Does a composite proteomic model identify at-risk steatohepatitis in patients with NAFLD?
A composite model of four circulating proteins, BMI, and T2DM status can non-invasively identify patients with at-risk non-alcoholic steatohepatitis.
Non-alcoholic fatty liver disease (NAFLD) is a common, progressive liver disease strongly associated with the metabolic syndrome. It is unclear how progression of NAFLD towards cirrhosis translates into systematic changes in circulating proteins. Here, we provide a detailed proteo-transcriptomic map of steatohepatitis and fibrosis during progressive NAFLD. In this multicentre proteomic study, we characterize 4,730 circulating proteins in 306 patients with histologically characterized NAFLD and integrate this with transcriptomic analysis in paired liver tissue. We identify circulating proteomic signatures for active steatohepatitis and advanced fibrosis, and correlate these with hepatic transcriptomics to develop a proteo-transcriptomic signature of 31 markers. Deconvolution of this signature by single-cell RNA sequencing reveals the hepatic cell types likely to contribute to proteomic changes with disease progression. As an exemplar of use as a non-invasive diagnostic, logistic regression establishes a composite model comprising four proteins (ADAMTSL2, AKR1B10, CFHR4 and TREM2), body mass index and type 2 diabetes mellitus status, to identify at-risk steatohepatitis.
Govaere et al. (2023) studied this question.