Prediction of allergic disease trajectories from birth up to adolescence

Leskien, Miriam ; Scheerer, Martin; Thiering, Elisabeth ; Kress, Sara ; Coffey, Claire ; Berdel, Dietrich; Berg, Andrea von; Bauer, Carl‐Peter; Gappa, Monika ; Heinrich, Joachim ; Koletzko, Sibylle ; Schikowski, Tamara; Koletzko, Berthold ; Peters, Annette und Standl, Marie (2026): Prediction of allergic disease trajectories from birth up to adolescence. In: Pediatric Allergy and Immunology, Vol. 37, No. 4, e70341

Abstract

Background: Allergic diseases often develop jointly during early childhood. Potential disease trajectories and relevant early-life factors have been described, yet existing prediction approaches mostly focus on single allergic diseases cross-sectionally. Models addressing allergic multimorbidity and disease trajectories are lacking. We aim to predict allergic disease trajectories from birth up to adolescence using early-life factors.

Methods: Preceding research using data from 4646 adolescents of the German birth cohorts GINIplus and LISA identified seven allergic disease trajectories up to the age of 15 years. A set of predictors comprising parental and perinatal factors, early allergic or respiratory symptoms, lifestyle and environmental factors was used with an XGBoost machine learning approach to perform multiclass classification. In a subsample (N = 2109), polygenic risk scores (PRS) for asthma, allergic rhinitis, atopic dermatitis, and any allergy were added to the predictor set.

Results: Our approach revealed moderate classification success (multiclass area under the curve (AUC) = 0.69). A macro-averaged sensitivity of 0.26 and specificity of 0.89 were obtained. The most important predictors were early-life skin rash, respiratory symptoms, and air pollution. In the sub-analysis, the PRS were among the factors with high importance, but the prediction performance in external test data was not improved.

Conclusions: Our prediction success was comparable to established prediction scores while accounting for multiple allergic disease trajectories and using solely early-life factors. This study cannot yet provide reliable individual-level prediction in a clinical setting but can inform development of future work on this.

• Item Type: Journal article
• EU Funded Grant Agreement Number: 949906; 261357
• EU Projects: Horizon 2020 > ERC Grants > ERC Starting Grant; 7. Framework Programme (FP7)
• Faculties: Medicine > Institute for Medical Information Processing, Biometry and Epidemiology; Medicine > Institute and Polyclinic for Occupational, Social and Environmental Medicine; Medicine > Medical Center of the University of Munich > Pediatric Clinic and Outpatient Clinic in the Dr. von Hauner Children‘s Hospital; Medicine > Medical Center of the University of Munich > Paediatric Surgery Clinic and Polyclinic in the Dr. von Hauner Children's Hospital
• Subjects: 600 Technology > 610 Medicine and health
• ISSN: 0905-6157
• Language: English