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dc.contributor.authorBeaumont, Robin N.
dc.contributor.authorWood, A. R.
dc.contributor.authorKnight, Bridget A.
dc.contributor.authorHattersley, Andrew T.
dc.contributor.authorFreathy, Rachel M.
dc.date.accessioned2021-07-05T13:49:39Z
dc.date.available2021-07-05T13:49:39Z
dc.date.issued2020-12-07
dc.identifier.citationBeaumont RN et al. Common maternal and fetal genetic variants show expected polygenic effects on risk of small- or large-for-gestational-age (SGA or LGA), except in the smallest 3% of babies. PLoS Genet. 2020 Dec 7;16(12):e1009191.en_US
dc.identifier.pmid33284794
dc.identifier.doi10.1371/journal.pgen.1009191
dc.identifier.urihttps://rde.dspace-express.com/handle/11287/621810
dc.description.abstractBabies born clinically Small- or Large-for-Gestational-Age (SGA or LGA; sex- and gestational age-adjusted birth weight (BW) <10th or >90th percentile, respectively), are at higher risks of complications. SGA and LGA include babies who have experienced environment-related growth-restriction or overgrowth, respectively, and babies who are heritably small or large. However, the relative proportions within each group are unclear. We assessed the extent to which common genetic variants underlying variation in birth weight influence the probability of being SGA or LGA. We calculated independent fetal and maternal genetic scores (GS) for BW in 11,951 babies and 5,182 mothers. These scores capture the direct fetal and indirect maternal (via intrauterine environment) genetic contributions to BW, respectively. We also calculated maternal fasting glucose (FG) and systolic blood pressure (SBP) GS. We tested associations between each GS and probability of SGA or LGA. For the BW GS, we used simulations to assess evidence of deviation from an expected polygenic model. Higher BW GS were strongly associated with lower odds of SGA and higher odds of LGA (ORfetal = 0.75 (0.71,0.80) and 1.32 (1.26,1.39); ORmaternal = 0.81 (0.75,0.88) and 1.17 (1.09,1.25), respectively per 1 decile higher GS). We found evidence that the smallest 3% of babies had a higher BW GS, on average, than expected from their observed birth weight (assuming an additive polygenic model: Pfetal = 0.014, Pmaternal = 0.062). Higher maternal SBP GS was associated with higher odds of SGA P = 0.005. We conclude that common genetic variants contribute to risk of SGA and LGA, but that additional factors become more important for risk of SGA in the smallest 3% of babies.en_US
dc.language.isoenen_US
dc.publisherPublic Library of Scienceen_US
dc.relation.urlhttps://dx.plos.org/10.1371/journal.pgen.1009191en_US
dc.rights© 2020 Beaumont et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.en_US
dc.rightsCC0 1.0 Universal*
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.subjectBirth Weighten_US
dc.subjectNewbornen_US
dc.subjectMultifactorial Inheritanceen_US
dc.subjectPolymorphismen_US
dc.subjectWessex Classification Subject Headings::Oncology. Pathology.::Geneticsen_US
dc.titleCommon maternal and fetal genetic variants show expected polygenic effects on risk of small- or large-for-gestational-age (SGA or LGA), except in the smallest 3% of babiesen_US
dc.typeJournal Articleen_US
dc.identifier.journalPLoS Geneticsen_US
dc.identifier.pmcidPMC7721187
dc.description.noteThis article is available to RD&E staff via NHS OpenAthens. Click on the Publisher URL, and log in with NHS OpenAthens if prompted.en_US
dc.description.fundingRMF and RNB are funded by a Wellcome Trust and Royal Society Sir Henry Dale Fellowship (104150/Z/14/Z). ATH is supported by a NIHR Senior Investigator award and also a Wellcome Trust Senior Investigator award (098395/Z/12/Z). The funders had no role in the design of the study, the collection, analysis, or interpretation of the data; the writing of the manuscript, or the decision to submit the manuscript for publication. The views expressed in this paper are those of the authors and not necessarily those of any funder. The UK Medical Research Council and Wellcome (Grant ref: 217065/Z/19/Z) and the University of Bristol provide core support for ALSPAC. This publication is the work of the authors and Rachel M. Freathy will serve as guarantor for the contents of this paper. Genotyping of the EFSOCH study samples was funded by the Wellcome Trust and Royal Society grant 104150/Z/14/Z. NFBC1966 and 1986 have received core funding for data generation and curation from the Academy of Finland (project grants 104781, 120315, 129269, 1114194, 24300796, 85547, 285547 (EGEA)), University Hospital Oulu, Finland (75617), the EU FP5 EURO-BLCS, QLG1-CT-2000-01643, ERDF European Regional Development Fund Grant no. 539/2010 A31592 and the EU H2020--PHC-2014 DynaHEALTH action (grant no. 633595). The NFBCs are also funded by EU-H2020 LifeCycle Action (grant no. 733206), EU-H2020 EDCMET (grant no. 825762), EU-H2020 EUCAN Connect (grant no 824989), EU H2020-MSCA-ITN-2016 CAPICE Marie Sklodowska-Curie grant (grant no. 721567) and the Medical Research Council, UK (grants no. MR/M013138/1, MRC/BBSRC MR/S03658X/1 (JPI HDHL)).en_US
dc.type.versionPublisheden_US


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© 2020 Beaumont et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Except where otherwise noted, this item's license is described as © 2020 Beaumont et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.