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Using Genomic Structural Equation Modeling to Partition the Genetic Covariance Between Birthweight and Cardiometabolic Risk Factors into Maternal and Offspring Components in the Norwegian HUNT Study

The Barker Hypothesis posits that adverse intrauterine environments result in fetal growth restriction and increased risk of cardiometabolic disease through developmental compensations. Here we introduce a new statistical model using the genomic SEM software that is capable of simultaneously partiti...

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Autores principales: Moen, Gunn-Helen, Nivard, Michel, Bhatta, Laxmi, Warrington, Nicole M, Willer, Cristen, Åsvold, Bjørn Olav, Brumpton, Ben, Evans, David M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9823066/
https://www.ncbi.nlm.nih.gov/pubmed/36322199
http://dx.doi.org/10.1007/s10519-022-10116-9
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author Moen, Gunn-Helen
Nivard, Michel
Bhatta, Laxmi
Warrington, Nicole M
Willer, Cristen
Åsvold, Bjørn Olav
Brumpton, Ben
Evans, David M.
author_facet Moen, Gunn-Helen
Nivard, Michel
Bhatta, Laxmi
Warrington, Nicole M
Willer, Cristen
Åsvold, Bjørn Olav
Brumpton, Ben
Evans, David M.
author_sort Moen, Gunn-Helen
collection PubMed
description The Barker Hypothesis posits that adverse intrauterine environments result in fetal growth restriction and increased risk of cardiometabolic disease through developmental compensations. Here we introduce a new statistical model using the genomic SEM software that is capable of simultaneously partitioning the genetic covariation between birthweight and cardiometabolic traits into maternally mediated and offspring mediated contributions. We model the covariance between birthweight and later life outcomes, such as blood pressure, non-fasting glucose, blood lipids and body mass index in the Norwegian HUNT study, consisting of 15,261 mother-eldest offspring pairs with genetic and phenotypic data. Application of this model showed some evidence for maternally mediated effects of systolic blood pressure on offspring birthweight, and pleiotropy between birthweight and non-fasting glucose mediated through the offspring genome. This underscores the importance of genetic links between birthweight and cardiometabolic phenotypes and offer alternative explanations to environmentally based hypotheses for the phenotypic correlation between these variables. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10519-022-10116-9.
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spelling pubmed-98230662023-01-08 Using Genomic Structural Equation Modeling to Partition the Genetic Covariance Between Birthweight and Cardiometabolic Risk Factors into Maternal and Offspring Components in the Norwegian HUNT Study Moen, Gunn-Helen Nivard, Michel Bhatta, Laxmi Warrington, Nicole M Willer, Cristen Åsvold, Bjørn Olav Brumpton, Ben Evans, David M. Behav Genet Original Research The Barker Hypothesis posits that adverse intrauterine environments result in fetal growth restriction and increased risk of cardiometabolic disease through developmental compensations. Here we introduce a new statistical model using the genomic SEM software that is capable of simultaneously partitioning the genetic covariation between birthweight and cardiometabolic traits into maternally mediated and offspring mediated contributions. We model the covariance between birthweight and later life outcomes, such as blood pressure, non-fasting glucose, blood lipids and body mass index in the Norwegian HUNT study, consisting of 15,261 mother-eldest offspring pairs with genetic and phenotypic data. Application of this model showed some evidence for maternally mediated effects of systolic blood pressure on offspring birthweight, and pleiotropy between birthweight and non-fasting glucose mediated through the offspring genome. This underscores the importance of genetic links between birthweight and cardiometabolic phenotypes and offer alternative explanations to environmentally based hypotheses for the phenotypic correlation between these variables. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10519-022-10116-9. Springer US 2022-11-02 2023 /pmc/articles/PMC9823066/ /pubmed/36322199 http://dx.doi.org/10.1007/s10519-022-10116-9 Text en © The Author(s) 2022 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/) .
spellingShingle Original Research
Moen, Gunn-Helen
Nivard, Michel
Bhatta, Laxmi
Warrington, Nicole M
Willer, Cristen
Åsvold, Bjørn Olav
Brumpton, Ben
Evans, David M.
Using Genomic Structural Equation Modeling to Partition the Genetic Covariance Between Birthweight and Cardiometabolic Risk Factors into Maternal and Offspring Components in the Norwegian HUNT Study
title Using Genomic Structural Equation Modeling to Partition the Genetic Covariance Between Birthweight and Cardiometabolic Risk Factors into Maternal and Offspring Components in the Norwegian HUNT Study
title_full Using Genomic Structural Equation Modeling to Partition the Genetic Covariance Between Birthweight and Cardiometabolic Risk Factors into Maternal and Offspring Components in the Norwegian HUNT Study
title_fullStr Using Genomic Structural Equation Modeling to Partition the Genetic Covariance Between Birthweight and Cardiometabolic Risk Factors into Maternal and Offspring Components in the Norwegian HUNT Study
title_full_unstemmed Using Genomic Structural Equation Modeling to Partition the Genetic Covariance Between Birthweight and Cardiometabolic Risk Factors into Maternal and Offspring Components in the Norwegian HUNT Study
title_short Using Genomic Structural Equation Modeling to Partition the Genetic Covariance Between Birthweight and Cardiometabolic Risk Factors into Maternal and Offspring Components in the Norwegian HUNT Study
title_sort using genomic structural equation modeling to partition the genetic covariance between birthweight and cardiometabolic risk factors into maternal and offspring components in the norwegian hunt study
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9823066/
https://www.ncbi.nlm.nih.gov/pubmed/36322199
http://dx.doi.org/10.1007/s10519-022-10116-9
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