Adapting under pressure: Host immune genotype drives hepatitis C viral polymorphism
posted June 8, 2017
Hepatitis C virus (HCV) infection poses a major global health issue. As reported by the World Health Organization, 71 million people worldwide suffer from chronic HCV infection, and 400,000 die every year of liver cirrhosis and carcinoma (1). Interestingly, genotypic variations in both host and virus have been identified to affect clinical outcomes (2-4). However, no vaccines are available due to the rapid mutation rate of the virus, which has acquired resistance to most direct-acting antiviral drugs (5). To better understand how the host drives viral adaptation, Ansari and colleagues (2017) adopted a host genome-to-viral genome co-analysis approach to decipher genes in chronically infected hosts that may shape HCV diversity (6)
The authors sequenced genomes of 542 HCV-infected patients, along with the full-length viral genome obtained from the host plasma. Approximately 330,000 common host SNPs and 1,226 variable sites in the HCV proteome, adjusted for sex and population structure, were subjected to association analysis (6). It was previously known that major histocompatibility complexes (MHCs) play a key role in in-host viral diversity by selectively presenting viral peptides on the cell surface to alarm the adaptive immune system (3,7). Therefore, unique MHC haplotypes can influence whether an infected cell is recognized and destroyed by the host killer T cells, thereby stopping viral spread (8). Consistent with this knowledge, the study found the most significant association between host MHC and the viral non-structural protein 3 (NS3). In fact, 5% of the viral amino acids (including a few previously reported) were found to significantly associate with the MHC locus (6). Understanding the relationship between MHC genotypes and viral peptides, such as potential preferential antigen presentation and conserved epitopes, may help in the design of vaccines that engage HCV-specific T cell responses.
A second highly significant association lies between the host innate immune gene interferon-lambda 4 (IFNL4) and the HCV protein NS5B. Genetic polymorphisms in IFNL4 have been shown to indicate disease severity and response to therapy (2,4). The study suggests that the “favourable” IFNL4 genotype corresponds to a CC-dinucleotide insertion, which abolishes the expression of IFNL4 and downstream interferon-stimulated genes (ISGs), resulting in better tolerance to viral replication and mutations (6). The authors reason that despite the high viral load and diversity, the lack of selection pressure renders these viral particles susceptible to other host immune mechanisms and antiviral therapies, which explains the clinical observations of spontaneous clearance and better treatment response. On the other hand, the “unfavourable” non-CC genotype (normal IFNL4 expression) exerts high “purifying pressure” that creates a hostile environment for survival, resulting in lower viral load. The story gets more interesting: IFNL4 genotypes only affect viral load when there is a serine residue at the 2,414 position of the viral NS5B protein; no association is found otherwise (6). This observation could provide an explanation for the unresponsiveness to interferon-based therapies seen in the clinic: since ISGs likely directly interact with certain residues like Ser2,414, by mutating them to establish chronic infection, the virus is no longer affected by ISGs and interferon-based therapies. Taken together, the authors propose that the outcome of a new infection may depend on the source of transmission, specifically the MHC and IFNL4 genotypes of the previous host. Further investigation is needed to fully understand the host-disease interplay.
Under the current state of technological development, powerful tools like whole-genome sequencing and analysis are becoming inexpensive and accessible for both research and medicine. This study shows a successful example of using such “-omics” approaches to systematically tackle research questions and possibly provide insights for clinical applications. In merely 60 hours, genome-wide data from more than 500 individuals, including 2,500 associations involving 330,000 host SNPs, were processed. This demonstrates a fast and simple method for studying genetic-level associations between the human hosts and co-living foreign entities. In addition to applying this method in other chronic infections to potentially find the “Achilles’ heel” of pathogens, scientists can perhaps tackle the important question of how human hosts interact and co-evolve with microbiota, which is of great research interest for its broad and fascinating implications in the host immune defense, metabolism, and reproduction (9).
1. Hepatitis C. World Health Organization. 2017. Available from:
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