A Blood–Bone–Tooth Model for Age Prediction in Forensic Contexts
The development of age prediction models (APMs) focusing on DNA methylation (DNAm) levels has revolutionized the forensic age estimation field. Meanwhile, the predictive ability of multi-tissue models with similar high accuracy needs to be explored. This study aimed to build multi-tissue APMs combin...
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MDPI AG
2021-12-01
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| Online Access: | https://www.mdpi.com/2079-7737/10/12/1312 |
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| author | Helena Correia Dias Licínio Manco Francisco Corte Real Eugénia Cunha |
| author_facet | Helena Correia Dias Licínio Manco Francisco Corte Real Eugénia Cunha |
| author_sort | Helena Correia Dias |
| collection | DOAJ |
| description | The development of age prediction models (APMs) focusing on DNA methylation (DNAm) levels has revolutionized the forensic age estimation field. Meanwhile, the predictive ability of multi-tissue models with similar high accuracy needs to be explored. This study aimed to build multi-tissue APMs combining blood, bones and tooth samples, herein named blood–bone–tooth-APM (BBT-APM), using two different methodologies. A total of 185 and 168 bisulfite-converted DNA samples previously addressed by Sanger sequencing and SNaPshot methodologies, respectively, were considered for this study. The relationship between DNAm and age was assessed using simple and multiple linear regression models. Through the Sanger sequencing methodology, we built a BBT-APM with seven CpGs in genes <i>ELOVL2</i>, <i>EDARADD</i>, <i>PDE4C</i>, <i>FHL2</i> and <i>C1orf132</i>, allowing us to obtain a Mean Absolute Deviation (MAD) between chronological and predicted ages of 6.06 years, explaining 87.8% of the variation in age. Using the SNaPshot assay, we developed a BBT-APM with three CpGs at <i>ELOVL2, KLF14</i> and <i>C1orf132</i> genes with a MAD of 6.49 years, explaining 84.7% of the variation in age. Our results showed the usefulness of DNAm age in forensic contexts and brought new insights into the development of multi-tissue APMs applied to blood, bone and teeth. |
| first_indexed | 2024-03-10T04:34:30Z |
| format | Article |
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| institution | Directory Open Access Journal |
| issn | 2079-7737 |
| language | English |
| last_indexed | 2024-03-10T04:34:30Z |
| publishDate | 2021-12-01 |
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| series | Biology |
| spelling | doaj.art-37437df9a48940b38457e228766094c02023-11-23T03:54:09ZengMDPI AGBiology2079-77372021-12-011012131210.3390/biology10121312A Blood–Bone–Tooth Model for Age Prediction in Forensic ContextsHelena Correia Dias0Licínio Manco1Francisco Corte Real2Eugénia Cunha3Research Centre for Anthropology and Health (CIAS), Department of Life Sciences, University of Coimbra, 3000-456 Coimbra, PortugalResearch Centre for Anthropology and Health (CIAS), Department of Life Sciences, University of Coimbra, 3000-456 Coimbra, PortugalNational Institute of Legal Medicine and Forensic Sciences, 3000-548 Coimbra, PortugalCentre for Functional Ecology (CEF), Laboratory of Forensic Anthropology, Department of Life Sciences, University of Coimbra, 3000-456 Coimbra, PortugalThe development of age prediction models (APMs) focusing on DNA methylation (DNAm) levels has revolutionized the forensic age estimation field. Meanwhile, the predictive ability of multi-tissue models with similar high accuracy needs to be explored. This study aimed to build multi-tissue APMs combining blood, bones and tooth samples, herein named blood–bone–tooth-APM (BBT-APM), using two different methodologies. A total of 185 and 168 bisulfite-converted DNA samples previously addressed by Sanger sequencing and SNaPshot methodologies, respectively, were considered for this study. The relationship between DNAm and age was assessed using simple and multiple linear regression models. Through the Sanger sequencing methodology, we built a BBT-APM with seven CpGs in genes <i>ELOVL2</i>, <i>EDARADD</i>, <i>PDE4C</i>, <i>FHL2</i> and <i>C1orf132</i>, allowing us to obtain a Mean Absolute Deviation (MAD) between chronological and predicted ages of 6.06 years, explaining 87.8% of the variation in age. Using the SNaPshot assay, we developed a BBT-APM with three CpGs at <i>ELOVL2, KLF14</i> and <i>C1orf132</i> genes with a MAD of 6.49 years, explaining 84.7% of the variation in age. Our results showed the usefulness of DNAm age in forensic contexts and brought new insights into the development of multi-tissue APMs applied to blood, bone and teeth.https://www.mdpi.com/2079-7737/10/12/1312DNA methylation (DNAm)epigenetic age estimationmulti-tissue age prediction models (APMs)Sanger sequencingSNaPshot |
| spellingShingle | Helena Correia Dias Licínio Manco Francisco Corte Real Eugénia Cunha A Blood–Bone–Tooth Model for Age Prediction in Forensic Contexts Biology DNA methylation (DNAm) epigenetic age estimation multi-tissue age prediction models (APMs) Sanger sequencing SNaPshot |
| title | A Blood–Bone–Tooth Model for Age Prediction in Forensic Contexts |
| title_full | A Blood–Bone–Tooth Model for Age Prediction in Forensic Contexts |
| title_fullStr | A Blood–Bone–Tooth Model for Age Prediction in Forensic Contexts |
| title_full_unstemmed | A Blood–Bone–Tooth Model for Age Prediction in Forensic Contexts |
| title_short | A Blood–Bone–Tooth Model for Age Prediction in Forensic Contexts |
| title_sort | blood bone tooth model for age prediction in forensic contexts |
| topic | DNA methylation (DNAm) epigenetic age estimation multi-tissue age prediction models (APMs) Sanger sequencing SNaPshot |
| url | https://www.mdpi.com/2079-7737/10/12/1312 |
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