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Placental epigenetic clocks: estimating gestational age using placental DNA methylation levels
The human pan-tissue epigenetic clock is widely used for estimating age across the entire lifespan, but it does not lend itself well to estimating gestational age (GA) based on placental DNAm methylation (DNAm) data. We replicate previous findings demonstrating a strong correlation between GA and ge...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6628997/ https://www.ncbi.nlm.nih.gov/pubmed/31235674 http://dx.doi.org/10.18632/aging.102049 |
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author | Lee, Yunsung Choufani, Sanaa Weksberg, Rosanna Wilson, Samantha L. Yuan, Victor Burt, Amber Marsit, Carmen Lu, Ake T. Ritz, Beate Bohlin, Jon Gjessing, Håkon K. Harris, Jennifer R. Magnus, Per Binder, Alexandra M. Robinson, Wendy P. Jugessur, Astanand Horvath, Steve |
author_facet | Lee, Yunsung Choufani, Sanaa Weksberg, Rosanna Wilson, Samantha L. Yuan, Victor Burt, Amber Marsit, Carmen Lu, Ake T. Ritz, Beate Bohlin, Jon Gjessing, Håkon K. Harris, Jennifer R. Magnus, Per Binder, Alexandra M. Robinson, Wendy P. Jugessur, Astanand Horvath, Steve |
author_sort | Lee, Yunsung |
collection | PubMed |
description | The human pan-tissue epigenetic clock is widely used for estimating age across the entire lifespan, but it does not lend itself well to estimating gestational age (GA) based on placental DNAm methylation (DNAm) data. We replicate previous findings demonstrating a strong correlation between GA and genome-wide DNAm changes. Using substantially more DNAm arrays (n=1,102 in the training set) than a previous study, we present three new placental epigenetic clocks: 1) a robust placental clock (RPC) which is unaffected by common pregnancy complications (e.g., gestational diabetes, preeclampsia), and 2) a control placental clock (CPC) constructed using placental samples from pregnancies without known placental pathology, and 3) a refined RPC for uncomplicated term pregnancies. These placental clocks are highly accurate estimators of GA based on placental tissue; e.g., predicted GA based on RPC is highly correlated with actual GA (r>0.95 in test data, median error less than one week). We show that epigenetic clocks derived from cord blood or other tissues do not accurately estimate GA in placental samples. While fundamentally different from Horvath’s pan-tissue epigenetic clock, placental clocks closely track fetal age during development and may have interesting applications. |
format | Online Article Text |
id | pubmed-6628997 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Impact Journals |
record_format | MEDLINE/PubMed |
spelling | pubmed-66289972019-07-18 Placental epigenetic clocks: estimating gestational age using placental DNA methylation levels Lee, Yunsung Choufani, Sanaa Weksberg, Rosanna Wilson, Samantha L. Yuan, Victor Burt, Amber Marsit, Carmen Lu, Ake T. Ritz, Beate Bohlin, Jon Gjessing, Håkon K. Harris, Jennifer R. Magnus, Per Binder, Alexandra M. Robinson, Wendy P. Jugessur, Astanand Horvath, Steve Aging (Albany NY) Research Paper The human pan-tissue epigenetic clock is widely used for estimating age across the entire lifespan, but it does not lend itself well to estimating gestational age (GA) based on placental DNAm methylation (DNAm) data. We replicate previous findings demonstrating a strong correlation between GA and genome-wide DNAm changes. Using substantially more DNAm arrays (n=1,102 in the training set) than a previous study, we present three new placental epigenetic clocks: 1) a robust placental clock (RPC) which is unaffected by common pregnancy complications (e.g., gestational diabetes, preeclampsia), and 2) a control placental clock (CPC) constructed using placental samples from pregnancies without known placental pathology, and 3) a refined RPC for uncomplicated term pregnancies. These placental clocks are highly accurate estimators of GA based on placental tissue; e.g., predicted GA based on RPC is highly correlated with actual GA (r>0.95 in test data, median error less than one week). We show that epigenetic clocks derived from cord blood or other tissues do not accurately estimate GA in placental samples. While fundamentally different from Horvath’s pan-tissue epigenetic clock, placental clocks closely track fetal age during development and may have interesting applications. Impact Journals 2019-06-24 /pmc/articles/PMC6628997/ /pubmed/31235674 http://dx.doi.org/10.18632/aging.102049 Text en Copyright © 2019 Lee et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution (CC BY) 3.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Paper Lee, Yunsung Choufani, Sanaa Weksberg, Rosanna Wilson, Samantha L. Yuan, Victor Burt, Amber Marsit, Carmen Lu, Ake T. Ritz, Beate Bohlin, Jon Gjessing, Håkon K. Harris, Jennifer R. Magnus, Per Binder, Alexandra M. Robinson, Wendy P. Jugessur, Astanand Horvath, Steve Placental epigenetic clocks: estimating gestational age using placental DNA methylation levels |
title | Placental epigenetic clocks: estimating gestational age using placental DNA methylation levels |
title_full | Placental epigenetic clocks: estimating gestational age using placental DNA methylation levels |
title_fullStr | Placental epigenetic clocks: estimating gestational age using placental DNA methylation levels |
title_full_unstemmed | Placental epigenetic clocks: estimating gestational age using placental DNA methylation levels |
title_short | Placental epigenetic clocks: estimating gestational age using placental DNA methylation levels |
title_sort | placental epigenetic clocks: estimating gestational age using placental dna methylation levels |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6628997/ https://www.ncbi.nlm.nih.gov/pubmed/31235674 http://dx.doi.org/10.18632/aging.102049 |
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