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
dc.contributor.author | Beaumont, RN | |
dc.contributor.author | Kotecha, SJ | |
dc.contributor.author | Wood, AR | |
dc.contributor.author | Knight, BA | |
dc.contributor.author | Sebert, S | |
dc.contributor.author | McCarthy, MI | |
dc.contributor.author | Hattersley, AT | |
dc.contributor.author | Järvelin, M-R | |
dc.contributor.author | Timpson, NJ | |
dc.contributor.author | Freathy, RM | |
dc.contributor.author | Kotecha, S | |
dc.date.accessioned | 2020-12-08T10:59:41Z | |
dc.date.issued | 2020-12-07 | |
dc.description.abstract | Babies 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_GB |
dc.description.sponsorship | Wellcome Trust | en_GB |
dc.description.sponsorship | Royal Society | en_GB |
dc.description.sponsorship | National Institute for Health Research (NIHR) | en_GB |
dc.identifier.citation | Vol. 16 (12), article e1009191 | en_GB |
dc.identifier.doi | 10.1371/journal.pgen.1009191 | |
dc.identifier.grantnumber | 104150/Z/14/Z | en_GB |
dc.identifier.grantnumber | 098395/Z/12/Z | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/123948 | |
dc.language.iso | en | en_GB |
dc.publisher | Public Library of Science (PLoS) | en_GB |
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_GB |
dc.title | 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 | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2020-12-08T10:59:41Z | |
dc.identifier.issn | 1553-7390 | |
dc.description | This is the final version. Available on open access from the Public Library of Science via the DOI in this record | en_GB |
dc.description | Data Availability: We used both published summary results (i.e. taking results from published research papers and websites) and individual participant cohort data as follows: Journal published and website summary data were used for generating the genetic scores of birth weight, fasting glucose and systolic blood pressure. The references to those published data sources are provided in the main paper. We used individual participant data from ALSPAC, EFSOCH and NFBC cohorts. The data in ALSPAC are fully available, via managed systems, to any researchers. The managed system is a requirement of the study funders but access is not restricted on the basis of overlap with other applications to use the data or on the basis of peer review of the proposed science. Researchers have to pay for a dataset to be prepared for them. ALSPAC. The ALSPAC data management plan (http://www.bristol.ac.uk/alspac/researchers/data-access/documents/alspac-data-management-plan.pdf) describes in detail the policy regarding data sharing, which is through a system of managed open access. The steps below highlight how to apply for access to the data included in this paper and all other ALSPAC data. 1. Please read the ALSPAC access policy (PDF, 627kB) which describes the process of accessing the data and samples in detail, and outlines the costs associated with doing so. 2. You may also find it useful to browse the fully searchable ALSPAC research proposals database, which lists all research projects that have been approved since April 2011. 3. Please submit your research proposal for consideration by the ALSPAC Executive Committee. You will receive a response within 10 working days to advise you whether your proposal has been approved. If you have any questions about accessing data, please email alspac-data@bristol.ac.uk. EFSOCH. Requests for access to the original EFSOCH dataset should be made in writing in the first instance to the EFSOCH data team via the Exeter Clinical Research Facility crf@exeter.ac.uk. NFBC: Data is available from the Northern Finland Birth Cohort (NFBC) for researchers who meet the criteria for accessing confidential data. Please, contact NFBC project center (NFBCprojectcenter@oulu.fi) and visit the cohort website (www.oulu.fi/nfbc) for more information. | en_GB |
dc.identifier.journal | PLoS Genetics | en_GB |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2020-10-13 | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2020-10-13 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2020-11-05T14:25:21Z | |
refterms.versionFCD | AM | |
refterms.dateFOA | 2020-12-08T10:59:45Z | |
refterms.panel | A | en_GB |
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Except where otherwise noted, this item's licence 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.