The Journal of allergy and clinical immunology · 2026
Epitope-specific IgE profiles are predictive of desensitization and remission in the IMPACT trial.
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Wang Julie, Khoshbakht Samane, Lee Kyung Won, Jones Stacie M, Huffaker Michelle F, Plaut Marshall, Wheatley Lisa M, Baloh Carolyn H, Suárez-Fariñas Mayte, Sampson Hugh A
Аннотация
BACKGROUND: Results from the IMPACT trial suggest that initiation of peanut oral immunotherapy (pnOIT) before age 4 years can increase chances of achieving desensitization and remission.
OBJECTIVE: We assessed sequential (linear) epitope-specific (es)-IgE and es-IgG4 profiles over the course of pnOIT to determine whether they could predict desensitization and remission outcomes.
METHODS: Participants in the IMPACT trial (NCT03345160) were randomized to pnOIT or placebo for 134 weeks. Desensitization and remission end points were assessed by oral food challenges. There were 93 (96.9%) of 96 participants in the pnOIT group and 47 (94%) of 50 in the placebo group. Specific IgE and IgG4 levels to peanut, component proteins, and 64 allergenic epitopes were measured. Machine learning was used to develop predictive models for desensitization and remission.
RESULTS: PnOIT was associated with an overall decrease in sequential es-IgE and increase in es-IgG4 levels. Younger subjects (<2.3 years old) had lower baseline es-IgE binding and lower fold change in es-IgE and es-IgG4 binding during pnOIT. Participants with desensitization had lower baseline es-IgE levels than those without desensitization. A machine learning model that included 9 es-IgE antibodies predicted remission with an overall performance as follows: accuracy 88.2%, area under the curve 88.2%, sensitivity 83.3%, and specificity 90.0%-comparable to, but not better than, models based on peanut IgE.
CONCLUSIONS: Baseline epitope IgE profiles can predict remission outcome for children undergoing pnOIT. Age and baseline peanut IgE remain important factors across models.
OBJECTIVE: We assessed sequential (linear) epitope-specific (es)-IgE and es-IgG4 profiles over the course of pnOIT to determine whether they could predict desensitization and remission outcomes.
METHODS: Participants in the IMPACT trial (NCT03345160) were randomized to pnOIT or placebo for 134 weeks. Desensitization and remission end points were assessed by oral food challenges. There were 93 (96.9%) of 96 participants in the pnOIT group and 47 (94%) of 50 in the placebo group. Specific IgE and IgG4 levels to peanut, component proteins, and 64 allergenic epitopes were measured. Machine learning was used to develop predictive models for desensitization and remission.
RESULTS: PnOIT was associated with an overall decrease in sequential es-IgE and increase in es-IgG4 levels. Younger subjects (<2.3 years old) had lower baseline es-IgE binding and lower fold change in es-IgE and es-IgG4 binding during pnOIT. Participants with desensitization had lower baseline es-IgE levels than those without desensitization. A machine learning model that included 9 es-IgE antibodies predicted remission with an overall performance as follows: accuracy 88.2%, area under the curve 88.2%, sensitivity 83.3%, and specificity 90.0%-comparable to, but not better than, models based on peanut IgE.
CONCLUSIONS: Baseline epitope IgE profiles can predict remission outcome for children undergoing pnOIT. Age and baseline peanut IgE remain important factors across models.