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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

Authors :
Gunn-Helen Moen
Michel Nivard
Laxmi Bhatta
Nicole M Warrington
Cristen Willer
Bjørn Olav Åsvold
Ben Brumpton
David M. Evans
Biological Psychology
APH - Mental Health
APH - Methodology
Source :
Behavior Genetics, Behavior Genetics, 53(1), 40-52. Springer, Moen, G H, Nivard, M, Bhatta, L, Warrington, N M, Willer, C, Åsvold, B O, Brumpton, B & Evans, D M 2023, ' 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 ', Behavior Genetics, vol. 53, no. 1, pp. 40-52 . https://doi.org/10.1007/s10519-022-10116-9
Publication Year :
2023
Publisher :
Springer, 2023.

Abstract

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.

Details

Language :
English
ISSN :
15733297 and 00018244
Volume :
53
Issue :
1
Database :
OpenAIRE
Journal :
Behavior Genetics
Accession number :
edsair.doi.dedup.....cfbd48c83d03d3a68f28d01292f0e5b2
Full Text :
https://doi.org/10.1007/s10519-022-10116-9