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Original Research ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Physiol. | doi: 10.3389/fphys.2019.00917

Integrated analysis of DNA methylation and biochemical/metabolic parameter during the long-term isolation environment

 Yuan Quan1,  Fengji Liang2, Yuexing Zhu3, Ying chen3,  Xu Zi3,  Fang Du3,  Ke Lv2,  Hailong Chen2,  Lina Qu2, Ruifeng Xu4, Hong-Yu Zhang5,  Yinghui Li2* and  Jianghui Xiong2*
  • 1Harbin Institute of Technology, Shenzhen, China
  • 2State Key Laboratory of Space Medicine Fundamentals and Application, China Astronaut Research and Training Center, China
  • 3Space Institute of Southern China, China
  • 4School of Computer Science and Technology, Harbin Institute of Technology, China
  • 5Huazhong Agricultural University, China

Numerous studies have shown that changes in the epigenome are an important cause of human biochemical or metabolic parameter changes. Biochemical/metabolic parameter disorders of the human body are usually closely related to the occurrence of disease. Therefore, constructing credible DNA methylation site-biochemical/metabolic parameter associations are key in interpreting the pathogenesis of diseases. However, there is a lack of research on systematic integration analysis of DNA methylation with biochemical/metabolic parameter and diseases. In this study, we attempted to use the 4-people, multiple time point detected data from the long-term isolation experiment to conduct a correlation analysis. We used the biclustering algorithm FABIA to cluster the DNA methylation site-parameter correlation matrixes into 28 biclusters. The results of the biological function analysis for these biclusters were consistent with the biochemical/metabolic parameter change characteristics of the human body during long-term isolation, demonstrating the reliability of the biclusters identified by our method. In addition, from these biclusters, we obtained highly credible biochemical/metabolic parameter-disease associations, which is supported by several studies. Our results indicate that there is an overlap of biochemical/metabolic parameter-disease associations derived from a small sample, multiple time point data in healthy populations and the associations obtained from a large sample data in patients during disease development. These findings provide insights into understanding the role of the epigenome in biochemical/metabolic parameter change and disease development and has potential applications in biology and medicine research.

Keywords: 多个时间点检测到的数据, 长期隔离环境, DNA甲基化, 化学/代谢参数, 疾病

Received: 01 Feb 2019; Accepted: 04 Jul 2019.

Edited by:

Airong Qian, Northwestern Polytechnical University, China

Reviewed by:

Shu Zhang, Fourth Military Medical University, China
Chen Wang, Mayo Clinic, United States  

Copyright: © 2019 Quan, Liang, Zhu, chen, Zi, Du, Lv, Chen, Qu, Xu, Zhang, Li and Xiong. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Prof. Yinghui Li, State Key Laboratory of Space Medicine Fundamentals and Application, China Astronaut Research and Training Center, Beijing, China,
Prof. Jianghui Xiong, State Key Laboratory of Space Medicine Fundamentals and Application, China Astronaut Research and Training Center, Beijing, China,