Development of a forensically useful age prediction method based on DNA methylation analysis

Development of a methylation marker set for forensic age estimation using analysis of public methylation data and the Agena Bioscience EpiTYPER system

Individual age estimation has the potential to provide key information that could enhance and extend DNA intelligence tools. Following predictive tests for externally visible characteristics developed in recent years, prediction of age could guide police investigations and improve the assessment of age-related phenotype expression patterns such as hair colour changes and early onset of male pattern baldness. DNA methylation at CpG positions has emerged as the most promising DNA tests to ascertain the individual age of the donor of a biological contact trace. Although different methodologies are available to detect DNA methylation, EpiTYPER technology (Agena Bioscience, formerly Sequenom) provides useful characteristics that can be applied as a discovery tool in localized regions of the genome. In our study, a total of twenty-two candidate genomic regions, selected from the assessment of publically available data from the Illumina HumanMethylation 450 BeadChip, had a total of 177 CpG sites with informative methylation patterns that were subsequently investigated in detail. From the methylation analyses made, a novel age prediction model based on a multivariate quantile regression analysis was built using the seven highest age-correlated loci of ELOVL2, ASPA, PDE4C, FHL2, CCDC102B, C1orf132 and chr16:85395429. The detected methylation levels in these loci provide a median absolute age prediction error of ±3.07years and a percentage of prediction error relative to the age of 6.3%. We report the predictive performance of the developed model using cross validation of a carefully age-graded training set of 725 European individuals and a test set of 52 monozygotic twin pairs. The multivariate quantile regression age predictor, using the CpG sites selected in this study, has been placed in the open-access Snipper forensic classification website.

Human age estimation from blood using mRNA, DNA methylation, DNA rearrangement, and telomere length

Establishing the age of unknown persons, or persons with unknown age, can provide important leads in police investigations, disaster victim identification, fraud cases, and in other legal affairs. Previous methods mostly relied on morphological features available from teeth or skeletal parts. The development of molecular methods for age estimation allowing to use human specimens that possess no morphological age information, such as bloodstains, is extremely valuable as this type of samples is commonly found at crime scenes. Recently, we introduced a DNA-based approach for human age estimation from blood based on the quantification of T-cell specific DNA rearrangements (sjTRECs), which achieves accurate assignment of blood DNA samples to one of four 20-year-interval age categories. Aiming at improving the accuracy of molecular age estimation from blood, we investigated different types of biomarkers. We started out by systematic genome-wide surveys for new age-informative mRNA and DNA methylation markers in blood from the same young and old individuals using microarray technologies. The obtained candidate markers were validated in independent samples covering a wide age range using alternative technologies together with previously proposed DNA methylation, sjTREC, and telomere length markers. Cross-validated multiple regression analysis was applied for estimating and validating the age predictive power of various sets of biomarkers within and across different marker types. We found that DNA methylation markers outperformed mRNA, sjTREC, and telomere length in age predictive power. The best performing model included 8 DNA methylation markers derived from 3 CpG islands reaching a high level of accuracy (cross-validated R(2)=0.88, SE±6.97 years, mean absolute deviation 5.07 years). However, our data also suggest that mRNA markers can provide independent age information: a model using a combined set of 5 DNA methylation markers and one mRNA marker could provide similarly high accuracy (cross-validated R(2)=0.86, SE±7.62 years, mean absolute deviation 4.60 years). Overall, our study provides new and confirms previously suggested molecular biomarkers for age estimation from blood. Moreover, our comparative study design revealed that DNA methylation markers are superior for this purpose over other types of molecular biomarkers tested. While the new and some previous findings are highly promising, before molecular age estimation can eventually meet forensic practice, the proposed biomarkers should be tested further in larger sets of blood samples from both healthy and unhealthy individuals, and markers and genotyping methods shall be validated to meet forensic standards.

Improved age determination of blood and teeth samples using a selected set of DNA methylation markers

Age estimation from DNA methylation markers has seen an exponential growth of interest, not in the least from forensic scientists. The current published assays, however, can still be improved by lowering the number of markers in the assay and by providing more accurate models to predict chronological age. From the published literature we selected 4 age-associated genes (ASPA, PDE4C, ELOVL2, and EDARADD) and determined CpG methylation levels from 206 blood samples of both deceased and living individuals (age range: 0-91 years). This data was subsequently used to compare prediction accuracy with both linear and non-linear regression models. A quadratic regression model in which the methylation levels of ELOVL2 were squared showed the highest accuracy with a Mean Absolute Deviation (MAD) between chronological age and predicted age of 3.75 years and an adjusted R(2) of 0.95. No difference in accuracy was observed for samples obtained either from living and deceased individuals or between the 2 genders. In addition, 29 teeth from different individuals (age range: 19-70 years) were analyzed using the same set of markers resulting in a MAD of 4.86 years and an adjusted R(2) of 0.74. Cross validation of the results obtained from blood samples demonstrated the robustness and reproducibility of the assay. In conclusion, the set of 4 CpG DNA methylation markers is capable of producing highly accurate age predictions for blood samples from deceased and living individuals.