Risk prediction model construction for asthma after allergic rhinitis by blood immune T effector cells.

Abstract

Allergic rhinitis (AR) and asthma (AS) are prevalent and frequently co-occurring respiratory diseases, with mutual influence on each other. They share similar etiology, pathogenesis, and pathological changes. Due to the anatomical continuity between the upper and lower respiratory tracts, allergic inflammation in the nasal cavity can readily propagate downwards, leading to bronchial inflammation and asthma. AR serves as a significant risk factor for AS by potentially inducing airway hyperresponsiveness in patients. Currently, there is a lack of reliable predictors for the progression from AR to AS. In this exhaustive investigation, we reexamined peripheral blood single cell RNA sequencing datasets from patients with AS following AR and healthy individuals. In addition, we used the bulk RNA sequencing dataset as a validation lineup, which included AS, AR, and healthy controls. Using marker genes of related cell subtype, signatures predicting the progression of AR to AS were generated. We identified a subtype of immune-activating effector T cells that can distinguish patients with AS after AR. By combining specific marker genes of effector T cell subtype, we established prediction models of 16 markers. The model holds great promise for assessing AS risk in individuals with AR, providing innovative avenues for clinical diagnosis and treatment strategies. Subcluster T effector cells may play a key role in post-AR AS. Notably, ACTR3 and HSPA8 genes were significantly upregulated in the blood of AS patients compared to healthy patients.