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Improvements and inter-laboratory implementation and optimization of blood-based single-locus age prediction models using DNA methylation of the ELOVL2 promoter.
Garali, Imene; Sahbatou, Mourad; Daunay, Antoine; Baudrin, Laura G; Renault, Victor; Bouyacoub, Yosra; Deleuze, Jean-François; How-Kit, Alexandre.
Afiliação
  • Garali I; Laboratory for Bioinformatics, Foundation Jean Dausset-CEPH, Paris, France.
  • Sahbatou M; Laboratory of Excellence GenMed, Paris, France.
  • Daunay A; Laboratory for Human Genetics, Foundation Jean Dausset-CEPH, Paris, France.
  • Baudrin LG; Laboratory for Genomics, Foundation Jean Dausset-CEPH, 75010, Paris, France.
  • Renault V; Laboratory of Excellence GenMed, Paris, France.
  • Bouyacoub Y; Laboratory for Genomics, Foundation Jean Dausset-CEPH, 75010, Paris, France.
  • Deleuze JF; Laboratory for Bioinformatics, Foundation Jean Dausset-CEPH, Paris, France.
  • How-Kit A; Laboratory of Excellence GenMed, Paris, France.
Sci Rep ; 10(1): 15652, 2020 09 24.
Article em En | MEDLINE | ID: mdl-32973211
ABSTRACT
Several blood-based age prediction models have been developed using less than a dozen to more than a hundred DNA methylation biomarkers. Only one model (Z-P1) based on pyrosequencing has been developed using DNA methylation of a single locus located in the ELOVL2 promoter, which is considered as one of the best age-prediction biomarker. Although multi-locus models generally present better performances compared to the single-locus model, they require more DNA and present more inter-laboratory variations impacting the predictions. Here we developed 17,018 single-locus age prediction models based on DNA methylation of the ELOVL2 promoter from pooled data of four different studies (training set of 1,028 individuals aged from 0 and 91 years) using six different statistical approaches and testing every combination of the 7 CpGs, aiming to improve the prediction performances and reduce the effects of inter-laboratory variations. Compared to Z-P1 model, three statistical models with the optimal combinations of CpGs presented improved performances (MAD of 4.41-4.77 in the testing set of 385 individuals) and no age-dependent bias. In an independent testing set of 100 individuals (19-65 years), we showed that the prediction accuracy could be further improved by using different CpG combinations and increasing the number of technical replicates (MAD of 4.17).
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Envelhecimento / Regiões Promotoras Genéticas / Metilação de DNA / Loci Gênicos / Elongases de Ácidos Graxos / Laboratórios Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Adolescent / Adult / Aged / Aged80 / Child / Child, preschool / Female / Humans / Infant / Male Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Envelhecimento / Regiões Promotoras Genéticas / Metilação de DNA / Loci Gênicos / Elongases de Ácidos Graxos / Laboratórios Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Adolescent / Adult / Aged / Aged80 / Child / Child, preschool / Female / Humans / Infant / Male Idioma: En Ano de publicação: 2020 Tipo de documento: Article