Evidence map›Paper›PMID 19223927›Full record

ReviewNature reviews. Genetics2009

Mapping complex disease traits with global gene expression.

William Cookson, Liming Liang, Gonçalo Abecasis, Miriam Moffatt, Mark Lathrop

Abstract readReview
In one paragraph

Review in Nature reviews. Genetics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 462 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
462citing papers in PubMed, 1 pooled it
–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

462 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. Identification ofFrontiers in aging neuroscience · 2026
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Generative prediction of causal gene sets responsible for complex traits.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  14. Identification and Functional Assessment of Candidate CausalCirculation. Genomic and precision medicine · 2025
    Article
  15. Review
  16. Article
  17. Article
  18. Copy Number Variation in Asthma: An Integrative Review.Clinical reviews in allergy & immunology · 2025
    Review
  19. Review
  20. Unsupervised pattern identification in spatial gene expression atlas reveals mouse brain regions beyond established ontology.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article

402 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

5 authors.

William CooksonNational Heart and Lung Institute, Imperial College London, London SW3 6LY, UK. w.cookson@imperial.ac.uk
Liming Liang
Gonçalo Abecasis
Miriam Moffatt
Mark Lathrop

Funding

Computational and Statistical Models for Human PedigreesR01HG002651 · NHGRI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ABECASIS, GONCALO · 2003 to 2008
$2.9M
Integrated Parametric and Non-parametric Mapping for Genome-Wife Association DataU01HL084729 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ABECASIS, GONCALO · 2006 to 2008
$872k
NHGRI NIH HHS R01 HG002651NHLBI NIH HHS U01 HL084729Wellcome Trust
6 · The paper itself

Abstract

Variation in gene expression is an important mechanism underlying susceptibility to complex disease. The simultaneous genome-wide assay of gene expression and genetic variation allows the mapping of the genetic factors that underpin individual differences in quantitative levels of expression (expression QTLs; eQTLs). The availability of systematically generated eQTL information could provide immediate insight into a biological basis for disease associations identified through genome-wide association (GWA) studies, and can help to identify networks of genes involved in disease pathogenesis. Although there are limitations to current eQTL maps, understanding of disease will be enhanced with novel technologies and international efforts that extend to a wide range of new samples and tissues.

Indexed as

Genome-Wide Association StudyQuantitative Trait LociAnimalsDiseaseGenetic VariationHumans

Identifiers

PMID19223927
PMCPMC4550035

What OpenQuestion holds

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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.