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

与电子烟使用相关的预期健康结果和炎症生物标志物

基本信息

  • 批准号:
    10226191
  • 负责人:
  • 金额:
    $ 51.27万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2019
  • 资助国家:
    美国
  • 起止时间:
    2019-09-15 至 2024-07-31
  • 项目状态:
    已结题

项目摘要

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.
项目摘要。该项目旨在确定用于评估的有效生物标志物 电子尼古丁输送系统(ENDS)自ENDS推出以来,通常 被称为电子烟,年轻人和老年人使用ENDS的人数大幅增加, 传统吸烟者也使用ENDS(双重使用者)。自2016年以来,食品和药物管理局 (FDA)已经对ENDS进行了监管,并且迫切需要ENDS相关的生物标志物 可用作评价新ENDS产品的经验证替代终点。目标 在两个独立的队列,COPDGene和UCSD ENDS研究中, 建议仅在ENDS和双重使用者中识别ENDS相关的炎症生物标志物并进行关联 这些生物标志物与五年肺部健康结果的关系。COPDGene是一项正在进行的纵向研究, > 6,000名目前和以前的传统香烟(t-cig)吸烟者, 具有详细的纵向肺表型数据(包括胸部CT)的疾病(COPD),全基因组血液 RNA-seq和蛋白质组学数据。UCSD ENDS研究是一项针对仅使用ENDS的年轻人的对照研究, 对照组详细评估口咽、气道和血液中的炎症生物标志物。 用作经验证替代指标的生物标志物必须1)与ENDS使用相关,2)预测 健康结果; 3)具有强大的生物学原理。我们假设炎症生物标志物 的ENDS使用将预测五年的肺部健康影响。在该提案的目标1中,发现 ENDS暴露的炎性转录组学和蛋白质组学生物标志物将在来自 COPDGene五年研究访视和生物标志物将在两组独立的受试者中进行验证 来自COPDGene十年访问和UCSD ENDS研究。在目标2中,我们将确定抗体特异性 使用适应性免疫受体库的ENDS暴露的适应性免疫应答生物标志物 测序(AIRR-seq)。自身抗体是与肺损伤程度相关的生物标志物 慢性阻塞性肺病AIIRR-seq是发现炎症生物标志物的强大工具,可表征个体的特征 几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 ENDS相关生物标志物面板与COPDGene的五年肺部健康结果调查 该研究小组在鉴定ENDS使用的新型炎症生物标志物方面处于有利地位。COPD基因 和UCSD队列有详细的肺表型和必要的分子特征,以发现 并在ENDS使用者的两个重要人群(即仅ENDS和双重使用者)中临床验证生物标志物。

项目成果

期刊论文数量(3)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Deleterious Association of Inhalant Use on Sleep Quality during the COVID-19 Pandemic.
Just When We Thought Nothing Could Be Worse Than Smoking Tobacco, Vaping e-Hookah Proves Us Wrong.
就在我们认为没有什么比吸烟更糟糕的时候,电子水烟却证明我们错了。
  • DOI:
    10.1016/j.chest.2021.08.042
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    9.6
  • 作者:
    Masso-Silva,JorgeA;CrottyAlexander,LauraE
  • 通讯作者:
    CrottyAlexander,LauraE
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Peter Castaldi其他文献

Peter Castaldi的其他文献

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{{ truncateString('Peter Castaldi', 18)}}的其他基金

Prospective Health Outcomes and Inflammatory Biomarkers Associated with e-Cigarette Use
与电子烟使用相关的预期健康结果和炎症生物标志物
  • 批准号:
    10018099
  • 财政年份:
    2019
  • 资助金额:
    $ 51.27万
  • 项目类别:
Using Integrative Genomics To Identify and Characterize Emphysema-Associated eQTL
使用综合基因组学来识别和表征肺气肿相关的 eQTL
  • 批准号:
    8762578
  • 财政年份:
    2014
  • 资助金额:
    $ 51.27万
  • 项目类别:
Using Integrative Genomics To Identify and Characterize Emphysema-Associated eQTL
使用综合基因组学来识别和表征肺气肿相关的 eQTL
  • 批准号:
    10653966
  • 财政年份:
    2014
  • 资助金额:
    $ 51.27万
  • 项目类别:
Using Integrative Genomics To Identify and Characterize Emphysema-Associated eQTL
使用综合基因组学来识别和表征肺气肿相关的 eQTL
  • 批准号:
    10471299
  • 财政年份:
    2014
  • 资助金额:
    $ 51.27万
  • 项目类别:
Using Integrative Genomics To Identify and Characterize Emphysema-Associated eQTL
使用综合基因组学来识别和表征肺气肿相关的 eQTL
  • 批准号:
    8913766
  • 财政年份:
    2014
  • 资助金额:
    $ 51.27万
  • 项目类别:
Using Integrative Genomics To Identify and Characterize Emphysema-Associated eQTL
使用综合基因组学来识别和表征肺气肿相关的 eQTL
  • 批准号:
    10298583
  • 财政年份:
    2014
  • 资助金额:
    $ 51.27万
  • 项目类别:
Predictive Modeling with Clinical and Genomic Data in COPD
利用 COPD 的临床和基因组数据进行预测建模
  • 批准号:
    8063638
  • 财政年份:
    2010
  • 资助金额:
    $ 51.27万
  • 项目类别:
Predictive Modeling with Clinical and Genomic Data in COPD
利用 COPD 的临床和基因组数据进行预测建模
  • 批准号:
    8500430
  • 财政年份:
    2010
  • 资助金额:
    $ 51.27万
  • 项目类别:
Predictive Modeling with Clinical and Genomic Data in COPD
利用 COPD 的临床和基因组数据进行预测建模
  • 批准号:
    8668035
  • 财政年份:
    2010
  • 资助金额:
    $ 51.27万
  • 项目类别:
Predictive Modeling with Clinical and Genomic Data in COPD
利用 COPD 的临床和基因组数据进行预测建模
  • 批准号:
    7875053
  • 财政年份:
    2010
  • 资助金额:
    $ 51.27万
  • 项目类别:

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