Impact of clinical factors and season on inflammatory cytokines in biologic-treated and untreated asthma.

BACKGROUND: Clinical features influence cytokine profiles and can inform biomarker studies. OBJECTIVES: We assessed the impact of 13 preselected patient characteristics on the circulating levels of 15 Th-1/2/17 cytokines in moderate-to-severe asthma patients on omalizumab, anti-IL-5 (mepolizumab, benralizumab), or dupilumab (n = 76) versus controls (n = 162) not yet on biologics but meeting eligibility criteria for a T2-biologic. METHODS: Plasma cytokines (Olink) were analyzed for associations with these clinical/lifestyle factors using LASSO regression and observed variance explained estimated using generalized linear models. Differential expression analysis was conducted using limma. RESULTS: In controls, IL-6 had the highest variance explained by clinical/lifestyle factors (50% in non-allergic rhinitis patients, 22% in allergic rhinitis), with BMI and exacerbations contributing most to this. In T2-biologics users, eotaxin-1 had the highest explained variance (26.0%) and smoking was the most linked to Th1/17 cytokines. In omalizumab users: IFN-γ (51%) was most explained (exacerbations, smoking, age). In anti-IL-5 users, eotaxin-1 (58%; BMI, sex) and in dupilumab users, IL-4 (83%) was most explained (exacerbations, sex, BMI). The association between patient characteristics and cytokine levels differed by the season of sample collection. In non-biologic users, IL-6 was the cytokine with the most explained variance in the Winter (asthma admissions accounted for most of this variance) and IL-18 in the Spring/Summer/Fall. In T2-biologic users, TNF-α was the top cytokine in the Winter (smoking accounted for most of this variance); IL-4 (allergic rhinitis), IL-33 (IgE and eosinophil), and CXCL10 (allergic rhinitis and IgE) were the top cytokines in the Spring/Summer/Fall. In differential expression analyses, IL-1β was lower in biologics users than non-biologics users. CONCLUSIONS: In moderate-to-severe asthma, multiple clinical features and season are associated with cytokine levels and might impact inference from proteomics studies. Smoking and BMI are the key proinflammatory factors in biologics-treated and untreated patients.