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Accelerated placental aging in early onset preeclampsia pregnancies identified by DNA methylation

AIM: To determine whether dynamic DNA methylation changes in the human placenta can be used to predict gestational age. MATERIALS & METHODS: Publicly available placental DNA methylation data from 12 studies, together with our own dataset, using Illumina Infinium Human Methylation BeadChip arrays...

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Autores principales: Mayne, Benjamin T, Leemaqz, Shalem Y, Smith, Alicia K, Breen, James, Roberts, Claire T, Bianco-Miotto, Tina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Future Medicine Ltd 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6040051/
https://www.ncbi.nlm.nih.gov/pubmed/27894195
http://dx.doi.org/10.2217/epi-2016-0103
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author Mayne, Benjamin T
Leemaqz, Shalem Y
Smith, Alicia K
Breen, James
Roberts, Claire T
Bianco-Miotto, Tina
author_facet Mayne, Benjamin T
Leemaqz, Shalem Y
Smith, Alicia K
Breen, James
Roberts, Claire T
Bianco-Miotto, Tina
author_sort Mayne, Benjamin T
collection PubMed
description AIM: To determine whether dynamic DNA methylation changes in the human placenta can be used to predict gestational age. MATERIALS & METHODS: Publicly available placental DNA methylation data from 12 studies, together with our own dataset, using Illumina Infinium Human Methylation BeadChip arrays. RESULTS & CONCLUSION: We developed an accurate tool for predicting gestational age of placentas using 62 CpG sites. There was a higher predicted gestational age for placentas from early onset preeclampsia cases, but not term preeclampsia, compared with their chronological age. Therefore, early onset preeclampsia is associated with placental aging. Gestational age acceleration prediction from DNA methylation array data may provide insight into the molecular mechanisms of pregnancy disorders.
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spelling pubmed-60400512018-07-12 Accelerated placental aging in early onset preeclampsia pregnancies identified by DNA methylation Mayne, Benjamin T Leemaqz, Shalem Y Smith, Alicia K Breen, James Roberts, Claire T Bianco-Miotto, Tina Epigenomics Research Article AIM: To determine whether dynamic DNA methylation changes in the human placenta can be used to predict gestational age. MATERIALS & METHODS: Publicly available placental DNA methylation data from 12 studies, together with our own dataset, using Illumina Infinium Human Methylation BeadChip arrays. RESULTS & CONCLUSION: We developed an accurate tool for predicting gestational age of placentas using 62 CpG sites. There was a higher predicted gestational age for placentas from early onset preeclampsia cases, but not term preeclampsia, compared with their chronological age. Therefore, early onset preeclampsia is associated with placental aging. Gestational age acceleration prediction from DNA methylation array data may provide insight into the molecular mechanisms of pregnancy disorders. Future Medicine Ltd 2017-03 2016-11-29 /pmc/articles/PMC6040051/ /pubmed/27894195 http://dx.doi.org/10.2217/epi-2016-0103 Text en © 2016 Tina Bianco-Miotto This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 Unported License (http://creativecommons.org/licenses/by-nc-nd/4.0/)
spellingShingle Research Article
Mayne, Benjamin T
Leemaqz, Shalem Y
Smith, Alicia K
Breen, James
Roberts, Claire T
Bianco-Miotto, Tina
Accelerated placental aging in early onset preeclampsia pregnancies identified by DNA methylation
title Accelerated placental aging in early onset preeclampsia pregnancies identified by DNA methylation
title_full Accelerated placental aging in early onset preeclampsia pregnancies identified by DNA methylation
title_fullStr Accelerated placental aging in early onset preeclampsia pregnancies identified by DNA methylation
title_full_unstemmed Accelerated placental aging in early onset preeclampsia pregnancies identified by DNA methylation
title_short Accelerated placental aging in early onset preeclampsia pregnancies identified by DNA methylation
title_sort accelerated placental aging in early onset preeclampsia pregnancies identified by dna methylation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6040051/
https://www.ncbi.nlm.nih.gov/pubmed/27894195
http://dx.doi.org/10.2217/epi-2016-0103
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