Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Variants in ADCY5 and near CCNL1 are associated with fetal growth and birth weight


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.

Access options

Rent or buy this article

Prices vary by article type



Prices may be subject to local taxes which are calculated during checkout

Figure 1: Regional plots of two previously unknown associations with birth weight.
Figure 2: Forest plots of the association between birth weight and genotype at each locus.


  1. 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).

    Article  CAS  Google Scholar 

  2. 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).

    Article  CAS  Google Scholar 

  3. 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).

    Article  Google Scholar 

  4. Bernstein, I.M. et al. Maternal smoking and its association with birth weight. Obstet. Gynecol. 106, 986–991 (2005).

    Article  Google Scholar 

  5. Battaglia, F.C. & Lubchenco, L.O. A practical classification of newborn infants by weight and gestational age. J. Pediatr. 71, 159–163 (1967).

    Article  CAS  Google Scholar 

  6. Acker, D.B., Sachs, B.P. & Friedman, E.A. Risk factors for shoulder dystocia. Obstet. Gynecol. 66, 762–768 (1985).

    CAS  PubMed  Google Scholar 

  7. Kramer, M.S. Determinants of low birth weight: methodological assessment and meta-analysis. Bull. World Health Organ. 65, 663–737 (1987).

    CAS  PubMed  PubMed Central  Google Scholar 

  8. 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).

    Article  Google Scholar 

  9. Knight, B. et al. Evidence of genetic regulation of fetal longitudinal growth. Early Hum. Dev. 81, 823–831 (2005).

    Article  Google Scholar 

  10. 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).

    Article  CAS  Google Scholar 

  11. 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).

    Article  CAS  Google Scholar 

  12. Freathy, R.M. et al. Type 2 diabetes risk alleles are associated with reduced size at birth. Diabetes 58, 1428–1433 (2009).

    Article  CAS  Google Scholar 

  13. Zhao, J. et al. Examination of type 2 diabetes loci implicates CDKAL1 as a birth weight gene. Diabetes 58, 2414–2418 (2009).

    Article  CAS  Google Scholar 

  14. Hattersley, A.T. et al. Mutations in the glucokinase gene of the fetus result in reduced birth weight. Nat. Genet. 19, 268–270 (1998).

    Article  CAS  Google Scholar 

  15. Higgins, J.P., Thompson, S.G., Deeks, J.J. & Altman, D.G. Measuring inconsistency in meta-analyses. Br. Med. J. 327, 557–560 (2003).

    Article  Google Scholar 

  16. 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).

    Article  CAS  Google Scholar 

  17. Weedon, M.N. et al. Genome-wide association analysis identifies 20 loci that influence adult height. Nat. Genet. 40, 575–583 (2008).

    Article  CAS  Google Scholar 

  18. 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).

    Article  CAS  Google Scholar 

  19. 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).

    Article  CAS  Google Scholar 

  20. 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).

    Article  CAS  Google Scholar 

  21. Dixon, A.L. et al. A genome-wide association study of global gene expression. Nat. Genet. 39, 1202–1207 (2007).

    Article  CAS  Google Scholar 

  22. Tesmer, J.J. & Sprang, S.R. The structure, catalytic mechanism and regulation of adenylyl cyclase. Curr. Opin. Struct. Biol. 8, 713–719 (1998).

    Article  CAS  Google Scholar 

  23. Hanoune, J. et al. Adenylyl cyclases: structure, regulation and function in an enzyme superfamily. Mol. Cell. Endocrinol. 128, 179–194 (1997).

    Article  CAS  Google Scholar 

  24. 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).

    Article  CAS  Google Scholar 

  25. Prokopenko, I., McCarthy, M.I. & Lindgren, C.M. Type 2 diabetes: new genes, new understanding. Trends Genet. 24, 613–621 (2008).

    Article  CAS  Google Scholar 

  26. Prokopenko, I. et al. Variants in MTNR1B influence fasting glucose levels. Nat. Genet. 41, 77–81 (2008).

    Article  Google Scholar 

  27. Ogura, K. et al. 8-bromo-cyclicAMP stimulates glucose transporter-1 expression in a human choriocarcinoma cell line. J. Endocrinol. 164, 171–178 (2000).

    Article  CAS  Google Scholar 

  28. D'Souza, V.M. et al. cAMP-coupled riboflavin trafficking in placental trophoblasts: a dynamic and ordered process. Biochemistry 45, 6095–6104 (2006).

    Article  CAS  Google Scholar 

  29. 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).

    Article  Google Scholar 

  30. 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).

    Article  CAS  Google Scholar 

  31. 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).

    Article  Google Scholar 

  32. 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).

    Article  Google Scholar 

  33. Krestyaninova, M. et al. A System for Information Management in BioMedical Studies–SIMBioMS. Bioinformatics 25, 2768–2769 (2009).

    Article  CAS  Google Scholar 

  34. Devlin, B. & Roeder, K. Genomic control for association studies. Biometrics 55, 997–1004 (1999).

    Article  CAS  Google Scholar 

  35. 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).

    Article  CAS  Google Scholar 

  36. 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). <>

  37. 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).

    Article  Google Scholar 

  38. 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).

    Article  CAS  Google Scholar 

Download references


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 (

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




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

Correspondence to Dorret I Boomsma, George Davey Smith, Chris Power, Vincent W V Jaddoe, Marjo-Riitta Jarvelin or Mark I McCarthy.

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

Reprints 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).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:

This article is cited by


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing