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| Home > Publications database > Age estimation based on different molecular clocks in several tissues and a multivariate approach: An explorative study |
| Journal Article | FZJ-2019-02320 |
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2020
Springer
Heidelberg
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Please use a persistent id in citations: http://hdl.handle.net/2128/24424 doi:10.1007/s00414-019-02054-9
Abstract: Several molecular modifications accumulate in the human organism with increasing age. Some of these „molecular clocks“ in DNA and in proteins open up promising approaches for the development of methods for forensic age estimation. A natural limitation of these methods arises from the fact that the chronological age is determined only indirectly by analyzing defined molecular changes that occur during aging. These changes are not linked exclusively to the expired life span but may be influenced significantly by intrinsic and extrinsic factors in the complex process of individual aging. We tested the hypothesis that a combined use of different “molecular clocks” in different tissues results in more precise age estimates because this approach addresses the complex ageing processes in a more comprehensive way. Two molecular clocks (accumulation of D-aspartic acid (D-Asp), accumulation of pentosidine (PEN)) in two different tissues (annulus fibrosus of intervertebral discs and elastic cartilage of the epiglottis) were analyzed in 95 cases, and uni- and multivariate models for age estimation were generated.The more parameters were included in the models for age estimation, the smaller the mean absolute errors (MAE) became. While the MAEs were 7.5 – 11.0 years in univariate models, a multivariate model based on the two protein clocks in the two tissues resulted in a MAE of 4.0 years. These results support our hypothesis. The tested approach of a combined analysis of different molecular clocks analyzed in different tissues opens up new possibilities in postmortem age estimation. In a next step, we will add the epigenetic clock (DNA methylation) to our protein clocks (PEN, D-Asp) and expand our set of tissues.Keywords: Age estimation, pentosidine, D-aspartic acid, machine learning, age prediction model, molecular clocks
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