ABSTRACT Alcoholic hepatitis (AH) has high mortality and management of these patients is limited by the lack of reliable markers of liver injury, inflammation and infection that determine clinical outcomes. Extracellular vesicles (EVs) are novel biomarkers that are more sensitive compared to serum associated-biomarkers because of the stability of biomolecules within the EVs. EVs contain characteristic RNA and protein cargo that can provide a unique signature of disease. While characterization of these different EV populations is an emerging field, the use of EVs as potential biomarkers is rapidly evolving in clinical applications. Our preliminary results suggest that there is an increased number of EVs in AH and these EVs have distinct RNA, micro-RNA and protein cargos compared to normal controls that indicate their potential for biomarker discovery. However, the features of biology that distinguish heavy drinkers with no liver disease from those who present with alcoholic hepatitis are unknown. In this application, we propose to take a two-step approach to study the EV cargo as a potential biomarker in alcoholic hepatitis. The UH2 phase will focus on the discovery phase in two steps: first, to define optimal approaches to EV isolation, RNA and protein sample preparation and, second, pilot proteomics and transcriptome analyses that will identify potential biomarker candidates in alcoholic hepatitis compared to normal controls (DASH samples). The second, UH3, phase will validate the proteomic and RNA-seq characteristic of EVs from the UH2 phase now in a larger cohort of AH patients from the AlcHepNet Observational study and compare those to heavy drinkers (HD) without liver disease (discovery). Proteomic and RNA transcriptomic profiles of the 3 sets of well-characterized human cohorts will identify EV-associated signatures of AH that is different from HD without liver disease and normal controls. Our study will further discover correlations between unique signatures in the protein cargo and/or RNA transcriptome profile of EVs that indicate survival and/or clinical outcomes in AH. The large dataset from these “omics” analyses will establish a unique AH-proteomic-transcriptome interface (AH-PTI) and this will provide invaluable resources for the AlcHepNet investigators and the entire alcohol research field for future hypothesis-driven studies.