Longitudinal paired liver biopsies and transcriptome profiling in alcohol-associated hepatitis reveal dynamic changes in cellular senescence

Abstract

Background and aims Alcohol-associated hepatitis (AH) is an acute form of alcohol-related liver disease (ALD) with high mortality rate. AH is histologically characterised by cellular processes, including steatosis, inflammation and cell death. Apoptosis is the most studied form of cell death in AH; however, the role of cellular senescence, another response to cellular injury, in AH is unknown. Here, we explore the mechanisms of ALD pathophysiology and describe the role of senescence in AH. Methods We performed RNA sequencing and bioinformatics analysis of 0- and 28-day transjugular liver biopsies (n=65) from patients with AH participating in the IL-1 Signal Inhibition In Alcoholic Hepatitis (ISAIAH) clinical trial. Additional bioinformatics reanalysis of existing AH transcriptomic datasets was conducted to confirm our findings. We also performed multiomic analysis of an in vitro model of AH with ethanol-treated hepatocytes overexpressing ethanol-metabolising enzymes. Results Our longitudinal analysis revealed that senescence and inflammation were reduced at transcriptomic level following AH resolution; the expression of hepatocyte markers was increased. We identified two senescence-associated protein complexes, cytochrome c oxidase and the proteasome, which may act as senescence-induction mechanisms. We confirmed that senescence markers and pathways were increasingly expressed in hepatocytes as ALD progressed towards AH; this was partially reversed following AH resolution. Our in vitro model revealed that ethanol directly induces senescence and was dependent on ethanol metabolism. Conclusions Our results suggest a possible pathogenic role for senescence in AH and indicate cellular senescence as a potential therapeutic target in early ALD to limit AH severity. Data are available in a public, open-access repository. Data are available in public, open-access repositories. The RNA-seq data generated in this study have been deposited in NCBI GEO () (SuperSeries GSE270043). The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium () via the PRIDE partner repository with the dataset identifier PXD053109.