Evidence map›Paper›PMID 33284794›Full record

ArticlePLoS genetics2020

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.

Robin N Beaumont, Sarah J Kotecha, Andrew R Wood, Bridget A Knight, Sylvain Sebert, Mark I McCarthy, Andrew T Hattersley, Marjo-Riitta Järvelin, Nicholas J Timpson, Rachel M Freathy and 1 more

Abstract read
In one paragraph

Article in PLoS genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Robin N BeaumontInstitute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, United Kingdom.ORCID 0000-0003-0750-8248
Sarah J KotechaDepartment of Child Health, School of Medicine, Cardiff University, Cardiff, United Kingdom.
Andrew R WoodInstitute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, United Kingdom.
Bridget A KnightInstitute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, United Kingdom.ORCID 0000-0002-2073-0487
Sylvain SebertCenter for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulun yliopisto, Finland.ORCID 0000-0001-6681-6983
Mark I McCarthyWellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.ORCID 0000-0002-4393-0510
Andrew T HattersleyInstitute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, United Kingdom.ORCID 0000-0001-5620-473X
Marjo-Riitta JärvelinCenter for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulun yliopisto, Finland.ORCID 0000-0002-2149-0630
Nicholas J TimpsonMedical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom.ORCID 0000-0002-7141-9189
Rachel M FreathyInstitute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, United Kingdom.ORCID 0000-0003-4152-2238
Sailesh KotechaDepartment of Child Health, School of Medicine, Cardiff University, Cardiff, United Kingdom.ORCID 0000-0003-3535-7627

Funding

Department of HealthMedical Research Council G9815508Medical Research Council MC_PC_15018Medical Research Council MC_PC_19009Medical Research Council MR/M008924/1Medical Research Council MR/M013138/1Medical Research Council MR/M013138/2Medical Research Council MR/S03658X/1Wellcome Trust 098395/Z/12/ZWellcome Trust 104150/Z/14/ZWellcome Trust 202802/Z/16/ZWellcome Trust 217065/Z/19/Z
6 · The paper itself

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.

Indexed as

Multifactorial InheritancePolymorphism, GeneticAdultBirth WeightFemaleHumansInfant, NewbornInfant, Small for Gestational AgeMale

Identifiers

PMID33284794
PMCPMC7721187

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.