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Rashmi Prasad

Rashmi Prasad

Assistant researcher

Rashmi Prasad

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

Author

  • 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

Summary, in English

Background: Epigenetic clocks have been recognized for their precise prediction of chronological age, age-related diseases, and all-cause mortality. Existing epigenetic clocks are based on CpGs from the Illumina HumanMethylation450 BeadChip (450 K) which has now been replaced by the latest platform, Illumina MethylationEPIC BeadChip (EPIC). Thus, it remains unclear to what extent EPIC contributes to increased precision and accuracy in the prediction of chronological age. Results: We developed three blood-based epigenetic clocks for human adults using EPIC-based DNA methylation (DNAm) data from the Norwegian Mother, Father and Child Cohort Study (MoBa) and the Gene Expression Omnibus (GEO) public repository: 1) an Adult Blood-based EPIC Clock (ABEC) trained on DNAm data from MoBa (n = 1592, age-span: 19 to 59 years), 2) an extended ABEC (eABEC) trained on DNAm data from MoBa and GEO (n = 2227, age-span: 18 to 88 years), and 3) a common ABEC (cABEC) trained on the same training set as eABEC but restricted to CpGs common to 450 K and EPIC. Our clocks showed high precision (Pearson correlation between chronological and epigenetic age (r) > 0.94) in independent cohorts, including GSE111165 (n = 15), GSE115278 (n = 108), GSE132203 (n = 795), and the Epigenetics in Pregnancy (EPIPREG) study of the STORK Groruddalen Cohort (n = 470). This high precision is unlikely due to the use of EPIC, but rather due to the large sample size of the training set. Conclusions: Our ABECs predicted adults’ chronological age precisely in independent cohorts. As EPIC is now the dominant platform for measuring DNAm, these clocks will be useful in further predictions of chronological age, age-related diseases, and mortality.

Department/s

  • Genomics, Diabetes and Endocrinology
  • EXODIAB: Excellence in Diabetes Research in Sweden

Publishing year

2020

Language

English

Publication/Series

BMC Genomics

Volume

21

Issue

1

Document type

Journal article

Publisher

BioMed Central (BMC)

Topic

  • Medical Genetics

Keywords

  • Chronological age
  • DNA methylation
  • Epigenetic age
  • Illumina MethylationEPIC BeadChip
  • MoBa

Status

Published

Research group

  • Genomics, Diabetes and Endocrinology

ISBN/ISSN/Other

  • ISSN: 1471-2164