Evidence map›Paper›PMID 24710510›Full record

SynthesisPloS one2014

Quantitative assessment of the effect of KCNJ11 gene polymorphism on the risk of type 2 diabetes.

Ling Qiu, Risu Na, Rong Xu, Siyang Wang, Hongguang Sheng, Wanling Wu, Yi Qu

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 2 pooled it
4.3field-weighted citation impact, top 5% 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

17 citing papers in PubMed, 2 syntheses or guidelines pooled it, 45 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Review
  5. Article
  6. Article
  7. Identifying the association between single nucleotide polymorphisms inInternational journal of medical sciences · 2020
    Observational
  8. Article
  9. Article
  10. Article
  11. Diabetes Mellitus and Ischemic Heart Disease: The Role of Ion Channels.International journal of molecular sciences · 2018
    Review
  12. Article
  13. Article
  14. Genetic variants inExperimental and therapeutic medicine · 2017
    Article
  15. Review
  16. Review
  17. 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

7 authors at 2 institutions in 1 country.

Ling QiuDepartment of Geriatrics, Shanghai Xuhui Central Hospital, Shanghai Clinical Center, Chinese Academy of Sciences, Shanghai, People's Republic of China.
Risu NaDepartment of Endocrinology, Shanghai Xuhui Central Hospital, Shanghai Clinical Center, Chinese Academy of Sciences, Shanghai, People's Republic of China.
Rong XuDepartment of Geriatrics, Shanghai Xuhui Central Hospital, Shanghai Clinical Center, Chinese Academy of Sciences, Shanghai, People's Republic of China.
Siyang WangDepartment of Geriatrics, Shanghai Xuhui Central Hospital, Shanghai Clinical Center, Chinese Academy of Sciences, Shanghai, People's Republic of China.
Hongguang ShengDepartment of Endocrinology, Shanghai Xuhui Central Hospital, Shanghai Clinical Center, Chinese Academy of Sciences, Shanghai, People's Republic of China.
Wanling WuDepartment of Endocrinology, The Ninth People's Hospital Attach to Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.
Yi QuDepartment of Geriatrics, Shanghai Xuhui Central Hospital, Shanghai Clinical Center, Chinese Academy of Sciences, Shanghai, People's Republic of China.
Shanghai Xuhui Central Hospital · CNShanghai Jiao Tong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To clarify the role of potassium inwardly-rectifying-channel, subfamily-J, member 11 (KCNJ11) variation in susceptibility to type 2 diabetes (T2D), we performed a systematic meta-analysis to investigate the association between the KCNJ11 E23K polymorphism (rs5219) and the T2D in different genetic models. Databases including PubMed, Medline, EMBASE, and ISI Web of Science were searched to identify relevant studies. A total of 48 published studies involving 56,349 T2D cases, 81,800 controls, and 483 family trios were included in this meta-analysis. Overall, the E23K polymorphism was significantly associated with increased T2D risk with per-allele odds ratio (OR) of 1.12 (95% CI: 1.09-1.16; P<10-5). The summary OR for T2D was 1.09 (95% CI: 1.03-1.14; P<10-5), and 1.26 (95% CI: 1.17-1.35; P<10-5), for heterozygous and homozygous, respectively. Similar results were also detected under dominant and recessive genetic models. When stratified by ethnicity, significantly increased risks were found for the polymorphism in Caucasians and East Asians. However, no such associations were detected among Indian and other ethnic populations. Significant associations were also observed in the stratified analyses according to different mean BMI of cases and sample size. Although significant between study heterogeneity was identified, meta-regression analysis suggested that the BMI of controls significantly correlated with the magnitude of the genetic effect. The current meta-analysis demonstrated that a modest but statistically significant effect of the 23K allele of rs5219 polymorphism in susceptibility to T2D. But the contribution of its genetic variants to the epidemic of T2D in Indian and other ethnic populations appears to be relatively low.

Indexed as

Genetic Predisposition to DiseasePolymorphism, Single NucleotideAllelesAsian PeopleDiabetes Mellitus, Type 2Genetic Association StudiesGenotypeHumansKcnj11 ChannelPotassium Channels, Inwardly RectifyingWhite PeopleKcnj11 ChannelPotassium Channels, Inwardly Rectifying

Identifiers

PMID24710510
PMCPMC3977990
OpenAlexW2073443363

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.