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

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.

Tweetable abstract

Hypomethylated cg01358804 (TXNIP) may be a novel marker related to FPG and HbA1c in a Chinese population. Differential methylation patterns from clusters contribute to regulation of glucose metabolism.

Keywords: :

• diabetes
• DNA methylation
• epigenomics
• glucose metabolism
• twin study

Supplementary data

To view the supplementary data that accompany this paper please visit the journal website at: wwww.tandfonline.com/doi/suppl/10.2217/epi-2023-0449

Author contributions

F Wu conceived of the project and designed the study. J Feng, Z Zhu, R Zhou, H Liu, Z Hu, F Wu, H Wang and J Yue collected the data. T Zhou and L Yang contributed to the genetic detection. J Feng and Z Hu analyzed the data and interpreted results. J Feng, Z Zhu and R Zhou drafted and edited manuscript. All authors read and approved the final manuscript.

Acknowledgments

The authors would like to acknowledge the participants and investigators in this study.

Financial disclosure

This work was supported by the National Key R&D Program of China (2022YFC3600801) and the construction plan of Shanghai high-level local colleges and universities (DGF201006-1/007). This work was also supported by the Medical Science Data Center in Shanghai Medical College of Fudan University. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Competing interests disclosure

The authors have no competing interests or relevant affiliations with any organization or entity with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Writing disclosure

No writing assistance was utilized in the production of this manuscript.

Ethical conduct of research

This study was approved by the ethics committee of Fudan University (approval number: IRB#2022-01-0939-S2), and this protocol is accordance with the Declaration of Helsinki and relevant laws and regulations in China. Informed consent was obtained from all twins included in the study.

Data sharing statement

Datasets generated and/or analyzed in the current study are available from the corresponding author on reasonable request.