Prospective Health Outcomes and Inflammatory Biomarkers Associated with e-Cigarette Use

项目摘要。该项目旨在确定评估中使用的经过验证的生物标志物 电子尼古丁输送系统(完)由FDA。由于引入了Ends，通常 被称为电子烟的电子烟，在年轻人和老年人中的终端使用量大幅增加 也使用烟头的传统吸烟者(双重吸烟者)。自2016年以来，美国食品和药物管理局 美国食品和药物管理局(FDA)对Ends拥有监管权力，迫切需要与Ends相关的生物标志物 可用作评估新终端产品的经过验证的代理端点。带着目标 在两个独立的队列中发现了经过验证的生物标记物，COPDgene和UCSD结束了研究，我们 建议仅在终端和双重使用者中识别与终端相关的炎症生物标志物，并与 这些生物标记物反映了五年的肺部健康结果。COPDgene是一项持续的、纵向的研究 &gt；6,000名现任和前任传统香烟(T-CIG)吸烟者因慢性阻塞性肺疾病而增加吸烟者 疾病(COPD)，具有详细的纵向肺部表型数据(包括胸部CT)、全基因组血液 RNA-seq和蛋白质组数据。加州大学圣迭戈分校的Ends研究是一项仅针对年轻终端用户和 对照，详细评估口咽、呼吸道和血液中的炎性生物标记物。 用作有效替代测量的生物标记物必须1)与终端使用相关，2)预测 健康结果，以及3)有很强的生物学基础。我们假设炎性生物标记物 最终使用量将预测五年内对肺部健康的影响。在本提案的目标1中，发现 END暴露的炎性转录和蛋白质组生物标记物将在来自 COPDgene为期五年的研究访问，生物标记物将在两组独立的受试者中得到验证 来自COPD基因十年的访问和加州大学圣地亚哥分校结束的研究。在目标2中，我们将识别抗体特异性 使用适应性免疫受体谱系的末端暴露的适应性免疫反应生物标记物 测序(AIRR-SEQ)。自身抗体是与肺损伤程度相关的生物标志物。 在慢性阻塞性肺病。AIRR-seq是发现炎性生物标记物的有力工具，它表征了个体的 长达数十年的抗体反应史。在目标3中，我们将使用机器学习预测模型来关联 COPDgene的五年肺部健康结果的END相关生物标志物面板。调查性的 这项赠款的团队处于很好的地位，可以识别终端使用的新的炎性生物标志物。COPD基因 加州大学伯克利分校的队列有详细的肺部表型和分子特征来发现 并在两个重要的终端用户群体，即仅终端用户和双重用户中临床验证生物标记物。

Project Summary. This project is designed to identify validated biomarkers for use in the assessment of electronic nicotine delivery systems (ENDS) by the FDA. Since the introduction of ENDS, commonly referred to as e-cigarettes, there has been a large increase in ENDS use among young adults and older traditional cigarette smokers who also use ENDS (dual users). Since 2016, the Food and Drug Administration (FDA) has had regulatory authority over ENDS, and there is an acute need for ENDS-related biomarkers that can be used as validated surrogate endpoints for evaluation of new ENDS products. With the goal of validated biomarker discovery in two independent cohorts, the COPDGene and UCSD ENDS studies, we propose to identify ENDS-related inflammatory biomarkers in ENDS only and dual users and relate these biomarkers to five-year lung health outcomes. COPDGene is an ongoing, longitudinal study of >6,000 current and former traditional cigarette (t-cig) smokers enriched for chronic obstructive pulmonary disease (COPD) with detailed longitudinal lung phenotyping data (including chest CT), genome-wide blood RNA-seq, and proteomic data. The UCSD ENDS Study is a controlled study of young ENDS only users and controls with detailed assessment of inflammatory biomarkers in the oropharynx, airways and blood. Biomarkers used as validated surrogate measures must be 1) associated with ENDS use, 2) predictive of health outcomes, and 3) have a strong biological rationale. We hypothesize that inflammatory biomarkers of ENDS use will be predictive of five-year lung health effects. In Aim 1 of this proposal, discovery of inflammatory transcriptomic and proteomic biomarkers of ENDS exposure will be performed in subjects from the COPDGene five-year study visit, and biomarkers will be validated in two independent sets of subjects from the COPDGene ten-year visit and the UCSD ENDS Study. In Aim 2 we will identify antibody-specific adaptive immune response biomarkers of ENDS exposure using adaptive immune receptor repertoire sequencing (AIRR-seq). Auto-antibodies are biomarkers that are associated with the degree of lung damage in COPD. AIRR-seq is a powerful tool for inflammatory biomarker discovery that characterizes an individual’s decades-long history of antibody responses. In Aim 3 we will use machine learning predictive models to relate ENDS-associated biomarker panels to five-year lung health outcomes from COPDGene. The investigative team for this grant is well-positioned to identify novel inflammatory biomarkers of ENDS use. The COPDGene and UCSD cohorts have the detailed lung phenotyping and molecular characterization necessary to discover and clinically validate biomarkers in two important populations of ENDS users, i.e. ENDS only and dual users.