Evidence map›Paper›PMID 21999673›Full record

SynthesisBMC genomics2011

Meta-analysis and genome-wide interpretation of genetic susceptibility to drug addiction.

Chuan-Yun Li, Wei-Zhen Zhou, Ping-Wu Zhang, Catherine Johnson, Liping Wei, George R Uhl

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in BMC genomics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 2 pooled it
2.8field-weighted citation impact, top 9% 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

24 citing papers in PubMed, 2 syntheses or guidelines pooled it, 37 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. An Inventory of Methods for the Assessment of Additive Increased Addictiveness of Tobacco Products.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2016
    Review
  12. A genome-wide investigation of food addiction.Obesity (Silver Spring, Md.) · 2016
    Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Review
  19. 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

6 authors at 3 institutions in 2 countries.

Chuan-Yun LiLaboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, Peking University, Beijing, China. lichuanyun@gmail.com
Wei-Zhen Zhou
Ping-Wu Zhang
Catherine Johnson
Liping Wei
George R Uhl
Peking University · CNNational Institute on Drug Abuse · USJohns Hopkins University · US

Funding

Genetic Approaches To Characterizing Drug Responses And Vulnerabilities: HumansZIADA000401 · NIDA · NATIONAL INSTITUTE ON DRUG ABUSE · PI UHL, GEORGE RICHARD · 2009 to 2015
$3.4M
Molecular Genetic Bases for Quit SuccessZIADA000537 · NIDA · NATIONAL INSTITUTE ON DRUG ABUSE · PI UHL, GEORGE RICHARD · 2009 to 2015
$2.9M
Understanding addiction vulnerability genesZIADA000492 · NIDA · NATIONAL INSTITUTE ON DRUG ABUSE · PI UHL, GEORGE RICHARD · 2009 to 2015
$1.9M
6 · The paper itself

Abstract

backgroundClassical genetic studies provide strong evidence for heritable contributions to susceptibility to developing dependence on addictive substances. Candidate gene and genome-wide association studies (GWAS) have sought genes, chromosomal regions and allelic variants likely to contribute to susceptibility to drug addiction.

resultsHere, we performed a meta-analysis of addiction candidate gene association studies and GWAS to investigate possible functional mechanisms associated with addiction susceptibility. From meta-data retrieved from 212 publications on candidate gene association studies and 5 GWAS reports, we linked a total of 843 haplotypes to addiction susceptibility. We mapped the SNPs in these haplotypes to functional and regulatory elements in the genome and estimated the magnitude of the contributions of different molecular mechanisms to their effects on addiction susceptibility. In addition to SNPs in coding regions, these data suggest that haplotypes in gene regulatory regions may also contribute to addiction susceptibility. When we compared the lists of genes identified by association studies and those identified by molecular biological studies of drug-regulated genes, we observed significantly higher participation in the same gene interaction networks than expected by chance, despite little overlap between the two gene lists.

conclusionsThese results appear to offer new insights into the genetic factors underlying drug addiction.

Indexed as

Genetic Predisposition to DiseaseGenome-Wide Association StudyDatabases, FactualGenome, HumanHaplotypesHumansOdds RatioPolymorphism, Single NucleotideSubstance-Related Disorders

Identifiers

PMID21999673
PMCPMC3215751
OpenAlexW2098134308

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.