A Blood–Bone–Tooth Model for Age Prediction in Forensic Contexts

Dias, Helena Correia; Manco, Licínio; Real, Francisco Corte; Cunha, Eugénia

doi:10.3390/biology10121312

Cited by 12 publications

(10 citation statements)

References 39 publications

(86 reference statements)

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“…In 2012, we reported the strong correlation between DNAm of cg16867657 within ELOVL2 and chronological age in whole blood [ 35 ], and since then this region has been confirmed as robustly associated with aging in several tissues [ 36 , 37 ]. The assessment of ELOVL2 DNAm is largely employed in targeted epigenetic biomarkers developed for forensic applications [ 38 , 39 , 40 , 41 ]. Although we previously reported that hypermethylation of this genomic region in blood is associated with the prospective development of breast cancer [ 42 ], ELOVL2 DNAm seems to depend mainly on chronological age, and Spólnicka et al reported that no changes in ELOVL2 DNAm occur in Alzheimer’s and Graves’ diseases [ 20 ].…”

Section: Resultsmentioning

confidence: 99%

A Targeted Epigenetic Clock for the Prediction of Biological Age

Gensous¹,

Sala

Pirazzini

et al. 2022

Cells

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Epigenetic clocks were initially developed to track chronological age, but accumulating evidence indicates that they can also predict biological age. They are usually based on the analysis of DNA methylation by genome-wide methods, but targeted approaches, based on the assessment of a small number of CpG sites, are advisable in several settings. In this study, we developed a targeted epigenetic clock purposely optimized for the measurement of biological age. The clock includes six genomic regions mapping in ELOVL2, NHLRC1, AIM2, EDARADD, SIRT7 and TFAP2E genes, selected from a re-analysis of existing microarray data, whose DNA methylation is measured by EpiTYPER assay. In healthy subjects (n = 278), epigenetic age calculated using the targeted clock was highly correlated with chronological age (Spearman correlation = 0.89). Most importantly, and in agreement with previous results from genome-wide clocks, epigenetic age was significantly higher and lower than expected in models of increased (persons with Down syndrome, n = 62) and decreased (centenarians, n = 106; centenarians’ offspring, n = 143; nutritional intervention in elderly, n = 233) biological age, respectively. These results support the potential of our targeted epigenetic clock as a new marker of biological age and open its evaluation in large cohorts to further promote the assessment of biological age in healthcare practice.

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Section: Resultsmentioning

confidence: 99%

A Targeted Epigenetic Clock for the Prediction of Biological Age

Gensous¹,

Sala

Pirazzini

et al. 2022

Cells

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“…An age prediction accuracy rate of 80% was established when we applied a ± 1 SEE value as the prediction interval. Comparable studies generally report MAE values ranging from 3 to 6.5 years [13, 47–49]. For instance, Onofri et al.…”

Section: Discussionmentioning

confidence: 99%

Epigenetic‐based age prediction in blood samples: Model development

Filoglu,

Sımsek,

Ersoy

et al. 2024

Journal of Forensic Sciences

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Aging is a complex process influenced by genetic, epigenetic, and environmental factors that lead to tissue deterioration and frailty. Epigenetic mechanisms, such as DNA methylation, play a significant role in gene expression regulation and aging. This study presents a new age estimation model developed for the Turkish population using blood samples. Eight CpG sites in loci TOM1L1, ELOVL2, ASPA, FHL2, C1orf132, CCDC102B, cg07082267, and RASSF5 were selected based on their correlation with age. Methylation patterns of these sites were analyzed in blood samples from 100 volunteers, grouped into age categories (20–35, 36–55, and ≥56). Sensitivity analysis indicated a reliable performance with DNA inputs ≥1 ng. Statistical modeling, utilizing Multiple Linear Regression, underscores the reliability of the primary 6‐CpG model, excluding cg07082267 and TOM1L1. This model demonstrates strong correlations with chronological age (r = 0.941) and explains 88% of the age variance with low error rates (MAE = 4.07, RMSE = 5.73 years). Validation procedures, including a training‐test split and fivefold cross‐validation, consistently confirm the model's accuracy and consistency. The study indicates minimal variation in error scores across age cohorts and no significant gender differences. The developed model showed strong predictive accuracy, with the ability to estimate age within certain prediction intervals. This study contributes to the age prediction by using DNA methylation patterns, which can have disparate applications, including forensic and clinical assessments.

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“…Jung et al showed that the prediction formulas differ slightly for blood, saliva, and buccal swabs, and presented a suitable formula for tissue samples tested [10]. Dias et al also reported a universal prediction formula using blood, bone, and tooth samples [24]. However, age prediction formulas using different amounts of DNA have not been reported, and the accuracy of using small amounts of DNA has not been clarified.…”

Section: Discussionmentioning

confidence: 99%

Age prediction by methylation analysis of small amounts of DNA using locked nucleic acids

Takahashi

Asari

Isozaki

et al. 2022

Journal of Forensic Sciences

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Age prediction based on methylation analysis has been reported in many populations, with 10 ng or more of DNA usually required for each determination. In this study, we designed thermostable locked nucleic acid (LNA) primers by replacing a small number of DNA bases in standard DNA primers with LNAs. We evaluated these primer sets by single-base extension analysis using 10, 5, or 2 ng of DNA that would be less than template DNA used in standard methylation testing, and determined sensitivity and accuracy. We analyzed EDARADD, SST, and KLF14 genes, targeting one CpG site in each gene. Melting temperature values of most LNA primers were 4°C higher than those of DNA primers. The intensities of signals from the EDARADD and SST genes were significantly improved by the LNA primers, by 3.3 times and 1.4 times, respectively, compared with the DNA primers using 2 ng of DNA. Coefficient of variation (CV) analysis was used to assess the accuracy of the determined methylation levels.CVs were increased using small amounts of DNA, but lower CVs were detected using LNA primers. We also showed high accuracy of age prediction for 51 individuals using LNA primers. The lowest mean absolute deviation was obtained using 10 ng of DNA and was 3.88 years with the LNA primers. Thermostable PCR primers were simply designed, and the LNAs improved the sensitivity and accuracy of methylation analysis for 10 ng or less of DNA.

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A Blood–Bone–Tooth Model for Age Prediction in Forensic Contexts

Cited by 12 publications

References 39 publications

A Targeted Epigenetic Clock for the Prediction of Biological Age

A Targeted Epigenetic Clock for the Prediction of Biological Age

Epigenetic‐based age prediction in blood samples: Model development

Age prediction by methylation analysis of small amounts of DNA using locked nucleic acids

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