Abstract
To identify genetic variants associated with birth weight, we meta-analyzed six genome-wide association (GWA) studies (n = 10,623 Europeans from pregnancy/birth cohorts) and followed up two lead signals in 13 replication studies (n = 27,591). rs900400 near LEKR1 and CCNL1 (P = 2 × 10−35) and rs9883204 in ADCY5 (P = 7 × 10−15) were robustly associated with birth weight. Correlated SNPs in ADCY5 were recently implicated in regulation of glucose levels and susceptibility to type 2 diabetes1, providing evidence that the well-described association between lower birth weight and subsequent type 2 diabetes2,3 has a genetic component, distinct from the proposed role of programming by maternal nutrition. Using data from both SNPs, we found that the 9% of Europeans carrying four birth weight–lowering alleles were, on average, 113 g (95% CI 89–137 g) lighter at birth than the 24% with zero or one alleles (Ptrend = 7 × 10−30). The impact on birth weight is similar to that of a mother smoking 4–5 cigarettes per day in the third trimester of pregnancy4.
This is a preview of subscription content, access via your institution
Relevant articles
Open Access articles citing this article.
-
Genetically-predicted placental gene expression is associated with birthweight and adult body mass index
Scientific Reports Open Access 06 January 2023
-
Placental multi-omics integration identifies candidate functional genes for birthweight
Nature Communications Open Access 02 May 2022
-
A fast wavelet-based functional association analysis replicates several susceptibility loci for birth weight in a Norwegian population
BMC Genomics Open Access 02 May 2021
Access options
Subscribe to this journal
Receive 12 print issues and online access
$209.00 per year
only $17.42 per issue
Rent or buy this article
Prices vary by article type
from$1.95
to$39.95
Prices may be subject to local taxes which are calculated during checkout
References
Dupuis, J. et al. New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nat. Genet. 42, 105–116 (2010).
Barker, D.J. et al. Type 2 (non-insulin-dependent) diabetes mellitus, hypertension and hyperlipidaemia (syndrome X): relation to reduced fetal growth. Diabetologia 36, 62–67 (1993).
Järvelin, M.R. et al. Early life factors and blood pressure at age 31 years in the 1966 northern Finland birth cohort. Hypertension 44, 838–846 (2004).
Bernstein, I.M. et al. Maternal smoking and its association with birth weight. Obstet. Gynecol. 106, 986–991 (2005).
Battaglia, F.C. & Lubchenco, L.O. A practical classification of newborn infants by weight and gestational age. J. Pediatr. 71, 159–163 (1967).
Acker, D.B., Sachs, B.P. & Friedman, E.A. Risk factors for shoulder dystocia. Obstet. Gynecol. 66, 762–768 (1985).
Kramer, M.S. Determinants of low birth weight: methodological assessment and meta-analysis. Bull. World Health Organ. 65, 663–737 (1987).
Järvelin, M.R. et al. Ecological and individual predictors of birthweight in a northern Finland birth cohort 1986. Paediatr. Perinat. Epidemiol. 11, 298–312 (1997).
Knight, B. et al. Evidence of genetic regulation of fetal longitudinal growth. Early Hum. Dev. 81, 823–831 (2005).
Klebanoff, M.A., Mednick, B.R., Schulsinger, C., Secher, N.J. & Shiono, P.H. Father's effect on infant birth weight. Am. J. Obstet. Gynecol. 178, 1022–1026 (1998).
Hattersley, A.T. & Tooke, J.E. The fetal insulin hypothesis: an alternative explanation of the association of low birthweight with diabetes and vascular disease. Lancet 353, 1789–1792 (1999).
Freathy, R.M. et al. Type 2 diabetes risk alleles are associated with reduced size at birth. Diabetes 58, 1428–1433 (2009).
Zhao, J. et al. Examination of type 2 diabetes loci implicates CDKAL1 as a birth weight gene. Diabetes 58, 2414–2418 (2009).
Hattersley, A.T. et al. Mutations in the glucokinase gene of the fetus result in reduced birth weight. Nat. Genet. 19, 268–270 (1998).
Higgins, J.P., Thompson, S.G., Deeks, J.J. & Altman, D.G. Measuring inconsistency in meta-analyses. Br. Med. J. 327, 557–560 (2003).
Freathy, R.M. et al. Type 2 diabetes TCF7L2 risk genotypes alter birth weight: a study of 24,053 individuals. Am. J. Hum. Genet. 80, 1150–1161 (2007).
Weedon, M.N. et al. Genome-wide association analysis identifies 20 loci that influence adult height. Nat. Genet. 40, 575–583 (2008).
Willer, C.J. et al. Six new loci associated with body mass index highlight a neuronal influence on body weight regulation. Nat. Genet. 41, 25–34 (2009).
Parsons, T.J., Power, C. & Manor, O. Fetal and early life growth and body mass index from birth to early adulthood in 1958 British cohort: longitudinal study. Br. Med. J. 323, 1331–1335 (2001).
Loyer, P. et al. Characterization of cyclin L1 and L2 interactions with CDK11 and splicing factors: influence of cyclin L isoforms on splice site selection. J. Biol. Chem. 283, 7721–7732 (2008).
Dixon, A.L. et al. A genome-wide association study of global gene expression. Nat. Genet. 39, 1202–1207 (2007).
Tesmer, J.J. & Sprang, S.R. The structure, catalytic mechanism and regulation of adenylyl cyclase. Curr. Opin. Struct. Biol. 8, 713–719 (1998).
Hanoune, J. et al. Adenylyl cyclases: structure, regulation and function in an enzyme superfamily. Mol. Cell. Endocrinol. 128, 179–194 (1997).
Ludwig, M.G. & Seuwen, K. Characterization of the human adenylyl cyclase gene family: cDNA, gene structure, and tissue distribution of the nine isoforms. J. Recept. Signal Transduct. Res. 22, 79–110 (2002).
Prokopenko, I., McCarthy, M.I. & Lindgren, C.M. Type 2 diabetes: new genes, new understanding. Trends Genet. 24, 613–621 (2008).
Prokopenko, I. et al. Variants in MTNR1B influence fasting glucose levels. Nat. Genet. 41, 77–81 (2008).
Ogura, K. et al. 8-bromo-cyclicAMP stimulates glucose transporter-1 expression in a human choriocarcinoma cell line. J. Endocrinol. 164, 171–178 (2000).
D'Souza, V.M. et al. cAMP-coupled riboflavin trafficking in placental trophoblasts: a dynamic and ordered process. Biochemistry 45, 6095–6104 (2006).
Leach, L. The phenotype of the human materno-fetal endothelial barrier: molecular occupancy of paracellular junctions dictate permeability and angiogenic plasticity. J. Anat. 200, 599–606 (2002).
van Baal, C.G. & Boomsma, D.I. Etiology of individual differences in birth weight of twins as a function of maternal smoking during pregnancy. Twin Res. 1, 123–130 (1998).
Lunde, A., Melve, K.K., Gjessing, H.K., Skjaerven, R. & Irgens, L.M. Genetic and environmental influences on birth weight, birth length, head circumference, and gestational age by use of population-based parent-offspring data. Am. J. Epidemiol. 165, 734–741 (2007).
Stein, A.D., Zybert, P.A., van de Bor, M. & Lumey, L.H. Intrauterine famine exposure and body proportions at birth: the Dutch Hunger Winter. Int. J. Epidemiol. 33, 831–836 (2004).
Krestyaninova, M. et al. A System for Information Management in BioMedical Studies–SIMBioMS. Bioinformatics 25, 2768–2769 (2009).
Devlin, B. & Roeder, K. Genomic control for association studies. Biometrics 55, 997–1004 (1999).
de Bakker, P.I. et al. Practical aspects of imputation-driven meta-analysis of genome-wide association studies. Hum. Mol. Genet. 17, R122–R128 (2008).
Harris, R. et al. METAN: Stata module for fixed and random effects meta-analysis (Statistical Software Components S456798, Boston College Department of Economics, revised 19 Feb 2007). <http://ideas.repec.org/c/boc/bocode/s456798.html>
Wallace, B.C., Schmid, C.H., Lau, J. & Trikalinos, T.A. Meta-Analyst: software for meta-analysis of binary, continuous and diagnostic data. BMC Med. Res. Methodol. 9, 80 (2009).
Niklasson, A. et al. An update of the Swedish reference standards for weight, length and head circumference at birth for given gestational age (1977–1981). Acta Paediatr. Scand. 80, 756–762 (1991).
Acknowledgements
See also Supplementary Note for detailed acknowledgments by study.
The authors of this manuscript would like to acknowledge the particular role of Leena Peltonen-Palotie in the research described in this manuscript, and to express our sadness at her untimely loss. Leena made a unique contribution to the field of human genetics research, and enriched the professional and social lives of all who worked with her. She will be sorely missed.
Major funding for the research in this paper is as follows: Academy of Finland (project grants 104781, 120315, 209072, 129255 and Center of Excellence in Complex Disease Genetics); Biocentrum Helsinki; Biocenter, University of Oulu, Finland; British Heart Foundation; Canadian Institutes of Health Research (grant MOP 82893); Center for Medical Systems Biology; Centre for Neurogenomics and Cognitive Research (CNCR-VU) (grant EU/QLRT-2001-01254); The Chief Scientist Office of the Scottish Government; The Children's Hospital of Philadelphia (Institute Development Award); Coca-Cola Hellas; Cotswold Foundation (Research Development Award); Darlington Trust; Department of Health's National Institute of Health Research UK; Diabetes UK (grant RD08/0003704); Dutch Asthma Foundation; Dutch Ministry of the Environment; Erasmus Medical Center Rotterdam; Erasmus University Rotterdam; European Commission (EURO-BLCS, Framework 5 award QLG1-CT-2000-01643); The European Community's Seventh Framework Programme (FP7/2007-2013), ENGAGE project, grant agreement HEALTH-F4-2007- 201413; The European Union Framework Program 6 EUROSPAN Project (LSHG-CT-2006-018947); Exeter National Health Service Research and Development; Friedrich-Schiller University Jena; Genetic Association Information Network; Healthway Western Australia; Helmholtz Zentrum Muenchen–German Research Center for Environment and Health; Institute of Epidemiology Neuherberg; Institut für Umweltmedizinische Forschung (IUF) Düsseldorf; Juvenile Diabetes Research Foundation International; Kompetenznetz Adipositas (Competence Network Obesity) funded by the German Federal Ministry of Education and Research (FKZ: 01GI0826); Marien-Hospital Wesel; MRC UK (grants G0601261, G0600705, studentship grant G0500539, G0000934, G0601653); Munich Center of Health Sciences (MCHEALTH); Municipal Health Service Rotterdam; National Health and Medical Research Council of Australia (grant 572613); National Human Genome Research Institute (US); National Institute of Allergy and Infectious Diseases (US); National Institute of Child Health and Human Development (US) (HD056465, HD034568, HD05450); National Institute of Diabetes and Digestive and Kidney Diseases (US) (DK075787, DK078150, DK56350); National Institute for Environmental Health Sciences (US) (ES10126); National Institute of Mental Health (US) (MH083268, MH63706); National Heart, Lung, and Blood Institute (US) (HL0876792 (STAMPEED program), HL085144, HL068041); National Institutes of Health (US) (Fogarty International Center Grant TW05596; National Center for Research Resources RR20649); National Public Health Institute, Helsinki, Finland; Netherlands Organisation for Scientific Research (NWO)/Netherlands Organisation for Health Research and Development (ZonMw) (grants SPI 56-464-14192, 904-61-090, 904-61-193, 480-04-004, 400-05-717); Office of Population Studies Foundation, University of San Carlos, Philippines; Peninsula NIHR Clinical Research Facility (UK); Raine Medical Research Foundation; Rotterdam Homecare Foundation; South West National Health Service Research and Development (UK) Spinoza; St. Georg Hospital Leipzig; Stichting Astmabestrijding; Stichting Trombosedienst & Artsenlaboratorium Rijnmond (STAR) Rotterdam; Technical University Munich; Telethon Institute for Child Health Research; Type 1 Diabetes Genetics Consortium; UFZ–Centre for Environmental Research Leipzig-Halle; University Hospital Oulu Biocenter, University of Oulu, Finland; University of Bristol; University of Leipzig; Wellcome Trust (grants 085301, 068545/Z/02, 076113/B/04/Z); Western Australian DNA Bank; Western Australian Genetic Epidemiology Resource; and the Wind Over Water Foundation.
Data exchange for the meta-analyses was facilitated by the SIMBioMS platform (http://simbioms.org).
Personal funding is as follows: R.M.F. by a Sir Henry Wellcome Postdoctoral Fellowship (Wellcome Trust grant 085541/Z/08/Z); E.W. by the Academy of Finland (grant 120315 and 129287); H.N.L. by US National Institutes of Health grant 1R01DK075787; E.H. by the Career Scientist Award, Department of Health, UK; C.M.L. by a Wellcome Trust Research Career Development Fellowship; A.R. by the UK Department of Health Policy Research Programme; B.M.S., B.A.K. and A.T.H. are employed as core members of the Peninsula NIHR Clinical Research Facility; J.F.W. by The Royal Society; L.P. by the Wellcome Trust (grant 89061/Z/09/Z); and V.W.V.J. by the Netherlands Organization for Health Research (ZonMw 90700303).
Author information
Authors and Affiliations
Consortia
Contributions
Project design: R.M.F., U.S., N.J.T., E.W., M. Kerkhof, H.N.L., L.S.A., J.B.B., E.J.C.d.G., A.-L.H., J.N.H., A.H., E.H., J.L., D.S.P., A.P., A.T., A.H.W., G.W., J.F.W., E.A.P.S., A.T.H., L.P., K.L.M., S.F.A.G., H.H., G.H.K., G.V.D., J.H., M.W.G., L.J.P., T.M.F., D.I.B., G.D.S., C.P., V.W.V.J., M.-R.J., M.I.M.
Sample collection and phenotyping: D.O.M.-K., U.S., D.J.B., M. Kaakinen, M. Kerkhof, L.S.A., A.J.B., J.B.B., P.E., A.-L.H., E.H., S.K., B.A.K., J.L., W.L.M., C.E.P., D.S.P., A.P., F.R., B.M.S., D.P.S., A.T., A.G.U., A.H.W., G.W., J.F.W., A.T.H., J.G.E., S.F.A.G., H.H., G.H.K., G.V.D., J.H., M.W.G., L.J.P., G.D.S., C.P., V.W.V.J., M.-R.J.
Genotyping: R.M.F., J.J.H., M. Kerkhof, H.N.L., A.J.B., N.B.-N., E.J.C.d.G., P.D., P.E., P.F., C.J.G., N.H., J.N.H., W.L.M., D.S.P., S.M.R., F.R., A.G.U., A.H.W., J.F.W., L.P., S.F.A.G., H.H., G.H.K., D.I.B., M.-R.J.
Statistical analysis: R.M.F., D.O.M.K., U.S., I.P., N.J.T., D.J.B., N.M.W., E.W., J.J.H., M. Kaakinen, L.A.L., J.P.B., M. Kerkhof, J.A.M., R.M., C.-M.C., H.N.L., M. Kirin, Y.S.A., P.C., L.J.M.C., D.L.C., D.M.E., B.G., C.M.L., P.F.O., D.S.P., A.R., N.W.R, B.M.S., I.S., C.T., C.M.v.D., A.H.W., J.Z., H.Z., G.H.K., M.W.G., L.J.P.
Writing: R.M.F., D.O.M.K., U.S., I.P., N.J.T., D.J.B., J.M.P.H., A.T.H., L.J.P., T.M.F., V.W.V.J., M.-R.J., M.I.M.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing financial interests.
Additional information
A complete list of members is available in a Supplementary Note.
A complete list of members is available in a Supplementary Note.
A complete list of members is available in a Supplementary Note.
Supplementary information
Supplementary Text and Figures
Supplementary Tables 1–5, Supplementary Figures 1–5 and Supplementary Note. (PDF 4251 kb)
Supplementary Table 1
Basic characteristics, exclusions, genotyping, quality control and imputation in discovery studies (XLS 98 kb)
Supplementary Table 2
Basic characteristics, exclusions, genotyping, quality control and imputation in European replication studies and non-European/admixed studies (XLS 114 kb)
Rights and permissions
About this article
Cite this article
Freathy, R., Mook-Kanamori, D., Sovio, U. et al. Variants in ADCY5 and near CCNL1 are associated with fetal growth and birth weight. Nat Genet 42, 430–435 (2010). https://doi.org/10.1038/ng.567
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/ng.567
This article is cited by
-
Genetically-predicted placental gene expression is associated with birthweight and adult body mass index
Scientific Reports (2023)
-
Genetic Contributions to Risk of Adverse Pregnancy Outcomes
Current Cardiovascular Risk Reports (2023)
-
Placental multi-omics integration identifies candidate functional genes for birthweight
Nature Communications (2022)
-
A fast wavelet-based functional association analysis replicates several susceptibility loci for birth weight in a Norwegian population
BMC Genomics (2021)
-
Polymorphic variants in Sweet and Umami taste receptor genes and birthweight
Scientific Reports (2021)
