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@ARTICLE{Becker:1030922,
author = {Becker, J. and Bühren, V. and Schmelzer, L. and Reckert,
A. and Eickhoff, S. B. and Ritz, S. and Naue, J.},
title = {{M}olecular age prediction using skull bone samples from
individuals with and without signs of decomposition: a
multivariate approach combining analysis of
posttranslational protein modifications and {DNA}
methylation},
journal = {International journal of legal medicine},
volume = {139},
issn = {0367-0031},
address = {Getzville, NY},
publisher = {HeinOnline},
reportid = {FZJ-2024-05515},
pages = {157-174},
year = {2025},
abstract = {The prediction of the chronological age of a deceased
individual at time of death can provide important
information in case of unidentified bodies. The
methodological possibilities in these cases depend on the
availability of tissues, whereby bones are preserved for a
long time due to their mineralization under normal
environmental conditions. Age-dependent changes in DNA
methylation (DNAm) as well as the accumulation of
pentosidine (Pen) and D-aspartic acid (D-Asp) could be
useful molecular markers for age prediction. A combination
of such molecular clocks into one age prediction model seems
favorable to minimize inter- and intra-individual variation.
We therefore developed (I) age prediction models based on
the three molecular clocks, (II) examined the improvement of
age prediction by combination, and (III) investigated if
samples with signs of decomposition can also be examined
using these three molecular clocks. Skull bone from deceased
individuals was collected to obtain a training dataset
(n = 86), and two independent test sets (without signs
of decomposition: n = 44, with signs of decomposition:
n = 48). DNAm of 6 CpG sites in ELOVL2, KLF14, PDE4C,
RPA2, TRIM59 and ZYG11A was analyzed using massive parallel
sequencing (MPS). The D-Asp and Pen contents were analyzed
by high performance liquid chromatography (HPLC). Age
prediction models based on ridge regression were developed
resulting in mean absolute errors (MAEs)/root mean square
errors (RMSE) of 5.5years /6.6 years (DNAm), 7.7 years /9.3
years (Pen) and 11.7 years /14.6 years (D-Asp) in the test
set. Unsurprisingly, a general lower accuracy for the DNAm,
D-Asp, and Pen models was observed in samples from
decomposed bodies (MAE: 7.4–11.8 years, RMSE: 10.4–15.4
years). This reduced accuracy could be caused by multiple
factors with different impact on each molecular clock. To
acknowledge general changes due to decomposition, a pilot
model for a possible age prediction based on the decomposed
samples as training set improved the accuracy evaluated by
leave-one-out-cross validation (MAE: 6.6–12 years, RMSE:
8.1–15.9 years). The combination of all three molecular
age clocks did reveal comparable MAE and RMSE results to the
pure analysis of the DNA methylation for the test set
without signs of decomposition. However, an improvement by
the combination of all three clocks was possible for the
decomposed samples, reducing especially the deviation in
case of outliers in samples with very high decomposition and
low DNA content. The results demonstrate the general
potential in a combined analysis of different molecular
clocks in specific cases.},
cin = {INM-7},
ddc = {610},
cid = {I:(DE-Juel1)INM-7-20090406},
pnm = {5254 - Neuroscientific Data Analytics and AI (POF4-525) /
5253 - Neuroimaging (POF4-525)},
pid = {G:(DE-HGF)POF4-5254 / G:(DE-HGF)POF4-5253},
typ = {PUB:(DE-HGF)16},
pubmed = {39256256},
UT = {WOS:001309228800002},
doi = {10.1007/s00414-024-03314-z},
url = {https://juser.fz-juelich.de/record/1030922},
}