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Characterization of age signatures of DNA methylation in normal and cancer tissues from multiple studies.

Authors
Kim, J | Kim, K | Kim, H | Yoon, G  | Lee, K
Citation
BMC genomics, 15. : 997-997, 2014
Journal Title
BMC genomics
ISSN
1471-2164
Abstract
BACKGROUND:



DNA methylation (DNAm) levels can be used to predict the chronological age of tissues; however, the characteristics of DNAm age signatures in normal and cancer tissues are not well studied using multiple studies.



RESULTS:



We studied approximately 4000 normal and cancer samples with multiple tissue types from diverse studies, and using linear and nonlinear regression models identified reliable tissue type-invariant DNAm age signatures. A normal signature comprising 127 CpG loci was highly enriched on the X chromosome. Age-hypermethylated loci were enriched for guanine-and-cytosine-rich regions in CpG islands (CGIs), whereas age-hypomethylated loci were enriched for adenine-and-thymine-rich regions in non-CGIs. However, the cancer signature comprised only 26 age-hypomethylated loci, none on the X chromosome, and with no overlap with the normal signature. Genes related to the normal signature were enriched for aging-related gene ontology terms including metabolic processes, immune system processes, and cell proliferation. The related gene products of the normal signature had more than the average number of interacting partners in a protein interaction network and had a tendency not to interact directly with each other. The genomic sequences of the normal signature were well conserved and the age-associated DNAm levels could satisfactorily predict the chronological ages of tissues regardless of tissue type. Interestingly, the age-associated DNAm increases or decreases of the normal signature were aberrantly accelerated in cancer samples.



CONCLUSION:



These tissue type-invariant DNAm age signatures in normal and cancer can be used to address important questions in developmental biology and cancer research.
MeSH

DOI
10.1186/1471-2164-15-997
PMID
25406591
Appears in Collections:
Journal Papers > School of Medicine / Graduate School of Medicine > Biochemistry & Molecular Biology
Journal Papers > School of Medicine / Graduate School of Medicine > Biomedical Informatics
Ajou Authors
윤, 계순  |  이, 기영
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