Defining the key intrahepatic gene networks in HCV infection driven by sex

Objective
The transcriptional response in the liver during HCV infection is critical for determining clinical outcomes. This issue remains relatively unexplored as tissue access to address this at scale is usually limited. We aimed to profile the transcriptomics of HCV-infected livers to describe the expression networks involved and assess the effect on them of major predictors of clinical outcome such as IFNL4 (interferon lambda 4) host genotype and sex.

Design
We took advantage of a large clinical study of HCV therapy accompanied by baseline liver biopsy to examine the drivers of transcription in tissue samples in 195 patients also genotyped genome-wide for host and viral single nucleotide polymorphisms. We addressed the role of host factors (disease status, sex, genotype, age) and viral factors (load, mutation) on transcriptional responses.

Results
We observe key modules of transcription which can be impacted differentially by host and viral factors. Underlying cirrhotic state had the most substantial impact, even in a stable, compensated population. Notably, sex had a major impact on antiviral responses in concert with IL28B (interleukin 28B)/IFNL4 genotype, with stronger interferon and humoral responses in females. Males tended towards a dominant cellular immune response. In both sexes, there was a strong influence of the underlying host disease status and of specific viral mutations, and sex-specific expression quantitative trait loci were also observed.

Conclusion
These features help define the major influences on tissue responses in HCV infection, impacting on the response to treatment and with broader implications for responses in other sex-biased infections.

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Aprile 2023

Omics studies in gastroenterological and hepatological patient populations: current impact and future promise exemplified by a large study of HCV-infected livers

‘But, where’s the beef?’, a colleague and friend asked me at a conference, right after a student from my group had presented our first transcriptional data set on T cells in viral hepatitis. I knew exactly what she meant. As scientists, we are accustomed to expect clear and definitive answers to specific questions that step by step prove or disprove a defined hypothesis developed on rigorous previous data. However, comprehensive and unbiased omics studies, like the analysis of genome-wide gene expression in liver tissue with HCV infection by Marchi et al in Gut,1 are in most instances neither aimed nor suited to deliver easy-to-grasp answers. This is especially true for cross-sectional analyses in humans with their inherent heterogeneity in mutable and immutable traits. The conversation mentioned previously happened almost 10 years ago, and studies using omics approaches in human cohorts have become commonplace in the meantime, but…

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Aprile 2023