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Age estimation can be useful information for narrowing down candidates of unidentified donors in criminal investigations. Various age estimation models based on DNA methylation biomarkers have been developed for forensic usage in the past decade. However, many of these models using ordinary least squares regression cannot generate an appropriate estimation due to the deterioration in prediction accuracy caused by an increased prediction error in older age groups. In the present study, to address this problem, we developed age estimation models that set an appropriate prediction interval for all age groups by two approaches: a statistical method using quantile regression (QR) and a machine learning method using an artificial neural network (ANN). Methylation datasets (n = 1280, age 0-91 years) of the promoter for the gene encoding ELOVL fatty acid elongase 2 were used to develop the QR and ANN models. By validation using several test datasets, both models were shown to enlarge prediction intervals in accordance with aging and have a high level of correct prediction (>90 %) for older age groups. The QR and ANN models also generated a point age prediction with high accuracy. The ANN model enabled a prediction with a mean absolute error (MAE) of 5.3 years and root mean square error (RMSE) of 7.3 years for the test dataset (n = 549), which were comparable to those of the QR model (MAE = 5.6 years, RMSE = 7.8 years). Their applicability to casework was also confirmed using bloodstain samples stored for various periods of time (1-14 years), indicating the stability of the models for aged bloodstain samples. From these results, it was considered that the proposed models can provide more useful and effective age estimation in forensic settings., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

In the last decade, extensive efforts have been made to identify biomarkers of biological age. DNA methylation levels of ELOVL fatty acid elongase 2 (ELOVL2) and the signal joint T-cell receptor rearrangement excision circles (sjTRECs) represent the most promising candidates. Although these two non-redundant biomarkers echo important biological aspects of the ageing process in humans, a well-validated molecular clock exploiting these powerful candidates has not yet been formulated. The present study aimed to develop a more accurate molecular clock in a sample of 194 Italian individuals by re-analyzing the previously obtained EVOLV2 methylation data together with the amount of sjTRECs in the same blood samples. The proposed model showed a high prediction accuracy both in younger individuals with an error of about 2.5 years and in older subjects where a relatively low error was observed if compared with those reported in previously published studies. In conclusion, an easy, cost-effective and reliable model to measure the individual rate and the quality of aging in human population has been proposed. Further studies are required to validate the model and to extend its use in an applicative context.

DNA methylation (DNAm) evaluation has been investigated in various tissues and body fluids allowing the identification of many CpG markers with high correlations with chronological age, potentially useful for forensic analysis. We developed a duplex droplet digital PCR (ddPCR) assay to address methylation levels of ELOVL2 gene CpG sites. DNA samples obtained from peripheral blood of 56 healthy individuals (35 women, 21 men; aged 1-94 years old) were submitted to bisulfite conversion, followed by ddPCR analysis for a selected region of ELOVL2 and the reference gene C-LESSC1. Simple linear regression revealed a strong correlation between DNAm simultaneous captured from five CpG sites of ELOVL2 gene and chronological age (R = 0.892; P = 2.84 × 10 -20 ), explaining 79.2% of age variation. The obtained mean absolute deviation (MAD) between predicted and chronological ages was 10.07 years. Here we describe a ddPCR-based assay to assess DNAm in ELOVL2 gene as a biomarker for potential use in forensic age prediction., Competing Interests: Declarations of Competing interest The authors declare that they have no conflict of interest., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Age-at-death estimation constitutes one of the key parameters for identification of human remains in forensic investigations. However, for applications in forensic anthropology, many current methods are not sufficiently accurate for adult individuals, leading to chronological age estimates erring by ±10 years. Based on recent trends in aging studies, DNA methylation has great potential as a solution to this problem. However, there are only a few studies that have been published utilizing DNA methylation to determine age from human remains. The aim of the present study was to expand the range of this work by analyzing DNA methylation in dental pulp from adult individuals. Healthy erupted third molars were extracted from individuals aged 22-70. DNA from pulp was isolated and bisulfite converted. Pyrosequencing was the chosen technique to assess DNA methylation. As noted in previous studies, we found that ELOVL2 and FHL2 CpGs played a role in age estimation. In addition, three new markers were evaluated-NPTX2, KLF14, and SCGN. A set of CpGs from these five loci was used in four different multivariate regression models, providing a Mean Absolute Error (MAE) between predicted and chronological age of 1.5-2.13 years. The findings from this research can improve age estimation, increasing the accuracy of identification in forensic anthropology.

Chronological age estimation is an important piece of human identification used in forensic practice. Epigenetic modifications, especially DNA methylation, have been proposed to predict age. The methylation of the ELOVL2 gene is one of the age-related markers that could be tested in fresh or postmortem blood sample. We study the use of DNA methylation markers on the ELOVL2 gene and develop a prediction model to estimate the age from a postmortem blood sample using pyrosequencing. From 100 anonymous blood samples, a correlation study of DNA methylation and age was investigated. The regression analysis revealed 2 CpG sites for model prediction with an adjusted R 2 value of 0.7 (p < 0.01). The model explained 74% of the variation in postmortem blood samples (n = 36) with a prediction error (RMSE) of 10.2 years and a mean absolute deviation (MAD) of 7.1 years, whereas the model (excluding a younger age group) had improved with a RMSE of 5.6 years and a MAD of 4.2 years. The performance parameters were analyzed in several simulated models and indicated that these markers are advantageous for age estimation in forensic scenarios. Finally, a robustness and reproducibility of the pyrosequencing technique would enable this approach to be the part of an age prediction in forensic investigation., (Copyright © 2020 Elsevier B.V. All rights reserved.)

The discovery of new biomarkers would be very valuable to improve the detection of early Alzheimer's disease (AD). DNA methylation marks may serve as epigenetic biomarkers of early AD. Here we identified epigenetic marks that are present in the human hippocampus from the earliest stages of AD. A previous methylome dataset of the human AD hippocampus was used to select a set of eight differentially methylated positions (DMPs) since early AD stages. Next, bisulphite pyrosequencing was performed in an expanded homogeneous cohort of 18 pure controls and 35 hippocampal samples with neuropathological changes of pure AD. Correlation between DNA methylation levels in DMPs and phospho-tau protein burden assessed by immunohistochemistry in the hippocampus was also determined. We found four DMPs showing higher levels of DNA methylation at early AD stages compared to controls, involving ELOVL2, GIT1/TP53I13 and the histone gene locus at chromosome 6. DNA methylation levels assessed by bisulphite pyrosequencing correlated with phospho-tau protein burden for ELOVL2 and HIST1H3E/HIST1H3 F genes. In this discovery study, a set of four epigenetic marks of early AD stages have been identified in the human hippocampus. It would be worth studying in-depth the specific pathways related to these epigenetic marks. These early alterations in DNA methylation in the AD hippocampus could be regarded as candidate biomarkers to be explored in future translational studies., Abbreviations: AD: Alzheimer's disease; DMPs: Differentially methylated positions; CSF: Cerebrospinal fluid; βA42: β-amyloid 42; PET: positron emission tomography; 5mC: 5-methyl cytosine; CpG: cytosine-guanine dinucleotides; ANK1 : ankyrin-1; BIN1 : amphiphysin II; p-tau: hyperphosphorylated tau; CERAD: Consortium to Establish A Registry for Alzheimer's Disease; SD: standard deviation; ANOVA: one-way analysis of variance; VLCFAs: very long-chain fatty acids; DHA: docosahexaenoic acid; mTOR: mechanistic target of rapamycin.

Aim: To study the impact of aging on DNA methylation and mRNA expression in human liver., Experimental Procedures: We analysed genome-wide DNA methylation and gene expression in human liver samples using Illumina 450K and HumanHT12 expression BeadChip arrays., Results: DNA methylation analysis of ∼455,000 CpG sites in human liver revealed that age was significantly associated with altered DNA methylation of 20,396 CpG sites. Comparison of liver methylation data with published methylation data in other tissues showed that vast majority of the age-associated significant CpG sites overlapped between liver and blood, whereas a smaller overlap was found between liver and pancreatic islets or adipose tissue, respectively. We identified 151 genes whose liver expression also correlated with age., Conclusions: We identified age-associated DNA methylation and expression changes in human liver that are partly reflected by epigenetic alterations in blood.

Objective: Current methods to determine chronological age from modern and ancient remains rely on both morphological and molecular approaches. However, low accuracy and the lack of standardized protocols make the development of alternative methods for the estimation of individual's age even more urgent for several research fields, such as biological anthropology, biodemography, forensics, evolutionary genetics, and ancient DNA studies. Therefore, the aim of this study is to identify genomic regions whose DNA methylation level correlates with age in modern teeth., Methods: We used MALDI-TOF mass spectrometry to analyze DNA methylation levels of specific CpGs located in the ELOVL2, FHL2, and PENK genes. We considered methylation data from cementum, dentin and pulp of 21 modern teeth (from 17 to 77 years old) to construct a mathematical model able to exploit DNA methylation values to predict age of the individuals., Results: The median difference between the real age and that estimated using DNA methylation values is 1.20 years (SD = 1.9) if DNA is recovered from both cementum and pulp of the same modern teeth, 2.25 years (SD = 2.5) if DNA is recovered from dental pulp, 2.45 years (SD = 3.3) if DNA is extracted from cementum and 7.07 years (SD = 7.0) when DNA is recovered from dentin only., Discussion: We propose for the first time the evaluation of DNA methylation at ELOVL2, FHL2, and PENK genes as a powerful tool to predict age in modern teeth for anthropological applications. Future studies are needed to apply this method also to historical and relatively ancient human teeth., (© 2015 Wiley Periodicals, Inc.)

The aim of this study was to evaluate whether genome-wide levels of DNA methylation are associated with age and the health risks of obesity (HRO); defined according to BMI categories as "Low HRO" (overweight and class 1 obesity) versus "High HRO" (class 2 and class 3 obesity). Anthropometric measurements were assessed in a subsample of 48 volunteers from the Metabolic Syndrome Reduction in Navarra (RESMENA) study and 24 women from another independent study, Effects of Lipoic Acid and Eicosapentaenoic Acid in Human Obesity (OBEPALIP study). In the pooled population; the methylation levels of 55 CpG sites were significantly associated with age after Benjamini-Hochberg correction. In addition, DNA methylation of three CpG sites located in ELOVL2; HOXC4 and PI4KB were further negatively associated with their mRNA levels. Although no differentially methylated CpG sites were identified in relation to HRO after multiple testing correction; several nominally significant CpG sites were identified in genes related to insulin signaling; energy and lipid metabolism. Moreover, statistically significant associations between BMI or mRNA levels and two HRO-related CpG sites located in GPR133 and ITGB5 are reported. As a conclusion, these findings from two Spanish cohorts add knowledge about the important role of DNA methylation in the age-related regulation of gene expression. In addition; a relevant influence of age on DNA methylation in white blood cells was found, as well as, on a trend level, novel associations between DNA methylation and obesity.

Age estimation in forensic investigations may complement the prediction of externally visible characteristics and the inference of biogeographical ancestry, thus allowing a better description of an unknown individual. Multiple CpG sites that show linear correlation between age and degree of DNA methylation have been identified in the human genome, providing a selection of candidates for age prediction. In this study, we optimized an assay based on bisulfite conversion and pyrosequencing of 7 CpG sites located in the ELOVL2 gene. Examination of 303 blood samples collected from individuals aged 2-75 years allowed selection of the most informative site, explaining 83% of variation in age. The final linear regression model included two CpG sites in ELOVL2 and enabled age prediction with R(2)=0.859, prediction error=6.85 and mean absolute deviation MAD=5.03. Examination of a testing set of 124 blood samples (MAD=5.75) showed that 68.5% of samples were correctly predicted, assuming that chronological and predicted ages matched ± 7 years. It was found that the ELOVL2 methylation status in bloodstains had not changed significantly after 4 weeks of storage in room temperature conditions. Analysis of 45 bloodstains deposited on tissue paper after 5, 10 and 15 years of storage in room conditions indicated that although a gradual decrease of positive PCR results was observed, the general age prediction success rate remained similar and equaled 60-78%. The obtained results show that the ELOVL2 locus provides a very good source of information about human chronological age based on analysis of blood, including bloodstains, and it may constitute a powerful and reliable predictor in future forensic age estimation models., (Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.)

Methylation of the regulatory region of the elongation of very-long-chain fatty acids-like 2 (ELOVL2) gene, an enzyme involved in elongation of long-chain polyunsaturated fatty acids, is one of the most robust biomarkers of human age, but the critical question of whether ELOVL2 plays a functional role in molecular aging has not been resolved. Here, we report that Elovl2 regulates age-associated functional and anatomical aging in vivo, focusing on mouse retina, with direct relevance to age-related eye diseases. We show that an age-related decrease in Elovl2 expression is associated with increased DNA methylation of its promoter. Reversal of Elovl2 promoter hypermethylation in vivo through intravitreal injection of 5-Aza-2'-deoxycytidine (5-Aza-dc) leads to increased Elovl2 expression and rescue of age-related decline in visual function. Mice carrying a point mutation C234W that disrupts Elovl2-specific enzymatic activity show electrophysiological characteristics of premature visual decline, as well as early appearance of autofluorescent deposits, well-established markers of aging in the mouse retina. Finally, we find deposits underneath the retinal pigment epithelium in Elovl2 mutant mice, containing components found in human drusen, a pathologic hallmark of age related macular degeneration. These findings indicate that ELOVL2 activity regulates aging in mouse retina, provide a molecular link between polyunsaturated fatty acids elongation and visual function, and suggest novel therapeutic strategies for the treatment of age-related eye diseases.

In the last decade, extensive efforts have been made to identify biomarkers of biological age. DNA methylation levels of ELOVL fatty acid elongase 2 (ELOVL2) and the signal joint T-cell receptor rearrangement excision circles (sjTRECs) represent the most promising candidates. Although these two non-redundant biomarkers echo important biological aspects of the ageing process in humans, a well-validated molecular clock exploiting these powerful candidates has not yet been formulated. The present study aimed to develop a more accurate molecular clock in a sample of 194 Italian individuals by re-analyzing the previously obtained EVOLV2 methylation data together with the amount of sjTRECs in the same blood samples. The proposed model showed a high prediction accuracy both in younger individuals with an error of about 2.5 years and in older subjects where a relatively low error was observed if compared with those reported in previously published studies. In conclusion, an easy, cost-effective and reliable model to measure the individual rate and the quality of aging in human population has been proposed. Further studies are required to validate the model and to extend its use in an applicative context. [ABSTRACT FROM AUTHOR]

Age estimation of unidentified bodies is important in forensic medicine and crime scenes. There is accumulating evidence that DNA methylation in the human genome isolated from body fluids changes with age. Most of the data have been obtained by pyrosequencing. In the forensic field, a simple, quick, and economical method is required to evaluate the age of various types of samples. In this study, an age estimation method based on methylation levels of DNA extracted from teeth using real-time methylation-specific PCR (MSP) was developed. The CpG island in the upstream region of ELOVL2, which is known as a validated biomarker in blood samples, was selected as a target site. The CpG methylation levels highly correlated with age (r = 0.843, n = 29). Age-related increase in DNA methylation levels was not affected by sex differences. In addition, the simple regression model based on methylation status of the CpG island exhibited moderate accuracy with a mean absolute deviation between chronological age and predicted age of 8.94 years. The results imply that real-time MSP can be a new tool to perform age prediction of unidentified bodies in forensic scenes. [ABSTRACT FROM AUTHOR]

Age prediction helps investigation to narrowing down the number of potential suspects and give more reliable predicted appearance. However, since it is not known if some of the widely used methylation markers (ELOVL2, C1orf132, TRIM59, KLF14 and FHL2) are applicable as age predictors in the Italian population, in this study we collected and analyzed a set of saliva samples from 96 Italian individuals aged 19–67 years. All DNA samples were quantified, bisulfite-converted, amplified with monoplex and analyzed using PyroMark Q48 Autoprep (Qiagen). The age prediction was performed according to reference (Zbieć-Piekarska et al. [1]). Preliminary results shown a linear correlation between the methylation markers studied and age in the Italian samples, with a Pearson correlation coefficient (PCC) of 0.75 and the value of median absolute deviation (MAD) of 5.4. The MAD value observed with group 1 (age 20 s or less) was 2.8, with group 2 (30 s) was 4.5, with group 3 (40 s) was 4.7 and with group 4 (50 s or more) was 5.4. If we take the assumption that age prediction is correct when predicted age is in the range of max ±5 years of the actual age, the number of correct prediction decrease with increasing of the age group. Moreover, in contrast of what expected, our data set has shown a bias in the underestimating of predicted age at the increasing of chronological age (20% group 1, 60% group 2, 79% group 3 and 88% group 4). This experiment suggest to increase the number of different population sampled since DNA methylation could be affected by genetic variation, environmental and lifestyle variation. [ABSTRACT FROM AUTHOR]