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Differential methylation patterns from clusters associated with glucose metabolism: evidence from a Shanghai twin study.

Jingyuan FengZhenni ZhuRongfei ZhouHongwei LiuZihan HuFei WuHuiting WangJunhong YueTong ZhouLi YangFan Wu
Published in: Epigenomics (2024)
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.
Keyphrases
  • dna methylation
  • genome wide
  • gene expression
  • copy number
  • type diabetes
  • blood pressure
  • adipose tissue
  • metabolic syndrome
  • skeletal muscle
  • nlrp inflammasome