A common epigenetic clock from childhood to old age

Freire-Aradas, Ana; Girón-Santamaría, Lorena; Mosquera-Miguel, Ana; Ambroa-Conde, A.; Phillips, Christopher; Cal, Magdalena; Gómez-Tato, Antonio; Álvarez‐Dios, José Antonio; Pośpiech, Ewelina; Aliferi, Anastasia; Court, Denise Syndercombe; Branicki, Wojciech; Lareu, Marı́a Victoria

doi:10.1016/j.fsigen.2022.102743

Cited by 29 publications

(20 citation statements)

References 46 publications

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“…Furthermore, MPS is already used in most forensic laboratories for DNA profiles with STR markers, but also for biogeographical ancestry information, mitochondrial DNA sequence analysis, and for forensic DNA phenotyping applications [44][45][46]. Regarding the different algorithms that have been formulated, the Machine Learning approach significantly outperforms other approaches [8,24,34,47].…”

Section: Discussionmentioning

confidence: 99%

“…Among them, the most accurate provide prediction errors of 3-4 years, which are in line with those from eyewitness reports. Most of them are based on multiple CpG sites from blood samples for which donors were restricted to adult age ranges, while only a few models covered a full spectrum of human ages from childhood to old age [24,47]. Only few attempts to simplify such epigenetic models have been proposed to date to make them easily applicable in forensic casework [16,53].…”

Section: Discussionmentioning

confidence: 99%

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An ELOVL2-Based Epigenetic Clock for Forensic Age Prediction: A Systematic Review

Paparazzo

Lagani

Geracitano

et al. 2023

IJMS

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The prediction of chronological age from methylation-based biomarkers represents one of the most promising applications in the field of forensic sciences. Age-prediction models developed so far are not easily applicable for forensic caseworkers. Among the several attempts to pursue this objective, the formulation of single-locus models might represent a good strategy. The present work aimed to develop an accurate single-locus model for age prediction exploiting ELOVL2, a gene for which epigenetic alterations are most highly correlated with age. We carried out a systematic review of different published pyrosequencing datasets in which methylation of the ELOVL2 promoter was analysed to formulate age prediction models. Nine of these, with available datasets involving 2298 participants, were selected. We found that irrespective of which model was adopted, a very strong relationship between ELOVL2 methylation levels and age exists. In particular, the model giving the best age-prediction accuracy was the gradient boosting regressor with a prediction error of about 5.5 years. The findings reported here strongly support the use of ELOVL2 for the formulation of a single-locus epigenetic model, but the inclusion of additional, non-redundant markers is a fundamental requirement to apply a molecular model to forensic applications with more robust results.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

An ELOVL2-Based Epigenetic Clock for Forensic Age Prediction: A Systematic Review

Paparazzo

Lagani

Geracitano

et al. 2023

IJMS

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“…The scale of chronological or biological age may match or diverge depending on both the individual’s lifestyle and the presence of disease. While chronological age has been shown to be a valuable tool in forensics, biological age may also be used to track the development of a person suffering from an illness or seeking therapy for a medical condition [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

“…A second generation of epigenetic clocks has been developed that utilizes DNA methylation to forecast biological qualities such as time to death or functional deterioration. These so-called “biological clocks” have been demonstrated to predict better outcomes in specific disease patterns [ 8 , 9 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

Forensic Age Estimation through a DNA Methylation-Based Age Prediction Model in the Italian Population: A Pilot Study

Onofri

Delicati

Marcante

et al. 2023

IJMS

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DNA methylation is one of the epigenetic marks which has been studied intensively in recent years for age predicting purposes in the forensic area. In order to integrate age prediction into routine forensic workflow, the purpose of this study was to standardize and optimize a DNA methylation-based protocol tailored to the Italian context. A previously published protocol and age-predictive method was implemented for the analysis of 84 blood samples originating from Central Italy. The study here presented is based on the Single Base Extension method, considering five genes: ELOVL2, FHL2, KLF14, C1orf132, now identified as MIR29B2C, and TRIM59. The precise and specific steps consist of DNA extraction and quantification, bisulfite conversion, amplification of converted DNA, first purification, single base extension, second purification, capillary electrophoresis, and analysis of the results to train and test the tool. The prediction error obtained, expressed as mean absolute deviation, showed a value of 3.12 years in the training set and 3.01 years in the test set. Given that population-based differences in DNA methylation patterns have been previously reported in the literature, it would be useful to further improve the study implementing additional samples representative of the entire Italian population.

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“…Large efforts toward the simplification of the epigenetic clock models have been carried out in the field of forensics, given the relatively high amount of input DNA necessary for the Illumina Infinium microarray protocol. Targeted predictive models based on quantitative PCR, pyrosequencing or Agena EpiTYPER system have been developed with promising results [ 17 , 18 , 19 , 20 , 21 , 22 , 23 ].…”

Section: Introductionmentioning

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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A common epigenetic clock from childhood to old age

Cited by 29 publications

References 46 publications

An ELOVL2-Based Epigenetic Clock for Forensic Age Prediction: A Systematic Review

An ELOVL2-Based Epigenetic Clock for Forensic Age Prediction: A Systematic Review

Forensic Age Estimation through a DNA Methylation-Based Age Prediction Model in the Italian Population: A Pilot Study

A Targeted Epigenetic Clock for the Prediction of Biological Age

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