pubmed.ncbi.nlm.nih.gov

Epigenetics Analysis and Integrated Analysis of Multiomics Data, Including Epigenetic Data, Using Artificial Intelligence in the Era of Precision Medicine - PubMed

  • ️Tue Jan 01 2019

Review

Epigenetics Analysis and Integrated Analysis of Multiomics Data, Including Epigenetic Data, Using Artificial Intelligence in the Era of Precision Medicine

Ryuji Hamamoto et al. Biomolecules. 2019.

Abstract

To clarify the mechanisms of diseases, such as cancer, studies analyzing genetic mutations have been actively conducted for a long time, and a large number of achievements have already been reported. Indeed, genomic medicine is considered the core discipline of precision medicine, and currently, the clinical application of cutting-edge genomic medicine aimed at improving the prevention, diagnosis and treatment of a wide range of diseases is promoted. However, although the Human Genome Project was completed in 2003 and large-scale genetic analyses have since been accomplished worldwide with the development of next-generation sequencing (NGS), explaining the mechanism of disease onset only using genetic variation has been recognized as difficult. Meanwhile, the importance of epigenetics, which describes inheritance by mechanisms other than the genomic DNA sequence, has recently attracted attention, and, in particular, many studies have reported the involvement of epigenetic deregulation in human cancer. So far, given that genetic and epigenetic studies tend to be accomplished independently, physiological relationships between genetics and epigenetics in diseases remain almost unknown. Since this situation may be a disadvantage to developing precision medicine, the integrated understanding of genetic variation and epigenetic deregulation appears to be now critical. Importantly, the current progress of artificial intelligence (AI) technologies, such as machine learning and deep learning, is remarkable and enables multimodal analyses of big omics data. In this regard, it is important to develop a platform that can conduct multimodal analysis of medical big data using AI as this may accelerate the realization of precision medicine. In this review, we discuss the importance of genome-wide epigenetic and multiomics analyses using AI in the era of precision medicine.

Keywords: DNA methylation; deep learning; epigenetics; histone modifications; machine learning; precision medicine.

PubMed Disclaimer

Conflict of interest statement

The authors declare that they have no conflicts of interest.

Figures

Figure 1
Figure 1

The summarized figure of epigenetic regulations and technologies for epigenetics analysis. Image credit: Shutterstock.com/ellepigrafica.

Figure 2
Figure 2

The summarized figure of artificial intelligence development.

Figure 3
Figure 3

Advantages of machine learning and deep learning technologies in medical research. (A) An example of multimodal learning analysis using multiomics data including epigenetic data. (B) An example of multitask learning analysis using gene mutation data, DNA methylation data and gene expression data. This is a modified figure from reference [113]. (C) An example of semi-supervised learning using epigenetic data. This is a modified figure from reference [114].

Similar articles

Cited by

References

    1. Hoosain N., Pearce B., Jacobs C., Benjeddou M. Mapping SLCO1B1 Genetic Variation for Global Precision Medicine in Understudied Regions in Africa: A Focus on Zulu and Cape Admixed Populations. OMICS. 2016;20:546–554. doi: 10.1089/omi.2016.0115. - DOI - PubMed
    1. Goyal M.R. Scientific and Technical Terms in Bioengineering and Biological Engineering. Apple Academic Press; Cambridge, MA, USA: 2018.
    1. Kasztura M., Richard A., Bempong N.E., Loncar D., Flahault A. Cost-effectiveness of precision medicine: A scoping review. Int. J. Public Health. 2019 doi: 10.1007/s00038-019-01298-x. - DOI - PMC - PubMed
    1. Zhang X., Yang H., Zhang R. Challenges and future of precision medicine strategies for breast cancer based on a database on drug reactions. Biosci. Rep. 2019;39 doi: 10.1042/BSR20190230. - DOI - PMC - PubMed
    1. Prasad V. Perspective: The precision-oncology illusion. Nature. 2016;537:S63. doi: 10.1038/537S63a. - DOI - PubMed

Publication types

MeSH terms

Substances

LinkOut - more resources