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Genome-wide DNA methylation analysis in monozygotic twins identifies potential biomarkers of fasting plasma glucose

<p><strong><span>Purpose:</span></strong><span> An epigenome-wide association study (EWAS) was conducted to detect specific epigenetic variants potentially related to fasting plasma glucose (FPG) in middle-aged and elderly Chinese monozygotic twins.</span></p> <p><span><strong>Methods:</strong> </span><span>Association between DNA methylation (DNAm) of single CpG and FPG was tested by applying generalized estimation equation in 52 twin pairs. Differentially methylated regions (DMRs) were identified by</span><em> <span>comb-P</span></em> <span>approach</span><span>. Inference about Causation through Examination of Familial Confounding (ICE FALCON) was utilized to perform the causal inference. Candidate CpGs were quantified using Sequenom MassARRAY platform in a community population. Weighted gene co-expression network analysis (WGCNA) was conducted using gene expression data. </span></p> <p><span><strong>Results</strong>: </span><span>The relationship between DNAm of 30 top CpGs and FPG reached <em>P</em>-value</span><span>&lt;</span><span>1×10<sup>-6</sup></span><span> level. Thirty-two DMRs within 24 genes, such as TLCD1, MRPS31P5, </span><span>CASZ1 </span><span>and CXADRP3, were identified. Causal relationship of 20 top CpGs within <em>TLCD1, MZF1, PTPRN2, SLC6A18, ASTN2, IQCA1, GRIN1</em>, and <em>PDE2A </em>with FPG were further identified. Pathways related to FPG such as mitogen-activated protein kinase p38 binding were found. Three CpGs mapped to <em>SLC6A18 </em>were</span><span> validated in a community population, with </span><span>a hypermethylated direction in type 2 diabetes cases. The gene expression levels of 18 genes where the top CpGs and DMRs located, such as <em>SLC6A18 </em>and <em>TLCD1</em>, were positively correlated with FPG. Besides, common biological pathways, such as dopamine binding, regulation of biosynthetic process, and neuron fate specification, were found in methylation and gene expression analyses.</span></p> <p><span><strong>Conclusion</strong>: </span><span>Our findings showed that</span> <span>multiple methylated CpGs and regions, crucial genes, and biological pathways were underlyingly associated with FPG and diabetes.</span></p>

ShareScore

28/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
0
Harmonization
12
Access
12
Reuse readiness
0
Engagement
4

Dataset details

Repository
dryad
Published
July 27, 2022
License
cc-zero
DOI
10.5061/dryad.xsj3tx9hd

Scored with release 0.9.0

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