Virus Genotype-Dependent Transcriptional Alterations in Lipid Metabolism and Inflammation Pathways in the Hepatitis C Virus-infected Liver.
W M H d'AvigdorM A BudzinskaM LeeR LamJ KenchM StapelbergS V McLennanG FarrellJacob GeorgeG W McCaughanThomas TuN A ShackelPublished in: Scientific reports (2019)
Despite advances in antiviral therapy, molecular drivers of Hepatitis C Virus (HCV)-related liver disease remain poorly characterised. Chronic infection with HCV genotypes (1 and 3) differ in presentation of liver steatosis and virological response to therapies, both to interferon and direct acting antivirals. To understand what drives these clinically important differences, liver expression profiles of patients with HCV Genotype 1 or 3 infection (n = 26 and 33), alcoholic liver disease (n = 8), and no liver disease (n = 10) were analysed using transcriptome-wide microarrays. In progressive liver disease, HCV genotype was the major contributor to altered liver gene expression with 2151 genes differentially expressed >1.5-fold between HCV Genotype 1 and 3. In contrast, only 6 genes were altered between the HCV genotypes in advanced liver disease. Induction of lipogenic, lipolytic, and interferon stimulated gene pathways were enriched in Genotype 1 injury whilst a broad range of immune-associated pathways were associated with Genotype 3 injury. The results are consistent with greater lipid turnover in HCV Genotype 1 patients. Moreover, the lower activity in inflammatory pathways associated with HCV genotype 1 is consistent with relative resistance to interferon-based therapy. This data provides a molecular framework to explain the clinical manifestations of HCV-associated liver disease.
Keyphrases
- hepatitis c virus
- human immunodeficiency virus
- gene expression
- genome wide
- oxidative stress
- end stage renal disease
- magnetic resonance
- chronic kidney disease
- dna methylation
- ejection fraction
- metabolic syndrome
- insulin resistance
- hiv infected
- copy number
- immune response
- adipose tissue
- newly diagnosed
- patient reported outcomes
- single cell
- prognostic factors
- mesenchymal stem cells
- genome wide identification
- contrast enhanced
- artificial intelligence
- bioinformatics analysis