Evidence map›Paper›PMID 19184112›Full record

ArticleHuman genetics2009

Identification of susceptibility genes for complex diseases using pooling-based genome-wide association scans.

Yohan Bossé, François Bacot, Alexandre Montpetit, Johan Rung, Hui-Qi Qu, James C Engert, Constantin Polychronakos, Thomas J Hudson, Philippe Froguel, Robert Sladek and 1 more

Abstract read
PubMed Publisher
In one paragraph

Article in Human genetics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 1 pooled it
5.6field-weighted citation impact, top 4% 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

38 citing papers in PubMed, 1 synthesis or guideline pooled it, 80 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Frontiers in genetics · 2021
    Article
  5. Review
  6. Article
  7. Review
  8. Article
  9. Genome-Wide Association Study of Acute Renal Graft Rejection.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2017
    Article
  10. Article
  11. Article
  12. A role for auto-immunity in chronic rhinosinusitis? Lessons learned from sub-epidermal bullous disorders of the skin.Allergy, asthma, and clinical immunology : official journal of the Canadian Society of Allergy and Clinical Immunology · 2016
    Review
  13. Article
  14. Article
  15. Risk factors for chronic rhinosinusitis.Current opinion in allergy and clinical immunology · 2015
    Review
  16. Review
  17. Pathophysiology of chronic rhinosinusitis, pharmaceutical therapy options.GMS current topics in otorhinolaryngology, head and neck surgery · 2015
    Review
  18. Article
  19. ICON: chronic rhinosinusitis.The World Allergy Organization journal · 2014
    Article
  20. 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

11 authors at 7 institutions in 2 countries.

Yohan BosséLaval Hospital Research Center, Laval University, Pavillon Margeritte-d'Youville, chemin Sainte-Foy, Quebec, QC, Canada. yohan.bosse@crhl.ulaval.ca
François Bacot
Alexandre Montpetit
Johan Rung
Hui-Qi Qu
James C Engert
Constantin Polychronakos
Thomas J Hudson
Philippe Froguel
Robert Sladek
Martin Desrosiers
McGill University · CAMcGill University and Génome Québec Innovation Centre · CACentre National de la Recherche Scientifique · FRMontreal Children's Hospital · CAOntario Institute for Cancer Research · CAUniversité de Montréal · CAUniversité Laval · CA

Funding

Medical Research Council G0600331
6 · The paper itself

Abstract

The success of genome-wide association studies (GWAS) to identify risk loci of complex diseases is now well-established. One persistent major hurdle is the cost of those studies, which make them beyond the reach of most research groups. Performing GWAS on pools of DNA samples may be an effective strategy to reduce the costs of these studies. In this study, we performed pooling-based GWAS with more than 550,000 SNPs in two case-control cohorts consisting of patients with Type II diabetes (T2DM) and with chronic rhinosinusitis (CRS). In the T2DM study, the results of the pooling experiment were compared to individual genotypes obtained from a previously published GWAS. TCF7L2 and HHEX SNPs associated with T2DM by the traditional GWAS were among the top ranked SNPs in the pooling experiment. This dataset was also used to refine the best strategy to correctly identify SNPs that will remain significant based on individual genotyping. In the CRS study, the top hits from the pooling-based GWAS located within ten kilobases of known genes were validated by individual genotyping of 1,536 SNPs. Forty-one percent (598 out of the 1,457 SNPs that passed quality control) were associated with CRS at a nominal P value of 0.05, confirming the potential of pooling-based GWAS to identify SNPs that differ in allele frequencies between two groups of subjects. Overall, our results demonstrate that a pooling experiment on high-density genotyping arrays can accurately determine the minor allelic frequency as compared to individual genotyping and produce a list of top ranked SNPs that captures genuine allelic differences between a group of cases and controls. The low cost associated with a pooling-based GWAS clearly justifies its use in screening for genetic determinants of complex diseases.

Indexed as

Genetic Predisposition to DiseasePolymorphism, Single NucleotideAllelesCase-Control StudiesChronic DiseaseCohort StudiesDiabetes Mellitus, Type 2DNAGene FrequencyGenome-Wide Association StudyHumansModels, GeneticRhinitisSinusitisDNA

Identifiers

PMID19184112
OpenAlexW2090716675

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.