Immune Signatures as Predictive Biomarkers for SCIT Response in Allergic Rhinitis Patients

A new study reveals immune signatures that predict the effectiveness of subcutaneous immunotherapy (SCIT) in allergic rhinitis (AR) patients with house dust mite allergies. The research aimed to identify biomarkers that could enhance clinical outcomes by distinguishing SCIT responders from nonresponders.
The study analyzed circulating T and B cell subsets, serum immunoglobulin levels, and combined symptom and medication scores (CSMS) in two cohorts: a discovery group (Tongji cohort, n=72) and a validation group (Wisco cohort, n=43). SCIT responders were defined by a ≥30% improvement in CSMS after 12 months.
Key findings indicate that SCIT responders exhibited higher baseline levels of allergen-specific IgE (sIgE)/total IgE (tIgE) ratio, Type 2 helper T (TH2) cells, Type 2 follicular helper T (TFH2) cells, and memory B cell subtypes (CD23+ nonswitched memory B cells and switched memory B cells), along with lower follicular regulatory T cells (TFR) and TFR/TFH2 cell ratio. 
Using random forest and logistic regression algorithms, three key biomarkers- sIgE/tIgE ratio, TFR/TFH2 ratio, and CD23+ B memory cell frequency, were identified as significant predictors of SCIT response. 
The predictive model demonstrated high accuracy (AUC = 0.899 in Tongji; AUC = 0.893 in Wisco), underscoring the potential of personalized immunotherapy approaches for AR patients based on immune signatures. 
These findings offer a promising step towards optimizing SCIT efficacy through biomarker-based treatment plans.