Independent validation of DNA-based approaches for age prediction in blood

Cho, Sohee; Jung, Seong‐Ook; Hong, Sae Rom; Lee, Eun Hee; Lee, Ji Hyun; Lee, Soong Deok; Lee, Hwan Young

doi:10.1016/j.fsigen.2017.04.020

Cited by 91 publications

(119 citation statements)

References 29 publications

Supporting

Mentioning

105

Contrasting

Unclassified

Order By: Relevance

“…The cross‐validation of the training set leads to a MAD of 7.22 years and evaluation of model performance using an independent test set of 19 individuals showed a MAD of 8.84 years. Previous forensic studies, most of them with blood samples of living individuals, using different loci and different number of markers, covering different age ranges and using different methodologies, gave values of MAD between 3.5 to 7.5 years . Thus, in our study the obtained MAD value, although less accurate, is in the range of other research approaches.…”

Section: Discussionmentioning

confidence: 46%

“…Zbi ec-Piekarska et al (6) published an assay which included in the overall model 5 CpG sites in the ELOVL2, FHL2, KLF14, C1orf132/MIR29B2C, and TRIM59 genes, resulting in a mean absolute deviation from the chronological age (MAD) of 3.9 years. Cho et al (9) replicated the strong age association for DNA methylation markers in the ELOVL2, C1orf132, TRIM59, KLF14, and FHL2 genes in blood samples of 100 Korean individuals.…”

mentioning

confidence: 87%

“…Cho et al. replicated the strong age association for DNA methylation markers in the ELOVL2, C1orf132, TRIM59, KLF14 , and FHL2 genes in blood samples of 100 Korean individuals.…”

mentioning

confidence: 89%

“…Several DNA methylation markers have been investigated in various tissues and body fluids using DNA-based methodologies such as bisulfite pyrosequencing (3)(4)(5)(6)(7)(8)(9), EpiTYPER technology (10), massively parallel sequencing (11)(12)(13), or SNaPshot assays (14)(15)(16).This allowed the identification of many CpG markers showing high correlations with chronological age, potentially useful as forensic age predictors. Thus, a number of high accurate age prediction models have been proposed for specific tissues, including blood (6,7,12), teeth (17), buccal swabs (8) or saliva (15), or as multi-tissue models (13,16,18,19).…”

mentioning

confidence: 99%

See 3 more Smart Citations

Age Estimation Based on DNA Methylation Using Blood Samples From Deceased Individuals

Dias

Cordeiro

Real

et al. 2019

Journal of Forensic Sciences

View full text Add to dashboard Cite

Age estimation using DNA methylation levels has been widely investigated in recent years because of its potential application in forensic genetics. The main aim of this study was to develop an age predictor model (APM) for blood samples of deceased individuals based in five age‐correlated genes. Fifty‐one samples were analyzed through the bisulfite polymerase chain reaction (PCR) sequencing method for DNA methylation evaluation in genes ELOVL2, FHL2, EDARADD, PDE4C, and C1orf132. Linear regression was used to analyze relationships between methylation levels and age. The model using the highest age‐correlated CpG from each locus revealed a correlation coefficient of 0.888, explaining 76.3% of age variation, with a mean absolute deviation from the chronological age (MAD) of 6.08 years. The model was validated in an independent test set of 19 samples producing a MAD of 8.84 years. The developed APM seems to be informative and could have potential application in forensic analysis.

show abstract

Section: Discussionmentioning

confidence: 46%

mentioning

confidence: 87%

“…Cho et al. replicated the strong age association for DNA methylation markers in the ELOVL2, C1orf132, TRIM59, KLF14 , and FHL2 genes in blood samples of 100 Korean individuals.…”

mentioning

confidence: 89%

mentioning

confidence: 99%

See 2 more Smart Citations

Age Estimation Based on DNA Methylation Using Blood Samples From Deceased Individuals

Dias

Cordeiro

Real

et al. 2019

Journal of Forensic Sciences

View full text Add to dashboard Cite

show abstract

“…The variability of methylation-based age estimation needs to be investigated on geographically broad and representative datasets in order to define the characteristics and limitations of such tests, as different populations have different health conditions, lifestyles and exposure to climatic and environmental factors that may affect the estimates. Studies have started to appear that analyse suggested marker sets and models developed in other populations, e.g., Cho et al [40] have investigated CpG markers, proposed and originally tested in a Polish population sample [26], in a dataset of Koreans. The authors of this study report relatively consistent age prediction results of the earlier developed models, but some markers required adjustment with the new data.…”

Section: Forensic Relevance and Outlookmentioning

confidence: 99%

Age Estimation with DNA: From Forensic DNA Fingerprinting to Forensic (Epi)Genomics: A Mini-Review

Parson

2018

Gerontology

View full text Add to dashboard Cite

Forensic genetics developed from protein-based techniques a quarter of a century ago and became famous as “DNA fingerprinting,” this being based on restriction fragment length polymorphisms (RFLPs) of high-molecular-weight DNA. The amplification of much smaller short tandem repeat (STR) sequences using the polymerase chain reaction soon replaced RFLP analysis and advanced to become the gold standard in genetic identification. Meanwhile, STR multiplexes have been developed and made commercially available which simultaneously amplify up to 30 STR loci from as little as 15 cells or fewer. The enormous information content that comes with the large variety of observed STR genotypes allows for genetic individualisation (with the exception of identical twins). Carefully selected core STR loci form the basis of intelligence-led DNA databases that provide investigative leads by linking unsolved crime scenes and criminals through their matched STR profiles. Nevertheless, the success of modern DNA fingerprinting depends on the availability of reference material from suspects. In order to provide new investigative leads in cases where such reference samples are absent, forensic scientists started to explore the prediction of phenotypic traits from the DNA of the evidentiary sample. This paradigm change now uses DNA and epigenetic markers to forecast characteristics that are useful to triage further investigative work. So far, the best investigated externally visible characteristics are eye, hair and skin colour, as well as geographic ancestry and age. Information on the chronological age of a stain donor (or any sample donor) is elemental for forensic investigations in a number of aspects and has, therefore, been explored by researchers in some detail. Among different methodological approaches tested to date, the methylation-sensitive analysis of carefully selected DNA markers (CpG sites) has brought the most promising results by providing prediction accuracies of ±3–4 years, which can be comparable to, or even surpass those from, eyewitness reports. This mini-review puts recent developments in age estimation via (epi)genetic methods in the context of the requirements and goals of forensic genetics and highlights paths to follow in the future of forensic genomics.

show abstract

Forensic DNA Analysis

Prinz¹,

Lessig²

2022

Handbook of Forensic Medicine

View full text Add to dashboard Cite

Independent validation of DNA-based approaches for age prediction in blood

Cited by 91 publications

References 29 publications

Age Estimation Based on DNA Methylation Using Blood Samples From Deceased Individuals

Age Estimation Based on DNA Methylation Using Blood Samples From Deceased Individuals

Age Estimation with DNA: From Forensic DNA Fingerprinting to Forensic (Epi)Genomics: A Mini-Review

Forensic DNA Analysis

Contact Info

Product

Resources

About