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

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 Existing epigenetic clocks are based on CpGs from the Illumina HumanMethylation450 BeadChip (450 K) which has now been replaced by the latest platform,...

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Autores principales: Lee, Yunsung, Haftorn, Kristine L., Denault, William R. P., Nustad, Haakon E., Page, Christian M., Lyle, Robert, Lee-Ødegård, Sindre, Moen, Gunn-Helen, Prasad, Rashmi B., Groop, Leif C., Sletner, Line, Sommer, Christine, Magnus, Maria C., Gjessing, Håkon K., Harris, Jennifer R., Magnus, Per, Håberg, Siri E., Jugessur, Astanand, Bohlin, Jon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7590728/
https://www.ncbi.nlm.nih.gov/pubmed/33109080
http://dx.doi.org/10.1186/s12864-020-07168-8
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author Lee, Yunsung
Haftorn, Kristine L.
Denault, William R. P.
Nustad, Haakon E.
Page, Christian M.
Lyle, Robert
Lee-Ødegård, Sindre
Moen, Gunn-Helen
Prasad, Rashmi B.
Groop, Leif C.
Sletner, Line
Sommer, Christine
Magnus, Maria C.
Gjessing, Håkon K.
Harris, Jennifer R.
Magnus, Per
Håberg, Siri E.
Jugessur, Astanand
Bohlin, Jon
author_facet Lee, Yunsung
Haftorn, Kristine L.
Denault, William R. P.
Nustad, Haakon E.
Page, Christian M.
Lyle, Robert
Lee-Ødegård, Sindre
Moen, Gunn-Helen
Prasad, Rashmi B.
Groop, Leif C.
Sletner, Line
Sommer, Christine
Magnus, Maria C.
Gjessing, Håkon K.
Harris, Jennifer R.
Magnus, Per
Håberg, Siri E.
Jugessur, Astanand
Bohlin, Jon
author_sort Lee, Yunsung
collection PubMed
description 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 Existing epigenetic clocks are based on CpGs from the Illumina HumanMethylation450 BeadChip (450 K) which has now been replaced by the latest platform, Illumina MethylationEPIC BeadChip (EPIC).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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-020-07168-8.
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spelling pubmed-75907282020-10-27 Blood-based epigenetic estimators of chronological age in human adults using DNA methylation data from the Illumina MethylationEPIC array Lee, Yunsung Haftorn, Kristine L. Denault, William R. P. Nustad, Haakon E. Page, Christian M. Lyle, Robert Lee-Ødegård, Sindre Moen, Gunn-Helen Prasad, Rashmi B. Groop, Leif C. Sletner, Line Sommer, Christine Magnus, Maria C. Gjessing, Håkon K. Harris, Jennifer R. Magnus, Per Håberg, Siri E. Jugessur, Astanand Bohlin, Jon BMC Genomics Methodology Article 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-020-07168-8. BioMed Central 2020-10-27 /pmc/articles/PMC7590728/ /pubmed/33109080 http://dx.doi.org/10.1186/s12864-020-07168-8 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Methodology Article
Lee, Yunsung
Haftorn, Kristine L.
Denault, William R. P.
Nustad, Haakon E.
Page, Christian M.
Lyle, Robert
Lee-Ødegård, Sindre
Moen, Gunn-Helen
Prasad, Rashmi B.
Groop, Leif C.
Sletner, Line
Sommer, Christine
Magnus, Maria C.
Gjessing, Håkon K.
Harris, Jennifer R.
Magnus, Per
Håberg, Siri E.
Jugessur, Astanand
Bohlin, Jon
Blood-based epigenetic estimators of chronological age in human adults using DNA methylation data from the Illumina MethylationEPIC array
title Blood-based epigenetic estimators of chronological age in human adults using DNA methylation data from the Illumina MethylationEPIC array
title_full Blood-based epigenetic estimators of chronological age in human adults using DNA methylation data from the Illumina MethylationEPIC array
title_fullStr Blood-based epigenetic estimators of chronological age in human adults using DNA methylation data from the Illumina MethylationEPIC array
title_full_unstemmed Blood-based epigenetic estimators of chronological age in human adults using DNA methylation data from the Illumina MethylationEPIC array
title_short Blood-based epigenetic estimators of chronological age in human adults using DNA methylation data from the Illumina MethylationEPIC array
title_sort blood-based epigenetic estimators of chronological age in human adults using dna methylation data from the illumina methylationepic array
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7590728/
https://www.ncbi.nlm.nih.gov/pubmed/33109080
http://dx.doi.org/10.1186/s12864-020-07168-8
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