Biomarker discovery for chronic liver diseases by multi-omics - a preclinical case study.

Nonalcoholic steatohepatitis (NASH) is a major cause of liver fibrosis with increasing prevalence worldwide. Currently there are no approved drugs available. The development of new therapies is difficult as diagnosis and staging requires biopsies. Consequently, predictive plasma biomarkers would be useful for drug development. Here we present a multi-omics approach to characterize the molecular pathophysiology and to identify new plasma biomarkers in a choline-deficient L-amino acid-defined diet rat NASH model. We analyzed liver samples by RNA-Seq and proteomics, revealing disease relevant signatures and a high correlation between mRNA and protein changes. Comparison to human data showed an overlap of inflammatory, metabolic, and developmental pathways. Using proteomics analysis of plasma we identified mainly secreted proteins that correlate with liver RNA and protein levels. We developed a multi-dimensional attribute ranking approach integrating multi-omics data with liver histology and prior knowledge uncovering known human markers, but also novel candidates. Using regression analysis, we show that the top-ranked markers were highly predictive for fibrosis in our model and hence can serve as preclinical plasma biomarkers. Our approach presented here illustrates the power of multi-omics analyses combined with plasma proteomics and is readily applicable to human biomarker discovery.