Evidence map›Paper›PMID 12826024›Full record

ArticleBMC immunology2003

Genetic control of the innate immune response.

Christine A Wells, Timothy Ravasi, Geoffrey J Faulkner, Piero Carninci, Yasushi Okazaki, Yoshihide Hayashizaki, Matthew Sweet, Brandon J Wainwright, David A Hume

Open access · goldAbstract read
In one paragraph

Article in BMC immunology, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed
3.3field-weighted citation impact, top 7% 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

62 citing papers in PubMed, 139 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Pathogens (Basel, Switzerland) · 2025
    Article
  5. Article
  6. InactivatedFrontiers in immunology · 2025
    Article
  7. Review
  8. Article
  9. A mutation inbioRxiv : the preprint server for biology · 2023
    Article
  10. Macrophages and Bone Remodeling.Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research · 2023
    Review
  11. Review
  12. Review
  13. The Interplay betweenPathogens (Basel, Switzerland) · 2021
    Review
  14. Article
  15. Proteome Profiling of PMJ2-R and Primary Peritoneal Macrophages.International journal of molecular sciences · 2021
    Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. Review

2 more citing papers are in PubMed but not listed here.

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

9 authors at 2 institutions in 2 countries.

Christine A WellsInstitute for Molecular Biosciences, The University of Queensland, Brisbane, QLD, 4072, Australia. c.wells@imb.uq.edu.au
Timothy Ravasi
Geoffrey J Faulkner
Piero Carninci
Yasushi Okazaki
Yoshihide Hayashizaki
Matthew Sweet
Brandon J Wainwright
David A Hume
University of Queensland · AUCenter for Genomic Science · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSusceptibility to infectious diseases is directed, in part, by the interaction between the invading pathogen and host macrophages. This study examines the influence of genetic background on host-pathogen interactions, by assessing the transcriptional responses of macrophages from five inbred mouse strains to lipopolysaccharide (LPS), a major determinant of responses to gram-negative microorganisms.

resultsThe mouse strains examined varied greatly in the number, amplitude and rate of induction of genes expressed in response to LPS. The response was attenuated in the C3H/HeJlpsd strain, which has a mutation in the LPS receptor Toll-like receptor 4 (TLR4). Variation between mouse strains allowed clustering into early (C57Bl/6J and DBA/2J) and delayed (BALB/c and C3H/ARC) transcriptional phenotypes. There was no clear correlation between gene induction patterns and variation at the Bcg locus (Slc11A1) or propensity to bias Th1 versus Th2 T cell activation responses.

conclusionMacrophages from each strain responded to LPS with unique gene expression profiles. The variation apparent between genetic backgrounds provides insights into the breadth of possible inflammatory responses, and paradoxically, this divergence was used to identify a common transcriptional program that responds to TLR4 signalling, irrespective of genetic background. Our data indicates that many additional genetic loci control the nature and the extent of transcriptional responses promoted by a single pathogen-associated molecular pattern (PAMP), such as LPS.

Indexed as

AnimalsCell DifferentiationCell DivisionCells, CulturedChromosome MappingGene Expression ProfilingImmunity, InnateInflammationKineticsLipopolysaccharidesMacrophage ActivationMacrophagesMembrane GlycoproteinsMiceMice, Inbred BALB CMice, Inbred C3HLipopolysaccharidesMembrane GlycoproteinsReceptors, Cell SurfaceToll-Like Receptor 4Toll-Like Receptors

Identifiers

PMID12826024
PMCPMC194878
OpenAlexW2157530588

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.