Targeted and non-targeted proteomics to identify the urinary protein biomarkers for Wilson disease

Wilson disease (WD) is an autosomal recessive genetic disease that causes copper levels to accumulate in multiple organs, especially in the liver and brain. Due to the lack of obvious symptoms in the early stage and the variety of onset symptoms, most WD patients have suffered severe liver injury and neurological dysfunction from the lagging in diagnosis and misdiagnosis. As a lifelong illness, the life quality of the patients primarily depends on the time of first diagnosis. Therefore, more convenient and effective non-invasive large-scale screening tools deserve to be developed. Using shotgun proteomics, this study provided a urinary proteomic profile of WD from 11 WD patients and 10 healthy controls. Alpha-2-macroglobulin, alpha-1-antitrypsin, complement C3, prothrombin, and complement factor B were identified as novel potential protein biomarkers and verified in a more extensive independent cohort by MRM assay. A Random Forest (RF) model constructed of five proteins was assessed for diagnostic capacity. The RF model showed an area under curve (AUC) of 0.99 for the training data and 0.83 for the testing data, exhibiting excellent accuracy for non-invasively diagnosis of WD.