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Sci Rep. 2019 Jun 20;9(1):8862. doi: 10.1038/s41598-019-45197-w.

Evaluation of six blood-based age prediction models using DNA methylation analysis by pyrosequencing.

Author information

1
Laboratory for Genomics, Foundation Jean Dausset - CEPH, Paris, France.
2
Laboratory of Excellence GenMed, Paris, France.
3
Centre National de Recherche en Génomique Humaine, CEA, Institut François Jacob, Evry, France.
4
Laboratory for Genomics, Foundation Jean Dausset - CEPH, Paris, France. alexandre.how-kit@fjd-ceph.org.

Abstract

DNA methylation has been identified as the most promising molecular biomarker for the prediction of age. Several DNA methylation-based models have been proposed for age prediction based on blood samples, using mainly pyrosequencing. These methods present different performances for age prediction and have rarely, if ever, been evaluated and intercompared in an independent validation study. Here, for the first time, we evaluate and compare six blood-based age prediction models (Bekaert1, Park2, Thong3, Weidner4, and the Zbiec-Piekarska 15 and Zbiec-Piekarska 26), using DNA methylation analysis by pyrosequencing on 100 blood samples from French individuals aged between 19-65 years. For each model, we perform correlation analysis and evaluate age-prediction performance (mean absolute deviation (MAD) and standard error of the estimate (SEE)). The best age-prediction performances were found with the Bekaert and Thong models (MAD of 4.5-5.2, SEE of 6.8-7.2), followed by the Zbiec-Piekarska 1 model (MAD of 6.8 and SEE of 9.2), while the Park, Weidner and Zbiec-Piekarska 2 models presented lower performances (MAD of 7.2-8.7 and SEE of 9.2-10.3). Given these results, we recommend performing systematic, independent evaluation of all age prediction models on a same cohort to validate the different models and compare their performance.

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