Evidence mapPaperPMID 39806965Full record

ArticleEndocrine, metabolic & immune disorders drug targets2025

Contribution of Type 2 Diabetes Susceptible Gene GCKR Polymorphisms Rs780094 and Rs1260326 to Gestational Diabetes Mellitus: A Meta-Analysis.

Yuke Zhang, Kuangyi Wang, Chenxi Ji, Yansi Lin, Zitong Liu, Jing Chen, Feifei Zheng, Xiaoqin Yang, Yi Sun

Abstract read
In one paragraph

Article in Endocrine, metabolic & immune disorders drug targets, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

1 citing paper in PubMed.

  1. 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

9 authors.

Yuke ZhangCenter for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Suzhou Medical College Soochow University, Suzhou 215123, China.
Kuangyi WangDepartment of Cardiology, the Fourth Affiliated Hospital of Soochow University and Medical Center Soochow University, Suzhou 215123, China.
Chenxi JiCenter for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Suzhou Medical College Soochow University, Suzhou 215123, China.
Yansi LinCenter for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Suzhou Medical College Soochow University, Suzhou 215123, China.
Zitong LiuCenter for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Suzhou Medical College Soochow University, Suzhou 215123, China.
Jing ChenCenter for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Suzhou Medical College Soochow University, Suzhou 215123, China.
Feifei ZhengCenter for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Suzhou Medical College Soochow University, Suzhou 215123, China.
Xiaoqin YangCenter for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Suzhou Medical College Soochow University, Suzhou 215123, China.
Yi SunDepartment of Genetics, School of Biology and Basic Medical Sciences, Suzhou Medical College Soochow University, Suzhou 215123, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is still no conclusive understanding of whether the glucokinase regulator (GCKR) gene rs780094 and rs1260326 polymorphisms predispose to gestational diabetes mellitus (GDM).

objectiveThis systematic review and meta-analysis aimed to determine the effect of the GCKR polymorphisms on GDM susceptibility.

methodsSeven literature databases were searched (from inception to February 17, 2024) to locate relevant studies included in further meta-analysis. Odds ratio (OR) and 95% confidence intervals (CI) in the pooled population were estimated to assess the effects of the variant allele on GDM risk.

resultsFor the rs780094 polymorphism, 13 datasets with 3443 GDM cases and 5930 nondiabetic controls were included. The pooled estimates in the allele model (OR: 1.19, 95% CI: 1.07~1.32), homozygote model (OR: 1.27, 95% CI: 1.10~1.47), dominant model (OR: 1.16, 95% CI: 1.03~1.31), and recessive model (OR: 1.31, 95% CI: 1.09~1.57) suggested that the C allele carriers were prone to GDM. For the rs1260326 polymorphism, five datasets with 1495 cases and 2678 controls were integrated. The statistically significant effect of the C allele was evident in the allele model (OR: 1.12, 95% CI: 1.01~1.24) and the homozygote model (OR: 1.26, 95% CI: 1.03~1.54).

conclusionThis meta-analysis suggested that the C allele of the rs780094 and rs1260326 polymorphisms in the GCKR gene are significantly associated with increased risk of GDM.

Indexed as

Gestational diabetes mellitusglucokinase regulator genemeta-analysisrs1260326rs780094susceptibility.

Identifiers

PMID39806965
PMCPMC13284661

What Socratic 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 Socratic graph.