Literature DB >> 30300865

DNA methylation of the ELOVL2, FHL2, KLF14, C1orf132/MIR29B2C, and TRIM59 genes for age prediction from blood, saliva, and buccal swab samples.

Sang-Eun Jung1, Seung Min Lim2, Sae Rom Hong2, Eun Hee Lee1, Kyoung-Jin Shin2, Hwan Young Lee3.   

Abstract

Many studies have reported age-associated DNA methylation changes and age-predictive models in various tissues and body fluids. Although age-associated DNA methylation changes can be tissue-specific, a multi-tissue age predictor that is applicable to various tissues and body fluids with considerable prediction accuracy might be valuable. In this study, DNA methylation at 5 CpG sites from the ELOVL2, FHL2, KLF14, C1orf132/MIR29B2C, and TRIM59 genes were investigated in 448 samples from blood, saliva, and buccal swabs. A multiplex methylation SNaPshot assay was developed to measure DNA methylation simultaneously at the 5 CpG sites. Among the 5 CpG sites, 3 CpG sites in the ELOVL2, KLF14 and TRIM59 genes demonstrated strong correlation between DNA methylation and age in all 3 sample types. Age prediction models built separately for each sample type using the DNA methylation values at the 5 CpG sites showed high prediction accuracy with a Mean Absolute Deviation from the chronological age (MAD) of 3.478 years in blood, 3.552 years in saliva and 4.293 years in buccal swab samples. A tissue-combined model constructed with 300 training samples including 100 samples from each blood, saliva and buccal swab samples demonstrated a very strong correlation between predicted and chronological ages (r = 0.937) and a high prediction accuracy with a MAD of 3.844 years in the 148 independent test set samples of 50 blood, 50 saliva and 48 buccal swab samples. Although more validation might be needed, the tissue-combined model's prediction accuracies in each sample type were very much similar to those obtained from each tissue-specific model. The multiplex methylation SNaPshot assay and the age prediction models in our study would be useful in forensic analysis, which frequently involves DNA from blood, saliva, and buccal swab samples.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Age; Blood; Buccal swab; DNA methylation; Methylation SNaPshot; Saliva

Mesh:

Substances:

Year:  2018        PMID: 30300865     DOI: 10.1016/j.fsigen.2018.09.010

Source DB:  PubMed          Journal:  Forensic Sci Int Genet        ISSN: 1872-4973            Impact factor:   4.882


  22 in total

1.  Age estimation based on different molecular clocks in several tissues and a multivariate approach: an explorative study.

Authors:  Julia Becker; Nina Sophia Mahlke; A Reckert; S B Eickhoff; S Ritz-Timme
Journal:  Int J Legal Med       Date:  2019-04-11       Impact factor: 2.686

Review 2.  Patterns of DNA methylation as an indicator of biological aging: State of the science and future directions in precision health promotion.

Authors:  Shannon L Gillespie; Lynda R Hardy; Cindy M Anderson
Journal:  Nurs Outlook       Date:  2019-05-17       Impact factor: 3.250

3.  Predicting Chronological Age from DNA Methylation Data: A Machine Learning Approach for Small Datasets and Limited Predictors.

Authors:  Anastasia Aliferi; David Ballard
Journal:  Methods Mol Biol       Date:  2022

4.  Accurate age estimation from blood samples of Han Chinese individuals using eight high-performance age-related CpG sites.

Authors:  Xueli Han; Chao Xiao; Shaohua Yi; Ya Li; Maomin Chen; Daixin Huang
Journal:  Int J Legal Med       Date:  2022-07-11       Impact factor: 2.791

5.  The biological age of the heart is consistently younger than chronological age.

Authors:  Sofia Pavanello; Manuela Campisi; Assunta Fabozzo; Giorgia Cibin; Vincenzo Tarzia; Giuseppe Toscano; Gino Gerosa
Journal:  Sci Rep       Date:  2020-07-01       Impact factor: 4.379

Review 6.  Novel Cellular Functions of Very Long Chain-Fatty Acids: Insight From ELOVL4 Mutations.

Authors:  Ferenc Deák; Robert E Anderson; Jennifer L Fessler; David M Sherry
Journal:  Front Cell Neurosci       Date:  2019-09-20       Impact factor: 5.505

7.  Postmortem age estimation via DNA methylation analysis in buccal swabs from corpses in different stages of decomposition-a "proof of principle" study.

Authors:  Barbara Elisabeth Koop; Felix Mayer; Tanju Gündüz; Jacqueline Blum; Julia Becker; Judith Schaffrath; Wolfgang Wagner; Yang Han; Petra Boehme; Stefanie Ritz-Timme
Journal:  Int J Legal Med       Date:  2020-07-07       Impact factor: 2.686

8.  Identifying Methylation Patterns in Dental Pulp Aging: Application to Age-at-Death Estimation in Forensic Anthropology.

Authors:  Sara C Zapico; Quentin Gauthier; Aleksandra Antevska; Bruce R McCord
Journal:  Int J Mol Sci       Date:  2021-04-02       Impact factor: 5.923

9.  Impact of a diet and activity health promotion intervention on regional patterns of DNA methylation.

Authors:  Elizabeth Hibler; Lei Huang; Jorge Andrade; Bonnie Spring
Journal:  Clin Epigenetics       Date:  2019-09-11       Impact factor: 6.551

10.  An epigenome-wide association study of sex-specific chronological ageing.

Authors:  Daniel L McCartney; Futao Zhang; Robert F Hillary; Qian Zhang; Anna J Stevenson; Rosie M Walker; Mairead L Bermingham; Thibaud Boutin; Stewart W Morris; Archie Campbell; Alison D Murray; Heather C Whalley; David J Porteous; Caroline Hayward; Kathryn L Evans; Tamir Chandra; Ian J Deary; Andrew M McIntosh; Jian Yang; Peter M Visscher; Allan F McRae; Riccardo E Marioni
Journal:  Genome Med       Date:  2019-12-31       Impact factor: 11.117

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.