TY - JOUR
T1 - DNA methylation-based age prediction from saliva
T2 - High age predictability by combination of 7 CpG markers
AU - Hong, Sae Rom
AU - Jung, Sang Eun
AU - Lee, Eun Hee
AU - Shin, Kyoung Jin
AU - Yang, Woo Ick
AU - Lee, Hwan Young
N1 - Publisher Copyright:
© 2017 Elsevier B.V.
PY - 2017/7/1
Y1 - 2017/7/1
N2 - 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 = 3.15 years). 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.
AB - 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 = 3.15 years). 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.
KW - Age
KW - DNA methylation
KW - HumanMethylation450 BeadChip
KW - SNaPshot
KW - Saliva
UR - http://www.scopus.com/inward/record.url?scp=85017426849&partnerID=8YFLogxK
U2 - 10.1016/j.fsigen.2017.04.006
DO - 10.1016/j.fsigen.2017.04.006
M3 - Article
C2 - 28419903
AN - SCOPUS:85017426849
VL - 29
SP - 118
EP - 125
JO - Forensic Science International: Genetics
JF - Forensic Science International: Genetics
SN - 1872-4973
ER -