Development of a methylation marker set for forensic age estimation using analysis of public methylation data and the Agena Bioscience EpiTYPER system |
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| Affiliation: | 1. Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Spain;2. Faculty of Mathematics, University of Santiago de Compostela, Spain;3. Spanish National Genotyping Center-USC-PRB2-ISCIII, Santiago de Compostela, Spain;4. Institute of Legal Medicine, Faculty of Medicine, University of Cologne, Cologne, Germany;5. Institute of Zoology, Faculty of Biology and Earth Sciences, Jagiellonian University, Krakow, Poland;6. Malopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland;7. Center of Excellence in Genomic Medicine Research, King Abdulaziz University, Jeddah, Saudi Arabia;1. Institute of Forensic Medicine, West China School of Preclinical and Forensic Medicine, Sichuan University, Chengdu 610041, Sichuan, China;2. Clinical and Translational Research Institute, University of California, San Diego. 9500 Gilman Dr., MC 0990, La Jolla, CA 92093-0990, USA;1. University of Amsterdam, Swammerdam Institute for Life Sciences, Science Park 904, 1098XH Amsterdam, The Netherlands;2. Amsterdam Medical Center, Clinical Genetics, Meibergdreef 9, 1105AZ, Amsterdam, The Netherlands;3. Netherlands Forensic Institute, Biological Traces, Laan van Ypenburg 6, 2497GB Den Haag, The Netherlands;4. University of Amsterdam, Institute for Biodiversity and Dynamics, Science Park 904, 1098XH Amsterdam, The Netherlands;1. Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands;2. Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China;3. Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands;4. Center for Biomics, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands;5. Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands;6. Epigenomics AG, Berlin, Germany;1. Department of Forensic Medicine, Graduate School of Medicine, Kyoto University, Sakyo-ku, Kyoto, Japan;2. Forensic Science Laboratory, Kyoto Prefectural Police Headquarters, Kamigyo-ku, Kyoto, Japan;1. Central Forensic Laboratory of the Police, Aleje Ujazdowskie 7, 00-583 Warsaw, Poland;2. Institute of Forensic Research, Westerplatte 9, 31-033 Krakow, Poland;3. BioVectis, Pawińskiego 5a/d, 02-106 Warsaw, Poland;4. Medical University of Warsaw, Żwirki i Wigury 61, 02-091 Warsaw, Poland |
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| Abstract: | 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 ±3.07 years 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. |
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| Keywords: | Forensic age estimation DNA methylation Agena Bioscience EpiTYPER Illumina HumanMethylation 450K CpG sites Multivariate quantile regression |
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