Suárez-Fariñas Mayte, Lee Kyung Won, Suprun Maria, Bahnson Henry T, Foong Ru-Xin, Du Toit George, Lack Gideon, Sampson Hugh A
Center for Biostatistics, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY.
Center for Biostatistics, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY; Department of Pediatrics, Allergy and Immunology, Icahn School of Medicine at Mount Sinai, New York, NY.
J Allergy Clin Immunol. 2025 Jun 30. doi: 10.1016/j.jaci.2025.06.022.
The development and resolution of peanut allergy (PA) was evaluated in children enrolled or screened for the Learning Early About Peanut (LEAP) intervention trial. The development of epitope-specific (es) IgE and es-IgG antibodies was evaluated in a subset of these children to determine whether their PA status could be predicted at 4-11 months of age.
Sera from 386 children enrolled or screened as part of the LEAP trial were assayed at 4-11 months (baseline) and 60 months of age, and final allergy status was established by oral food challenge at 60 months. Es-IgE and es-IgG to 64 informative peanut epitopes were analyzed by linear mixed-effect models, and machine learning was used to develop a predictive algorithm.
Children were categorized in 4 groups: 37 developed PA early that persisted (EP), 17 developed PA early that resolved (ER), 33 developed PA later in childhood (by 60 months of age, LA), and 298 never developed PA. Differences among groups in es-IgE and es-IgG were detectable at baseline. ER showed lower levels of Ara h 2_008 es-IgE and higher es-IgG levels to several epitopes compared to the EP group. Both EP and ER groups had greater levels of several baseline es-IgE antibodies compared to the LA group. By 60 months, all 3 groups had significant increases in both the levels and diversity of es-IgG antibodies, while es-IgE antibodies increased only in EP and LA groups and decreased in ER group. Machine learning models were predictive of persistent allergy by 60 months of age, with an average area under the curve in testing of 0.75.
These results suggest that baseline es-IgE in children sensitized in the first year of life can predict likely persistent PA.
在参与或接受“早期了解花生(LEAP)”干预试验入组或筛查的儿童中,评估了花生过敏(PA)的发生及缓解情况。在这些儿童的一个亚组中,评估了表位特异性(es)IgE和es-IgG抗体的产生情况,以确定在4至11个月龄时能否预测其PA状态。
对386名作为LEAP试验一部分入组或筛查的儿童,在4至11个月(基线)和60个月龄时检测血清,并在60个月时通过口服食物激发确定最终过敏状态。采用线性混合效应模型分析针对64个信息丰富的花生表位的es-IgE和es-IgG,并使用机器学习开发预测算法。
儿童分为4组:37名早期发生PA且持续存在(EP),17名早期发生PA但已缓解(ER),33名在儿童期后期(至60个月龄)发生PA(LA),298名从未发生PA。在基线时可检测到各组之间es-IgE和es-IgG的差异。与EP组相比,ER组的Ara h 2_008 es-IgE水平较低,而对几个表位的es-IgG水平较高。与LA组相比,EP组和ER组的几种基线es-IgE抗体水平更高。到60个月时,所有3组es-IgG抗体的水平和多样性均显著增加,而es-IgE抗体仅在EP组和LA组增加,在ER组减少。机器学习模型可预测60个月龄时的持续性过敏,测试中的平均曲线下面积为0.75。
这些结果表明,1岁内致敏儿童中的基线es-IgE可预测可能持续存在的PA。