A collaborative exercise on DNA methylation-based age prediction and body fluid typing

Lee, Jeong Min; Naue, Jana; Fleckhaus, Jan; Freire-Aradas, Ana; Neubauer, Jacqueline; Pośpiech, Ewelina; McCord, Bruce; Kalamara, Vivian; Gauthier, Quentin; Mills, Carly; Cao, Yejie; Wang, Zheng; Oh, Yu Na; Feng, Lei; Schneider, Peter M.; Phillips, Christopher; Haas, Cordula; Pisarek, Aleksandra; Branicki, Wojciech; Podini, Daniele; Vidaki, Athina; Tejero, Nicole Fernández; Ambroa-Conde, A.; Mosquera-Miguel, Ana; Lareu, Marı́a Victoria; Hou, Yiping; Lee, Joo Young; Lee, Hwan Young

doi:10.1016/j.fsigen.2021.102656

Cited by 18 publications

(32 citation statements)

References 45 publications

(62 reference statements)

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“…The four amplification products followed the same downstream process and the SBE step was repeated once for each of them. After capillary electrophoresis, the methylation levels at each locus (namely, ELOVL2, FHL2, KLF14, C1orf132/MIR29B2C, TRIM59) were calculated and initially inserted in the tool developed by Lee et al [ 18 ]. However, given the modifications performed on the original protocol and the different populations studied, the data thus obtained were used to create a novel age-predictive tool.…”

Section: Resultsmentioning

confidence: 99%

Forensic Age Estimation through a DNA Methylation-Based Age Prediction Model in the Italian Population: A Pilot Study

Onofri

Delicati

Marcante

et al. 2023

IJMS

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DNA methylation is one of the epigenetic marks which has been studied intensively in recent years for age predicting purposes in the forensic area. In order to integrate age prediction into routine forensic workflow, the purpose of this study was to standardize and optimize a DNA methylation-based protocol tailored to the Italian context. A previously published protocol and age-predictive method was implemented for the analysis of 84 blood samples originating from Central Italy. The study here presented is based on the Single Base Extension method, considering five genes: ELOVL2, FHL2, KLF14, C1orf132, now identified as MIR29B2C, and TRIM59. The precise and specific steps consist of DNA extraction and quantification, bisulfite conversion, amplification of converted DNA, first purification, single base extension, second purification, capillary electrophoresis, and analysis of the results to train and test the tool. The prediction error obtained, expressed as mean absolute deviation, showed a value of 3.12 years in the training set and 3.01 years in the test set. Given that population-based differences in DNA methylation patterns have been previously reported in the literature, it would be useful to further improve the study implementing additional samples representative of the entire Italian population.

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Section: Resultsmentioning

confidence: 99%

Forensic Age Estimation through a DNA Methylation-Based Age Prediction Model in the Italian Population: A Pilot Study

Onofri

Delicati

Marcante

et al. 2023

IJMS

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“…A wide variety of research papers have been published discussing age prediction using DNA methylation markers with different sequencing/typing techniques. These include pyrosequencing [59,60,74], massively parallel sequencing [75][76][77], and SNaPshot assays [78][79][80], with the majority using pyrosequencing. Different population groups were studied, including Chinese [59,81], Japanese [60], German [26,60], Thai [63], Spanish [64], Iraqi [82], Italian [83], and French [84].…”

Section: Age Predictionmentioning

confidence: 99%

Pyrosequencing: Current forensic methodology and future applications—a review

et al. 2022

Self Cite

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The recent development of small, single-amplicon-based benchtop systems for pyrosequencing has opened up a host of novel procedures for applications in forensic science. Pyrosequencing is a sequencing by synthesis technique, based on chemiluminescent inorganic pyrophosphate detection. This review explains the pyrosequencing workflow and illustrates the step-by-step chemistry, followed by a description of the assay design and factors to keep in mind for an exemplary assay. Existing and potential forensic applications are highlighted using this technology. Current applications include identifying species, identifying bodily fluids, and determining smoking status. We also review progress in potential applications for the future, including research on distinguishing monozygotic twins, detecting alcohol and drug abuse, and other phenotypic characteristics such as diet and body mass index. Overall, the versatility of the pyrosequencing technologies renders it a useful tool in forensic genomics.

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“…Studies examining the aging‐dependent dynamics of DNA and RNA were shown to be promising and have taken up considerable interest in recent years 14–23 …”

Section: Introductionmentioning

confidence: 99%

“…12,13 Studies examining the aging-dependent dynamics of DNA and RNA were shown to be promising and have taken up considerable interest in recent years. [14][15][16][17][18][19][20][21][22][23] High-performance liquid chromatography coupled to mass spectrometry (HPLC-MS)-based approaches have recently been used to study TsD determination. 3,[24][25][26][27][28] Seok et al 24 and Lee et al 27 have already applied untargeted metabolomics approaches to tackle TsD determination over 21 or 7 days, respectively.…”

mentioning

confidence: 99%

Determination of the Time since Deposition of blood‐traces in a forensic context: Application of untargeted LC‐HR‐MS/MS metabolomics profiling

Schneider

Kræmer

Steuer

2023

Drug Testing and Analysis

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Being able to attest when a bloodstain was deposited at a crime scene can be invaluable to a prosecution process, and methods to provide that information have long been desired. Determining the Time since Deposition (TsD) of a trace would allow placing a subject both in space and time to the crime scene-or prove that a trace left by that person was unrelated to it because it was deposited before or after the time the crime had occurred. To this day, no method for TsD determination has made its way into routine forensic casework, mainly because of the numerous challenges that await when trying to understand and account for all the influencing and confounding factors that affect the aging process (such as, e.g., temperature, UV-light exposure, or humidity). Here, we present an untargeted metabolomics-based study using liquid chromatography high-resolution mass spectrometry (LC-HR-MS) and data-dependent acquisition to analyze blood samples aged under two distinctly different storage conditions over 48 weeks. Global differences in age-and storage-dependent changes in blood metabolomes were described, and TsD-classification strategies based on qualitative and quantitative assessment of molecular features (MFs) have been proposed.Based on the selected criteria to best predict the TsD, the dipeptide Phenylalanylalanine (PheAla) can be considered as a promising candidate for TsD prediction. In essence, changes in the blood metabolome dynamics showed a strong association with increasing TsD, but significant differences depending on storage conditioning were observed, facilitating the need to study further the influence of individual influencing factors on TsD determination.

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A collaborative exercise on DNA methylation-based age prediction and body fluid typing

Cited by 18 publications

References 45 publications

Forensic Age Estimation through a DNA Methylation-Based Age Prediction Model in the Italian Population: A Pilot Study

Forensic Age Estimation through a DNA Methylation-Based Age Prediction Model in the Italian Population: A Pilot Study

Pyrosequencing: Current forensic methodology and future applications—a review

Determination of the Time since Deposition of blood‐traces in a forensic context: Application of untargeted LC‐HR‐MS/MS metabolomics profiling

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