Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors

Kim F. Michaelsen; Rachel M Freathy; EGG Consortium

doi:10.1038/s41588-019-0403-1

Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors

Kim F. Michaelsen, Rachel M Freathy^*, EGG Consortium

^*Corresponding author for this work

93 Citations (Scopus)

Abstract

Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight–blood pressure association is attributable to genetic effects, and not to intrauterine programming.

Original language	English
Journal	Nature Genetics
Volume	51
Issue number	5
Pages (from-to)	804-814
Number of pages	11
ISSN	1061-4036
DOIs	https://doi.org/10.1038/s41588-019-0403-1
Publication status	Published - 2019

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title = "Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors",

abstract = "Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight–blood pressure association is attributable to genetic effects, and not to intrauterine programming.",

author = "Warrington, {Nicole M.} and Beaumont, {Robin N.} and Momoko Horikoshi and Day, {Felix R.} and {\O}yvind Helgeland and Charles Laurin and Jonas Bacelis and Shouneng Peng and Ke Hao and Bjarke Feenstra and Wood, {Andrew R.} and Anubha Mahajan and Jessica Tyrrell and Robertson, {Neil R.} and Rayner, {N. William} and Zhen Qiao and Moen, {Gunn Helen} and Marc Vaudel and Marsit, {Carmen J.} and Jia Chen and Michael Nodzenski and Schnurr, {Theresia M.} and Zafarmand, {Mohammad H.} and Bradfield, {Jonathan P.} and Niels Grarup and Kooijman, {Marjolein N.} and Ruifang Li-Gao and Frank Geller and Ahluwalia, {Tarunveer S.} and Have, {Christian T.} and Morgen, {Camilla S.} and Zhao, {Jing Hua} and Appel, {Emil V.R.} and Fonvig, {Cilius E.} and Caecilie Trier and Allan Linneberg and Chawes, {Bo L.} and Peter Kovacs and Michaelsen, {Kim F.} and Kadarmideen, {Haja N.} and Holm, {Jens Christian} and S{\o}rensen, {Thorkild I.A.} and Hans Bisgaard and Klaus B{\o}nnelykke and Mads Melbye and Nohr, {Ellen A.} and Torben Hansen and Charlotta Pisinger and Vaag, {Allan A.} and Oluf Pedersen and Freathy, {Rachel M} and {EGG Consortium}",

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AU - Warrington, Nicole M.

AU - Beaumont, Robin N.

AU - Horikoshi, Momoko

AU - Day, Felix R.

AU - Helgeland, Øyvind

AU - Laurin, Charles

AU - Bacelis, Jonas

AU - Peng, Shouneng

AU - Hao, Ke

AU - Feenstra, Bjarke

AU - Wood, Andrew R.

AU - Mahajan, Anubha

AU - Tyrrell, Jessica

AU - Robertson, Neil R.

AU - Rayner, N. William

AU - Qiao, Zhen

AU - Moen, Gunn Helen

AU - Vaudel, Marc

AU - Marsit, Carmen J.

AU - Chen, Jia

AU - Nodzenski, Michael

AU - Schnurr, Theresia M.

AU - Zafarmand, Mohammad H.

AU - Bradfield, Jonathan P.

AU - Grarup, Niels

AU - Kooijman, Marjolein N.

AU - Li-Gao, Ruifang

AU - Geller, Frank

AU - Ahluwalia, Tarunveer S.

AU - Have, Christian T.

AU - Morgen, Camilla S.

AU - Zhao, Jing Hua

AU - Appel, Emil V.R.

AU - Fonvig, Cilius E.

AU - Trier, Caecilie

AU - Linneberg, Allan

AU - Chawes, Bo L.

AU - Kovacs, Peter

AU - Michaelsen, Kim F.

AU - Kadarmideen, Haja N.

AU - Holm, Jens Christian

AU - Sørensen, Thorkild I.A.

AU - Bisgaard, Hans

AU - Bønnelykke, Klaus

AU - Melbye, Mads

AU - Nohr, Ellen A.

AU - Hansen, Torben

AU - Pisinger, Charlotta

AU - Vaag, Allan A.

AU - Pedersen, Oluf

AU - Freathy, Rachel M

AU - EGG Consortium

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N2 - Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight–blood pressure association is attributable to genetic effects, and not to intrauterine programming.

AB - Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight–blood pressure association is attributable to genetic effects, and not to intrauterine programming.

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Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors

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