Evidence map›Paper›PMID 35585257›Full record

ReviewGenes and immunity2022

The role of IFNL4 in liver inflammation and progression of fibrosis.

Michelle Møhlenberg, Thomas R O'Brien, Rune Hartmann

Abstract readReview
PubMed Publisher
In one paragraph

Review in Genes and immunity, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 29% of its field
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

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Frequencies of anInternational journal of molecular sciences · 2024
    Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 2 countries.

Michelle MøhlenbergDepartment of Molecular Biology and Genetics, Aarhus University, Universitetsbyen 81, 8000, Aarhus C, Denmark.ORCID 0000-0002-3769-4902
Thomas R O'BrienInfections and Immunoepidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
Rune HartmannDepartment of Molecular Biology and Genetics, Aarhus University, Universitetsbyen 81, 8000, Aarhus C, Denmark. rh@mbg.au.dk.ORCID 0000-0003-1159-066X
Aarhus University · DKNational Cancer Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The discovery that genetic variation within the interferon lambda locus has a profound effect on the outcome of hepatitis C virus (HCV) treatment and spontaneous clearance of HCV is one of the great triumphs of genomic medicine. Subsequently, the IFNL4 gene was discovered and proposed as the causal gene underlying this association. However, there has been a lively debate within the field concerning the causality, which has been further complicated by a change in naming. This review summarizes the genetic data available for the IFNL3/IFNl4 loci and provides an in-depth discussion of causality. We also discuss a new series of interesting data suggesting that the genetic variation at the IFNL4 loci influences the evolution of the HCV virus and the implication this relationship between our genetic makeup and virus evolution has upon our understanding of the IFNL4 system. Finally, new data support an influence of the IFNL4 gene upon liver inflammation and fibrosis that is independent of etiology, thereby linking the IFNL4 gene to some of the major liver diseases of today.

Indexed as

Hepatitis CInterleukinsFibrosisGenotypeHepacivirusHumansInflammationInterferon LambdaInterferonsPolymorphism, Single NucleotideIFNL4 protein, humanInterferon LambdaInterferonsInterleukins

Identifiers

PMID35585257
OpenAlexW4280584758

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.