Leveraging bulk RNA-seq data to explore the impact of cirrhosis and PNPLA3 on liver gene expression in HCV-infected patients

Abstract

Hepatitis C virus (HCV) is a hepatotropic RNA virus that is associated with significant morbidity and mortality. Despite interventions to prevent transmission, HCV infection continues to result in 400,000 annual deaths worldwide and is a primary indication of liver transplantation. While a quarter of patients with acute infection clear the virus spontaneously, the remaining three-quarters develop chronic infection and cirrhosis. Alongside HCV, the primary aetiologies of cirrhosis include non-alcoholic fatty liver disease (NAFLD), and alcoholic fatty liver disease (ALD). The risk of cirrhosis is influenced by the complex interplay between host, viral and environmental factors. A single nucleotide polymorphism (SNP), rs738409, is the strongest genetic risk factor for ARLD- and NAFLD-related cirrhosis. To date, no study has been conducted that investigates the impact of cirrhosis on liver gene expression during chronic HCV. To address this knowledge gap, we leveraged bulk RNA-seq data from a cohort of 196 HCV-infected patients enrolled in the BOSON clinical trial to investigate the effect of cirrhosis and PNPLA3 on liver gene expression. Our analyses showed that thousands of genes are upregulated and downregulated by cirrhosis, many of which are linked to extracellular matrix remodelling processes (such as MMP7), inflammation (CCL2) and other cirrhosis-related pathways, but also several potentially novel pathways as well. PNPLA3 was found to be downregulated during cirrhosis, as previously reported in the literature. We demonstrated that rs738409 is linked with several expression patterns and pathways, namely mitochondrial transcripts (e.g. MT-TC, MT-TN) and apoptosis-related signaling genes (e.g. BAX). These insights may generate novel hypotheses to test downstream for additional targets in drug development for liver cirrhosis. Overall, our analyses demonstrate how gene expression data combined with robust statistical methodology holds the potential to serve basis for elucidating the underlying mechanisms of cirrhosis.