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.

Identification of low-frequency and rare sequence variants associated with elevated or reduced risk of type 2 diabetes


Through whole-genome sequencing of 2,630 Icelanders and imputation into 11,114 Icelandic cases and 267,140 controls followed by testing in Danish and Iranian samples, we discovered 4 previously unreported variants affecting risk of type 2 diabetes (T2D). A low-frequency (1.47%) variant in intron 1 of CCND2, rs76895963[G], reduces risk of T2D by half (odds ratio (OR) = 0.53, P = 5.0 × 10−21) and is correlated with increased CCND2 expression. Notably, this variant is also associated with both greater height and higher body mass index (1.17 cm per allele, P = 5.5 × 10−12 and 0.56 kg/m2 per allele, P = 6.5 × 10−7, respectively). In addition, two missense variants in PAM, encoding p.Asp563Gly (frequency of 4.98%) and p.Ser539Trp (frequency of 0.65%), confer moderately higher risk of T2D (OR = 1.23, P = 3.9 × 10−10 and OR = 1.47, P = 1.7 × 10−5, respectively), and a rare (0.20%) frameshift variant in PDX1, encoding p.Gly218Alafs*12, associates with high risk of T2D (OR = 2.27, P = 7.3 × 10−7).

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

Get just this article for as long as you need it


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

Figure 1: Manhattan plots of association results.

Accession codes

Primary accessions

Gene Expression Omnibus


  1. Hindorff, L.A. et al. A Catalog of Published Genome-Wide Association Studies

  2. Kong, A. et al. Detection of sharing by descent, long-range phasing and haplotype imputation. Nat. Genet. 40, 1068–1075 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Kong, A. et al. Parental origin of sequence variants associated with complex diseases. Nature 462, 868–874 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Styrkarsdottir, U. et al. Nonsense mutation in the LGR4 gene is associated with several human diseases and other traits. Nature 497, 517–520 (2013).

    Article  CAS  PubMed  Google Scholar 

  5. Kristinsson, S.Y. et al. MODY in Iceland is associated with mutations in HNF-1α and a novel mutation in NeuroD1. Diabetologia 44, 2098–2103 (2001).

    Article  CAS  PubMed  Google Scholar 

  6. Morris, A.P. et al. Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nat. Genet. 44, 981–990 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Sandhu, M.S. et al. Common variants in WFS1 confer risk of type 2 diabetes. Nat. Genet. 39, 951–953 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Saxena, R. et al. Large-scale gene-centric meta-analysis across 39 studies identifies type 2 diabetes loci. Am. J. Hum. Genet. 90, 410–425 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Huyghe, J.R. et al. Exome array analysis identifies new loci and low-frequency variants influencing insulin processing and secretion. Nat. Genet. 45, 197–201 (2013).

    CAS  PubMed  Google Scholar 

  10. Georgia, S. & Bhushan, A. β cell replication is the primary mechanism for maintaining postnatal β cell mass. J. Clin. Invest. 114, 963–968 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Kushner, J.A. et al. Cyclins D2 and D1 are essential for postnatal pancreatic β-cell growth. Mol. Cell. Biol. 25, 3752–3762 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Emilsson, V. et al. Genetics of gene expression and its effect on disease. Nature 452, 423–428 (2008).

    Article  CAS  PubMed  Google Scholar 

  13. Eipper, B.A., Stoffers, D.A. & Mains, R.E. The biosynthesis of neuropeptides: peptide α-amidation. Annu. Rev. Neurosci. 15, 57–85 (1992).

    Article  CAS  PubMed  Google Scholar 

  14. Czyzyk, T.A. et al. Deletion of peptide amidation enzymatic activity leads to edema and embryonic lethality in the mouse. Dev. Biol. 287, 301–313 (2005).

    Article  CAS  PubMed  Google Scholar 

  15. Yin, P. et al. Probing the production of amidated peptides following genetic and dietary copper manipulations. PLoS ONE 6, e28679 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Stoffers, D.A., Ferrer, J., Clarke, W.L. & Habener, J.F. Early-onset type-II diabetes mellitus (MODY4) linked to IPF1. Nat. Genet. 17, 138–139 (1997).

    Article  CAS  PubMed  Google Scholar 

  17. Edghill, E.L. et al. Sequencing PDX1 (insulin promoter factor 1) in 1788 UK individuals found 5% had a low frequency coding variant, but these variants are not associated with type 2 diabetes. Diabet. Med. 28, 681–684 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Helgason, A. et al. Refining the impact of TCF7L2 gene variants on type 2 diabetes and adaptive evolution. Nat. Genet. 39, 218–225 (2007).

    Article  CAS  PubMed  Google Scholar 

  19. Steinthorsdottir, V. et al. A variant in CDKAL1 influences insulin response and risk of type 2 diabetes. Nat. Genet. 39, 770–775 (2007).

    Article  CAS  PubMed  Google Scholar 

  20. Jørgensen, T. et al. A randomized non-pharmacological intervention study for prevention of ischaemic heart disease: baseline results Inter99. Eur. J. Cardiovasc. Prev. Rehabil. 10, 377–386 (2003).

    Article  PubMed  Google Scholar 

  21. Thyssen, J.P., Linneberg, A., Menne, T., Nielsen, N.H. & Johansen, J.D. The prevalence and morbidity of sensitization to fragrance mix I in the general population. Br. J. Dermatol. 161, 95–101 (2009).

    Article  CAS  PubMed  Google Scholar 

  22. Lauritzen, T. et al. The ADDITION study: proposed trial of the cost-effectiveness of an intensive multifactorial intervention on morbidity and mortality among people with type 2 diabetes detected by screening. Int. J. Obes. Relat. Metab. Disord. 24 (suppl. 3), S6–S11 (2000).

    Article  PubMed  Google Scholar 

  23. Azizi, F. et al. Prevention of non-communicable disease in a population in nutrition transition: Tehran Lipid and Glucose Study phase II. Trials 10, 5 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Kutyavin, I.V. et al. A novel endonuclease IV post-PCR genotyping system. Nucleic Acids Res. 34, e128 (2006).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Albrechtsen, A. et al. Exome sequencing–driven discovery of coding polymorphisms associated with common metabolic phenotypes. Diabetologia 56, 298–310 (2013).

    Article  CAS  PubMed  Google Scholar 

  26. Pruitt, K.D., Tatusova, T., Brown, G.R. & Maglott, D.R. NCBI Reference Sequences (RefSeq): current status, new features and genome annotation policy. Nucleic Acids Res. 40, D130–D135 (2012).

    Article  CAS  PubMed  Google Scholar 

  27. Kent, W.J. et al. The human genome browser at UCSC. Genome Res. 12, 996–1006 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. McLaren, W. et al. Deriving the consequences of genomic variants with the Ensembl API and SNP Effect Predictor. Bioinformatics 26, 2069–2070 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Gretarsdottir, S. et al. The gene encoding phosphodiesterase 4D confers risk of ischemic stroke. Nat. Genet. 35, 131–138 (2003).

    Article  CAS  PubMed  Google Scholar 

  30. Mantel, N. & Haenszel, W. Statistical aspects of the analysis of data from retrospective studies of disease. J. Natl. Cancer Inst. 22, 719–748 (1959).

    CAS  PubMed  Google Scholar 

Download references


We thank the subjects of the Icelandic deCODE study, the Danish studies and the Iranian study for their participation. We also thank the staff at the deCODE Genetics core facilities and all our colleagues for their important contributions to this work. The Danish studies were supported by the Lundbeck Foundation (Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention and Care (LuCamp), and the Danish Council for Independent Research. The Novo Nordisk Foundation Center for Basic Metabolic Research is an independent research center at the University of Copenhagen partially funded by an unrestricted donation from the Novo Nordisk Foundation (

Author information

Authors and Affiliations



V.S., G.T., D.F.G., A.K., U.T. and K.S. designed the study and interpreted the results. G.T., P.S., H.H., D.F.G., O.T.M., A.H., A.K. and G.M. performed analysis of sequence data, imputation and association analysis. N.G., J.M.J., M.N.H., T.H., G.T. and O.P. performed analysis and interpretation of Danish clinical and physiological data. Subject recruitment, phenotype analysis and biological material collection were organized and carried out by A.B.H., G.S. and R.B. in Iceland; T.J., A.L., M.E.J., C.C., I.B., A. Sandbæk, T.L., H.V., T.H. and O.P. in Denmark; and M.S.D., M.-S.F. and F.A. in Iran. O.T.M. and U.T. supervised sequencing and genotyping. N.G., T.H. and O.P. supervised genotyping of Danish samples. S.A.G. performed bioinformatics analyses. A. Sigurdsson, H.T.H. and H.J. performed and analyzed data from Sanger sequencing and Centaurus genotyping. G.T. and A. Sigurdsson performed and analyzed data from expression experiments. V.S., G.T., N.G., O.P., U.T. and K.S. drafted the manuscript. All authors contributed to the final version of the manuscript.

Corresponding authors

Correspondence to Unnur Thorsteinsdottir or Kari Stefansson.

Ethics declarations

Competing interests

V.S., G.T., P.S., H.H., A. Sigurdsson, A.H., H.T.H., H.J., O.T.M., S.A.G., G.M., D.F.G., A.K., U.T. and K.S. are employees of deCODE Genetics/Amgen, Inc.

Integrated supplementary information

Supplementary Figure 1 Correlation between genotypes of rs76895963 and the expression of CCND2 in adipose tissue samples from 637 individuals.

The vertical axis shows the average relative expression, i.e. 10^(average MLR), where MLR is the mean log expression ratio, and the average is over individuals with a particular genotypes. The error bars indicate the standard error of the mean. Regressing the MLR values on the number of at-risk alleles rs76895963-G that an individual carries, adjusting for the effects of age, sex and BMI by including those as explanatory variables, yields an estimated 38% increase in expression per allele carried (P = 0.000011). All P values were adjusted for the relatedness of the individuals by simulating genotypes through the Icelandic genealogy. The resulting adjustment factors for the χ2 statistic were 1.08 for adipose. We also tested the correlation of the expression of CCND2 with all variants in a 1-Mb region centered on the gene to compare with the observed correlation with rs76895963.

Supplementary information

Supplementary Text and Figures

Supplementary Note, Supplementary Tables 1–7 and Supplementary Figure 1 (PDF 760 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Steinthorsdottir, V., Thorleifsson, G., Sulem, P. et al. Identification of low-frequency and rare sequence variants associated with elevated or reduced risk of type 2 diabetes. Nat Genet 46, 294–298 (2014).

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