0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Join our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessGenome-wide association studies of birth weight have focused on fetal genetics, whereas relatively little is known about the role of maternal genetic variation. We aimed to identify maternal genetic variants associated with birth weight that could highlight potentially relevant maternal determinants of fetal growth. We meta-analysed data on up to 8.7 million SNPs in up to 86 577 women of European descent from the Early Growth Genetics (EGG) Consortium and the UK Biobank. We used structural equation modelling (SEM) and analyses of mother-child pairs to quantify the separate maternal and fetal genetic effects. Maternal SNPs at 10 loci (MTNR1B, HMGA2, SH2B3, KCNAB1, L3MBTL3, GCK, EBF1, TCF7L2, ACTL9, CYP3A7) were associated with offspring birth weight at P<5×10 -8. In SEM analyses, at least 7 of the 10 associations were consistent with effects of the maternal genotype acting via the intrauterine environment, rather than via effects of shared alleles with the fetus. Variants, or correlated proxies, at many of the loci had been previously associated with adult traits, including fasting glucose (MTNR1B, GCK and TCF7L2) and sex hormone levels (CYP3A7), and one (EBF1) with gestational duration. The identified associations indicate that genetic effects on maternal glucose, cytochrome P450 activity and gestational duration, and potentially on maternal blood pressure and immune function, are relevant for fetal growth. Further characterization of these associations in mechanistic and causal analyses will enhance understanding of the potentially modifiable maternal determinants of fetal growth, with the goal of reducing the morbidity and mortality associated with low and high birth weights.
Robin N. Beaumont, Nicole M. Warrington, Alana Cavadino, Jessica Tyrrell, Michael Nodzenski, Momoko Horikoshi, Frank Geller, Ronny Myhre, Rebecca C. Richmond, Lavinia Paternoster, Jonathan P. Bradfield, Eskil Kreiner‐Møller, Ville Huikari, Sarah Metrustry, Kathryn L. Lunetta, Jodie N. Painter, Jouke‐Jan Hottenga, Catherine Allard, Sheila J. Barton, Ana Espinosa, Julie Marsh, Catherine Potter, Ge Zhang, Wei Ang, Diane J. Berry, Luigi Bouchard, Shikta Das, Hákon Hákonarson, Jani Heikkinen, Øyvind Helgeland, Berthold Hocher, Albert Hofman, Hazel Inskip, Samuel E. Jones, Manolis Kogevinas, Penelope A. Lind, Letizia Marullo, Sarah E. Medland, Anna Murray, Jeffrey C. Murray, Pål R. Njølstad, Ellen A. Nøhr, Christoph Reichetzeder, Susan M. Ring, Katherine S. Ruth, Loreto Santa‐Marina, Denise Scholtens, Sylvain Sebért, Verena Sengpiel, Marcus A. Tuke, Marc Vaudel, Michael N. Weedon, Gonneke Willemsen, Andrew R. Wood, Hanieh Yaghootkar, Louis J. Muglia, Meike Bartels, Caroline L. Relton, Craig E. Pennell, Leda Chatzi, Xavier Estivill, John W. Holloway, Dorret I. Boomsma, Grant W. Montgomery, Joanne M. Murabito, Tim D. Spector, Christine Power, Paul M Ridker, Hans Bisgaard, Struan F.A. Grant, Thorkild I. A. Sørensen, Vincent W.V. Jaddoe, Bo Jacobsson, Mads Melbye, Mark I. McCarthy, Andrew T. Hattersley, M. Geoffrey Hayes, Timothy M. Frayling, Marie‐France Hivert, Janine F. Felix, Elina Hyppönen, William L. Lowe, David M. Evans, Debbie A. Lawlor, Bjarke Feenstra, Rachel M. Freathy (2018). Genome-wide association study of offspring birth weight in 86 577 women identifies five novel loci and highlights maternal genetic effects that are independent of fetal genetics. , 27(4), DOI: https://doi.org/10.1093/hmg/ddx429.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Article
Year
2018
Authors
86
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1093/hmg/ddx429
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free AccessYes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaboration
