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使用表位特异性 IgE 抗体分析预测过敏儿童耐受离散量花生蛋白的概率。

Predicting probability of tolerating discrete amounts of peanut protein in allergic children using epitope-specific IgE antibody profiling.

机构信息

Icahn School of Medicine at Mount Sinai, New York, New York, USA.

AllerGenis LLC, Hatfield, Pennsylvania, USA.

出版信息

Allergy. 2022 Oct;77(10):3061-3069. doi: 10.1111/all.15477. Epub 2022 Aug 17.

Abstract

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.

摘要

背景

IgE-表位分析可准确诊断临床花生过敏。

目的

我们旨在确定在接受 PRACTALL 剂量的双盲、安慰剂对照食物挑战的过敏受试者中,连续(线性)表位特异性 IgE(ses-IgE)分析是否能提供耐受离散剂量花生蛋白的可能性。

方法

使用基于珠子的表位分析,在 75 名来自发现队列的受试者的血液样本中定量了 64 种 ses-IgE 抗体。在 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。该基于表位的预测因子在来自五个独立队列(4-25 岁)的 331 名受试者中进行了验证。根据预测值将受试者分组,并计算每个 CTD 阈值的反应概率。

结果

在发现队列中,使用两种 ses-IgE 抗体的算法与 CTD 相关(rho=0.61,p<0.05);在验证队列中,该相关性为 0.51(p<0.05)。使用基于 ses-IgE 的预测因子,将受试者分为“高”、“中”或“低”剂量反应组。平均而言,“高”组的受试者耐受特定剂量的可能性是“低”组的四倍。例如,在“低”组中,预测耐受 4、14、44 和 144 或 444mg 的概率分别为 92%、77%、53%、29%和 10%,而在“高”组中,相应的概率分别为 98%、95%、94%、88%和 73%。

结论

由于每个剂量的应答者样本量有限以及研究特异性挑战方案的变化等因素,食物挑战阈值的准确预测较为复杂。尽管存在这些局限性,但基于表位的预测因子仍能准确识别 CTD,并可能为花生挑战提供有用的替代方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd68/10286745/b8c0e0a01744/ALL-77-3061-g005.jpg

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