摘要
背景：成分分辨诊断（CRD）在探索IgE致敏机制方面具有决定性作用，但检测哮喘的预测能力尚未得到解决。
目的：本研究旨在开发和评估一种个性化哮喘预测算法的性能，该算法使用CRD整合过敏致敏信息。
方法：从第21代出生队列中随机选择1125名儿童进行过敏原致敏筛查试验，并使用CRD对112种过敏原成分进行亚样本表征分析。使用火山图和偏最小二乘法（PLS）分析过敏原成分。采用Logistic回归评估所获得潜在成分（LC）与过敏结果（哮喘、鼻炎、湿疹）之间的相关性，包括既往哮喘风险评分中使用的其他潜在预测因素。采用受试者操作特征（ROC）曲线统计评估该模型预测哮喘的准确性。
结果：在PLS中，第一个LC与哮喘、鼻炎和湿疹呈正相关。该LC主要由Der p 1/2/23、Der f 1/2和Fel d1的正权重驱动。第二个LC的主要成分是花粉和食物过敏原。早期喘息史和父母过敏史纳入预测模型后，曲线下面积可提高至0.82。
结论：该方法首次通过综合CRD和临床数据预测13岁时哮喘发生情况，以提高CRD临床适用性。机体对特定过敏原分子高敏似乎与提高哮喘预测模型的准确性相关。
Component-resolved diagnosis in childhood and prediction of asthma in early adolescence A birth cohort study.
Farraia M, Mendes FC, Sokhatska O, Rama T, Severo M, Custovic A, Rufo JC, Barros H, Moreira A.
Abstract
BACKGROUND: Component-resolved diagnosis (CRD) has been decisive in exploring the mechanisms of IgE sensitization, but the predictive ability to detect asthma has not been addressed.
OBJECTIVE: We aim to develop and evaluate the performance of a personalized predictive algorithm for asthma that integrates information on allergic sensitization using CRD.
METHODS: One thousand one hundred one twenty-five children from the Generation XXI birth cohort were randomly selected to perform a screening test for allergic sensitization and a subsample was characterized using CRD against 112 allergen components. Allergen components were analyzed using volcano plots and partial least squares (PLS) analysis. Logistic regression was performed to assess the associations between the obtained latent components (LC) and allergic outcomes (asthma, rhinitis, eczema) including other potential predictors used in previous asthma risk scores. The accuracy of the model in predicting asthma was assessed using Receiver Operating Characteristic (ROC) curve statistics.
RESULTS: In the PLS, the first LC was positively associated with asthma, rhinitis, and eczema. This LC was mainly driven by positive weights for Der p 1/2/23, Der f 1/2, and Fel d 1. The main components in the second LC were pollen and food allergens. History of early wheezing and parental allergy were included in the predictive model and the area under the curve improved to 0.82.
CONCLUSION: This is the first approach to improve the clinical applicability of CRD by combining CRD and clinical data to predict asthma at 13 years. Sensitization to distinct allergen molecules seems relevant to improve the accuracy of asthma prediction models.
背景：成分分辨诊断（CRD）在探索IgE致敏机制方面具有决定性作用，但检测哮喘的预测能力尚未得到解决。
目的：本研究旨在开发和评估一种个性化哮喘预测算法的性能，该算法使用CRD整合过敏致敏信息。
方法：从第21代出生队列中随机选择1125名儿童进行过敏原致敏筛查试验，并使用CRD对112种过敏原成分进行亚样本表征分析。使用火山图和偏最小二乘法（PLS）分析过敏原成分。采用Logistic回归评估所获得潜在成分（LC）与过敏结果（哮喘、鼻炎、湿疹）之间的相关性，包括既往哮喘风险评分中使用的其他潜在预测因素。采用受试者操作特征（ROC）曲线统计评估该模型预测哮喘的准确性。
结果：在PLS中，第一个LC与哮喘、鼻炎和湿疹呈正相关。该LC主要由Der p 1/2/23、Der f 1/2和Fel d1的正权重驱动。第二个LC的主要成分是花粉和食物过敏原。早期喘息史和父母过敏史纳入预测模型后，曲线下面积可提高至0.82。
结论：该方法首次通过综合CRD和临床数据预测13岁时哮喘发生情况，以提高CRD临床适用性。机体对特定过敏原分子高敏似乎与提高哮喘预测模型的准确性相关。
(中日友好医院呼吸与危重症医学科 张婧媛 摘译 林江涛 审校)
(Pediatr Allergy Immunol. 2023 Dec;34(12):e14056. doi: 10.1111/pai.14056.)
(Pediatr Allergy Immunol. 2023 Dec;34(12):e14056. doi: 10.1111/pai.14056.)
Component-resolved diagnosis in childhood and prediction of asthma in early adolescence A birth cohort study.
Farraia M, Mendes FC, Sokhatska O, Rama T, Severo M, Custovic A, Rufo JC, Barros H, Moreira A.
Abstract
BACKGROUND: Component-resolved diagnosis (CRD) has been decisive in exploring the mechanisms of IgE sensitization, but the predictive ability to detect asthma has not been addressed.
OBJECTIVE: We aim to develop and evaluate the performance of a personalized predictive algorithm for asthma that integrates information on allergic sensitization using CRD.
METHODS: One thousand one hundred one twenty-five children from the Generation XXI birth cohort were randomly selected to perform a screening test for allergic sensitization and a subsample was characterized using CRD against 112 allergen components. Allergen components were analyzed using volcano plots and partial least squares (PLS) analysis. Logistic regression was performed to assess the associations between the obtained latent components (LC) and allergic outcomes (asthma, rhinitis, eczema) including other potential predictors used in previous asthma risk scores. The accuracy of the model in predicting asthma was assessed using Receiver Operating Characteristic (ROC) curve statistics.
RESULTS: In the PLS, the first LC was positively associated with asthma, rhinitis, and eczema. This LC was mainly driven by positive weights for Der p 1/2/23, Der f 1/2, and Fel d 1. The main components in the second LC were pollen and food allergens. History of early wheezing and parental allergy were included in the predictive model and the area under the curve improved to 0.82.
CONCLUSION: This is the first approach to improve the clinical applicability of CRD by combining CRD and clinical data to predict asthma at 13 years. Sensitization to distinct allergen molecules seems relevant to improve the accuracy of asthma prediction models.
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