Age-at-death estimation is central to bioarchaeological and forensic research, for reconstructing past population demographics and for narrowing down the identity of individuals from their unidentified remains. Recent advances in genetics have led to the identification of DNA methylation markers that change with age and could be used in new methods of age prediction, but generally using tissue types that are not always available in archaeological and forensic contexts. In this doctoral dissertation project, samples of human bone across a range of known ages will be analyzed to determine regions of the genome that change most reliably with age. These data will be used to develop a method of predicting an individual's age from their bones, which may show different patterns of methylation compared with other tissue types. The protocol and algorithms used in this project will be made freely available online, and the project will support graduate and undergraduate training and research in a STEM discipline.
While age-associated changes in DNA methylation are well known in the field of epigenetics, most research conducted so far has been in blood and saliva tissues that can be easily obtained from living individuals. DNA methylation patterns are known to differ significantly between tissue types, and epigenetic age prediction models developed for a particular tissue type cannot be automatically applied to another. Therefore, in order to extend the applicability of DNA methylation-based age prediction to forensic contexts, more research on specific forensically relevant tissues is necessary. In this project, the researchers will first generate a genome-wide DNA methylation dataset from human bone collected through a body donation program. DNA will be extracted from these bone samples and their DNA methylation levels will be measured at over 850,000 sites across the genome using a commercially available array. This dataset will be analyzed statistically to identify specific regions of the genome that vary in a strong, predictable manner with age. The DNA methylation patterns at these regions will be used to develop a statistical model that can accurately estimate chronological age. Finally, a protocol to target and measure methylation levels at only these highly age-associated genomic regions will be developed, which will allow the age estimation method to be applied at a much lower cost
This grant is jointly supported by NSF and the National Institute of Justice, Office of Investigative and Forensic Sciences.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
