标题： 使用单细胞检测和配对的对照样本确定存在基础免疫力时的疫苗应答者 显示英文标题

标题： Determining vaccine responders in the presence of baseline immunity using single-cell assays and paired control samples

摘要： 一个关键目标是在疫苗研究中评估疫苗诱导的免疫原性，并确定参与者是否已对疫苗产生了反应。细胞免疫反应对于评估疫苗诱导的免疫原性至关重要，单细胞检测方法，如细胞内细胞因子染色（ICS）常用于分析个体免疫细胞表型及其在刺激后产生的细胞因子。在本文中，我们介绍了一种新的统计框架，利用接种前和接种后收集的ICS数据来识别疫苗应答者。该框架结合了配对的对照数据，以考虑实验运行之间的潜在意外变化，如批次效应，这可能导致参与者被错误分类为疫苗应答者。为了正式整合配对对照数据以考虑不同时间点（即接种前和接种后）的实验变异，我们提出的框架计算并报告两个p值，这两个p值均对配对对照数据进行调整，但方式不同：(i) 最大调整的p值，对未调整的p值应用最保守的调整，确保在与配对对照样本数据一致的所有可能批次效应下保持有效性，以及(ii) 最小调整的p值，仅对未调整的p值进行最小调整，使得调整后的p值不能被配对对照样本的数据所伪造。我们将此框架应用于分析来自新冠状病毒预防网络（CoVPN）3008研究的基线和接种后4周的ICS数据。我们的分析有助于解决两个临床问题：1）哪些参与者表现出新发奥密克戎感染的证据，以及2）哪些参与者显示出针对奥密克戎BA.4/5刺突蛋白的疫苗诱导的T细胞反应。 显示英文摘要

摘要： A key objective in vaccine studies is to evaluate vaccine-induced immunogenicity and determine whether participants have mounted a response to the vaccine. Cellular immune responses are essential for assessing vaccine-induced immunogenicity, and single-cell assays, such as intracellular cytokine staining (ICS) are commonly employed to profile individual immune cell phenotypes and the cytokines they produce after stimulation. In this article, we introduce a novel statistical framework for identifying vaccine responders using ICS data collected before and after vaccination. This framework incorporates paired control data to account for potential unintended variations between assay runs, such as batch effects, that could lead to misclassification of participants as vaccine responders. To formally integrate paired control data for accounting for assay variation across different time points (i.e., before and after vaccination), our proposed framework calculates and reports two p-values, both adjusting for paired control data but in distinct ways: (i) the maximally adjusted p-value, which applies the most conservative adjustment to the unadjusted p-value, ensuring validity over all plausible batch effects consistent with the paired control samples' data, and (ii) the minimally adjusted p-value, which imposes only the minimal adjustment to the unadjusted p-value, such that the adjusted p-value cannot be falsified by the paired control samples' data. We apply this framework to analyze ICS data collected at baseline and 4 weeks post-vaccination from the COVID-19 Prevention Network (CoVPN) 3008 study. Our analysis helps address two clinical questions: 1) which participants exhibited evidence of an incident Omicron infection, and 2) which participants showed vaccine-induced T cell responses against the Omicron BA.4/5 Spike protein.