Epigenetic clocks are valuable tools to generate investigative leads for the identification of unknown DNA donors. Most existing clocks have been developed using tissues that are easily accessible and easy to work with, such as blood. However, only a limited number of studies have focused on human remains, specifically bone, although it is crucial in forensic anthropology. In this field, skeletal remains are often recovered years post-mortem, after the decomposition of soft tissues. Similarly, mass disasters require the identification of numerous remains within a limited time frame. In such circumstances, estimating the age-at-death from bone samples could substantially support the identification process.

This study aims to discover novel CpG sites correlated with age in bone tissue using a targeted DNA methylation analysis system. To do so, a subset of bone samples was analyzed using the Twist Human Methylome Panel (Twist Bioscience), which targets approximately four million CpG sites and uses an enzymatic conversion process. Prior to bone sample analysis, the protocol was optimized using artificial human DNA methylation controls prepared with different methylation percentages (0% to 100% methylated) at varying genomic DNA inputs (20ng, 80ng and 130ng) to determine the optimal amount of input genomic DNA. DNA methylation data from all samples were generated using a bioinformatic pipeline developed in Linux (Ubuntu). With DNA methylation data generated from bone samples, Spearman correlations were calculated. Based on those correlations, the most informative CpG sites were selected, and a comparative analysis with the CpG sites already reported in the literature was carried out. 

The study received funding from the European Union’s Horizon Europe Programme under Grant agreement no. 101225631. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or REA.

Authors

• Mafalda Silva (Forensic Genetics Unit, Institute of Forensic Sciences, Universidade de Santiago de Compostela, Spain)
• Miguel Boullón-Cassau (Forensic Genetics Unit, Institute of Forensic Sciences, Universidade de Santiago de Compostela, Spain)
• Adrián Ambroa-Conde (Forensic Genetics Unit, Institute of Forensic Sciences, Universidade de Santiago de Compostela, Spain)
• Antonio Gómez-Tato (CITMAga (Center for Mathematical Research and Technology of Galicia), Universidade de Santiago de Compostela, Spain)
• María de los Ángeles Casares de Cal (CITMAga (Center for Mathematical Research and Technology of Galicia), Universidade de Santiago de Compostela, Spain)
• Aleksandra Pisarek-Pacek (Institute of Zoology and Biomedical Research, Jagiellonski University, Poland)
• Ewelina Pośpiech (Department of Genomics and Forensic Genetics, Pomenarian Medical University, Poland)
• Kamila Marszałek (Department of Genomics and Forensic Genetics, Pomenarian Medical University, Poland)
• Walther Parson (Institute of Legal Medicine, Medizinische Universität Innsbruck, Austria; Forensic Science Program, The Pennsylvania State University, University Park, PA, United States, United States of America)
• Antonia Heidegger (Institute of Legal Medicine, Medizinische Universität Innsbruck, Austria)
• Wojciech Branicki (Institute of Zoology and Biomedical Research, Jagiellonski University; Institute of Forensic Research in Kraków, Poland)
• M Victoria Lareu (Forensic Genetics Unit, Institute of Forensic Sciences, Universidade de Santiago de Compostela, Spain)
• Ana Freire-Aradas (Forensic Genetics Unit, Institute of Forensic Sciences, Universidade de Santiago de Compostela, Spain)