Abstract

We report sequencing-based whole-genome association analyses to evaluate the impact of rare and founder variants on stature in 6,307 individuals on the island of Sardinia. We identify two variants with large effects. One variant, which introduces a stop codon in the GHR gene, is relatively frequent in Sardinia (0.87% versus <0.01% elsewhere) and in the homozygous state causes Laron syndrome involving short stature. We find that this variant reduces height in heterozygotes by an average of 4.2 cm (−0.64 s.d.). The other variant, in the imprinted KCNQ1 gene (minor allele frequency (MAF) = 7.7% in Sardinia versus <1% elsewhere) reduces height by an average of 1.83 cm (−0.31 s.d.) when maternally inherited. Additionally, polygenic scores indicate that known height-decreasing alleles are at systematically higher frequencies in Sardinians than would be expected by genetic drift. The findings are consistent with selection for shorter stature in Sardinia and a suggestive human example of the proposed 'island effect' reducing the size of large mammals.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

References

  1. 1.

    et al. Heritability of cardiovascular and personality traits in 6,148 Sardinians. PLoS Genet. 2, e132 (2006).

  2. 2.

    , , & Relative effect of genetic and environmental factors on body height: differences across birth cohorts among Finnish men and women. Am. J. Public Health 90, 627–630 (2000).

  3. 3.

    et al. Hundreds of variants clustered in genomic loci and biological pathways affect human height. Nature 467, 832–838 (2010).

  4. 4.

    et al. Defining the role of common variation in the genomic and biological architecture of adult human height. Nat. Genet. 46, 1173–1186 (2014).

  5. 5.

    et al. Low-pass DNA sequencing of 1200 Sardinians reconstructs European Y-chromosome phylogeny. Science 341, 565–569 (2013).

  6. 6.

    et al. Genome sequencing elucidates Sardinian genetic architecture and augments association analyses for lipid and blood inflammatory markers. Nat. Genet. doi: (14 September 2015).

  7. 7.

    Secular trend and regional differences in the stature of Italians. J. Anthropol. Sci. 90, 233–237 (2012).

  8. 8.

    Laron Syndrome—From Man to Mouse (Springer-Verlag, 2011).

  9. 9.

    The syndrome of familial dwarfism and high plasma immunoreactive human growth hormone. Birth Defects Orig. Artic. Ser. 10, 231–238 (1974).

  10. 10.

    , , & The little women of Loja—growth hormone–receptor deficiency in an inbred population of southern Ecuador. N. Engl. J. Med. 323, 1367–1374 (1990).

  11. 11.

    , , & Serum GH binding protein activities identifies the heterozygous carriers for Laron type dwarfism. Acta Endocrinol. (Copenh.) 121, 603–608 (1989).

  12. 12.

    et al. Effects of heterozygosity for the E180 splice mutation causing growth hormone receptor deficiency in Ecuador on IGF-I, IGFBP-3, and stature. Growth Horm. IGF Res. 17, 261–264 (2007).

  13. 13.

    et al. Meta-analysis of dense genecentric association studies reveals common and uncommon variants associated with height. Am. J. Hum. Genet. 88, 6–18 (2011).

  14. 14.

    et al. Loss of imprinting of a paternally expressed transcript, with antisense orientation to KVLQT1, occurs frequently in Beckwith-Wiedemann syndrome and is independent of insulin-like growth factor II imprinting. Proc. Natl. Acad. Sci. USA 96, 5203–5208 (1999).

  15. 15.

    & Epigenetic and genetic alterations of the imprinting disorder Beckwith-Wiedemann syndrome and related disorders. J. Hum. Genet. 58, 402–409 (2013).

  16. 16.

    et al. New loci associated with birth weight identify genetic links between intrauterine growth and adult height and metabolism. Nat. Genet. 45, 76–82 (2013).

  17. 17.

    et al. Genome-wide meta-analyses identifies seven loci associated with platelet aggregation in response to agonists. Nat. Genet. 42, 608–613 (2010).

  18. 18.

    et al. Common variants at ten loci influence QT interval duration in the QTGEN Study. Nat. Genet. 41, 399–406 (2009).

  19. 19.

    et al. Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis. Nat. Genet. 42, 579–589 (2010).

  20. 20.

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

  21. 21.

    et al. Genetic variants regulating immune cell levels in health and disease. Cell 155, 242–256 (2013).

  22. 22.

    et al. Evidence of widespread selection on standing variation in Europe at height-associated SNPs. Nat. Genet. 44, 1015–1019 (2012).

  23. 23.

    & A population genetic signal of polygenic adaptation. PLoS Genet. 10, e1004412 (2014).

  24. 24.

    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).

  25. 25.

    et al. Genome-wide association analyses based on whole-genome sequencing in Sardinia provide insights into regulation of hemoglobin levels. Nat. Genet. doi: (14 September 2015).

  26. 26.

    Morphological evolution is accelerated among island mammals. PLoS Biol. 4, e321 (2006).

  27. 27.

    , , & in Evolution of Island Mammals 103–130 (Wiley-Blackwell, 2010).

  28. 28.

    et al. Eight thousand years of natural selection in Europe. bioRxiv 016477 (2015).

  29. 29.

    et al. Ancient human genomes suggest three ancestral populations for present-day Europeans. Nature 513, 409–413 (2014).

  30. 30.

    et al. Massive migration from the steppe was a source for Indo-European languages in Europe. Nature 522, 207–211 (2015).

  31. 31.

    et al. Rare variant genotype imputation with thousands of study-specific whole-genome sequences: implications for cost-effective study designs. Eur. J. Hum. Genet. 23, 975–983 (2015).

  32. 32.

    et al. Variance component model to account for sample structure in genome-wide association studies. Nat. Genet. 42, 348–354 (2010).

  33. 33.

    & selscan: an efficient multithreaded program to perform EHH-based scans for positive selection. Mol. Biol. Evol. 31, 2824–2827 (2014).

  34. 34.

    , , & Merlin—rapid analysis of dense genetic maps using sparse gene flow trees. Nat. Genet. 30, 97–101 (2002).

  35. 35.

    , , & Widespread genomic signatures of natural selection in hominid evolution. PLoS Genet. 5, e1000471 (2009).

Download references

Acknowledgements

We thank all the volunteers who generously participated in this study and made this research possible. All participants provided informed consent, and the studies were approved by local research ethic committees: Comitato Etico di Azienda Sanitaria Locale 8, Lanusei (2009/0016600) and Comitato Etico di Azienda Sanitaria Locale 1, Sassari (2171/CE). This study was funded in part by the US National Institutes of Health (National Institute on Aging, National Heart, Lung, and Blood Institute, and National Human Genome Research Institute). This research was supported by National Human Genome Research Institute grants HG005581, HG005552, HG006513, HG007089, HG007022 and HG007089; by National Heart, Lung, and Blood Institute grant HL117626; by the Intramural Research Program of the US National Institutes of Health, National Institute on Aging, contracts N01-AG-1-2109 and HHSN271201100005C; by Sardinian Autonomous Region (L.R. 7/2009) grant cRP3-154; by grant FaReBio2011 'Farmaci e Reti Biotecnologiche di Qualità'; by the PB05 InterOmics MIUR Flagship Project; by a US National Institutes of Health National Research Service Award (NRSA) postdoctoral fellowship (F32GM106656) to C.W.K.C.; by UC MEXUS-CONACYT doctoral fellowship 213627 to D.O.D.V.; and by Italian Ministry of Education, University and Research (MIUR) grant 5571/DSPAR/2002. The HELIC study was funded by the Wellcome Trust (098051) and the European Research Council (ERC-2011-StG 280559-SEPI). The TEENAGE study has been supported by the Wellcome Trust (098051), European Union (European Social Fund (ESF)) and Greek national funds through the Operational Programme 'Education and Lifelong Learning' of the National Strategic Reference Framework (NSRF) research funding programme Heracleitus II, Investing in Knowledge Society Through the European Social Fund. The UK Household Longitudinal Study is led by the Institute for Social and Economic Research at the University of Essex and funded by the Economic and Social Research Council. Information on how to access the data can be found on the Understanding Society website (https://www.understandingsociety.ac.uk/). This study makes use of data generated by the UK10K Consortium, derived from samples from UK10K_COHORTS_TWINSUK (the TwinsUK cohort) and UK10K_COHORT_ALSPAC (the Avon Longitudinal Study of Parents and Children cohort). A full list of the investigators who contributed to the generation of the data is available from http://www.UK10K.org/. Funding for UK10K was provided by the Wellcome Trust under award WT091310. We thank J. Berg for scripts and suggestions on the polygenic score analysis.

Author information

Author notes

    • Magdalena Zoledziewska
    • , Carlo Sidore
    • , Charleston W K Chiang
    •  & Serena Sanna

    These authors contributed equally to this work.

    • Gonçalo R Abecasis
    • , John Novembre
    • , David Schlessinger
    •  & Francesco Cucca

    These authors jointly supervised this work.

Affiliations

  1. Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche (CNR), Monserrato, Cagliari, Italy.

    • Magdalena Zoledziewska
    • , Carlo Sidore
    • , Serena Sanna
    • , Antonella Mulas
    • , Maristella Steri
    • , Fabio Busonero
    • , Michele Marongiu
    • , Andrea Maschio
    • , Matteo Floris
    • , Maria Pina Concas
    • , Federico Murgia
    • , Simona Vaccargiu
    • , Andrea Angius
    •  & Francesco Cucca
  2. Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, USA.

    • Carlo Sidore
    • , Andrea Maschio
    •  & Gonçalo R Abecasis
  3. Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, California, USA.

    • Charleston W K Chiang
    •  & Kirk E Lohmueller
  4. Dipartimento di Scienze Biomediche, Università degli Studi di Sassari, Sassari, Italy.

    • Antonella Mulas
    • , Matteo Floris
    • , Sergio Uzzau
    •  & Francesco Cucca
  5. Department of Human Genetics, University of Chicago, Chicago, Illinois, USA.

    • Joseph H Marcus
    •  & John Novembre
  6. DNA Sequencing Core, University of Michigan, Ann Arbor, Michigan, USA.

    • Andrea Maschio
    •  & Robert Lyons
  7. Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, California, USA.

    • Diego Ortega Del Vecchyo
  8. Center for Advanced Studies, Research and Development in Sardinia (CRS4), Advanced Genomics Computing Technology (AGCT) Program, Parco Scientifico e Tecnologico della Sardegna, Pula, Italy.

    • Matteo Floris
    • , Chris Jones
    •  & Andrea Angius
  9. II Clinica Pediatrica, Ospedale Microcitemico, Cagliari, Italy.

    • Antonella Meloni
  10. Department of Clinical and Experimental Medicine, Azienda Ospedaliero Universitaria di Sassari, Sassari, Italy.

    • Alessandro Delitala
  11. Istituto di Genetica Molecolare, CNR, Pavia, Italy.

    • Ginevra Biino
  12. Laboratory of Genetics, National Institute on Aging, US National Institutes of Health, Baltimore, Maryland, USA.

    • Ramaiah Nagaraja
    •  & David Schlessinger
  13. Medical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, UK.

    • Nicholas J Timpson
  14. Human Genetics, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK.

    • Nicole Soranzo
    • , Ioanna Tachmazidou
    •  & Eleftheria Zeggini
  15. Department of Haematology, University of Cambridge, Cambridge, UK.

    • Nicole Soranzo
  16. Department of Dietetics-Nutrition, Harokopio University, Athens, Greece.

    • George Dedoussis
  17. Porto Conte Ricerche, Tramariglio, Alghero, Italy.

    • Sergio Uzzau

Consortia

  1. UK10K Consortium

    A full list of members and affiliations appears in the Supplementary Note.

  2. The Understanding Society Scientific Group

    A full list of members and affiliations appears in the Supplementary Note.

Authors

  1. Search for Magdalena Zoledziewska in:

  2. Search for Carlo Sidore in:

  3. Search for Charleston W K Chiang in:

  4. Search for Serena Sanna in:

  5. Search for Antonella Mulas in:

  6. Search for Maristella Steri in:

  7. Search for Fabio Busonero in:

  8. Search for Joseph H Marcus in:

  9. Search for Michele Marongiu in:

  10. Search for Andrea Maschio in:

  11. Search for Diego Ortega Del Vecchyo in:

  12. Search for Matteo Floris in:

  13. Search for Antonella Meloni in:

  14. Search for Alessandro Delitala in:

  15. Search for Maria Pina Concas in:

  16. Search for Federico Murgia in:

  17. Search for Ginevra Biino in:

  18. Search for Simona Vaccargiu in:

  19. Search for Ramaiah Nagaraja in:

  20. Search for Kirk E Lohmueller in:

  21. Search for Nicholas J Timpson in:

  22. Search for Nicole Soranzo in:

  23. Search for Ioanna Tachmazidou in:

  24. Search for George Dedoussis in:

  25. Search for Eleftheria Zeggini in:

  26. Search for Sergio Uzzau in:

  27. Search for Chris Jones in:

  28. Search for Robert Lyons in:

  29. Search for Andrea Angius in:

  30. Search for Gonçalo R Abecasis in:

  31. Search for John Novembre in:

  32. Search for David Schlessinger in:

  33. Search for Francesco Cucca in:

Contributions

M.Z., G.R.A., J.N., D.S. and F.C. conceived and supervised the study. M.Z., C.S., C.W.K.C., J.N., D.S. and F.C. drafted the manuscript. S.S., K.E.L. and G.R.A. revised the manuscript and wrote specific sections of it. A.A., C.J. and R.L. supervised sequencing experiments. F.B. and A. Maschio performed sequencing experiments. C.S., M.S., M.M. and S.S. carried out genetic association analyses. C.S. analyzed DNA sequence data. M.Z., A. Mulas, F.B., S.U. and R.N. carried out SNP array genotyping. M.Z. and A. Mulas verified genotypes by TaqMan genotyping. J.H.M., C.W.K.C., M.S., M.F., D.O.D.V., K.E.L. and J.N. performed polygenic score and related population genetic analyses. A. Meloni and A.D. performed clinical characterization of Laron carriers. S.V. provided DNA for the Sardinian replication sample set. F.M., M.P.C., G.B., M.S. and S.S. performed replication analysis. N.S., N.J.T., G.D., I.T., E.Z. and the UK10K group provided KCNQ1 fine-mapping data. All authors reviewed and approved the final manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Magdalena Zoledziewska or David Schlessinger or Francesco Cucca.

Integrated supplementary information

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–5, Supplementary Tables 1–4 and Supplementary Note.

About this article

Publication history

Received

Accepted

Published

DOI

https://doi.org/10.1038/ng.3403

Further reading

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