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An ELOVL2-Based Epigenetic Clock for Forensic Age Prediction: A Systematic Review.
Paparazzo, Ersilia; Lagani, Vincenzo; Geracitano, Silvana; Citrigno, Luigi; Aceto, Mirella Aurora; Malvaso, Antonio; Bruno, Francesco; Passarino, Giuseppe; Montesanto, Alberto.
Afiliação
  • Paparazzo E; Department of Biology, Ecology and Earth Sciences, University of Calabria, 87036 Rende, Italy.
  • Lagani V; Biological and Environmental Sciences and Engineering Division (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal 23952, Saudi Arabia.
  • Geracitano S; Institute of Chemical Biology, Ilia State University, Tbilisi 0162, Georgia.
  • Citrigno L; SDAIA-KAUST Center of Excellence in Data Science and Artificial Intelligence, Thuwal 23952, Saudi Arabia.
  • Aceto MA; Department of Biology, Ecology and Earth Sciences, University of Calabria, 87036 Rende, Italy.
  • Malvaso A; National Research Council (CNR)-Institute for Biomedical Research and Innovation-(IRIB), 87050 Mangone, Italy.
  • Bruno F; Department of Biology, Ecology and Earth Sciences, University of Calabria, 87036 Rende, Italy.
  • Passarino G; Department of Brain and Behavioral Sciences, IRCCS "C. Mondino" Foundation, National Neurological Institute, University of Pavia, 27100 Pavia, Italy.
  • Montesanto A; Regional Neurogenetic Centre (CRN), Department of Primary Care, ASP Catanzaro, 88046 Lamezia Terme, Italy.
Int J Mol Sci ; 24(3)2023 Jan 23.
Article em En | MEDLINE | ID: mdl-36768576
ABSTRACT
The prediction of chronological age from methylation-based biomarkers represents one of the most promising applications in the field of forensic sciences. Age-prediction models developed so far are not easily applicable for forensic caseworkers. Among the several attempts to pursue this objective, the formulation of single-locus models might represent a good strategy. The present work aimed to develop an accurate single-locus model for age prediction exploiting ELOVL2, a gene for which epigenetic alterations are most highly correlated with age. We carried out a systematic review of different published pyrosequencing datasets in which methylation of the ELOVL2 promoter was analysed to formulate age prediction models. Nine of these, with available datasets involving 2298 participants, were selected. We found that irrespective of which model was adopted, a very strong relationship between ELOVL2 methylation levels and age exists. In particular, the model giving the best age-prediction accuracy was the gradient boosting regressor with a prediction error of about 5.5 years. The findings reported here strongly support the use of ELOVL2 for the formulation of a single-locus epigenetic model, but the inclusion of additional, non-redundant markers is a fundamental requirement to apply a molecular model to forensic applications with more robust results.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Envelhecimento / Genética Forense Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Envelhecimento / Genética Forense Idioma: En Ano de publicação: 2023 Tipo de documento: Article