the time of exacerbation highlight the unmet and pressing need to further understand the mechanisms at play in non-T2 asthma. Clinical trial registered with www.clinicaltrials.gov (NCT02717689).

Rationale: Blood eosinophil counts are used to inform diagnosis/management of eosinophilic asthma. Objectives: Examine blood eosinophil variability and identify factors affecting eosinophil levels to inform clinical interpretation. Methods: Post hoc analysis to understand eosinophil variability using data from four randomized controlled asthma trials. We examined 1 ) influence of intrinsic/extrinsic factors (comorbidities, medication, and patient history) using baseline data ( n  = 2,612); 2 ) monthly variation using placebo-treated patient data ( n  = 713); 3 ) stability of eosinophil classification (<150, 150-299, and ⩾300 cells/μl) in placebo-treated patients with monthly measurements over a 1-year period ( n  = 751); and 4 ) impact of technical factors (laboratory-to-laboratory differences and time from collection to analysis). Results: Of intrinsic/extrinsic factors examined, nasal polyps increased eosinophil levels by 38%, whereas current smoking decreased levels by 23%. Substantial seasonal differences in eosinophil counts were observed, with differences of ∼20% between July and January. Eosinophil levels between 150 and 299 cells/μl were least stable, with 44% of patients remaining in the same classification for seven of 10 measurements versus 59% and 66% of patients in the <150 and ⩾300 cells/μl subgroups, respectively. Measurements at different laboratories showed high association (Spearman's correlation coefficient, R  = 0.89); however, eosinophil counts were reduced, with longer time from collection to analysis, and variability increased with increasing eosinophil counts. Conclusions: Several intrinsic, extrinsic, and technical factors may influence, and should be considered in, clinical interpretation of eosinophil counts. Additionally, a single measurement may not be sufficient when using eosinophil counts for diagnosis/management of eosinophilic asthma.

Rationale: New approaches are needed to guide personalized treatment of asthma. Objectives: To test if urinary eicosanoid metabolites can direct asthma phenotyping. Methods: Urinary metabolites of prostaglandins (PGs), cysteinyl leukotrienes (CysLTs), and isoprostanes were quantified in the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Diseases Outcomes) study including 86 adults with mild-to-moderate asthma (MMA), 411 with severe asthma (SA), and 100 healthy control participants. Validation was performed internally in 302 participants with SA followed up after 12-18 months and externally in 95 adolescents with asthma. Measurement and Main Results: Metabolite concentrations in healthy control participants were unrelated to age, body mass index, and sex, except for the PGE 2 pathway. Eicosanoid concentrations were generally greater in participants with MMA relative to healthy control participants, with further elevations in participants with SA. However, PGE 2 metabolite concentrations were either the same or lower in male nonsmokers with asthma than in healthy control participants. Metabolite concentrations were unchanged in those with asthma who adhered to oral corticosteroid treatment as documented by urinary prednisolone detection, whereas those with SA treated with omalizumab had lower concentrations of LTE 4 and the PGD 2 metabolite 2,3-dinor-11β-PGF 2α . High concentrations of LTE 4 and PGD 2 metabolites were associated with lower lung function and increased amounts of exhaled nitric oxide and eosinophil markers in blood, sputum, and urine in U-BIOPRED participants and in adolescents with asthma. These type 2 (T2) asthma associations were reproduced in the follow-up visit of the U-BIOPRED study and were found to be as sensitive to detect T2 inflammation as the established biomarkers. Conclusions: Monitoring of urinary eicosanoids can identify T2 asthma and introduces a new noninvasive approach for molecular phenotyping of adult and adolescent asthma.Clinical trial registered with www.clinicaltrials.gov (NCT01976767).