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

Gunn-Helen Moen; Michel Nivard; Laxmi Bhatta; Nicole M Warrington; Cristen Willer; Bjørn Olav Åsvold; Ben Brumpton; David M Evans

doi:10.1007/s10519-022-10116-9

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

Behav Genet. 2023 Feb;53(1):40-52. doi: 10.1007/s10519-022-10116-9. Epub 2022 Nov 2.

Authors

Gunn-Helen Moen^{1

2

3

4

5}, Michel Nivard^{6

7}, Laxmi Bhatta⁸, Nicole M Warrington^{9

8

10}, Cristen Willer^{11

12

13}, Bjørn Olav Åsvold^{8

14

15}, Ben Brumpton^{8

15

16}, David M Evans^{17

18

19}

Affiliations

¹ Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway. g.h.moen@medisin.uio.no.
² Institute of Molecular Biosciences, The University of Queensland, Brisbane, Australia. g.h.moen@medisin.uio.no.
³ Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, NTNU, Norwegian University of Science and Technology, Trondheim, Norway. g.h.moen@medisin.uio.no.
⁴ Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK. g.h.moen@medisin.uio.no.
⁵ The University of Queensland Diamantina Institute, The University of Queensland, 4102, Woolloongabba, QLD, Australia. g.h.moen@medisin.uio.no.
⁶ Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
⁷ Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, Amsterdam, The Netherlands.
⁸ Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.
⁹ Institute of Molecular Biosciences, The University of Queensland, Brisbane, Australia.
¹⁰ The University of Queensland Diamantina Institute, The University of Queensland, 4102, Woolloongabba, QLD, Australia.
¹¹ Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, USA.
¹² Department of Internal Medicine, University of Michigan, Ann Arbor, MI, US.
¹³ Department of Human Genetics, University of Michigan, Ann Arbor, USA.
¹⁴ Department of Endocrinology, Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway.
¹⁵ Department of Public Health and Nursing, HUNT Research Centre, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.
¹⁶ Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway.
¹⁷ Institute of Molecular Biosciences, The University of Queensland, Brisbane, Australia. d.evans1@uq.edu.au.
¹⁸ The University of Queensland Diamantina Institute, The University of Queensland, 4102, Woolloongabba, QLD, Australia. d.evans1@uq.edu.au.
¹⁹ Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK. d.evans1@uq.edu.au.

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.

Keywords: Birthweight; Developmental Origin of Health and Disease; Genomic SEM; Maternal genetic effect; Offspring genetic effect.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Birth Weight / genetics
Cardiometabolic Risk Factors*
Cardiovascular Diseases* / genetics
Genomics
Humans
Latent Class Analysis
Risk Factors

Abstract

Publication types

MeSH terms

Grants and funding