Updated project metadata. High-calorie diets lead hepatic steatosis and to the development of non-alcoholic fatty liver disease (NAFLD), which can evolve over many years into the inflammatory form non-alcoholic steatohepatits (NASH) posing a risk for the development of hepatocellular carcinoma (HCC). Due to the diet and the liver alteration, the axis between liver and gut is disturbed, resulting in gut microbiome alterations. Consequently, detecting these gut microbiome alterations repre-sents a promising strategy for early NASH and HCC detection. We analyzed medical parame-ters and the fecal metaproteome of 19 healthy controls, 32 NASH, and 29 HCC patients target-ing the discovery of diagnostic biomarkers. Here, NASH and HCC resulted in increased in-flammation status and shifts within the composition of the gut microbiome. Increased abun-dance of kielin/chordin, E3 ubiquitin ligase, and nucleophosmin 1 represented valuable fecal biomarkers indicating disease-related changes in the liver. Whereas a single biomarker failed to separate NASH and HCC, machine learning-based classification algorithms provided 0.86% accuracy in distinguishing between controls, NASH, and HCC. Conclusion: Fecal metaproteomics enables early detection of NASH and HCC by providing single biomarkers and ma-chine learning-based metaprotein panels.