DNA methylation analysis of ELOVL2 gene using droplet digital PCR for age estimation purposes

Forensic Age Estimation From Blood Samples by Combining DNA Methylation and MicroRNA Markers Using Droplet Digital PCR

Age estimation is important in criminal investigations and forensic practice, and extensive studies have focused on age determination based on DNA methylation (DNAm) and miRNA markers. Interestingly, it has been reported that combining different types of molecular omics data helps build more accurate predictive models. However, few studies have compared the application of combined DNAm and miRNA data to predict age in the same cohort. In this study, a novel multiplex droplet digital PCR (ddPCR) system that allows for the simultaneous detection of age-associated DNAm and miRNA markers, including KLF14, miR-106b-5p, and two reference genes (C-LESS-C1 and RNU6B), was developed. Next, we examined and calculated the methylation levels of KLF14 and relative expression levels of miR-106b-5p in 132 blood samples. The collected data were used to establish age prediction models. Finally, the optimal models were evaluated using bloodstain samples. The results revealed that the random forest (RF) model had a minimum mean absolute deviation (MAD) value of 3.51 years and a maximum R2 of 0.84 for the validation sets in the combined age prediction models. However, the MAD was 5.66 years and the absolute error ranged from 3.16 to 10.54 years for bloodstain samples. Larger sample sizes and validation datasets are required to confirm these results in future studies. Overall, a stable method for the detection of KLF14, miR-106b-5p, C-LESS-C1, and RNU6B by 4-plex ddPCR was successfully established, and our study suggests that combining DNAm and miRNA data can improve the accuracy of age prediction, which has potential applications in forensic science.

Reproducibility and validation of a targeted and flexible epigenetic clock for forensic applications

DNA methylation variants have been widely used as biomarkers of ageing and several mathematical models have been developed to estimate the biological age. More recently, DNA technology has triggered efforts toward the simplification of the array-based epigenetic clocks and targeted approaches, based on the assessment of a small number of CpG sites have been developed. Among the markers included in these clocks, ELOVL2, FHL2, KLF14, C1orf132/MIR29B2C, and TRIM59 resulted to be the most strongly validated markers. We tested the reproducibility and validation of a previously developed targeted epigenetic clock purposely optimized for the measurement of chronological age in blood samples. The clock includes DNAm biomarkers strongly correlated with chronological age whose DNA methylation levels were measured by using a multiplex methylation SNaPshot assay. We found that epigenetic age, calculated using the developed clock, was highly correlated with age (r = 0.97) in a total of 201 blood samples covering a full spectrum of human ages. For 74 of these, methylation profiles of the whole genome were obtained through the Infinium Methylation EPIC v2.0 Kit which also allowed to estimate the most frequently used clocks of Horvath. These results show the potential of our efficient and affordable test for simultaneously measuring DNA methylation levels at multiple target CpG sites to assess chronological age. We observed a strong correlation between the prediction models for the analyzed CpG sites measured using the SNaPshot method and those obtained with the Illumina EPIC array, especially with the Horvath2 clock, which was specifically developed for DNA from skin and blood cells.

Advancing Forensic Human Chronological Age Estimation: Biochemical, Genetic, and Epigenetic Approaches from the Last 15 Years: A Systematic Review

Forensic age estimation is crucial for identifying unknown individuals and narrowing suspect pools in criminal investigations. Over the past 15 years, significant progress has been made in using biochemical, genetic, and epigenetic markers to estimate chronological age.

METHODS

From research on PubMed a total of 155 studies, related to advancements in age prediction techniques, were selected following PRISMA guidelines. Studies considered eligible dealt with radiocarbon dating, aspartic acid racemization, mitochondrial DNA analysis, signal joint T-cell receptor excision circles, RNA analysis, telomeres, and DNA methylation in the last 15 years and were summarized in a table.

RESULTS

Despite these advancements, challenges persist, including variability in prediction accuracy, sample degradation, and the lack of standardization and reproducibility. DNA methylation emerged as the most promising approach capable of high accuracy across diverse populations and age ranges. Multimodal methods integrating several biomarkers show promise in improving reliability and addressing these limitations.

CONCLUSION

While significant progress has been made, further standardization, validation, and technological integration are needed to enhance forensic age estimation. These efforts are essential for meeting the growing demands of forensic science while addressing ethical and legal considerations.

A new robust AI/ML based model for accurate forensic age estimation using DNA methylation markers

CpG sites are regions of DNA where a cytosine nucleotide is followed by a guanine nucleotide in the 5' → 3' direction. Epigenetic markers based on methylation values at CpG sites are valuable for accurate age prediction and have become essential in forensic science, supporting criminal investigations and human identification. The present study identified 12 CpG sites from a collection of 476,366 CpG sites based on the following criteria: (a) CpG sites were retained if the Pearson correlation coefficient between the methylation values and the chronological age of the individual is greater than 0.85, and (b) if the mutual correlation coefficient between a pair of selected CpG sites is greater than 0.15, only one of them is retained. The identified CpG sites are associated with genes FHL2, ELOVL2, TRIM59, PCDHB1, KLF14, C1orf132, ACSS3, and CCDC102B. To ensure that the predictive accuracy is intrinsic to the selected CpG sites and not model dependent, the identified CpG sites were passed to three different Neural network models. All models achieved comparable accuracy across diverse populations, genders, and health conditions. The model's accuracy and reliability were validated through age predictions on independent datasets. By utilizing a minimal set of CpG sites, this approach offers a robust and efficient solution for forensic age estimation, significantly enhancing the precision and reliability of forensic investigations.

Epigenetic Clock: DNA Methylation as a Marker of Biological Age and Age-Associated Diseases

Age is one of the key criteria of human health used in practical medicine to predict the risk of common chronic diseases. However, biological age, which reflects the state of an individual organism, functional capabilities, social well-being, and risk of premature death from various causes, often does not coincide with chronological age. To determine biological age of a particular individuals and the rate of their aging, specific panels of DNA methylation markers called "epigenetic clock" (EC) were proposed. This review summarizes the data about the main types of ECs developed to date and their key characteristics. We described the results of works studying individual aging rates in common age-associated diseases and outlined main directions, development of which could expand application of ECs in fundamental and practical medicine. There is no doubt that revealing complex mechanisms underlying interaction between the rate of epigenetic aging and the risk of age-associated diseases could play a key role for prediction and early diagnosis, as well as for the development of preventive measures that could delay onset of the disease.

Age estimation of burnt human remains through DNA methylation analysis

The identification of human fire victims is a challenging task in forensic medicine. The heat-induced alterations of biological tissues can make the conventional anthropological analyses difficult. Even if the DNA profile of the victim is achieved, it is possible that no match can be found in a forensic DNA database, thus hindering positive identification. In such cases, any information useful to nail down a possible identity should be collected, such as DNA methylation analysis which could provide useful investigative leads. In the present study, five age-related epigenetic markers (ELOVL2, FHL2, KLF14, C1orf132, and TRIM59) were initially analysed in blood samples of 72 living Italian individuals of known age, using a Single Base Extension (SBE) assay. An age prediction model was built by multiple linear regression including all the markers (Mean Absolute Error, MAE: 3.15 years). This model was tested on 29 blood samples collected during autopsies from burnt human remains, already identified through DNA analysis, providing a MAE of 6.92 years. The model allowed a correct prediction in 79.3% of the cases (95% prediction interval), while six cases were associated with inaccurate predictions (min-max prediction error: 9.8-37.3 years). Among the different sample variables considered to explain these results, only the DNA degradation index was a relevant factor affecting the reliability of the predictions. In conclusion, the SBE typing of blood from burnt remains proved to be a reliable tool to estimate chronological age of most of the samples, also in consideration of its cost-effectiveness and the availability of CE sequencers in every forensic genetics laboratory.

Permeability-Engineered Compartmentation System-Enabled Digital PCR (PECS-dPCR): A Digital Platform toward Multistep Biomolecular Assays

Droplet-based digital PCR has emerged as a powerful platform for nucleic acid-based detection. However, the formation of droplet compartments and the subsequent amplification process in oil present significant drawbacks: instability under harsh thermal conditions, high background fluorescent noise inside droplets, and major difficulty in supporting multistep assays. Alternatively, droplets made of a hydrogel, or other advanced materials, have been adopted and demonstrate promising improvement over conventional droplet-based platforms. In this context, we present permeability-engineered compartmentation system-enabled digital PCR (PECS-dPCR), a novel digital platform that facilitates multistep biomolecular assays with thermal stability, minimized background noise, and long-term preservation capability. We achieve compartmentalization by forming a core-shell structure using the aqueous two-phase system (ATPS). The hydrogel shell provides exceptional mechanical strength and thermal stability to these compartments. The permeability of the shell can be fine-tuned to retain larger DNA targets while sieving out smaller ancillary molecules. Therefore, we can significantly improve the signal-to-noise ratio inside the compartments by washing out fluorescent background. Furthermore, these core-shell compartments remain intact in aqueous solution and are able to exchange materials with the ambient environment. This critical feature offers the capability to execute multistep assays in simple operational settings, enabling the demonstration of multitarget single-bacteria quantification in our platform. We further show that the assay can be paused with samples preserved for >2 weeks between different detection steps thanks to the excellent biochemical stability offered by the core-shell compartments. We envision PECS-dPCR becoming a versatile platform supporting multiple-reaction-step digital assays, offering high-quality detection signals and long-term stability.

Male-specific age prediction based on Y-chromosome DNA methylation with blood using pyrosequencing

Age prediction is an important aspect of forensic science that offers valuable insight into identification. In recent years, extensive studies have been conducted on age prediction based on DNA methylation, and numerous studies have demonstrated that DNA methylation is a reliable biomarker for age prediction. However, almost all studies on age prediction based on DNA methylation have focused on age-related CpG sites in autosomes, which are concentrated on single-source DNA samples. Mixed samples, especially male-female mixed samples, are common in forensic casework. The application of Y-STRs and Y-SNPs can provide clues for the genetic typing of male individuals in male-female mixtures, but they cannot provide the age information of male individuals. Studies on Y-chromosome DNA methylation can address this issue. In this study, we identified five age-related CpG sites on the Y chromosome (Y-CpGs) and developed a male-specific age prediction model using pyrosequencing combined with a support vector machine algorithm. The mean absolute deviation of the model was 5.50 years in the training set and 6.74 years in the testing set. When we used a male blood sample to predict age, the deviation between the predicted and chronological age was 1.18 years. Then, we mixed the genomic DNA of the male and a female at ratios of 1:1, 1:5, 1:10, and 1:50, the range of deviation between the predicted and chronological age of the male in the mixture was 1.16-1.74 years. In addition, there was no significant difference between the methylation values of bloodstains and blood in the same sample, which indicates that our model is also suitable for bloodstain samples. Overall, our results show that age prediction using DNA methylation of the Y chromosome has potential applications in forensic science and can be of great help in predicting the age of males in male-female mixtures. Furthermore, this work lays the foundation for future research on age-related applications of Y-CpGs.

Uncovering Forensic Evidence: A Path to Age Estimation through DNA Methylation

Age estimation is a critical aspect of reconstructing a biological profile in forensic sciences. Diverse biochemical processes have been studied in their correlation with age, and the results have driven DNA methylation to the forefront as a promising biomarker. DNA methylation, an epigenetic modification, has been extensively studied in recent years for developing age estimation models in criminalistics and forensic anthropology. Epigenetic clocks, which analyze DNA sites undergoing hypermethylation or hypomethylation as individuals age, have paved the way for improved prediction models. A wide range of biomarkers and methods for DNA methylation analysis have been proposed, achieving different accuracies across samples and cell types. This review extensively explores literature from the past 5 years, showing scientific efforts toward the ultimate goal: applying age prediction models to assist in human identification.

Loss of the Y Chromosome: A Review of Molecular Mechanisms, Age Inference, and Implications for Men's Health

Until a few years ago, it was believed that the gradual mosaic loss of the Y chromosome (mLOY) was a normal age-related process. However, it is now known that mLOY is associated with a wide variety of pathologies in men, such as cardiovascular diseases, neurodegenerative disorders, and many types of cancer. Nevertheless, the mechanisms that generate mLOY in men have not been studied so far. This task is of great importance because it will allow focusing on possible methods of prophylaxis or therapy for diseases associated with mLOY. On the other hand, it would allow better understanding of mLOY as a possible marker for inferring the age of male samples in cases of human identification. Due to the above, in this work, a comprehensive review of the literature was conducted, presenting the most relevant information on the possible molecular mechanisms by which mLOY is generated, as well as its implications for men's health and its possible use as a marker to infer age.

A high-throughput droplet digital PCR system aiming eight DNA methylation targets for age prediction

The droplet digital Polymerase Chain Reaction (ddPCR) has garnered recognition for its distinctive attribute of absolute quantification. And it has found practical utility in age prediction through DNA methylation profiles. However, a prevalent limitation in current ddPCR methodologies is the restricted capacity to detect only two targets concurrently in most instruments, leading to high costs, sample wastage, and labor-intensive procedures. To address the limitations, a novel high-throughput ddPCR system allowing for the simultaneous detection of eight targets was developed. Through the implementation of a new 8-plex ddPCR assay, coupled with comprehensive linear regression analyses involving primers and probes ratios, diverse inputs of single CpG sites with distinct primers and probes, and varying plex assay configurations, stable DNA methylation values for four CpGs and stable measurement precisions for distinct multiplex systems were consistently observed. These findings pave the way for advancing the field of chemistry science by enabling more efficient and cost-effective methods. Furthermore, the comparative validation of ddPCR and SNaPshot demonstrated a remarkable concordance in results, and the system also displayed well in the field of various aspects, including species specificity, DNA input, and aged samples. In this study, the recommended input of bisulfite-converted DNA was determined to be 10-50 ng due to the double-positive droplets. Notably, the Pearson correlation coefficient squared values of four CpGs were 0.4878 (ASPA), 0.4832 (IGSF1), 0.6881 (COL1A1), and 0.6475 (MEIS1-AS3). And the testing set exhibited a mean absolute error of 4.5923 years, indicating the robustness and accuracy of the age-predictive model.

Predicting age from blood by droplet digital PCR using a set of three DNA methylation markers

Evaluation of DNA methylation (DNAm) patterns is a promising tool for age estimation. The duplex droplet digital PCR (ddPCR) method has been recently investigated for DNAm evaluation, revealing to be a potential methodology for DNAm evaluation and molecular age estimation. In this study, we evaluated DNAm levels of CpGs located at the three age-associated genes ELOVL2, FHL2 and PDE4C using ddPCR to develop an age prediction model. Blood-derived DNA samples from 58 healthy individuals (42 women and 16 men; aged 1-93 years old) were submitted to bisulfite conversion followed by ddPCR using dual-labeled probes targeting methylated and unmethylated DNA sequences. Simple linear regression statistics revealed a strong correlation between DNAm levels and chronological age for FHL2 (R = 0.948; P = 1.472 × 10-29) and PDE4C (R = 0.819; P = 3.917 × 10-15), addressing only one CpG for each gene. For the ELOVL2 gene, evaluating five CpG sites in simultaneous, revealed a strong age correlation (R = 0.887; P = 2.099 × 10-20) in a simple linear regression statistics and very strong age correlation (R = 0.926; P = 2.202 × 10-25) when using quadratic regression statistics. The multivariable regression analysis, using methylation information captured on ELOVL2 (squared), FHL2 and PDE4C genes, revealed a very strong age correlation (R = 0.970; P = 5.356 ×10-33), explaining 93.7 % of age variance, displaying a mean absolute deviation (MAD) between chronological and predicted age of 4.657 years (RMSE = 6.044). We postulate that the ddPCR method should be further investigated for DNAm-based age prediction, because it is a relatively simple and an accurate method that can be routinely used in forensic laboratories for testing a few numbers of markers.

Estimation of cadaveric age in crime scenes using Raman spectroscopy

The number of unidentified corpses has been increasing in recent years. There is a need for an objective and readily applicable method to estimate age, which is important information for identification. In previous reports, we reported that the protein folding ratio (RPF) of skin, as measured by Raman spectroscopy using cross sections of skin samples, is highly correlated with age. In this study, we investigated the possibility of estimating age by measuring Raman spectra from the skin surface of cadavers using a portable device. The resultant intercept, slope, and root mean square error were 97.9, - 63.7 (p < 0.0001), and 11.68, respectively. We evaluated this regression formula by using 10-fold cross-validation, resulting in a coefficient of determination of 0.51. The portable Raman spectrometer may be of assistance in estimating age at death of corpses at the scene of discovery.

Epigenetic modifiers as game changers for healthy ageing

Epigenetic alterations during ageing are manifested with altered gene expression linking it to lifespan regulation, genetic instability, and diseases. Diet and epigenetic modifiers exert a profound effect on the lifespan of an organism by modulating the epigenetic marks. However, our understanding of the multifactorial nature of the epigenetic process during ageing and the onset of disease conditions as well as its reversal by epidrugs, diet, or environmental factors is still mystifying. This review covers the key findings in epigenetics related to ageing and age-related diseases. Further, it holds a discussion about the epigenetic clocks and their implications in various age-related disease conditions including cancer. Although, epigenetics is a reversible process how fast the epigenetic alterations can revert to normal is an intriguing question. Therefore, this paper touches on the possibility of utilizing nutrition and MSCs secretome to accelerate the epigenetic reversal and emphasizes the identification of new therapeutic epigenetic modifiers to counter epigenetic alteration during ageing.

Recent advances in Forensic DNA Phenotyping of appearance, ancestry and age

Forensic DNA Phenotyping (FDP) comprises the prediction of a person's externally visible characteristics regarding appearance, biogeographic ancestry and age from DNA of crime scene samples, to provide investigative leads to help find unknown perpetrators that cannot be identified with forensic STR-profiling. In recent years, FDP has advanced considerably in all of its three components, which we summarize in this review article. Appearance prediction from DNA has broadened beyond eye, hair and skin color to additionally comprise other traits such as eyebrow color, freckles, hair structure, hair loss in men, and tall stature. Biogeographic ancestry inference from DNA has progressed from continental ancestry to sub-continental ancestry detection and the resolving of co-ancestry patterns in genetically admixed individuals. Age estimation from DNA has widened beyond blood to more somatic tissues such as saliva and bones as well as new markers and tools for semen. Technological progress has allowed forensically suitable DNA technology with largely increased multiplex capacity for the simultaneous analysis of hundreds of DNA predictors with targeted massively parallel sequencing (MPS). Forensically validated MPS-based FDP tools for predicting from crime scene DNA i) several appearance traits, ii) multi-regional ancestry, iii) several appearance traits together with multi-regional ancestry, and iv) age from different tissue types, are already available. Despite recent advances that will likely increase the impact of FDP in criminal casework in the near future, moving reliable appearance, ancestry and age prediction from crime scene DNA to the level of detail and accuracy police investigators may desire, requires further intensified scientific research together with technical developments and forensic validations as well as the necessary funding.

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

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.

A Blood-Based Molecular Clock for Biological Age Estimation

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.