Evidence map›Paper›PMID 22278598›Full record

ArticleHepatology (Baltimore, Md.)2012

Early transcriptional programming links progression to hepatitis C virus-induced severe liver disease in transplant patients.

Angela L Rasmussen, Nicolas Tchitchek, Nathan J Susnow, Alexei L Krasnoselsky, Deborah L Diamond, Matthew M Yeh, Sean C Proll, Marcus J Korth, Kathie-Anne Walters, Sharon Lederer and 4 more

Abstract readComparative Study
In one paragraph

Article in Hepatology (Baltimore, Md.), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors.

Angela L RasmussenDepartment of Microbiology, University of Washington School of Medicine, Seattle, WA 98195, USA.
Nicolas Tchitchek
Nathan J Susnow
Alexei L Krasnoselsky
Deborah L Diamond
Matthew M Yeh
Sean C Proll
Marcus J Korth
Kathie-Anne Walters
Sharon Lederer
Anne M Larson
Robert L Carithers
Arndt Benecke
Michael G Katze

Funding

PROTEOMICS COREP30DA015625 · NIDA · UNIVERSITY OF WASHINGTON · PI KATZE, MICHAEL G · 2002 to 2012
$18.9M
NIDA NIH HHS P30 DA015625
6 · The paper itself

Abstract

unlabelledLiver failure resulting from chronic hepatitis C virus (HCV) infection is a major cause for liver transplantation worldwide. Recurrent infection of the graft is universal in HCV patients after transplant and results in a rapid progression to severe fibrosis and end-stage liver disease in one third of all patients. No single clinical variable, or combination thereof, has, so far, proven accurate in identifying patients at risk of hepatic decompensation in the transplant setting. A combination of longitudinal, dimensionality reduction and categorical analysis of the transcriptome from 111 liver biopsy specimens taken from 57 HCV-infected patients over time identified a molecular signature of gene expression of patients at risk of developing severe fibrosis. Significantly, alterations in gene expression occur before histologic evidence of liver disease progression, suggesting that events that occur during the acute phase of infection influence patient outcome. Additionally, a common precursor state for different severe clinical outcomes was identified.

conclusionBased on this patient cohort, incidence of severe liver disease is a process initiated early during HCV infection of the donor organ. The probable cellular network at the basis of the initial transition to severe liver disease was identified and characterized.

Indexed as

AgedBiopsy, NeedleCohort StudiesDisease ProgressionFemaleGene Expression RegulationGraft RejectionHepacivirusHepatitis C, ChronicHumansImmunohistochemistryLiver FailureLiver TransplantationLongitudinal StudiesMaleMiddle Aged

Identifiers

PMID22278598
PMCPMC3349763

What OpenQuestion holds

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Registered trials

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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.