Literature DB >> 31546163

Identifying blood-specific age-related DNA methylation markers on the Illumina MethylationEPIC® BeadChip.

Hussain Alsaleh1, Penelope R Haddrill2.   

Abstract

The past decade has seen rapid development in DNA methylation (DNAm) microarrays, including the Illumina HumanMethylation27 and HumanMethylation450 (450K) chips, which have played an essential role in identifying and evaluating age-related (AR) DNAm markers in different tissues. Recently, a new array, the Illumina MethylationEPIC (EPIC) was introduced, with nearly double the number of probes as the 450K (∼850,000 probes). In this study, we test these newly added probes for age association using a large cohort of 754 DNAm profiles from blood samples assayed on the EPIC BeadChip, for individuals aged 0-88 years old. 52 AR CpG sites (Spearman's abs(rho) >0.6 and P-value <10-83) were identified, 21 of which were novel sites and mapped to 18 genes, nine of which (LHFPL4, SLC12A8, EGFEM1P, GPR158, TAL1, KIAA1755, LOC730668, DUSP16, and FAM65C) have never previously been reported to be associated with age. The data were subsequently split into a 527-sample training set and a 227-sample testing set to build and validate two age prediction models using elastic net regression and multivariate regression. Elastic net regression selected 425 CpG markers with a mean absolute deviation (MAD) of 2.6 years based on the testing set. To build a multivariate linear regression model, AR CpG sites with R2 > 0.5 at FDR < 0.05 were input into stepwise regression to select the best subset for age prediction. The resulting six CpG markers were linearly modelled with age and explained 81% of age-correlated variation in DNAm levels. Age estimation accuracy using bootstrap analysis was 4.5 years, with 95% confidence intervals of 4.56 to 4.57 years based on the testing set. These results suggest that EPIC BeadChip probes for age estimation fall within the range of probes found on the previous Illumina HumanMethylation platforms in terms of their age-prediction ability.
Copyright © 2019 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Age; CpG sites; DNA methylation; Forensic age estimation; Forensic epigenetics; Illumina MethylationEPIC

Year:  2019        PMID: 31546163     DOI: 10.1016/j.forsciint.2019.109944

Source DB:  PubMed          Journal:  Forensic Sci Int        ISSN: 0379-0738            Impact factor:   2.395


  6 in total

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2.  Chronological Age Prediction: Developmental Evaluation of DNA Methylation-Based Machine Learning Models.

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5.  Blood-based epigenetic estimators of chronological age in human adults using DNA methylation data from the Illumina MethylationEPIC array.

Authors:  Yunsung Lee; Kristine L Haftorn; William R P Denault; Haakon E Nustad; Christian M Page; Robert Lyle; Sindre Lee-Ødegård; Gunn-Helen Moen; Rashmi B Prasad; Leif C Groop; Line Sletner; Christine Sommer; Maria C Magnus; Håkon K Gjessing; Jennifer R Harris; Per Magnus; Siri E Håberg; Astanand Jugessur; Jon Bohlin
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  6 in total

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