ReviewAntiviral research2009
Using high-throughput genomics to study hepatitis C: what determines the outcome of infection?
Review in Antiviral research, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- A novel microRNA boosts hyper-β-oxidation of fatty acids in liver by impeding CEP350-mediated sequestration of PPARα and thus restricts chronic hepatitis C.RNA biology · 2020Article
- ADAR1 polymorphisms are related to severity of liver fibrosis in HIV/HCV-coinfected patients.Scientific reports · 2017Article
- Proteome and computational analyses reveal new insights into the mechanisms of hepatitis C virus-mediated liver disease posttransplantation.Hepatology (Baltimore, Md.) · 2012Article
- Genomics and proteomics in liver fibrosis and cirrhosis.Fibrogenesis & tissue repair · 2012Article
- Individualized treatment of chronic hepatitis C with pegylated interferon and ribavirin.Pharmacogenomics and personalized medicine · 2010Article
- Applications of high-throughput genomics to antiviral research: evasion of antiviral responses and activation of inflammation during fulminant RNA virus infection.Antiviral research · 2009Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
High-throughput genomic methods are now being used to study a wide variety of viral diseases, in an effort to understand how host responses to infection can lead either to efficient elimination of the pathogen or the development of severe disease. This article reviews how gene expression studies are addressing important clinical issues related to hepatitis C virus infection, in which some 15-25% of infected individuals are able to clear the virus without treatment, while the remainder progress to chronic liver disease that can lead to cirrhosis and death. Similar methods are also being used in an effort to identify the mechanisms underlying the failure of some hepatitis C patients to respond to interferon-alpha/ribavirin therapy. By providing a detailed picture of virus-host interactions, high-throughput genomics could potentially lead to the identification of novel cellular targets for the treatment of hepatitis C.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.