Title |
Genome-wide associations for birth weight and correlations with adult disease
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Published in |
Nature, September 2016
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DOI | 10.1038/nature19806 |
Pubmed ID | |
Authors |
Momoko Horikoshi, Robin N. Beaumont, Felix R. Day, Nicole M. Warrington, Marjolein N. Kooijman, Juan Fernandez-Tajes, Bjarke Feenstra, Natalie R. van Zuydam, Kyle J. Gaulton, Niels Grarup, Jonathan P. Bradfield, David P. Strachan, Ruifang Li-Gao, Tarunveer S. Ahluwalia, Eskil Kreiner, Rico Rueedi, Leo-Pekka Lyytikäinen, Diana L. Cousminer, Ying Wu, Elisabeth Thiering, Carol A. Wang, Christian T. Have, Jouke-Jan Hottenga, Natalia Vilor-Tejedor, Peter K. Joshi, Eileen Tai Hui Boh, Ioanna Ntalla, Niina Pitkänen, Anubha Mahajan, Elisabeth M. van Leeuwen, Raimo Joro, Vasiliki Lagou, Michael Nodzenski, Louise A. Diver, Krina T. Zondervan, Mariona Bustamante, Pedro Marques-Vidal, Josep M. Mercader, Amanda J. Bennett, Nilufer Rahmioglu, Dale R. Nyholt, Ronald C. W. Ma, Claudia H. T. Tam, Wing Hung Tam, Santhi K. Ganesh, Frank J. A. van Rooij, Samuel E. Jones, Po-Ru Loh, Katherine S. Ruth, Marcus A. Tuke, Jessica Tyrrell, Andrew R. Wood, Hanieh Yaghootkar, Denise M. Scholtens, Lavinia Paternoster, Inga Prokopenko, Peter Kovacs, Mustafa Atalay, Sara M. Willems, Kalliope Panoutsopoulou, Xu Wang, Lisbeth Carstensen, Frank Geller, Katharina E. Schraut, Mario Murcia, Catharina E. M. van Beijsterveldt, Gonneke Willemsen, Emil V. R. Appel, Cilius E. Fonvig, Caecilie Trier, Carla M. T. Tiesler, Marie Standl, Zoltán Kutalik, Sílvia Bonàs-Guarch, David M. Hougaard, Friman Sánchez, David Torrents, Johannes Waage, Mads V. Hollegaard, Hugoline G. de Haan, Frits R. Rosendaal, Carolina Medina-Gomez, Susan M. Ring, Gibran Hemani, George McMahon, Neil R. Robertson, Christopher J. Groves, Claudia Langenberg, Jian’an Luan, Robert A. Scott, Jing Hua Zhao, Frank D. Mentch, Scott M. MacKenzie, Rebecca M. Reynolds, William L. Lowe, Anke Tönjes, Michael Stumvoll, Virpi Lindi, Timo A. Lakka, Cornelia M. van Duijn, Wieland Kiess, Antje Körner, Thorkild I. A. Sørensen, Harri Niinikoski, Katja Pahkala, Olli T. Raitakari, Eleftheria Zeggini, George V. Dedoussis, Yik-Ying Teo, Seang-Mei Saw, Mads Melbye, Harry Campbell, James F. Wilson, Martine Vrijheid, Eco J. C. N. de Geus, Dorret I. Boomsma, Haja N. Kadarmideen, Jens-Christian Holm, Torben Hansen, Sylvain Sebert, Andrew T. Hattersley, Lawrence J. Beilin, John P. Newnham, Craig E. Pennell, Joachim Heinrich, Linda S. Adair, Judith B. Borja, Karen L. Mohlke, Johan G. Eriksson, Elisabeth Widén, Mika Kähönen, Jorma S. Viikari, Terho Lehtimäki, Peter Vollenweider, Klaus Bønnelykke, Hans Bisgaard, Dennis O. Mook-Kanamori, Albert Hofman, Fernando Rivadeneira, André G. Uitterlinden, Charlotta Pisinger, Oluf Pedersen, Christine Power, Elina Hyppönen, Nicholas J. Wareham, Hakon Hakonarson, Eleanor Davies, Brian R. Walker, Vincent W. V. Jaddoe, Marjo-Riitta Järvelin, Struan F. A. Grant, Allan A. Vaag, Debbie A. Lawlor, Timothy M. Frayling, George Davey Smith, Andrew P. Morris, Ken K. Ong, Janine F. Felix, Nicholas J. Timpson, John R. B. Perry, David M. Evans, Mark I. McCarthy, Rachel M. Freathy |
Abstract |
Birth weight (BW) has been shown to be influenced by both fetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease. These life-course associations have often been attributed to the impact of an adverse early life environment. Here, we performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where fetal genotype was associated with BW (P < 5 × 10(-8)). Overall, approximately 15% of variance in BW was captured by assays of fetal genetic variation. Using genetic association alone, we found strong inverse genetic correlations between BW and systolic blood pressure (Rg = -0.22, P = 5.5 × 10(-13)), T2D (Rg = -0.27, P = 1.1 × 10(-6)) and coronary artery disease (Rg = -0.30, P = 6.5 × 10(-9)). In addition, using large -cohort datasets, we demonstrated that genetic factors were the major contributor to the negative covariance between BW and future cardiometabolic risk. Pathway analyses indicated that the protein products of genes within BW-associated regions were enriched for diverse processes including insulin signalling, glucose homeostasis, glycogen biosynthesis and chromatin remodelling. There was also enrichment of associations with BW in known imprinted regions (P = 1.9 × 10(-4)). We demonstrate that life-course associations between early growth phenotypes and adult cardiometabolic disease are in part the result of shared genetic effects and identify some of the pathways through which these causal genetic effects are mediated. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 57 | 18% |
United Kingdom | 38 | 12% |
Australia | 11 | 3% |
Canada | 10 | 3% |
Spain | 10 | 3% |
India | 7 | 2% |
Netherlands | 7 | 2% |
Japan | 6 | 2% |
Italy | 6 | 2% |
Other | 64 | 20% |
Unknown | 101 | 32% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 191 | 60% |
Scientists | 94 | 30% |
Practitioners (doctors, other healthcare professionals) | 25 | 8% |
Science communicators (journalists, bloggers, editors) | 7 | 2% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 3 | <1% |
United States | 2 | <1% |
Switzerland | 1 | <1% |
Australia | 1 | <1% |
Sweden | 1 | <1% |
Finland | 1 | <1% |
Netherlands | 1 | <1% |
India | 1 | <1% |
Korea, Republic of | 1 | <1% |
Other | 2 | <1% |
Unknown | 594 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 120 | 20% |
Student > Ph. D. Student | 99 | 16% |
Student > Master | 63 | 10% |
Student > Bachelor | 52 | 9% |
Professor > Associate Professor | 29 | 5% |
Other | 116 | 19% |
Unknown | 129 | 21% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 130 | 21% |
Agricultural and Biological Sciences | 96 | 16% |
Biochemistry, Genetics and Molecular Biology | 88 | 14% |
Nursing and Health Professions | 21 | 3% |
Neuroscience | 14 | 2% |
Other | 94 | 15% |
Unknown | 165 | 27% |