Fig. 1: A framework for biomarker discovery in liver disease.

High-throughput, MS-based proteomics technology used to profile paired liver and plasma samples from 459 patients with ALD and 137 matched healthy controls. Proteome dysregulation in liver and plasma were integrated to capture disease-stage-relevant protein signatures in the bloodstream that were concordant with the liver. Last, a machine learning model was built to identify early stages of liver fibrosis, inflammatory activity and steatosis. We used the diagnostic models to assess their prognostic capabilities. We also validated model performance to rule out disease in low-incidence populations. In addition, the diagnostic capability of identified protein marker panels was evaluated in an independent cohort of 63 patients with ALD.