Evidence map›Paper›PMID 23124883›Full record

ArticleFrontiers of medicine2012

Genome-wide association studies: inherent limitations and future challenges.

Yan Du, Jiaxin Xie, Wenjun Chang, Yifang Han, Guangwen Cao

Abstract read
PubMed Publisher
In one paragraph

Article in Frontiers of medicine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Article
  6. Artificial Intelligence Enhances Studies on Inflammatory Bowel Disease.Frontiers in bioengineering and biotechnology · 2021
    Review
  7. Article
  8. Review
  9. Article
  10. [Hepatocellular carcinoma: co - evolution of hepatocytes and hepatitis B virus].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2017
    Article
  11. Review
  12. Article
  13. Article
  14. 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

5 authors.

Yan DuDepartment of Epidemiology, Second Military Medical University, Shanghai 200433, China.
Jiaxin Xie
Wenjun Chang
Yifang Han
Guangwen Cao

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genome-wide association studies (GWAS) have achieved great success in identifying genetic variants related to complex human diseases such as cancer and have provided valuable insights into their genetic architecture. Recently, GWAS is quite the fashion in China. However, there are issues related to its nature. Enormous work needs to be done in the post-GWAS era. Deep sequencing followed by functional studies will be needed to elucidate the underpinning biological mechanisms and further translate GWAS findings into medical practice. Along with pharmacogenomics, the success of GWAS in identifying genetic risk factors and genetic differences in drug response has been gradually enabling personalized medicine. In this article, we used hepatocellular carcinoma (HCC) as an example to demonstrate some of the inherent limitations and summarized future challenges of GWAS.

Indexed as

Genetic ResearchGenome-Wide Association StudyChinaGenetic Diseases, InbornGenetic Predisposition to DiseaseHumans

Identifiers

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.