Evidence map›Paper›PMID 37461060›Full record

ArticleDiabetology & metabolic syndrome2023

Identification of key DNA methylation changes on fasting plasma glucose: a genome-wide DNA methylation analysis in Chinese monozygotic twins.

Weijing Wang, Wenqin Yao, Qihua Tan, Shuxia Li, Haiping Duan, Xiaocao Tian, Chunsheng Xu, Dongfeng Zhang

Open access · goldAbstract read
In one paragraph

Article in Diabetology & metabolic syndrome, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.8field-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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
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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

8 authors at 3 institutions in 2 countries.

Weijing Wang *Department of Epidemiology and Health Statistics, School of Public Health, Qingdao University, No. 308 Ningxia Road, Qingdao, 266071, Shandong Province, China. wangwj793@126.com.ORCID http://orcid.org/0000-0001-7747-7649
Wenqin YaoDepartment of Epidemiology and Health Statistics, School of Public Health, Qingdao University, No. 308 Ningxia Road, Qingdao, 266071, Shandong Province, China.
Qihua TanEpidemiology and Biostatistics, Department of Public Health, University of Southern Denmark, Odense, Denmark.
Shuxia LiEpidemiology and Biostatistics, Department of Public Health, University of Southern Denmark, Odense, Denmark.
Haiping DuanQingdao Municipal Center for Disease Control and Prevention/Qingdao Institute of Preventive Medicine, Qingdao, Shandong, China.
Xiaocao TianQingdao Municipal Center for Disease Control and Prevention/Qingdao Institute of Preventive Medicine, Qingdao, Shandong, China.
Chunsheng XuQingdao Municipal Center for Disease Control and Prevention/Qingdao Institute of Preventive Medicine, Qingdao, Shandong, China.
Dongfeng ZhangDepartment of Epidemiology and Health Statistics, School of Public Health, Qingdao University, No. 308 Ningxia Road, Qingdao, 266071, Shandong Province, China.
Qingdao Municipal Center for Disease Control and Prevention · CNQingdao University · CNUniversity of Southern Denmark · DK

Funding

China Postdoctoral Science Foundation 2020M682129National Natural Science Foundation of China 31741063Natural Science Foundation of Shandong Province ZR2020QH304
6 · The paper itself

Abstract

backgroundElevated fasting plasma glucose (FPG) levels can increase morbidity and mortality even when it is below the diagnostic threshold of type 2 diabetes mellitus (T2DM). We conducted a genome-wide DNA methylation analysis to detect DNA methylation (DNAm) variants potentially related to FPG in Chinese monozygotic twins.

methodsGenome-wide DNA methylation profiling in whole blood of twins was performed using Reduced Representation Bisulfite Sequencing (RRBS), yielding 551,447 raw CpGs. Association between DNAm of single CpG and FPG was tested using a generalized estimation equation. Differentially methylated regions (DMRs) were identified using comb-P approach. ICE FALCON method was utilized to perform the causal inference. Candidate CpGs were quantified and validated using Sequenom MassARRAY platform in a community population. Weighted gene co-expression network analysis (WGCNA) was conducted using gene expression data from twins.

resultsThe mean age of 52 twin pairs was 52 years (SD: 7). The relationship between DNAm of 142 CpGs and FPG reached the genome-wide significance level. Thirty-two DMRs within 24 genes were identified, including TLCD1, MRPS31P5, CASZ1, and CXADRP3. The causal relationship of top CpGs mapped to TLCD1, MZF1, PTPRN2, SLC6A18, ASTN2, IQCA1, GRIN1, and PDE2A genes with FPG were further identified using ICE FALCON method. Pathways potentially related to FPG were also identified, such as phospholipid-hydroperoxide glutathione peroxidase activity and mitogen-activated protein kinase p38 binding. Three CpGs mapped to SLC6A18 gene were validated in a community population, with a hypermethylated direction in diabetic patients. The expression levels of 18 genes (including SLC6A18 and TLCD1) were positively correlated with FPG levels.

conclusionsWe detect many DNAm variants that may be associated with FPG in whole blood, particularly the loci within SLC6A18 gene. Our findings provide important reference for the epigenetic regulation of elevated FPG levels and diabetes.

Indexed as

CausalityDNA methylationFasting plasma glucoseMonozygotic twins

Identifiers

PMID37461060
PMCPMC10351111
OpenAlexW4384557643

What Socratic holds

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LicenceCC BY
Read underepoch 390

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 Socratic graph.