IgE表位分析可以准确诊断临床花生过敏。
我们试图确定顺序(线性)表位特异性IgE(ses-IgE)分析是否可以在经历双盲的过敏受试者中提供耐受离散剂量花生蛋白的可能性,使用PRACTALL给药的安慰剂对照食物挑战。
使用基于珠的表位测定对血液样品中的64种ses-IgE抗体进行定量。在来自发现队列的75名受试者中使用回归确定预测累积耐受剂量(CTD)的一对ses-IgE。该基于表位的预测因子在来自5个独立队列(年龄4-25岁)的331名受试者上进行了验证。基于受试者的预测值对受试者进行分组,并计算在每个CTD阈值下的反应概率。
在发现中,使用两种ses-IgE抗体的算法与CTD相关(rho=0.61,p<.05);在验证中,该相关性为0.51(p<.05)。使用基于ses-IgE的预测因子,受试者被分配到“高,“”适度,\"或\"低剂量\"反应性群体。平均而言,“高”组的受试者耐受特定剂量的可能性要高出四倍,与“低”组相比。例如,“低”组中耐受4、14、44和144或444mg的预测概率为92%,77%,53%,29%,10%与98%相比,95%,94%,88%,73%的人在“高”组中。
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挑战方案的变化。尽管有这些限制,基于表位的预测因子能够准确识别CTD,并可能为花生挑战提供有用的替代指标.
IgE-epitope profiling can accurately diagnose clinical peanut allergy.
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.
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.
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.
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.