Literature DB >> 35819508

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

Xueli Han1, Chao Xiao1, Shaohua Yi1, Ya Li1, Maomin Chen1, Daixin Huang2.   

Abstract

Age-related CpG sites (AR-CpGs) are currently the most promising biomarkers for forensic age estimation. In our previous studies, we first validated the age correlation of seven reported AR-CpGs in blood samples of Chinese Han population. Subsequently, we screened some good age predictors from blood samples of Chinese Han population, and built pyrosequencing-based age prediction models. However, it is still important to select a set of high-performance AR-CpGs in a specific racial group and establish a simple and efficient method for accurate age estimation for forensic purpose. In this study, eight AR-CpGs, namely chr6: 11,044,628 (ELOVL2), cg06639320 (FHL2), chr1: 207,823,723 (C1orf132), cg19283806 (CCDC102B), cg14361627 (KLF14), cg17740900 (SYNE2), cg07553761 (TRIM59), and cg26947034, were selected based on our previous studies, and a multiplex methylation SNaPshot assay was developed to investigate DNA methylation levels at these AR-CpGs in 529 blood samples (aged 2-82 years) from Han Chinese population. All selected CpG sites showed strong age correlation with the correlation coefficient (r) from 0.8363 to 0.9251. Multiple linear regression (MLR) and support vector regression (SVR) age prediction models were simultaneously established to fit change characteristics of DNA methylation levels of eight AR-CpGs with the age in 374 donors' blood samples. The MLR model enabled age prediction with R2 = 0.923, mean absolute error (MAE) = 3.52, while the SVR model enabled age prediction with R2 = 0.935, MAE = 2.88. One hundred fifty-five independent samples were used as a validation set to test the two models' performance, and the prediction MAE for the validation set was 3.71 and 3.34 for the MLR and SVR models, respectively. For the MLR and SVR models, the correct prediction rate at ± 5 years reached a high level of 79.35% and 83.23%, respectively. In general, these statistical parameters indicated that the SVR model outperformed the MLR model in age prediction of the Han Chinese population. In addition, our method provides sufficient sensitivity in forensic applications and allows for 100% efficiency when examining bloodstains kept in room conditions for up to 43 days. These results indicate that our multiplex methylation SNaPshot assay is a reliable, effective, and accurate method for age prediction in blood samples from the Chinese Han population.
© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Entities:  

Keywords:  Age prediction; Blood samples; DNA methylation; Forensic science; Methylation SNaPshot

Mesh:

Substances:

Year:  2022        PMID: 35819508     DOI: 10.1007/s00414-022-02865-3

Source DB:  PubMed          Journal:  Int J Legal Med        ISSN: 0937-9827            Impact factor:   2.791


  34 in total

Review 1.  The role of AGEs in aging: causation or correlation.

Authors:  J W Baynes
Journal:  Exp Gerontol       Date:  2001-09       Impact factor: 4.032

Review 2.  Molecular pathology and age estimation.

Authors:  Christoph Meissner; Stefanie Ritz-Timme
Journal:  Forensic Sci Int       Date:  2010-08-10       Impact factor: 2.395

3.  Ascertaining year of birth/age at death in forensic cases: A review of conventional methods and methods allowing for absolute chronology.

Authors:  Niels Lynnerup; Henrik Kjeldsen; Ralf Zweihoff; Steffen Heegaard; Christina Jacobsen; Jan Heinemeier
Journal:  Forensic Sci Int       Date:  2010-04-15       Impact factor: 2.395

4.  Estimating human age from T-cell DNA rearrangements.

Authors:  D Zubakov; F Liu; M C van Zelm; J Vermeulen; B A Oostra; C M van Duijn; G J Driessen; J J M van Dongen; M Kayser; A W Langerak
Journal:  Curr Biol       Date:  2010-11-23       Impact factor: 10.834

5.  Detection and quantification of the age-related sjTREC decline in human peripheral blood.

Authors:  Xueling Ou; Hu Zhao; Hongyu Sun; Zhengfei Yang; Bailu Xie; Yanwei Shi; Xinyao Wu
Journal:  Int J Legal Med       Date:  2010-11-25       Impact factor: 2.686

6.  Meta-analysis of age-related gene expression profiles identifies common signatures of aging.

Authors:  João Pedro de Magalhães; João Curado; George M Church
Journal:  Bioinformatics       Date:  2009-02-02       Impact factor: 6.937

Review 7.  Telomeres and human disease: ageing, cancer and beyond.

Authors:  Maria A Blasco
Journal:  Nat Rev Genet       Date:  2005-08       Impact factor: 53.242

8.  Age-associated oxygen damage and mutations in mitochondrial DNA in human hearts.

Authors:  M Hayakawa; K Hattori; S Sugiyama; T Ozawa
Journal:  Biochem Biophys Res Commun       Date:  1992-12-15       Impact factor: 3.575

9.  A pattern of accumulation of a somatic deletion of mitochondrial DNA in aging human tissues.

Authors:  G A Cortopassi; D Shibata; N W Soong; N Arnheim
Journal:  Proc Natl Acad Sci U S A       Date:  1992-08-15       Impact factor: 11.205

10.  DNA methylation age of human tissues and cell types.

Authors:  Steve Horvath
Journal:  Genome Biol       Date:  2013       Impact factor: 13.583

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.