A validation study of DNA methylation-based age prediction using semen in forensic casework samples

A SNaPshot Assay for Epigenetic Age Prediction of Costal Cartilage

Estimating age at death narrows the pool of potential donors in mass disasters and criminal investigations. In this study, we developed a capillary electrophoresis-based SNaPshot assay for age prediction of costal cartilage and used it to analyze DNA methylation at 11 CpG sites across six genes in 136 samples from deceased Koreans aged 28-84 years. To develop the predictive model, DNA methylation levels at these sites from a training set of 83 samples were analyzed using multivariate linear regression in five ways. We then compared the performance parameters calculated from the training set and a test set of 53 samples. Considering experimental simplicity, we selected a model that incorporates four CpGs (MIR29B2CHG_C2, FHL2_C4, TRIM59_C3, and KLF14_C3) as the optimal age prediction model, demonstrating high performance with a mean absolute error of 4.60 years and a root mean square error of 5.41 years in the test set. Subsequently, we developed a multiplex SNaPshot system covering CpGs included in the optimal model, requiring a minimum of 4 ng of bisulfite-converted DNA for reliable prediction and demonstrating multi-tissue applicability, particularly in blood and buccal swabs. We believe this tool will support forensic investigations, including the identification of victims and missing persons.

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.

DNA methylation-based semen age prediction using the markers identified in Koreans and Europeans

In the forensic field, sexual assaults have consistently been the important issue, with semen frequently serving as the primary evidence. When the suspect is unidentified, estimating the perpetrator's age using investigating semen can provide important information. The VISAGE consortium conducted research on the semen age prediction focused on European semen samples, but the age prediction model has remained undisclosed. Additionally, several studies have reported methylation differences across populations, indicating that the European semen age prediction model might not be broadly applicable to other groups. A study did explore semen age prediction in Koreans using Illumina's Infinium Methylation450K BeadChip array, however recent developments in technology could enhance this approach. To address this, we conducted a study on Korean males aged 18-70 years. We initially analyzed 49 samples utilizing Illumina's Infinium MethylationEPIC BeadChip array to identify age-related CpG sites. From this analysis, we identified 9 age-related CpG markers, excluding one due to difficulties in locus-specific analysis. As a result, we used 11 markers including 8 newly identified CpGs from the EPIC array and 3 CpG markers from previous research utilizing the SNaPshot assay. Furthermore, we incorporated 13 CpG markers from the European study to analyze a total of 159 semen samples using the Illumina Nextera MPS system. This approach enabled us to test age-related markers identified in Europeans within the Korean population and to construct a more accurate age prediction model using markers from both Korean and European sources.

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.

DNA methylation-based age estimation from semen: Genome-wide marker identification and model development

DNA methylation at age-related CpG (AR-CpG) sites holds significant promise for forensic age estimation. However, somatic models perform poorly in semen due to unique methylation dynamics during spermatogenesis, and current studies are constrained by the limited coverage of methylation microarrays. This study aimed to identify novel semen-specific AR-CpG sites using double-enzyme reduced representation bisulfite sequencing (dRRBS) and validate these markers, alongside previously reported sites and neighboring CpGs, using bisulfite amplicon sequencing (BSAS) to develop robust age estimation models. A methylome-wide association study was conducted on semen samples from 21 healthy Chinese men across three age groups, generating over 4 million CpG sites per sample at ≥ 5 × depth. Analysis of 721,840 shared CpG sites revealed that more than 95 % were not covered by conventional methylation microarrays. Differential methylation and correlation analyses identified 139 AR-CpG sites. A two-stage validation process using multiplex PCR-based BSAS was performed. In the first stage, 47 top dRRBS-identified AR-CpG sites, 26 literature-reported sites, and 242 neighboring CpGs were assessed in 129 semen samples (22-64 years), validating 31 dRRBS, 26 literature-reported, and 152 neighboring CpGs as age-related. The second stage examined 154 CpG sites in 247 samples (22-67 years), confirming 71 AR-CpG sites with |rho| > 0.50. Among these, chr2:129071885 (cg19998819) emerged as the strongest age-associated marker (rho = 0.81). Using the second BSAS dataset, age estimation models were developed with multiple linear regression and random forest (RF) algorithms within a repeated nested cross-validation (CV) framework (10-fold outer CV with 10-fold inner CV, repeated 10 times). The RF models demonstrated superior accuracy across feature subsets of 5-25 CpGs. The optimized 9-CpG RF model achieved an average root mean square error of 4.73 years (4.62-4.96, SD=0.10) and an average mean absolute error of 3.30 years (3.23-3.43, SD=0.06). This study demonstrates the utility of dRRBS for large-scale AR-CpG discovery and provides a robust age estimation model and a comprehensive reference database of semen-specific AR-CpG sites for forensic applications.

A Ge.F.I. Collaborative Study: Evaluating Reproducibility and Accuracy of a DNA-Methylation-Based Age-Predictive Assay for Routine Implementation in Forensic Casework

The increasing interest in DNA methylation (DNAm) analysis within the forensic scientific community prompted a collaborative project by Ge.F.I. (Genetisti Forensi Italiani). The study evaluated a standardized bisulfite conversion-based Single Base Extension (SBE) protocol for the analysis of the methylation levels at five age-predictive loci (ELOVL2, FHL2, KLF14, C1orf132/MIR29B2C, and TRIM59). The study encompassed three phases: (1) setting up and validating the protocol to ensure consistency and reproducibility; (2) comparing fresh peripheral blood with blood spots; and (3) evaluating sources of intra- and inter-laboratory variability. Samples from 22 Italian volunteers were analyzed by 6 laboratories in replicates for a total of 528 records. From phase I emerged that the choice of genetic sequencer significantly contributed to inter-laboratory data variation, resulting in separate regression analyses performed for each laboratory. In phase II, blood spots were found to be a reliable source for DNAm analysis, despite exhibiting increased experimental variation compared to fresh peripheral blood. In phase III, a strong correlation between the individual's predicted and true ages was observed across different laboratories. Analysis of variance (ANOVA) of the residuals indicated that one-third of the total variance could be attributed to laboratory-specific factors, whereas two-thirds could be attributed to inter-individual biological differences. The leave-one-out cross-validation (LOO-CV) method yielded an overall mean absolute deviation (MAD) value of 4.41 years, with an average 95% confidence interval of 5.24 years. Stepwise regression analysis proved that a restricted model (ELOVL2, C1orf132/MIR29B2C, and TRIM59) produced results virtually indistinguishable from the five-loci model. Additionally, the analysis of samples in replicates greatly improved the fit of the regression model, balancing the slight effects of intra-laboratory variability. In conclusion, the bisulfite conversion-based SBE protocol, combined with replicate analysis and in-lab calibration of a regression-prediction model, proves to be a reliable and easily implementable method for age prediction in forensic laboratories.

A semen-specific deoxyribonucleic acid methylation model for epigenetic age estimation and its robustness under environmental challenges

In forensic investigations, semen samples are a common form of biological evidence, especially in cases involving sexual assault. Therefore, accurately estimating the age of an individual is crucial in criminal cases. This study presents a novel age estimation model based on semen-specific CpG methylation patterns. A multiplex panel was developed, consisting of 12 CpG sites (PARP14, C5orf25, cg23488376, MXRA5, PFKFB3, DLL1, NOX4, cg12837463, TTC7B, KCNA7, NKX2-1, and SYNE4), which exhibit strong correlations with age. Additionally, this study investigates the resilience of these methylation markers under simulated environmental challenges. We collected ejaculate samples from a diverse cohort of 115 male individuals, aged 20-71 years, who underwent deoxyribonucleic acid extraction and bisulfite conversion. Methylation levels of the selected CpG sites were assessed using a SNaPshot assay, which revealed significant correlations with chronological age. We developed and validated two robust age estimation models through stepwise and enter regression analyses, achieving reliable accuracy with mean absolute errors ranging from 3.81 to 4.1 years. Additionally, the study also investigated the robustness of semen stains under diverse environmental conditions, including fabric type, washing, hematin exposure, and UV-C light. The selected methylation markers demonstrated remarkable resilience despite the challenges posed by washing procedures and environmental exposure, confirming their potential for age estimation in forensic genetics. This research presents successful age estimation models, emphasizing the strong correlations between methylation levels and chronological age. The proposed methodology's accuracy is affirmed through model validation on an independent test set, while also highlighting the resilience of semen stains on fabrics under varying storage and washing conditions.

Strategies to deal with genetic analyzer-specific DNA methylation measurements

Targeted bisulfite sequencing using single-base extension (SBE) can be used to measure DNA methylation via capillary electrophoresis on genetic analyzers in forensic labs. Several accurate age prediction models have been reported using this method. However, using different genetic analyzers with different software settings can generate different methylation values, leading to significant errors in age prediction. To address this issue, the study proposes and compares four methods as follows: (1) adjusting methylation values using numerous actual body fluid DNA samples, (2) adjusting methylation values using control DNAs with varying methylation ratios, (3) constructing new age prediction models for each genetic analyzer type, and (4) constructing new age prediction models that could be applied to all types of genetic analyzers. To test the methods for adjusting values using actual body fluid DNA samples, previously reported adjusting equations were used for blood/saliva DNA age prediction markers (ELOVL2, FHL2, KLF14, MIR29B2CHG/C1orf132, and TRIM59). New equations were generated for semen DNA age prediction markers (TTC7B, LOC401324/cg12837463, and LOC729960/NOX4) by drawing polynomial regression lines between the results of the three types of genetic analyzers (3130, 3500, and SeqStudio). The same method was applied to obtain adjustment equations using 11 control DNA samples. To develop new age prediction models for each genetic analyzer type, linear regression analysis was conducted using DNA methylation data from 150 blood, 150 saliva, and 62 semen samples. For the genetic analyzer-independent models, control DNAs were used to formulate equations for calibrating the bias of the data from each genetic analyzer, and linear regression analysis was performed using calibrated body fluid DNA data. In the comparison results, the genetic analyzer-specific models showed the highest accuracy. However, genetic analyzer-independent models through bias adjustment also provided accurate age prediction results, suggesting its use as an alternative in situations with multiple constraints.

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.

Age-related changes in sperm DNA methylation and their forensic and clinical implications

As a link between a stable genome and a dynamic environment, epigenetics is a promising tool for mapping age-related changes in human DNA. Methylated cytosine changes at specific loci are generally less studied in sperm DNA than in somatic cell DNA. Age-related methylation changes can be connected to various reproductive health problems and multiple disorders in offspring. In addition, they can be helpful in forensic fields, where testing of specific loci in semen samples found at sexual assault crime scenes can predict a perpetrator's age and narrow down the police investigation. This review focuses on age-related methylation changes in sperm. It covers the biological role of methylation, methylation testing techniques and the implications of methylation changes in forensics and clinical practice.

Getting the chronological age out of DNA: using insights of age-dependent DNA methylation for forensic DNA applications

BACKGROUND

DNA analysis for forensic investigations has a long tradition with important developments and optimizations since its first application. Traditionally, short tandem repeats analysis has been the most powerful method for the identification of individuals. However, in addition, epigenetic changes, i.e., DNA methylation, came into focus of forensic DNA research. Chronological age prediction is one promising application to allow for narrowing the pool of possible individuals who caused a trace, as well as to support the identification of unknown bodies and for age verification of living individuals.

OBJECTIVE

This review aims to provide an overview of the current knowledge, possibilities, and (current) limitations about DNA methylation-based chronological age prediction with emphasis on forensic application.

METHODS

The development, implementation and application of age prediction tools requires a deep understanding about the biological background, the analysis methods, the age-dependent DNA methylation markers, as well as the mathematical models for age prediction and their evaluation. Furthermore, additional influences can have an impact. Therefore, the literature was evaluated in respect to these diverse topics.

CONCLUSION

The numerous research efforts in recent years have led to a rapid change in our understanding of the application of DNA methylation for chronological age prediction, which is now on the way to implementation and validation. Knowledge of the various aspects leads to a better understanding and allows a more informed interpretation of DNAm quantification results, as well as the obtained results by the age prediction tools.

Prediction of chronological age and its applications in forensic casework: methods, current practices, and future perspectives

Estimating an individual's age can be relevant in several areas primarily related to the clinical and forensic fields. In the latter, estimation of an individual's chronological age from biological material left by the perpetrator at a crime scene may provide helpful information for police investigation. Estimation of age is also beneficial in immigration cases, where age can affect the person's protection status under the law, or in disaster victim identification to narrow the list of potential missing persons. In the last decade, research has focused on establishing new approaches for age prediction in the forensic field. From the first forensic age estimations based on morphological inspections of macroscopic changes in bone and teeth, the focus has shifted to molecular methods for age estimation. These methods allow the use of samples from human biological material that does not contain morphological age features and can, in theory, be investigated in traces containing only small amounts of biological material. Molecular methods involving DNA analyses are the primary choice and estimation of DNA methylation levels at specific sites in the genome is the most promising tool. This review aims to provide an overview of the status of forensic age prediction using molecular methods, with particular focus in DNA methylation. The frequent challenges that impact forensic age prediction model development will be addressed, together with the importance of validation efforts within the forensic community.

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.

DNA methylation-based age prediction with bloodstains using pyrosequencing and random forest regression

The use of DNA methylation to predict chronological age has shown promising potential for obtaining additional information in forensic investigations. To date, several studies have reported age prediction models based on DNA methylation in body fluids with high DNA content. However, it is often difficult to apply these existing methods in practice due to the low amount of DNA present in stains of body fluids that are part of a trace material. In this study, we present a sensitive and rapid test for age prediction with bloodstains based on pyrosequencing and random forest regression. This assay requires only 0.1 ng of genomic DNA and the entire procedure can be completed within 10 h, making it practical for forensic investigations that require a short turnaround time. We examined the methylation levels of 46 CpG sites from six genes using bloodstain samples from 128 males and 113 females aged 10-79 years. A random forest regression model was then used to construct an age prediction model for males and females separately. The final age prediction models were developed with seven CpG sites (three for males and four for females) based on the performance of the random forest regression. The mean absolute deviation was less than 3 years for each model. Our results demonstrate that DNA methylation-based age prediction using pyrosequencing and random forest regression has potential applications in forensics to accurately predict the biological age of a bloodstain donor.

A collaborative exercise on DNA methylation-based age prediction and body fluid typing

DNA methylation has become one of the most useful biomarkers for age prediction and body fluid identification in the forensic field. Therefore, several assays have been developed to detect age-associated and body fluid-specific DNA methylation changes. Among the many methods developed, SNaPshot-based assays should be particularly useful in forensic laboratories, as they permit multiplex analysis and use the same capillary electrophoresis instrumentation as STR analysis. However, technical validation of any developed assays is crucial for their proper integration into routine forensic workflow. In the present collaborative exercise, two SNaPshot multiplex assays for age prediction and a SNaPshot multiplex for body fluid identification were tested in twelve laboratories. The experimental set-up of the exercise was designed to reflect the entire workflow of SNaPshot-based methylation analysis and involved four increasingly complex tasks designed to detect potential factors influencing methylation measurements. The results of body fluid identification from each laboratory provided sufficient information to determine appropriate age prediction methods in subsequent analysis. In age prediction, systematic measurement differences resulting from the type of genetic analyzer used were identified as the biggest cause of DNA methylation variation between laboratories. Also, the use of a buffer that ensures a high ratio of specific to non-specific primer binding resulted in changes in DNA methylation measurement, especially when using degenerate primers in the PCR reaction. In addition, high input volumes of bisulfite-converted DNA often caused PCR failure, presumably due to carry-over of PCR inhibitors from the bisulfite conversion reaction. The proficiency of the analysts and experimental conditions for efficient SNaPshot reactions were also important for consistent DNA methylation measurement. Several bisulfite conversion kits were used for this study, but differences resulting from the use of any specific kit were not clearly discerned. Even when different experimental settings were used in each laboratory, a positive outcome of the study was a mean absolute age prediction error amongst participant's data of only 2.7 years for semen, 5.0 years for blood and 3.8 years for saliva.

Development and inter-laboratory validation of the VISAGE enhanced tool for age estimation from semen using quantitative DNA methylation analysis

The analysis of DNA methylation has become an established method for chronological age estimation. This has triggered interest in the forensic community to develop new methods for age estimation from biological crime scene material. Various assays are available for age estimation from somatic tissues, the majority from blood. Age prediction from semen requires different DNA methylation markers and the only assays currently developed for forensic analysis are based on SNaPshot or pyrosequencing. Here, we describe a new assay using massively parallel sequencing to analyse 13 candidate CpG sites targeted in two multiplex PCRs. The assay has been validated by five consortium laboratories of the VISible Attributes through GEnomics (VISAGE) project within a collaborative exercise and was tested for reproducible quantification of DNA methylation levels and sensitivity with DNA methylation controls. Furthermore, DNA extracts and stains on Whatman FTA cards from two semen samples were used to evaluate concordance and mimic casework samples. Overall, the assay yielded high read depths (> 1000 reads) at all 13 marker positions. The methylation values obtained indicated robust quantification with an average standard deviation of 2.8% at the expected methylation level of 50% across the 13 markers and a good performance with 50 ng DNA input into bisulfite conversion. The absolute difference of quantifications from one participating laboratory to the mean quantifications of concordance and semen stains of remaining laboratories was approximately 1%. These results demonstrated the assay to be robust and suitable for age estimation from semen in forensic investigations. In addition to the 13-marker assay, a more streamlined protocol combining only five age markers in one multiplex PCR was developed. Preliminary results showed no substantial differences in DNA methylation quantification between the two assays, indicating its applicability with the VISAGE age model for semen developed with data from the complete 13-marker tool.

Epigenetic age prediction in semen - marker selection and model development

DNA methylation analysis is becoming increasingly useful in biomedical research and forensic practice. The discovery of differentially methylated sites (DMSs) that continuously change over an individual's lifetime has led to breakthroughs in molecular age estimation. Although semen samples are often used in forensic DNA analysis, previous epigenetic age prediction studies mainly focused on somatic cell types. Here, Infinium MethylationEPIC BeadChip arrays were applied to semen-derived DNA samples, which identified numerous novel DMSs moderately correlated with age. Validation of the ten most age-correlated novel DMSs and three previously known sites in an independent set of semen-derived DNA samples using targeted bisulfite massively parallel sequencing, confirmed age-correlation for nine new and three previously known markers. Prediction modelling revealed the best model for semen, based on 6 CpGs from newly identified genes SH2B2, EXOC3, IFITM2, and GALR2 as well as the previously known FOLH1B gene, which predict age with a mean absolute error of 5.1 years in an independent test set. Further increases in the accuracy of age prediction from semen DNA will require technological progress to allow sensitive, simultaneous analysis of a much larger number of age correlated DMSs from the compromised DNA typical of forensic semen stains.

Development of a multiplex methylation-sensitive restriction enzyme-based SNP typing system for deconvolution of semen-containing mixtures

The identification of mixed stains has always been a difficult problem in personal identification in the forensic field. In recent years, tissue-specific methylation sites have proven to be very stable biomarkers for distinguishing tissue origin. However, it is still challenging to perform tissue source identification and individual identification simultaneously. In this study, we developed a method that uses tissue-specific methylation markers combined with single-nucleotide polymorphism (SNP) markers to detect semen from mixed biofluids and to identify individuals simultaneously. Semen-specific CpG markers were chosen from the literature and further validated utilizing methylation-sensitive restriction endonuclease (MSRE) combined with PCR technology. The neighboring SNP markers were searched in the flanking sequence of the target CpG within 400 bp, and SNP typing was then carried out through a single-base extension reaction followed by capillary electrophoresis. Eventually, a method of MSRE combined with SNaPshot that could detect 12 compound CpG-SNP markers was developed. Using this system, 10 ng of total DNA and DNA mixture with semen content up to 25% could be typed successfully. Moreover, the cumulative discrimination power of the system in the northern Chinese Han population is 0.9998. This study provides a valuable strategy for forensic practice to perform tissue origin and individual identification from mixed stains simultaneously.

Age estimation using DNA methylation technique in forensics: a systematic review

Background

In addition to the DNA sequence, epigenetic markers have become substantial forensic tools during the last decade. Estimating the age of an individual from human biological remains may provide information for a forensic investigation. Age estimation in molecular strategies can be obtained by telomere length, mRNa mutation, or by sjTRECs but the accuracy is not sufficient in forensic practice because of high margin error.

Main body

One solution to this problem is to use DNA methylation methods. DNA methylation markers for tissue identification at age-associated CpG sites have been suggested as the most informative biomarkers for estimating the age of an unknown donor. This review aims to give an overview of DNA methylation profiling for estimating the age in cases of forensic relevance and the important aspects in determining the mean absolute deviation (MAD) or mean absolute error (MAE) of the estimated age. Online database searching was performed through PubMed, Scopus, and Google Scholar with keywords selected for forensic age estimation. Thirty-two studies were included in the review, with variable DNA samples but blood commonly as a source. Pyrosequencing and EpiTYPER were methods mostly used in DNA analysis. The MAD in the estimates from DNA methylation was about 3 to 5 years, which was better than other methods such as those based on telomere length or signal-joint T-cell receptor excision circles. The ELOVL2 gene was a commonly used DNA methylation marker in age estimation.

Conclusion

DNA methylation is a favorable candidate for estimating the age at the time of death in forensic profiling, with an uncertainty mean absolute deviation of about 3 to 5 years in the predicted age. The sample type, platform techniques used, and methods to construct age predictive models were important in determining the accuracy in mean absolute deviation or mean absolute error. The DNA methylation outcome suggests good potential to support conventional STR profiling in forensic cases.

Serum dioxin levels and sperm DNA methylation age: Findings in Vietnam war veterans exposed to Agent Orange

Exposure to dioxin, a known endocrine disruptor and carcinogen, is associated with poor reproductive outcomes. Yet, few studies have explored the role of DNA methylation in these relationships. Utilizing a publicly available dataset from 37 male Air Force Health Study participants exposed to dioxin-contaminated Agent Orange during the Vietnam war, we cross-sectionally examined the relationship of serum dioxin levels with a novel DNA methylation-based measure of sperm age (DNAm-agesperm). DNAm-agesperm was calculated using CpG sites on the Illumina HumanMethylation450 BeadChip. We estimated associations of dioxin levels with DNAm-agesperm using linear regression models adjusted for chronological age, body mass index, and smoking status. Chronological age was highly correlated with DNAmagesperm (r = 0.80). In fully-adjusted linear models, a one percent increase in serum dioxin levels was significantly associated with a 0.0126-year (i.e. 4.6-day) increase in DNAm-agesperm (95%CI: 0.003, 0.022, p = 0.01). Further analyses demonstrated significant negative associations of dioxin levels (β = -0.0005, 95%CI: -0.0010, 0.00004, P = 0.03) and DNAm-agesperm (β = -0.02, 95%CI: -0.04, -0.001, P = 0.03) with methylation levels of FOXK2 - a gene previously reported to be hypomethylated in infertile men. In sum, we demonstrate associations of dioxin with increased methylation aging of sperm. DNAm-agesperm may provide utility for understanding how dioxin levels impact sperm health and potentially male reproductive capacity in human population studies. Moreover, our pilot study contributes further evidence that some environmental toxicants are associated with methylation aging. Additional studies are necessary to confirm these findings, and better characterize dioxin and sperm methylation relationships with male reproductive health.

Estimation of the age of human semen stains by attenuated total reflection Fourier transform infrared spectroscopy: a preliminary study

Semen stain is one of the most important biological evidence at sexual crime scenes. Age estimation of human semen stains plays an important role in forensic work, and it is rarely studied due to lack of well-established methods. In this study, the technique called attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR) coupled with advanced chemometric methods was employed to determine the age of semen stains on three different substrates: glass slides, tissues and fabric made of regenerated cellulose fibres up to 6 d. Partial least squares regression (PLSR) was used in conjunction with spectral analysis for age estimation, and the results generated high R² values (cross-validation: 0.81, external validation: 0.74) but a narrow margin of error for root mean square error (RMSE) (RMSE of cross-validation: 0.77 d, RMSE of prediction: 1.02 d). Additionally, our results indicated the robustness of PLSR model was not weaken by the influence of different substrates in this study. Our results indicate that ATR-FTIR, combined with chemometric methods, shows great potential as a convenient and efficient tool for age estimation of semen stains. Moreover, the method could be applied to routine forensic investigations in the future.

Methylation-Based Age Prediction Using Pyrosequencing Platform from Seminal Stains in Han Chinese Males

Various methods have been performed to predict an unknown individual's age from biological traces in forensic investigations. A considerably accurate age prediction for the semen donor can help narrow down the search in a sexual assault case. The aim of this study was to develop an assay for age prediction from seminal stains in Han Chinese males. We built a sperm-specific linear regression model using bisulfite pyrosequencing. Validations were conducted with a Mean Absolute Deviation from the chronological age (MAD) of 4.219 years in liquid semen, 4.158 years in fresh seminal stains, 4.393 years in aged seminal stains, and 3.880 years in mixed stains, respectively. Furthermore, our strategy enables accurate age prediction using a forensic casework sample. The strategy indicated that we produced an accurate and reliable age prediction tool for the semen donors in Han Chinese males for forensic purposes.

Age Prediction Based on Brain MRI Image: A Survey

Human age prediction is an interesting and applicable issue in different fields. It can be based on various criteria such as face image, DNA methylation, chest plate radiographs, knee radiographs, dental images and etc. Most of the age prediction researches have mainly been based on images. Since the image processing and Machine Learning (ML) techniques have grown up, the investigations were led to use them in age prediction problem. The implementations would be used in different fields, especially in medical applications. Brain Age Estimation (BAE) has attracted more attention in recent years and it would be so helpful in early diagnosis of some neurodegenerative diseases such as Alzheimer, Parkinson, Huntington, etc. BAE is performed on Magnetic Resonance Imaging (MRI) images to compute the brain ages. Studies based on brain MRI shows that there is a relation between accelerated aging and accelerated brain atrophy. This refers to the effects of neurodegenerative diseases on brain structure while making the whole of it older. This paper reviews and summarizes the main approaches for age prediction based on brain MRI images including preprocessing methods, useful tools used in different research works and the estimation algorithms. We categorize the BAE methods based on two factors, first the way of processing MRI images, which includes pixel-based, surface-based, or voxel-based methods and second, the generation of ML algorithms that includes traditional or Deep Learning (DL) methods. The modern techniques as DL methods help MRI based age prediction to get results that are more accurate. In recent years, more precise and statistical ML approaches have been utilized with the help of related tools for simplifying computations and getting accurate results. Pros and cons of each research and the challenges in each work are expressed and some guidelines and deliberations for future research are suggested.

Epigenetic Clocks

Recent research has revealed clock-like patterns of epigenetic change across the life span in humans. Models describing these epigenetic changes have been dubbed "epigenetic clocks," and they can not only predict chronological age but also reveal biological age, which measures physiological homeostasis and deterioration over the life span. Comparative studies of the epigenetic clocks of different primate species are likely to provide insights into the evolution of life history schedules, as well as shed light on the physiological and genetic bases of aging and aging-related diseases. Chronological age estimation using clock-based calculators may also offer biological anthropologists a useful tool for applying to forensic and demographic studies.