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An EPIC predictor of gestational age and its application to newborns conceived by assisted reproductive technologies
BACKGROUND: Gestational age is a useful proxy for assessing developmental maturity, but correct estimation of gestational age is difficult using clinical measures. DNA methylation at birth has proven to be an accurate predictor of gestational age. Previous predictors of epigenetic gestational age we...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8056641/ https://www.ncbi.nlm.nih.gov/pubmed/33875015 http://dx.doi.org/10.1186/s13148-021-01055-z |
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author | Haftorn, Kristine L. Lee, Yunsung Denault, William R. P. Page, Christian M. Nustad, Haakon E. Lyle, Robert Gjessing, Håkon K. Malmberg, Anni Magnus, Maria C. Næss, Øyvind Czamara, Darina Räikkönen, Katri Lahti, Jari Magnus, Per Håberg, Siri E. Jugessur, Astanand Bohlin, Jon |
author_facet | Haftorn, Kristine L. Lee, Yunsung Denault, William R. P. Page, Christian M. Nustad, Haakon E. Lyle, Robert Gjessing, Håkon K. Malmberg, Anni Magnus, Maria C. Næss, Øyvind Czamara, Darina Räikkönen, Katri Lahti, Jari Magnus, Per Håberg, Siri E. Jugessur, Astanand Bohlin, Jon |
author_sort | Haftorn, Kristine L. |
collection | PubMed |
description | BACKGROUND: Gestational age is a useful proxy for assessing developmental maturity, but correct estimation of gestational age is difficult using clinical measures. DNA methylation at birth has proven to be an accurate predictor of gestational age. Previous predictors of epigenetic gestational age were based on DNA methylation data from the Illumina HumanMethylation 27 K or 450 K array, which have subsequently been replaced by the Illumina MethylationEPIC 850 K array (EPIC). Our aims here were to build an epigenetic gestational age clock specific for the EPIC array and to evaluate its precision and accuracy using the embryo transfer date of newborns from the largest EPIC-derived dataset to date on assisted reproductive technologies (ART). METHODS: We built an epigenetic gestational age clock using Lasso regression trained on 755 randomly selected non-ART newborns from the Norwegian Study of Assisted Reproductive Technologies (START)—a substudy of the Norwegian Mother, Father, and Child Cohort Study (MoBa). For the ART-conceived newborns, the START dataset had detailed information on the embryo transfer date and the specific ART procedure used for conception. The predicted gestational age was compared to clinically estimated gestational age in 200 non-ART and 838 ART newborns using MM-type robust regression. The performance of the clock was compared to previously published gestational age clocks in an independent replication sample of 148 newborns from the Prediction and Prevention of Preeclampsia and Intrauterine Growth Restrictions (PREDO) study—a prospective pregnancy cohort of Finnish women. RESULTS: Our new epigenetic gestational age clock showed higher precision and accuracy in predicting gestational age than previous gestational age clocks (R(2) = 0.724, median absolute deviation (MAD) = 3.14 days). Restricting the analysis to CpGs shared between 450 K and EPIC did not reduce the precision of the clock. Furthermore, validating the clock on ART newborns with known embryo transfer date confirmed that DNA methylation is an accurate predictor of gestational age (R(2) = 0.767, MAD = 3.7 days). CONCLUSIONS: We present the first EPIC-based predictor of gestational age and demonstrate its robustness and precision in ART and non-ART newborns. As more datasets are being generated on the EPIC platform, this clock will be valuable in studies using gestational age to assess neonatal development. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13148-021-01055-z. |
format | Online Article Text |
id | pubmed-8056641 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-80566412021-04-20 An EPIC predictor of gestational age and its application to newborns conceived by assisted reproductive technologies Haftorn, Kristine L. Lee, Yunsung Denault, William R. P. Page, Christian M. Nustad, Haakon E. Lyle, Robert Gjessing, Håkon K. Malmberg, Anni Magnus, Maria C. Næss, Øyvind Czamara, Darina Räikkönen, Katri Lahti, Jari Magnus, Per Håberg, Siri E. Jugessur, Astanand Bohlin, Jon Clin Epigenetics Research BACKGROUND: Gestational age is a useful proxy for assessing developmental maturity, but correct estimation of gestational age is difficult using clinical measures. DNA methylation at birth has proven to be an accurate predictor of gestational age. Previous predictors of epigenetic gestational age were based on DNA methylation data from the Illumina HumanMethylation 27 K or 450 K array, which have subsequently been replaced by the Illumina MethylationEPIC 850 K array (EPIC). Our aims here were to build an epigenetic gestational age clock specific for the EPIC array and to evaluate its precision and accuracy using the embryo transfer date of newborns from the largest EPIC-derived dataset to date on assisted reproductive technologies (ART). METHODS: We built an epigenetic gestational age clock using Lasso regression trained on 755 randomly selected non-ART newborns from the Norwegian Study of Assisted Reproductive Technologies (START)—a substudy of the Norwegian Mother, Father, and Child Cohort Study (MoBa). For the ART-conceived newborns, the START dataset had detailed information on the embryo transfer date and the specific ART procedure used for conception. The predicted gestational age was compared to clinically estimated gestational age in 200 non-ART and 838 ART newborns using MM-type robust regression. The performance of the clock was compared to previously published gestational age clocks in an independent replication sample of 148 newborns from the Prediction and Prevention of Preeclampsia and Intrauterine Growth Restrictions (PREDO) study—a prospective pregnancy cohort of Finnish women. RESULTS: Our new epigenetic gestational age clock showed higher precision and accuracy in predicting gestational age than previous gestational age clocks (R(2) = 0.724, median absolute deviation (MAD) = 3.14 days). Restricting the analysis to CpGs shared between 450 K and EPIC did not reduce the precision of the clock. Furthermore, validating the clock on ART newborns with known embryo transfer date confirmed that DNA methylation is an accurate predictor of gestational age (R(2) = 0.767, MAD = 3.7 days). CONCLUSIONS: We present the first EPIC-based predictor of gestational age and demonstrate its robustness and precision in ART and non-ART newborns. As more datasets are being generated on the EPIC platform, this clock will be valuable in studies using gestational age to assess neonatal development. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13148-021-01055-z. BioMed Central 2021-04-19 /pmc/articles/PMC8056641/ /pubmed/33875015 http://dx.doi.org/10.1186/s13148-021-01055-z Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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 | Research Haftorn, Kristine L. Lee, Yunsung Denault, William R. P. Page, Christian M. Nustad, Haakon E. Lyle, Robert Gjessing, Håkon K. Malmberg, Anni Magnus, Maria C. Næss, Øyvind Czamara, Darina Räikkönen, Katri Lahti, Jari Magnus, Per Håberg, Siri E. Jugessur, Astanand Bohlin, Jon An EPIC predictor of gestational age and its application to newborns conceived by assisted reproductive technologies |
title | An EPIC predictor of gestational age and its application to newborns conceived by assisted reproductive technologies |
title_full | An EPIC predictor of gestational age and its application to newborns conceived by assisted reproductive technologies |
title_fullStr | An EPIC predictor of gestational age and its application to newborns conceived by assisted reproductive technologies |
title_full_unstemmed | An EPIC predictor of gestational age and its application to newborns conceived by assisted reproductive technologies |
title_short | An EPIC predictor of gestational age and its application to newborns conceived by assisted reproductive technologies |
title_sort | epic predictor of gestational age and its application to newborns conceived by assisted reproductive technologies |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8056641/ https://www.ncbi.nlm.nih.gov/pubmed/33875015 http://dx.doi.org/10.1186/s13148-021-01055-z |
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