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.