Predictive modeling for cow's milk allergy remission by low-dose oral immunotherapy in young children

Background: The effectiveness of slow low-dose oral immunotherapy (SLOIT) for cow's milk (CM) allergy has been reported. Most OIT studies have discussed the target populations over 4 years old. Furthermore, no predicting modeling is reported for CM allergy remission by CM-SLOIT under 4 years of age. Objective: We sought to develop a predictive model for CM allergy remission by SLOIT after 3 years in young children who started CM-SLOIT under 4 years of age. Methods: We included young children with cow's milk allergy or cow's milk sensitization (development modeling set with 120 children and validation modeling set with 71 children). We did logistic regression analysis to develop the models. We calculated the area under the receiver operating curves (ROC-AUCs) to evaluate the predictive modeling performance. Results: The model (CM-sIgE before SLOIT + age at beginning SLOIT + serum TARC before starting SLOIT + CM-sIgE titer one year after OIT) showed good discrimination with the ROC-AUC of 0.83 (95% CI:0.76–0.91) on internal validation. Applying the model to the validation set gave good discrimination (ROC-AUC = 0.89, 95% CI:0.80–0.97) and a reasonable calibration (intraclass correlation coefficient = 0.88, 95% CI:0.62–0.97). Conclusion: We developed and validated predictive modeling for determining the remission rate of CM allergy at 3 years after SLOIT under 4 years of age in children with CM allergy. This predictive model is highly accurate and can support CM allergy management. (226 words

A genome-wide association study for allergen component sensitizations identifies allergen component–specific and allergen protein group–specific associations

Background: Allergic diseases are some of the most common diseases worldwide. Genome-wide association studies (GWASs) have been conducted to elucidate the genetic factors of allergic diseases. However, no GWASs for allergen component sensitization have been performed. Objective: We sought to detect genetic variants associated with differences in immune responsiveness against allergen components. Methods: The participants of the present study were recruited from the Tokyo Children’s Health, Illness, and Development study, and allergen component–specific IgE level at age 9 years was measured by means of allergen microarray immunoassays. We performed GWASs for allergen component sensitization against each allergen (single allergen component sensitization, number of allergen components analyzed, n = 31), as well as against allergen protein families (allergen protein group sensitization, number of protein groups analyzed, n = 16). Results: We performed GWAS on 564 participants of the Tokyo Children’s Health, Illness, and Development study and found associations between Amb a 1 sensitization and the immunoglobulin heavy-chain variable gene on chromosome 14 and between Phl p 1 sensitization and the HLA class II region on chromosome 6 (P < 5.0 × 10−8). A GWAS-significant association was also observed between the HLA class II region and profilin sensitization (P < 5.0 × 10−8). Conclusions: Our data provide the first demonstration of genetic risk for allergen component sensitization and show that this genetic risk is related to immune response genes including immunoglobulin heavy-chain variable gene and HLA