Biomarkers of Macrophage Activation and Immune Danger Signals Predict Clinical Outcomes in Alcoholic Hepatitis.

Although mortality due to acute alcoholic hepatitis (AH) correlates with Model for End-Stage Liver Disease (MELD) scores, biomarkers are critically needed to manage this disease. Increases in inflammatory markers and macrophage activation are associated with acute AH and could be potential biomarkers of clinical events and/or mortality. We enrolled 89 clinically diagnosed AH patients in four US academic medical centers. Plasma from AH patients had a significant increase in gut microbial translocation indicators (endotoxin, bacterial 16S ribosomal DNA) and host response indicators (soluble cluster of differentiation 14 [sCD14] and lipopolysaccharide binding protein [LBP]) compared to controls. Patient MELD score and Glasgow Alcoholic Hepatitis score (GAHS) correlated with endotoxin levels. AH patients also had a significant increase in high mobility group protein 1 (HMGB1), a sterile danger signal molecule, and osteopontin (OPN), a multifunctional phosphoprotein involved in neutrophil activation, compared to controls. Increased levels of OPN positively correlated with increasing MELD score, GAHS, and LBP levels. Consistent with these results, AH patients had significantly increased circulating levels of macrophage activation (sCD163 and sCD206) markers compared to healthy controls, and sCD163 and sCD206 significantly and positively correlated with OPN, HMGB1, and LBP levels as well as with MELD score and GAHS. These findings indicate a connection between microbial translocation, immune cell activation, and AH severity. Plasma sCD14, OPN, sCD163, and sCD206 levels were significantly higher in nonsurvivors than survivors. In multivariate regression models, we identified sCD14, sCD163, and OPN as independent predictors of 90-day mortality, infection, and organ failure development, respectively.

Conclusion

Our study suggests that sCD14, LBP, OPN, sCD163, and sCD206 are biomarkers to indicate severity and predict clinical outcomes in AH.