Evidence map›Paper›PMID 30055620›Full record

ArticleLipids in health and disease2018

Gene-gene interactions lead to higher risk for development of type 2 diabetes in a Chinese Han population: a prospective nested case-control study.

Wen Zhou, Yuqian Li, Lulu Zhang, Yuanyuan Shi, Chongjian Wang, Dongdong Zhang, Xuejiao Liu, Zhenxing Mao, Linlin Li

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Lipids in health and disease, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.5field-weighted citation impact, top 27% 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

6 citing papers in PubMed, 8 citations in OpenAlex.

  1. Relationship betweenWorld journal of diabetes · 2023
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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 at 1 institution in 1 country.

Wen ZhouDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, China.
Yuqian LiDepartment of Clinical Pharmacology, School of Pharmaceutical Science, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, China.
Lulu ZhangDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, China.
Yuanyuan ShiDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, China.
Chongjian WangDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, China.
Dongdong ZhangDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, China.
Xuejiao LiuDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, China.
Zhenxing MaoDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, China.
Linlin LiDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, China. 13623850209@163.com.ORCID http://orcid.org/0000-0001-7076-2594
Zhengzhou University · CN

Funding

National Natural Science Foundation of China 8150120621
6 · The paper itself

Abstract

backgroundThe purpose of this study was to evaluate the effect of single-nucleotide polymorphisms (SNPs) of the GCKR and G6PC2 genes on risk for type 2 diabetes and the SNP-SNP and haplotype-based interactions between these genes.

methodsSubjects of this nested case-control study were selected from a prospective cohort residing in the rural area of Luoyang city in China. Cases (n = 538) were individually matched with controls. Six SNPs in the GCKR and G6PC2 genes were selected and genotyped using an SNPscan™ kit. Stratified Cox proportional hazards regression models were used to generate odds ratios (ORs) and 95% confidence intervals (CI) for different genotype models for the risk of T2DM. Generalized multifactor dimensionality reduction (GMDR) was used to analyze the interactions between two genes with among six SNPs. The linkage disequilibrium (LD) analysis and the haplotype analysis were carried out by SHEsis online.

resultsWe found that the C allele of rs780094 was associated with increased risk for T2DM in Han Chinese population. However, the rs492594-C allele in G6PC2 was associated with a decreased risk of T2DM. We also found a significant SNP-SNP interaction between rs2293572 and rs492594, and the CCCCGC and CGCCCA haplotypes significantly increased the risk of T2DM, however, the CCCCCA haplotype had lower susceptibility to T2DM.

conclusionThe results suggest that the GCKR and G6PC2 genes may contribute to the risk of T2DM independently and/or in an interactive manner in the Han Chinese population.

Indexed as

Genetic Predisposition to DiseasePolymorphism, Single NucleotideAdaptor Proteins, Signal TransducingAdultAgedAllelesBlood GlucoseCase-Control StudiesChinaCholesterol, HDLCholesterol, LDLDiabetes Mellitus, Type 2FemaleGene ExpressionGene FrequencyGlucose-6-PhosphataseAdaptor Proteins, Signal TransducingBlood GlucoseCholesterol, HDLCholesterol, LDLG6PC2 protein, humanGCKR protein, humanGlucose-6-PhosphataseTriglyceridesGeneHaplotypeInteractionNested case-control studyType 2 diabetes mellitus

Identifiers

PMID30055620
PMCPMC6064617
OpenAlexW2883543468

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Registered trials

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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.