Mechanism-based serum biomarkers and validation of ensemble model for excessive alcohol use

项目摘要 提高生物标志物识别近期过度饮酒（EAU）的敏感性和特异性， 退伍军人是一个及时的研究目标。EAU被认为是一个新出现的健康相关问题 尤其是从战场上回来的老兵。因此，有必要提高警惕并采取行动 识别和辅导有风险的退伍军人。老年EAU患者的诊断和护理受到以下因素的阻碍： 缺乏具有高诊断性能的测试，可以检测出饮酒或复发的危险水平 在治疗期间。这些测试对于EAU退伍军人的筛查和护理是必不可少的。的 EAU检测不足的后果，因此延迟干预是严重的，因为酒精的相对风险- 相关的健康状况随着每天饮酒的量和持续时间的增加而增加。过度 酒精使用（EAU）正在被认为是一个新出现的健康相关问题，特别是在退伍军人中 从战斗中归来。我们的初步数据使用蛋白质组学和转录组学的新景观， 方法已经揭示了EAU的病理生理学的几个途径;这可能导致 人类的病理学本次CSR&D Merit Review Award申请旨在寻求支持， 生物标志物组的作用;来自EAU对炎症反应的影响，以筛选 EAU和近期饮酒量以及戒酒监测。我们假设 (i)这些源自系统生物学分析的生物标志物是有用的 在临床实践中筛查EAU和近期饮酒量，与 常规标志物和（ii）将这些标志物组合成单一风险模型预测， 机器学习和统计力学将彻底改变我们在临床实践中筛选EAU的方式。到 为了检验这一假设，我们计划追求以下具体目标：具体目标#1：确定 通过系统生物学方法鉴定EAU对器官系统的影响， 作为EAU潜在生物标志物的这些新靶点的相对量，以及具体目标#2：开发 并结合机器学习和统计学方面验证用于预测EAU的风险模型 力学如果成功的话，这个项目的结果将彻底改变退伍军人的筛选方法 过量饮酒

Project Summary Increasing the sensitivity and specificity of biomarkers for recognizing recent, excessive alcohol use (EAU) in Veterans is a timely goal of research. EAU is becoming recognized as an emerging health-related problem especially among veterans returning from combats. As such, there is a need for increased vigilance and action to identify and counsel at-risk veterans. The diagnosis and care of veteran patients with EAU is hampered by the lack of tests with high diagnostic performance that can detect dangerous levels of drinking or relapse during therapy. Such tests would be indispensable for screening and care for veterans with EAU. The consequences of under-detection of EAU, thus delayed intervention are serious because relative risk of alcohol- related health conditions is increased with the amounts and duration of alcohol consumed per day. Excessive alcohol use (EAU) is becoming recognized as an emerging health-related problem especially among veterans returning from combats. Our preliminary data using the new landscape of proteomic and transcriptomic approaches have uncovered the pathophysiology of EAU on several pathways; which might lead to pathology in human. This renewal CSR&D Merit Review Award application seeks the support to define the roles of the panels of biomarkers; derived from the effect of EAU on inflammatory response to screen for EAU and quantity of recent alcohol consumption and monitoring for abstinence. We hypothesize that (i) these biomarkers derived from system biology analyses are useful and have a better diagnostic performance to screen for EAU and the quantity of recent alcohol consumption in clinical practice, when compared to the conventional markers and (ii) the combination of these markers into a single risk model prediction using machine learning and statistical mechanics will revolutionize the way we screen for EAU in clinical practice. To test this hypothesis, we plan to pursue the following specific aims; SPECIFIC AIM # 1: Determine the effect of EAU on organ system identified by system biology approach and by detecting, identifying, and comparing the relative quantity of these novel targets as potential biomarkers for EAU, and SPECIFIC AIM # 2: To develop and validate of a risk model for prediction of EAU combining aspects of machine learning and statistical mechanics. If successful, the results from this project will revolutionize the screening methods for veterans with excessive alcohol use.