University of Oulu

Bond, T.A., Richmond, R.C., Karhunen, V. et al. Exploring the causal effect of maternal pregnancy adiposity on offspring adiposity: Mendelian randomisation using polygenic risk scores. BMC Med 20, 34 (2022). https://doi.org/10.1186/s12916-021-02216-w

Exploring the causal effect of maternal pregnancy adiposity on offspring adiposity : Mendelian randomisation using polygenic risk scores

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Author: Bond, Tom A.1,2,3,4,5; Richmond, Rebecca C.4,5; Karhunen, Ville1,6,7;
Organizations: 1Department of Epidemiology and Biostatistics, Imperial College London, London, UK
2MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
3The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, Australia
4MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
5Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
6Center for Life-course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
7Research Unit of Mathematical Sciences, University of Oulu, Oulu, Finland
823andMe, Inc., Sunnyvale, CA, USA
9MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
10School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
11Born in Bradford, Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
12Section of Nutrition and Metabolism, IARC, Lyon, France
13Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
14Institute for Molecular Bioscience, University of Queensland, Brisbane, Australia
15Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
16Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
17Unit of Primary Care, Oulu University Hospital, Oulu, Finland
18Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.4 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2022060844267
Language: English
Published: Springer Nature, 2022
Publish Date: 2022-08-16
Description:

Abstract

Background: Greater maternal adiposity before or during pregnancy is associated with greater offspring adiposity throughout childhood, but the extent to which this is due to causal intrauterine or periconceptional mechanisms remains unclear. Here, we use Mendelian randomisation (MR) with polygenic risk scores (PRS) to investigate whether associations between maternal pre-/early pregnancy body mass index (BMI) and offspring adiposity from birth to adolescence are causal.

Methods: We undertook confounder adjusted multivariable (MV) regression and MR using mother-offspring pairs from two UK cohorts: Avon Longitudinal Study of Parents and Children (ALSPAC) and Born in Bradford (BiB). In ALSPAC and BiB, the outcomes were birthweight (BW; N = 9339) and BMI at age 1 and 4 years (N = 8659 to 7575). In ALSPAC only we investigated BMI at 10 and 15 years (N = 4476 to 4112) and dual-energy X-ray absorptiometry (DXA) determined fat mass index (FMI) from age 10–18 years (N = 2659 to 3855). We compared MR results from several PRS, calculated from maternal non-transmitted alleles at between 29 and 80,939 single nucleotide polymorphisms (SNPs).

Results: MV and MR consistently showed a positive association between maternal BMI and BW, supporting a moderate causal effect. For adiposity at most older ages, although MV estimates indicated a strong positive association, MR estimates did not support a causal effect. For the PRS with few SNPs, MR estimates were statistically consistent with the null, but had wide confidence intervals so were often also statistically consistent with the MV estimates. In contrast, the largest PRS yielded MR estimates with narrower confidence intervals, providing strong evidence that the true causal effect on adolescent adiposity is smaller than the MV estimates (Pdifference = 0.001 for 15-year BMI). This suggests that the MV estimates are affected by residual confounding, therefore do not provide an accurate indication of the causal effect size.

Conclusions: Our results suggest that higher maternal pre-/early-pregnancy BMI is not a key driver of higher adiposity in the next generation. Thus, they support interventions that target the whole population for reducing overweight and obesity, rather than a specific focus on women of reproductive age.

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Series: BMC medicine
ISSN: 1741-7015
ISSN-E: 1741-7015
ISSN-L: 1741-7015
Volume: 20
Article number: 34
DOI: 10.1186/s12916-021-02216-w
OADOI: https://oadoi.org/10.1186/s12916-021-02216-w
Type of Publication: A1 Journal article – refereed
Field of Science: 3111 Biomedicine
3142 Public health care science, environmental and occupational health
Subjects:
BMI
Funding: The UK Medical Research Council and Wellcome (102215/2/13/2) and the University of Bristol provide core support for ALSPAC. Genotyping of the ALSPAC maternal samples was funded by the Wellcome Trust (WT088806) and the offspring samples were genotyped by Sample Logistics and Genotyping Facilities at the Wellcome Trust Sanger Institute and LabCorp (Laboratory Corporation of America) using support from 23andMe. A comprehensive list of grants funding is available on the ALSPAC website (http://www.bristol.ac.uk/alspac/external/documents/grant-acknowledgements.pdf). BiB receives core infrastructure funding from the Wellcome Trust (WT101597MA), a joint grant from the UK Medical Research Council (MRC) and UK Economic and Social Science Research Council (ESRC) (MR/N024397/1), the British Heart Foundation (CS/16/4/32482) and the National Institute for Health Research (NIHR) under its Applied Research Collaboration Yorkshire and Humber (NIHR200166). Further support for genome-wide data is from the UK Medical Research Council (G0600705) and the National Institute of Health Research (NF-SI-0611-10196). The work presented here was supported by the US National Institute of Health (R01 DK10324), the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement (669545) and the British Heart Foundation (AA/18/7/34219). TAB is supported by the Medical Research Council (MRC) (UK) (MR/K501281/1); TAB and DME are supported by the NHMRC (Australia) (GNT1183074 and GNT1157714); DAL, TAB, MCB and RCR work in/are affiliated with a unit that is supported by the UK Medical Research Council (MC_UU_00011/1 & MC_UU_00011/6); and DAL is a British Heart Foundation Chair (CH/F/20/90003) and NIHR Senior Investigator (NF-0616-10102). DAL, MCB and TAB are supported by the British Heart Foundation Accelerator Award at the University of Bristol (AA/18/7/34219). MCB’s contribution to this work was supported by a UK MRC Skills Development Fellowship (MR/P014054/1). VK is funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant (721567). MRJ is funded by EU-H2020 LifeCycle Action (733206) which also supports DAL’s research, EU-H2020 EDCMET (825762), EU-H2020 EUCAN Connect (824989), EU H2020-MSCA-ITN-2016 CAPICE Marie Sklodowska-Curie grant (721567) and the MRC (UK) (MRC/BBSRC MR/S03658X/1 [JPI HDHL]). RCR is a de Pass Vice Chancellor’s Research Fellow at the University of Bristol. AL and MRJ are supported by the MRC (UK) (MR/M013138/1) and the European Union Horizon 2020 programme (633595). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.
EU Grant Number: (733206) LIFECYCLE - Early-life stressors and LifeCycle health
(633595) DYNAHEALTH - Understanding the dynamic determinants of glucose homeostasis and social capability to promote Healthy and active aging
(824989) EUCAN-Connect - A federated FAIR platform enabling large-scale analysis of high-value cohort data connecting Europe and Canada in personalized health
(825762) EDCMET - Metabolic effects of Endocrine Disrupting Chemicals: novel testing METhods and adverse outcome pathways
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