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

基于机制的血清生物标志物和过量饮酒整体模型的验证

• 批准号: 10426278
• 负责人: Suthat Liangpunsakul
• 金额: --
• 依托单位: RLR VA MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-10-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10426278
• 关键词: Abstinence; Alcohol consumption; Alcohols; Award; Biological Markers; Caring; Cells; Clinical; Consumption; Counseling; Dangerousness; Data; Detection; Diabetes Mellitus; Diagnosis; Diagnostic; Disease; Dyslipidemias; Functional disorder; Funding; Glucose; Goals; Health; Hemoglobin; Human; Individual; Inflammatory; Inflammatory Response; Intervention; Laboratories; Lead; Link; Lipids; Machine Learning; Methods; Modeling; Pathology; Pathway interactions; Patient Self-Report; Patients; Performance; Prevalence; Process; Proteomics; Questionnaires; Relapse; Relative Risks; Research; Risk; Role; Screening procedure; Sensitivity and Specificity; Serum; Statistical Mechanics; Systems Biology; Testing; Time; Veterans; adverse outcome; alcohol measurement; alcohol monitoring; alcohol rehabilitation; alcohol related problem; alcohol risk; alcohol screening; base; biomarker panel; biomarker validation; body system; clinical care; clinical practice; disease phenotype; drinking; drinking behavior; monocyte; novel; potential biomarker; relapse patients; response; risk prediction model; screening; statistical and machine learning; transcriptomics; trend; vigilance

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.

项目概要 提高生物标志物的敏感性和特异性，用于识别近期过度饮酒 (EAU) 退伍军人是一个及时的研究目标。 EAU 逐渐被认为是一个新兴的健康相关问题 尤其是从战斗归来的退伍军人中。因此，需要提高警惕并采取行动 识别高危退伍军人并为其提供咨询。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来检测饮酒的危险程度或复发 治疗期间。此类测试对于筛查和护理患有 EAU 的退伍军人来说是必不可少的。这 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量和持续时间的增加而增加。过多的 酒精使用（EAU）正被认为是一个新出现的健康相关问题，尤其是在退伍军人中 从战斗中归来。我们使用蛋白质组学和转录组学新领域的初步数据 多种方法揭示了 EAU 在多个途径上的病理生理学；这可能会导致 人类病理学。此次更新的 CSR&D 优异评审奖申请寻求支持来定义 生物标志物组的作用；源自EAU对炎症反应的影响来筛选 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并且具有更好的诊断性能 在临床实践中筛查 EAU 和近期饮酒量，并与 传统标记和 (ii) 将这些标记组合成单个风险模型预测，使用 机器学习和统计力学将彻底改变我们在临床实践中筛查 EAU 的方式。到 检验这一假设，我们计划追求以下具体目标；具体目标#1：确定效果 通过系统生物学方法并通过检测、识别和比较来识别器官系统的 EAU 这些新靶点作为 EAU 潜在生物标志物的相对数量，以及具体目标#2：开发 结合机器学习和统计方面的 EAU 预测风险模型的验证 机械师。如果成功，该项目的结果将彻底改变退伍军人的筛查方法 过度饮酒。