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DNA methylation-based age prediction from saliva: High age predictability by combination of 7 CpG markers

Authors
 Sae Rom Hong  ;  Sang-Eun Jung  ;  Eun Hee Lee  ;  Kyoung-Jin Shin  ;  Woo Ick Yang  ;  Hwan Young Lee 
Citation
 FORENSIC SCIENCE INTERNATIONAL-GENETICS, Vol.29 : 118-125, 2017 
Journal Title
 FORENSIC SCIENCE INTERNATIONAL-GENETICS 
ISSN
 1872-4973 
Issue Date
2017
MeSH
Adolescent ; Adult ; Aged ; Aging/genetics* ; CpG Islands/genetics* ; DNA Methylation* ; Forensic Genetics ; Genetic Markers ; Humans ; Linear Models ; Middle Aged ; Nucleic Acid Hybridization ; Saliva/chemistry* ; Young Adult
Keywords
Age ; DNA methylation ; HumanMethylation450 BeadChip ; SNaPshot ; Saliva
Abstract
DNA methylation is currently one of the most promising age-predictive biomarkers. Many studies have reported DNA methylation-based age predictive models, but most of these are based on DNA methylation patterns from blood. Only a few studies have examined age-predictive DNA patterns in saliva, which is one of the most frequently-encountered body fluids at crime scenes. In this study, we generated genome-wide DNA methylation profiles of saliva from 54 individuals and identified CpG markers that showed a high correlation between methylation and age. Because the age-associated marker candidates from saliva differed from those of blood, we investigated DNA methylation patterns of 6 age-associated CpG marker candidates (cg00481951, cg19671120, cg14361627, cg08928145, cg12757011, and cg07547549 of the SST, CNGA3, KLF14, TSSK6, TBR1, and SLC12A5 genes, respectively) in addition to a cell type-specific CpG marker (cg18384097 of the PTPN7 gene) in an independent set of saliva samples obtained from 226 individuals aged 18 to 65 years. Multiplex methylation SNaPshot reactions were used to generate the data. We then generated a linear regression model with age information and the methylation profile from the 113 training samples. The model exhibited a 94.5% correlation between predicted and chronological age with a mean absolute deviation (MAD) from chronological age of 3.13 years. In subsequent validation using 113 test samples, we also observed a high correlation between predicted and chronological age (Spearman's rho=0.952, MAD from chronological age=3.15years). The model composed of 7 selected CpG sites enabled age prediction in saliva with high accuracy, which will be useful in saliva analysis for investigative leads.
Full Text
https://www.sciencedirect.com/science/article/pii/S187249731730090X
DOI
10.1016/j.fsigen.2017.04.006
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Forensic Medicine (법의학과) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Pathology (병리학교실) > 1. Journal Papers
Yonsei Authors
Shin, Kyoung Jin(신경진) ORCID logo https://orcid.org/0000-0002-1059-9665
Yang, Woo Ick(양우익) ORCID logo https://orcid.org/0000-0002-6084-5019
Lee, Eun Hee(이은희)
Lee, Hwan Young(이환영)
Jung, Sang Eun(정상은)
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/160224
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