Evidence map›Paper›PMID 23922971›Full record

SynthesisPloS one2013

Genetic associations with diabetes: meta-analyses of 10 candidate polymorphisms.

Linlin Tang, Lingyan Wang, Qi Liao, Qinwen Wang, Leiting Xu, Shizhong Bu, Yi Huang, Cheng Zhang, Huadan Ye, Xuting Xu and 4 more

Abstract readMeta-Analysis
In one paragraph

Synthesis in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

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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

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

  1. Pooled it
  2. Review
  3. Review
  4. Association ofBiomedical reports · 2017
    Article
  5. Meta-analyses of sevenBiomedical reports · 2014
    Article
  6. Association betweenBiomedical reports · 2014
    Article
  7. Association ofBiomedical reports · 2014
    Article
  8. 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

14 authors.

Linlin TangZhejiang Provincial Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, Zhejiang, China.
Lingyan Wang
Qi Liao
Qinwen Wang
Leiting Xu
Shizhong Bu
Yi Huang
Cheng Zhang
Huadan Ye
Xuting Xu
Qiong Liu
Meng Ye
Yifeng Mai
Shiwei Duan

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsThe goal of our study is to investigate the combined contribution of 10 genetic variants to diabetes susceptibility.

methodsBibliographic databases were searched from 1970 to Dec 2012 for studies that reported on genetic association study of diabetes. After a comprehensive filtering procedure, 10 candidate gene variants with informative genotype information were collected for the current meta-anlayses. Using the REVMAN software, odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to evaluate the combined contribution of the selected genetic variants to diabetes.

resultsA total of 37 articles among 37,033 cases and 54,716 controls were involved in the present meta-analyses of 10 genetic variants. Three variants were found to be significantly associated with type 1 diabetes (T1D): NLRP1 rs12150220 (OR = 0.71, 95% CI = 0.55-0.92, P = 0.01), IL2RA rs11594656 (OR = 0.86, 95% CI = 0.82-0.91, P<0.00001), and CLEC16A rs725613 (OR = 0.71, 95% CI = 0.55-0.92, P = 0.01). APOA5 -1131T/C polymorphism was shown to be significantly associated with of type 2 diabetes (T2D, OR = 1.27, 95% CI = 1.03-1.57, P = 0.03). No association with diabetes was showed in the meta-analyses of other six genetic variants, including SLC2A10 rs2335491, ATF6 rs2070150, KLF11 rs35927125, CASQ1 rs2275703, GNB3 C825T, and IL12B 1188A/C.

conclusionOur results demonstrated that IL2RA rs11594656 and CLEC16A rs725613 are protective factors of T1D, while NLRP1 rs12150220 and APOA5 -1131T/C are risky factors of T1D and T2D, respectively.

Indexed as

Genetic Predisposition to DiseasePolymorphism, GeneticDiabetes MellitusDiabetes Mellitus, Type 1Diabetes Mellitus, Type 2HumansOdds RatioPolymorphism, Single Nucleotide

Identifiers

PMID23922971
PMCPMC3726433

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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.