利用表位特异性IgE抗体谱预测过敏儿童对离散量花生蛋白的耐受概率
2022/09/20
摘要
背景：IgE表位分析可能准确诊断临床花生过敏。
目的：我们试图确定连续（线性）表位特异性 IgE (ses-IgE) 分析是否可以提供在使用 PRACTALL 给药进行双盲、安慰剂对照食物挑战的过敏受试者中耐受离散剂量花生蛋白的概率。
方法：采用微珠表位法在血液样本中定量检测了64个ses-IgE抗体。在来自已发现队列的 75 名受试者中使用回归确定了一对预测累积耐受剂量 (CTD) 的 ses-IgE。 这种基于表位的预测因子在来自五个独立队列（年龄 4-25 岁）的 331 名受试者中得到验证。 根据他们的预测值对受试者进行分组，并计算每个 CTD 阈值的反应概率。
结果：发现，使用两种 ses-IgE 抗体的算法与 CTD 相关（rho = 0.61，p < 0.05）； 这种相关性在验证中为 0.51 (p <0 .05)。 使用基于 ses-IgE 的预测因子，受试者被分配到“高”、“中”或“低”剂量反应组。 平均而言，“高剂量”组的受试者对特定剂量的耐受性是“低剂量”组的四倍。例如，“低”组对4、14、44和144或444 mg耐受的预测概率分别为92%、77%、53%、29%和10%，而“高”组为98%、95%、94%、88%和73%。
结论：食物挑战阈值的准确预测是复杂的，原因包括每个剂量的应答者样本量有限以及研究特定研究方案的变化。尽管存在这些限制，但基于表位的预测能够准确识别 CTD，并可能为花生挑战阈值提供有用的替代物。
Predicting probability of tolerating discrete amounts of peanut protein in allergic children using epitope-specific IgE antibody profiling.
Maria Suprun, Paul Kearney, Clive Hayward
Abstrast
Background: IgE-epitope profiling can accurately diagnose clinical peanut allergy.
Objective：We sought to determine whether sequential (linear) epitope-specific IgE (ses-IgE) profiling can provide probabilities of tolerating discrete doses of peanut protein in allergic subjects undergoing double-blind, placebo-controlled food challenges utilizing PRACTALL dosing.
Methods: Sixty four ses-IgE antibodies were quantified in blood samples using a bead-based epitope assay. A pair of ses-IgEs that predicts Cumulative Tolerated Dose (CTD) was determined using regression in 75 subjects from the discovery cohort. This epitope-based predictor was validated on 331 subjects from five independent cohorts (ages 4-25 years). Subjects were grouped based on their predicted values and probabilities of reactions at each CTD threshold were calculated.
Results: In discovery, an algorithm using two ses-IgE antibodies was correlated with CTDs (rho = 0.61, p < .05); this correlation was 0.51 (p < .05) in validation. Using the ses-IgE-based predictor, subjects were assigned into "high," "moderate," or "low" dose-reactivity groups. On average, subjects in the "high" group were four times more likely to tolerate a specific dose, compared with the "low" group. For example, predicted probabilities of tolerating 4, 14, 44, and 144 or 444 mg in the "low" group were 92%, 77%, 53%, 29%, and 10% compared with 98%, 95%, 94%, 88%, and 73% in the "high" group.
Conclusions: Accurate predictions of food challenge thresholds are complex due to factors including limited responder sample sizes at each dose and variations in study-specific challenge protocols. Despite these limitations, an epitope-based predictor was able to accurately identify CTDs and may provide a useful surrogate for peanut challenges.
背景：IgE表位分析可能准确诊断临床花生过敏。
目的：我们试图确定连续（线性）表位特异性 IgE (ses-IgE) 分析是否可以提供在使用 PRACTALL 给药进行双盲、安慰剂对照食物挑战的过敏受试者中耐受离散剂量花生蛋白的概率。
方法：采用微珠表位法在血液样本中定量检测了64个ses-IgE抗体。在来自已发现队列的 75 名受试者中使用回归确定了一对预测累积耐受剂量 (CTD) 的 ses-IgE。 这种基于表位的预测因子在来自五个独立队列（年龄 4-25 岁）的 331 名受试者中得到验证。 根据他们的预测值对受试者进行分组，并计算每个 CTD 阈值的反应概率。
结果：发现，使用两种 ses-IgE 抗体的算法与 CTD 相关（rho = 0.61，p < 0.05）； 这种相关性在验证中为 0.51 (p <0 .05)。 使用基于 ses-IgE 的预测因子，受试者被分配到“高”、“中”或“低”剂量反应组。 平均而言，“高剂量”组的受试者对特定剂量的耐受性是“低剂量”组的四倍。例如，“低”组对4、14、44和144或444 mg耐受的预测概率分别为92%、77%、53%、29%和10%，而“高”组为98%、95%、94%、88%和73%。
结论：食物挑战阈值的准确预测是复杂的，原因包括每个剂量的应答者样本量有限以及研究特定研究方案的变化。尽管存在这些限制，但基于表位的预测能够准确识别 CTD，并可能为花生挑战阈值提供有用的替代物。
(中日友好医院呼吸与危重症医学科 万静萱 摘译 林江涛 审校)
(Allergy 2022 Aug 12; doi:10.1111/all.15477.)
(Allergy 2022 Aug 12; doi:10.1111/all.15477.)
Predicting probability of tolerating discrete amounts of peanut protein in allergic children using epitope-specific IgE antibody profiling.
Maria Suprun, Paul Kearney, Clive Hayward
Abstrast
Background: IgE-epitope profiling can accurately diagnose clinical peanut allergy.
Objective：We sought to determine whether sequential (linear) epitope-specific IgE (ses-IgE) profiling can provide probabilities of tolerating discrete doses of peanut protein in allergic subjects undergoing double-blind, placebo-controlled food challenges utilizing PRACTALL dosing.
Methods: Sixty four ses-IgE antibodies were quantified in blood samples using a bead-based epitope assay. A pair of ses-IgEs that predicts Cumulative Tolerated Dose (CTD) was determined using regression in 75 subjects from the discovery cohort. This epitope-based predictor was validated on 331 subjects from five independent cohorts (ages 4-25 years). Subjects were grouped based on their predicted values and probabilities of reactions at each CTD threshold were calculated.
Results: In discovery, an algorithm using two ses-IgE antibodies was correlated with CTDs (rho = 0.61, p < .05); this correlation was 0.51 (p < .05) in validation. Using the ses-IgE-based predictor, subjects were assigned into "high," "moderate," or "low" dose-reactivity groups. On average, subjects in the "high" group were four times more likely to tolerate a specific dose, compared with the "low" group. For example, predicted probabilities of tolerating 4, 14, 44, and 144 or 444 mg in the "low" group were 92%, 77%, 53%, 29%, and 10% compared with 98%, 95%, 94%, 88%, and 73% in the "high" group.
Conclusions: Accurate predictions of food challenge thresholds are complex due to factors including limited responder sample sizes at each dose and variations in study-specific challenge protocols. Despite these limitations, an epitope-based predictor was able to accurately identify CTDs and may provide a useful surrogate for peanut challenges.
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