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Ambroa-Conde A, Casares de Cal MA, Gómez-Tato A, Robinson O, Mosquera-Miguel A, de la Puente M, Ruiz-Ramírez J, Phillips C, Lareu MV, Freire-Aradas A. Inference of tobacco and alcohol consumption habits from DNA methylation analysis of blood. Forensic Sci Int Genet 2024; 70:103022. [PMID: 38309257 DOI: 10.1016/j.fsigen.2024.103022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 12/22/2023] [Accepted: 01/25/2024] [Indexed: 02/05/2024]
Abstract
DNA methylation has become a biomarker of great interest in the forensic and clinical fields. In criminal investigations, the study of this epigenetic marker has allowed the development of DNA intelligence tools providing information that can be useful for investigators, such as age prediction. Following a similar trend, when the origin of a sample in a criminal scenario is unknown, the inference of an individual's lifestyle such as tobacco use and alcohol consumption could provide relevant information to help in the identification of DNA donors at the crime scene. At the same time, in the clinical domain, prediction of these trends of consumption could allow the identification of people at risk or better identification of the causes of different pathologies. In the present study, DNA methylation data from the UK AIRWAVE study was used to build two binomial logistic models for the inference of smoking and drinking status. A total of 348 individuals (116 non-smokers, 116 former smokers and 116 smokers) plus a total of 237 individuals (79 non-drinkers, 79 moderate drinkers and 79 drinkers) were used for development of tobacco and alcohol consumption prediction models, respectively. The tobacco prediction model was composed of two CpGs (cg05575921 in AHRR and cg01940273) and the alcohol prediction model three CpGs (cg06690548 in SLC7A11, cg0886875 and cg21294714 in MIR4435-2HG), providing correct classifications of 86.49% and 74.26%, respectively. Validation of the models was performed using leave-one-out cross-validation. Additionally, two independent testing sets were also assessed for tobacco and alcohol consumption. Considering that the consumption of these substances could underlie accelerated epigenetic ageing patterns, the effect of these lifestyles on the prediction of age was evaluated. To do that, a quantile regression model based on previous studies was generated, and the potential effect of tobacco and alcohol consumption with the epigenetic age was assessed. The Wilcoxon test was used to evaluate the residuals generated by the model and no significant differences were observed between the categories analyzed.
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Affiliation(s)
- A Ambroa-Conde
- Forensic Genetics Unit, Institute of Forensic Sciences, Universidade de Santiago de Compostela, Spain
| | - M A Casares de Cal
- CITMAga (Center for Mathematical Research and Technology of Galicia), University of Santiago de Compostela, Spain
| | - A Gómez-Tato
- CITMAga (Center for Mathematical Research and Technology of Galicia), University of Santiago de Compostela, Spain
| | - O Robinson
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - A Mosquera-Miguel
- Forensic Genetics Unit, Institute of Forensic Sciences, Universidade de Santiago de Compostela, Spain
| | - M de la Puente
- Forensic Genetics Unit, Institute of Forensic Sciences, Universidade de Santiago de Compostela, Spain
| | - J Ruiz-Ramírez
- Forensic Genetics Unit, Institute of Forensic Sciences, Universidade de Santiago de Compostela, Spain
| | - C Phillips
- Forensic Genetics Unit, Institute of Forensic Sciences, Universidade de Santiago de Compostela, Spain
| | - M V Lareu
- Forensic Genetics Unit, Institute of Forensic Sciences, Universidade de Santiago de Compostela, Spain
| | - A Freire-Aradas
- Forensic Genetics Unit, Institute of Forensic Sciences, Universidade de Santiago de Compostela, Spain.
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2
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Casanova-Adán L, Mosquera-Miguel A, González-Bao J, Ambroa-Conde A, Ruiz-Ramírez J, Cabrejas-Olalla A, González-Martín E, Freire-Aradas A, Rodríguez-López A, Phillips C, Lareu MV, de la Puente M. Adapting an established Ampliseq microhaplotype panel to nanopore sequencing through direct PCR. Forensic Sci Int Genet 2023; 67:102937. [PMID: 37812882 DOI: 10.1016/j.fsigen.2023.102937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 09/21/2023] [Accepted: 09/27/2023] [Indexed: 10/11/2023]
Abstract
We have adapted an established Ampliseq microhaplotype panel for nanopore sequencing with the Oxford Nanopore Technologies (ONT) system, as a cost-effective and highly scalable solution for forensic genetics applications. For this purpose, we designed a protocol combining direct PCR amplification from unextracted DNA with ONT library construction and sequencing using the MinION device and workflow. The analysis of reference samples at input amounts of 5-10 ng of DNA demonstrates stable coverage patterns, allele balance, and strand bias, reaching profile completeness and concordance rates of ∼95%. Similar levels were achieved when using direct-PCR from blood, buccal and semen swabs. Dilution series results indicate sensitivity is maintained down to 250 pg of input DNA, and informative profiles are produced down to 62.5 pg. Finally, we demonstrated the forensic utility of the nanopore workflow by analyzing two third degree pedigrees that showed low likelihood ratio values after the analysis of an extended panel of 38 STRs, achieving likelihood ratios 2-3 orders of magnitude higher when testing with the MinION-based haplotype data.
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Affiliation(s)
- L Casanova-Adán
- Forensic Genetics Unit, Institute of Forensic Sciences, Universidade de Santiago de Compostela, Spain
| | - A Mosquera-Miguel
- Forensic Genetics Unit, Institute of Forensic Sciences, Universidade de Santiago de Compostela, Spain
| | - J González-Bao
- Forensic Genetics Unit, Institute of Forensic Sciences, Universidade de Santiago de Compostela, Spain
| | - A Ambroa-Conde
- Forensic Genetics Unit, Institute of Forensic Sciences, Universidade de Santiago de Compostela, Spain
| | - J Ruiz-Ramírez
- Forensic Genetics Unit, Institute of Forensic Sciences, Universidade de Santiago de Compostela, Spain
| | - A Cabrejas-Olalla
- Forensic Genetics Unit, Institute of Forensic Sciences, Universidade de Santiago de Compostela, Spain
| | - E González-Martín
- Forensic Genetics Unit, Institute of Forensic Sciences, Universidade de Santiago de Compostela, Spain
| | - A Freire-Aradas
- Forensic Genetics Unit, Institute of Forensic Sciences, Universidade de Santiago de Compostela, Spain
| | - A Rodríguez-López
- Forensic Genetics Unit, Institute of Forensic Sciences, Universidade de Santiago de Compostela, Spain
| | - C Phillips
- Forensic Genetics Unit, Institute of Forensic Sciences, Universidade de Santiago de Compostela, Spain
| | - M V Lareu
- Forensic Genetics Unit, Institute of Forensic Sciences, Universidade de Santiago de Compostela, Spain
| | - M de la Puente
- Forensic Genetics Unit, Institute of Forensic Sciences, Universidade de Santiago de Compostela, Spain.
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3
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Freire-Aradas A, Tomsia M, Piniewska-Róg D, Ambroa-Conde A, Casares de Cal MA, Pisarek A, Gómez-Tato A, Álvarez-Dios J, Pośpiech E, Parson W, Kayser M, Phillips C, Branicki W. Development of an epigenetic age predictor for costal cartilage with a simultaneous somatic tissue differentiation system. Forensic Sci Int Genet 2023; 67:102936. [PMID: 37783021 DOI: 10.1016/j.fsigen.2023.102936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 09/13/2023] [Accepted: 09/27/2023] [Indexed: 10/04/2023]
Abstract
Age prediction from DNA has been a topic of interest in recent years due to the promising results obtained when using epigenetic markers. Since DNA methylation gradually changes across the individual's lifetime, prediction models have been developed accordingly for age estimation. The tissue-dependence for this biomarker usually necessitates the development of tissue-specific age prediction models, in this way, multiple models for age inference have been constructed for the most commonly encountered forensic tissues (blood, oral mucosa, semen). The analysis of skeletal remains has also been attempted and prediction models for bone have now been reported. Recently, the VISAGE Enhanced Tool was developed for the simultaneous DNA methylation analysis of 8 age-correlated loci using targeted high-throughput sequencing. It has been shown that this method is compatible with epigenetic age estimation models for blood, buccal cells, and bone. Since when dealing with decomposed cadavers or postmortem samples, cartilage samples are also an important biological source, an age prediction model for cartilage has been generated in the present study based on methylation data collected using the VISAGE Enhanced Tool. In this way, we have developed a forensic cartilage age prediction model using a training set composed of 109 samples (19-74 age range) based on DNA methylation levels from three CpGs in FHL2, TRIM59 and KLF14, using multivariate quantile regression which provides a mean absolute error (MAE) of ± 4.41 years. An independent testing set composed of 72 samples (19-75 age range) was also analyzed and provided an MAE of ± 4.26 years. In addition, we demonstrate that the 8 VISAGE markers, comprising EDARADD, TRIM59, ELOVL2, MIR29B2CHG, PDE4C, ASPA, FHL2 and KLF14, can be used as tissue prediction markers which provide reliable blood, buccal cells, bone, and cartilage differentiation using a developed multinomial logistic regression model. A training set composed of 392 samples (n = 87 blood, n = 86 buccal cells, n = 110 bone and n = 109 cartilage) was used for building the model (correct classifications: 98.72%, sensitivity: 0.988, specificity: 0.996) and validation was performed using a testing set composed of 192 samples (n = 38 blood, n = 36 buccal cells, n = 46 bone and n = 72 cartilage) showing similar predictive success to the training set (correct classifications: 97.4%, sensitivity: 0.968, specificity: 0.991). By developing both a new cartilage age model and a tissue differentiation model, our study significantly expands the use of the VISAGE Enhanced Tool while increasing the amount of DNA methylation-based information obtained from a single sample and a single forensic laboratory analysis. Both models have been placed in the open-access Snipper forensic classification website.
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Affiliation(s)
- A Freire-Aradas
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Spain.
| | - M Tomsia
- Department of Forensic Medicine and Forensic Toxicology, Medical University of Silesia, Katowice, Poland
| | - D Piniewska-Róg
- Department of Forensic Medicine, Jagiellonian University Medical College, Kraków, Poland
| | - A Ambroa-Conde
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Spain
| | - M A Casares de Cal
- CITMAga (Center for Mathematical Research and Technology of Galicia), University of Santiago de Compostela, Spain
| | - A Pisarek
- Institute of Zoology and Biomedical Research, Jagiellonian University, Kraków, Poland
| | - A Gómez-Tato
- CITMAga (Center for Mathematical Research and Technology of Galicia), University of Santiago de Compostela, Spain
| | - J Álvarez-Dios
- Faculty of Mathematics, University of Santiago de Compostela, Spain
| | - E Pośpiech
- Malopolska Centre of Biotechnology, Jagiellonian University, Kraków, Poland; Department of Forensic Genetics, Pomeranian Medical University in Szczecin, Poland
| | - W Parson
- Institute of Legal Medicine, Medical University of Innsbruck, Austria; Forensic Science Program, Pennsylvania State University, PA, USA
| | - M Kayser
- Department of Forensic Molecular Biology, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - C Phillips
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Spain
| | - W Branicki
- Institute of Zoology and Biomedical Research, Jagiellonian University, Kraków, Poland; Institute of Forensic Research, Kraków, Poland.
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Ruiz-Ramírez J, de la Puente M, Xavier C, Ambroa-Conde A, Álvarez-Dios J, Freire-Aradas A, Mosquera-Miguel A, Ralf A, Amory C, Katsara MA, Khellaf T, Nothnagel M, Cheung EYY, Gross TE, Schneider PM, Uacyisrael J, Oliveira S, Klautau-Guimarães MDN, Carvalho-Gontijo C, Pośpiech E, Branicki W, Parson W, Kayser M, Carracedo A, Lareu MV, Phillips C. Development and evaluations of the ancestry informative markers of the VISAGE Enhanced Tool for Appearance and Ancestry. Forensic Sci Int Genet 2023; 64:102853. [PMID: 36917866 DOI: 10.1016/j.fsigen.2023.102853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 02/15/2023] [Accepted: 03/02/2023] [Indexed: 03/07/2023]
Abstract
The VISAGE Enhanced Tool for Appearance and Ancestry (ET) has been designed to combine markers for the prediction of bio-geographical ancestry plus a range of externally visible characteristics into a single massively parallel sequencing (MPS) assay. We describe the development of the ancestry panel markers used in ET, and the enhanced analyses they provide compared to previous MPS-based forensic ancestry assays. As well as established autosomal single nucleotide polymorphisms (SNPs) that differentiate sub-Saharan African, European, East Asian, South Asian, Native American, and Oceanian populations, ET includes autosomal SNPs able to efficiently differentiate populations from Middle East regions. The ability of the ET autosomal ancestry SNPs to distinguish Middle East populations from other continentally defined population groups is such that characteristic patterns for this region can be discerned in genetic cluster analysis using STRUCTURE. Joint cluster membership estimates showing individual co-ancestry that signals North African or East African origins were detected, or cluster patterns were seen that indicate origins from central and Eastern regions of the Middle East. In addition to an augmented panel of autosomal SNPs, ET includes panels of 85 Y-SNPs, 16 X-SNPs and 21 autosomal Microhaplotypes. The Y- and X-SNPs provide a distinct method for obtaining extra detail about co-ancestry patterns identified in males with admixed backgrounds. This study used the 1000 Genomes admixed African and admixed American sample sets to fully explore these enhancements to the analysis of individual co-ancestry. Samples from urban and rural Brazil with contrasting distributions of African, European, and Native American co-ancestry were also studied to gauge the efficiency of combining Y- and X-SNP data for this purpose. The small panel of Microhaplotypes incorporated in ET were selected because they showed the highest levels of haplotype diversity amongst the seven population groups we sought to differentiate. Microhaplotype data was not formally combined with single-site SNP genotypes to analyse ancestry. However, the haplotype sequence reads obtained with ET from these loci creates an effective system for de-convoluting two-contributor mixed DNA. We made simple mixture experiments to demonstrate that when the contributors have different ancestries and the mixture ratios are imbalanced (i.e., not 1:1 mixtures) the ET Microhaplotype panel is an informative system to infer ancestry when this differs between the contributors.
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Affiliation(s)
- J Ruiz-Ramírez
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain
| | - M de la Puente
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain.
| | - C Xavier
- Institute of Legal Medicine, Medical University of Innsbruck, 6020 Innsbruck, Austria
| | - A Ambroa-Conde
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain
| | - J Álvarez-Dios
- Faculty of Mathematics, University of Santiago de Compostela, 15705 Santiago de Compostela, Spain
| | - A Freire-Aradas
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain
| | - A Mosquera-Miguel
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain
| | - A Ralf
- Department of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, 3015 CN Rotterdam, South Holland, the Netherlands
| | - C Amory
- Institute of Legal Medicine, Medical University of Innsbruck, 6020 Innsbruck, Austria
| | - M A Katsara
- Cologne Center for Genomics, University of Cologne, 50823 Cologne, Germany
| | - T Khellaf
- Cologne Center for Genomics, University of Cologne, 50823 Cologne, Germany
| | - M Nothnagel
- Cologne Center for Genomics, University of Cologne, 50823 Cologne, Germany; University Hospital Cologne, 50937 Cologne, Germany
| | - E Y Y Cheung
- Institute of Legal Medicine, Faculty of Medicine and University Clinic, University of Cologne, 50823 Cologne, Germany
| | - T E Gross
- Institute of Legal Medicine, Faculty of Medicine and University Clinic, University of Cologne, 50823 Cologne, Germany
| | - P M Schneider
- Institute of Legal Medicine, Faculty of Medicine and University Clinic, University of Cologne, 50823 Cologne, Germany
| | - J Uacyisrael
- Fiji Police Forensic Biology and DNA Laboratory, Nasova, Suva, Fiji
| | - S Oliveira
- Departamento Genética e Morfologia, Universidade de Brasília, Brasília, DF, Brazil
| | | | - C Carvalho-Gontijo
- Departamento Genética e Morfologia, Universidade de Brasília, Brasília, DF, Brazil
| | - E Pośpiech
- Malopolska Centre of Biotechnology, Jagiellonian University, 30-387 Kraków, Poland
| | - W Branicki
- Institute of Zoology and Biomedical Research, Jagiellonian University, 30-387 Kraków, Poland
| | - W Parson
- Institute of Legal Medicine, Medical University of Innsbruck, 6020 Innsbruck, Austria; Forensic Science Program, The Pennsylvania State University, University Park, State College, PA 16802, USA
| | - M Kayser
- Department of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, 3015 CN Rotterdam, South Holland, the Netherlands
| | - A Carracedo
- Fundación Pública Galega de Medicina Xenómica (FPGMX), Instituto de Investigación Sanitaria (IDIS),15706 Santiago de Compostela, Spain; Genomics Group, CIBERER, CIMUS, University of Santiago de Compostela, Spain
| | - M V Lareu
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain
| | - C Phillips
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain.
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5
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Ambroa-Conde A, Girón-Santamaría L, Mosquera-Miguel A, Phillips C, Casares de Cal M, Gómez-Tato A, Álvarez-Dios J, de la Puente M, Ruiz-Ramírez J, Lareu M, Freire-Aradas A. Epigenetic age estimation in saliva and in buccal cells. Forensic Sci Int Genet 2022; 61:102770. [DOI: 10.1016/j.fsigen.2022.102770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 08/22/2022] [Accepted: 08/24/2022] [Indexed: 11/04/2022]
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6
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Phillips C, de la Puente M, Ruiz-Ramirez J, Staniewska A, Ambroa-Conde A, Freire-Aradas A, Mosquera-Miguel A, Rodriguez A, Lareu MV. Eurasiaplex-2: Shifting the focus to SNPs with high population specificity increases the power of forensic ancestry marker sets. Forensic Sci Int Genet 2022; 61:102780. [PMID: 36174251 DOI: 10.1016/j.fsigen.2022.102780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 09/16/2022] [Accepted: 09/18/2022] [Indexed: 11/27/2022]
Abstract
To compile a new South Asian-informative panel of forensic ancestry SNPs, we changed the strategy for selecting the most powerful markers for this purpose by targeting polymorphisms with near absolute specificity - when the South Asian-informative allele identified is absent from all other populations or present at frequencies below 0.001 (one in a thousand). More than 120 candidate SNPs were identified from 1000 Genomes datasets satisfying an allele frequency screen of ≥ 0.1 (10 % or more) allele frequency in South Asians, and ≤ 0.001 (0.1 % or less) in African, East Asian, and European populations. From the candidate pool of markers, a final panel of 36 SNPs, widely distributed across most autosomes, were selected that had allele frequencies in the five 1000 Genomes South Asian populations ranging from 0.4 to 0.15. Slightly lower average allele frequencies, but consistent patterns of informativeness were observed in gnomAD South Asian datasets used to validate the 1000 Genomes variant annotations. We named the panel of 36 South Asian-specific SNPs Eurasiaplex-2, and the informativeness of the panel was evaluated by compiling worldwide population data from 4097 samples in four genome variation databases that largely complement the global sampling of 1000 Genomes. Consistent patterns of allele frequency distribution, which were specific to South Asia, were observed in all populations in, or closely sited to, the Indian sub-continent. Pakistani populations from the HGDP-CEPH panel had markedly lower allele frequencies, highlighting the need to develop a statistical system to evaluate the ancestry inference value of counting the number of population-specific alleles present in an individual.
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Affiliation(s)
- C Phillips
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Spain; Institute of Anthropology and Ethnology, Adam Mickiewicz University in Poznań, Poland..
| | - M de la Puente
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Spain
| | - J Ruiz-Ramirez
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Spain
| | - A Staniewska
- Institute of Anthropology and Ethnology, Adam Mickiewicz University in Poznań, Poland
| | - A Ambroa-Conde
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Spain
| | - A Freire-Aradas
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Spain
| | - A Mosquera-Miguel
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Spain
| | - A Rodriguez
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Spain
| | - M V Lareu
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Spain
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7
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Freire-Aradas A, Girón-Santamaría L, Mosquera-Miguel A, Ambroa-Conde A, Phillips C, Casares de Cal M, Gómez-Tato A, Álvarez-Dios J, Pospiech E, Aliferi A, Syndercombe Court D, Branicki W, Lareu M. A common epigenetic clock from childhood to old age. Forensic Sci Int Genet 2022; 60:102743. [DOI: 10.1016/j.fsigen.2022.102743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 06/22/2022] [Accepted: 06/23/2022] [Indexed: 11/04/2022]
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8
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Freire-Aradas A, Pośpiech E, Aliferi A, Girón-Santamaría L, Mosquera-Miguel A, Pisarek A, Ambroa-Conde A, Phillips C, Casares de Cal MA, Gómez-Tato A, Spólnicka M, Woźniak A, Álvarez-Dios J, Ballard D, Court DS, Branicki W, Carracedo Á, Lareu MV. A Comparison of Forensic Age Prediction Models Using Data From Four DNA Methylation Technologies. Front Genet 2020; 11:932. [PMID: 32973877 PMCID: PMC7466768 DOI: 10.3389/fgene.2020.00932] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Accepted: 07/27/2020] [Indexed: 12/20/2022] Open
Abstract
Individual age estimation can be applied to criminal, legal, and anthropological investigations. DNA methylation has been established as the biomarker of choice for age prediction, since it was observed that specific CpG positions in the genome show systematic changes during an individual’s lifetime, with progressive increases or decreases in methylation levels. Subsequently, several forensic age prediction models have been reported, providing average age prediction error ranges of ±3–4 years, using a broad spectrum of technologies and underlying statistical analyses. DNA methylation assessment is not categorical but quantitative. Therefore, the detection platform used plays a pivotal role, since quantitative and semi-quantitative technologies could potentially result in differences in detected DNA methylation levels. In the present study, we analyzed as a shared sample pool, 84 blood-based DNA controls ranging from 18 to 99 years old using four different technologies: EpiTYPER®, pyrosequencing, MiSeq, and SNaPshotTM. The DNA methylation levels detected for CpG sites from ELOVL2, FHL2, and MIR29B2 with each system were compared. A restricted three CpG-site age prediction model was rebuilt for each system, as well as for a combination of technologies, based on previous training datasets, and age predictions were calculated accordingly for all the samples detected with the previous technologies. While the DNA methylation patterns and subsequent age predictions from EpiTYPER®, pyrosequencing, and MiSeq systems are largely comparable for the CpG sites studied, SNaPshotTM gives bigger differences reflected in higher predictive errors. However, these differences can be reduced by applying a z-score data transformation.
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Affiliation(s)
- A Freire-Aradas
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Galicia, Spain
| | - E Pośpiech
- Malopolska Centre of Biotechnology, Jagiellonian University, Kraków, Poland
| | - A Aliferi
- King's Forensics, Department of Analytical, Environmental and Forensic Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom
| | - L Girón-Santamaría
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Galicia, Spain
| | - A Mosquera-Miguel
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Galicia, Spain
| | - A Pisarek
- Malopolska Centre of Biotechnology, Jagiellonian University, Kraków, Poland
| | - A Ambroa-Conde
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Galicia, Spain
| | - C Phillips
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Galicia, Spain
| | - M A Casares de Cal
- Faculty of Mathematics, University of Santiago de Compostela, Galicia, Spain
| | - A Gómez-Tato
- Faculty of Mathematics, University of Santiago de Compostela, Galicia, Spain
| | - M Spólnicka
- Central Forensic Laboratory of the Police, Warsaw, Poland
| | - A Woźniak
- Central Forensic Laboratory of the Police, Warsaw, Poland
| | - J Álvarez-Dios
- Faculty of Mathematics, University of Santiago de Compostela, Galicia, Spain
| | - D Ballard
- King's Forensics, Department of Analytical, Environmental and Forensic Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom
| | - D Syndercombe Court
- King's Forensics, Department of Analytical, Environmental and Forensic Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom
| | - W Branicki
- Malopolska Centre of Biotechnology, Jagiellonian University, Kraków, Poland.,Central Forensic Laboratory of the Police, Warsaw, Poland
| | - Ángel Carracedo
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Galicia, Spain.,Fundación Pública Galega de Medicina Xenómica - CIBERER-IDIS, Santiago de Compostela, Spain
| | - M V Lareu
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Galicia, Spain
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