{"title":"Differential methylation patterns from clusters associated with glucose metabolism: evidence from a Shanghai twin study.","authors":"Jingyuan Feng, Zhenni Zhu, Rongfei Zhou, Hongwei Liu, Zihan Hu, Fei Wu, Huiting Wang, Junhong Yue, Tong Zhou, Li Yang, Fan Wu","doi":"10.2217/epi-2023-0449","DOIUrl":null,"url":null,"abstract":"<p><p><b>Aim:</b> To assess the associations between genome-wide DNA methylation (DNAm) and glucose metabolism among a Chinese population, in particular the multisite correlation. <b>Materials & methods:</b> Epigenome-wide associations with fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) were analyzed among 100 Shanghai monozygotic (MZ) twin pairs using the Infinium HumanMethylationEPIC v2.0 BeadChip. We conducted a Pearson's correlation test, hierarchical cluster and pairwise analysis to examine the differential methylation patterns from clusters. <b>Results:</b> Cg01358804 (<i>TXNIP</i>) was identified as the most significant site associated with FPG and HbA1c. Two clusters with hypermethylated and hypomethylated patterns were observed for both FPG and HbA1c. <b>Conclusion:</b> Differential methylation patterns from clusters may provide new clues for epigenetic changes and biological mechanisms in glucose metabolism.</p>","PeriodicalId":11959,"journal":{"name":"Epigenomics","volume":" ","pages":"445-459"},"PeriodicalIF":3.0000,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Epigenomics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2217/epi-2023-0449","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/2/27 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
引用次数: 0
Abstract
Aim: To assess the associations between genome-wide DNA methylation (DNAm) and glucose metabolism among a Chinese population, in particular the multisite correlation. Materials & methods: Epigenome-wide associations with fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) were analyzed among 100 Shanghai monozygotic (MZ) twin pairs using the Infinium HumanMethylationEPIC v2.0 BeadChip. We conducted a Pearson's correlation test, hierarchical cluster and pairwise analysis to examine the differential methylation patterns from clusters. Results: Cg01358804 (TXNIP) was identified as the most significant site associated with FPG and HbA1c. Two clusters with hypermethylated and hypomethylated patterns were observed for both FPG and HbA1c. Conclusion: Differential methylation patterns from clusters may provide new clues for epigenetic changes and biological mechanisms in glucose metabolism.
期刊介绍：
Epigenomics provides the forum to address the rapidly progressing research developments in this ever-expanding field; to report on the major challenges ahead and critical advances that are propelling the science forward. The journal delivers this information in concise, at-a-glance article formats – invaluable to a time constrained community.
Substantial developments in our current knowledge and understanding of genomics and epigenetics are constantly being made, yet this field is still in its infancy. Epigenomics provides a critical overview of the latest and most significant advances as they unfold and explores their potential application in the clinical setting.
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