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

Diabetology & Metabolic Syndrome

Research

Dongfeng Zhang¹  Weijing Wang¹  Wenqin Yao²  Qihua Tan³  Shuxia Li³  Haiping Duan⁴  Chunsheng Xu⁴  Xiaocao Tian⁴ 

[1]Department of Epidemiology and Health Statistics, School of Public Health, Qingdao University, No. 308 Ningxia Road, 266071, Qingdao, Shandong Province, China

[2]Department of Epidemiology and Health Statistics, School of Public Health, Qingdao University, No. 308 Ningxia Road, 266071, Qingdao, Shandong Province, China

[3]Shandong Province Center for Disease Control and Prevention, Shandong, China

[4]Epidemiology and Biostatistics, Department of Public Health, University of Southern Denmark, Odense, Denmark

[5]Qingdao Municipal Center for Disease Control and Prevention/Qingdao Institute of Preventive Medicine, Qingdao, Shandong, China

关键词: Causality;    DNA methylation;    Fasting plasma glucose;    Monozygotic twins;   

DOI  :  10.1186/s13098-023-01136-4

 received in 2023-03-29, accepted in 2023-07-09,  发布年份 2023

来源: Springer

【 摘 要 】

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.

【 授权许可】

CC BY   
© The Author(s) 2023

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