Across-nation differences in the mean values for complex traits are common1,2,3,4,5,6,7,8, but the reasons for these differences are unknown. Here we find that many independent loci contribute to population genetic differences in height and body mass index (BMI) in 9,416 individuals across 14 European countries. Using discovery data on over 250,000 individuals and unbiased effect size estimates from 17,500 sibling pairs, we estimate that 24% (95% credible interval (CI) = 9%, 41%) and 8% (95% CI = 4%, 16%) of the captured additive genetic variance for height and BMI, respectively, reflect population genetic differences. Population genetic divergence differed significantly from that in a null model (height, P < 3.94 × 10−8; BMI, P < 5.95 × 10−4), and we find an among-population genetic correlation for tall and slender individuals (r = −0.80, 95% CI = −0.95, −0.60), consistent with correlated selection for both phenotypes. Observed differences in height among populations reflected the predicted genetic means (r = 0.51; P < 0.001), but environmental differences across Europe masked genetic differentiation for BMI (P < 0.58).

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.


  1. 1.

    et al. Depression, chronic diseases, and decrements in health: results from the World Health Surveys. Lancet 370, 851–858 (2007).

  2. 2.

    , , , & Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. Diabetes Care 27, 1047–1053 (2004).

  3. 3.

    Global burden of tuberculosis: estimated incidence, prevalence, and mortality by country. J. Am. Med. Assoc. 282, 677–686 (1999).

  4. 4.

    , , , & Global and regional burden of disease and risk factors, 2001: systematic analysis of population health data. Lancet 367, 1747–1757 (2006).

  5. 5.

    et al. Age-specific and sex-specific mortality in 187 countries, 1970–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 380, 2071–2094 (2012).

  6. 6.

    , , & Global patterns of cancer incidence and mortality rates and trends. Cancer Epidemiol. Biomarkers Prev. 19, 1893–1907 (2010).

  7. 7.

    & Global variation in the relative burden of stroke and ischemic heart disease. Circulation 124, 314–323 (2011).

  8. 8.

    , & Global variation in stroke burden and mortality: estimates from monitoring, surveillance, and modelling. Lancet Neurol. 8, 345–354 (2009).

  9. 9.

    , & Sporadic cases are the norm for complex disease. Eur. J. Hum. Genet. 18, 1039–1043 (2010).

  10. 10.

    , & Data and theory point to mainly additive genetic variance for complex traits. PLoS Genet. 4, e1000008 (2008).

  11. 11.

    et al. Common SNPs explain a large proportion of the heritability for human height. Nat. Genet. 42, 565–569 (2010).

  12. 12.

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

  13. 13.

    et al. Estimation and partitioning of polygenic variation captured by common SNPs for Alzheimer's disease, multiple sclerosis and endometriosis. Hum. Mol. Genet. 22, 832–841 (2013).

  14. 14.

    et al. Ubiquitous polygenicity of human complex traits: genome-wide analysis of 49 traits in Koreans. PLoS Genet. 9, e1003355 (2013).

  15. 15.

    , & Explaining additional genetic variation in complex traits. Trends Genet. 30, 124–132 (2014).

  16. 16.

    , , , & The burden and costs of chronic diseases in low-income and middle-income countries. Lancet 370, 1929–1938 (2007).

  17. 17.

    & Temporal and geographic trends in the global stroke epidemic. Stroke 44, S123–S125 (2013).

  18. 18.

    & Can noncommunicable diseases be prevented? Lessons from studies of populations and individuals. Science 337, 1482–1487 (2012).

  19. 19.

    & Principles of Population Genetics (Sinauer Associates, 1997).

  20. 20.

    , , & QST-FST comparisons: evolutionary and ecological insights from genomic heterogeneity. Nat. Rev. Genet. 14, 179–190 (2013).

  21. 21.

    , & The obesity epidemic, metabolic syndrome and future prevention strategies. Eur. J. Cardiovasc. Prev. Rehabil. 11, 3–8 (2004).

  22. 22.

    Global nutrition dynamics: the world is shifting rapidly toward a diet linked with noncommunicable diseases. Am. J. Clin. Nutr. 84, 289–298 (2006).

  23. 23.

    , , , & Health and economic burden of the projected obesity trends in the USA and the UK. Lancet 378, 815–825 (2011).

  24. 24.

    et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 384, 766–781 (2014).

  25. 25.

    et al. National, regional, and global trends in body-mass index since 1980: systematic analysis of health examination surveys and epidemiological studies with 960 country-years and 9·1 million participants. Lancet 377, 557–567 (2011).

  26. 26.

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

  27. 27.

    et al. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat. Genet. 42, 937–948 (2010).

  28. 28.

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

  29. 29.

    et al. Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits. Nat. Genet. 44, 369–375 (2012).

  30. 30.

    et al. FTO genotype is associated with phenotypic variability of body mass index. Nature 490, 267–272 (2012).

  31. 31.

    , , & Signs of selective pressure on genetic variants affecting human height. PLoS ONE 6, e27588 (2011).

  32. 32.

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

  33. 33.

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

  34. 34.

    et al. Genetic studies of body mass index yeild new insights for obesity biology. Nature 518, 197–206 (2015).

  35. 35.

    et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).

  36. 36.

    Power and predictive accuracy of polygenic risk scores. PLoS Genet. 9, e1003348 (2013).

  37. 37.

    & Growing tall but unequal: new findings and new background evidence on anthropometric welfare in 156 countries, 1810–1989. Econ. Hist. Dev. Reg. 27, S66–S85 (2012).

  38. 38.

    et al. Genome-wide detection and characterization of positive selection in human populations. Nature 449, 913–918 (2007).

  39. 39.

    , , , & Recent and ongoing selection in the human genome. Nat. Rev. Genet. 8, 857–868 (2007).

  40. 40.

    et al. Natural selection on protein-coding genes in the human genome. Nature 437, 1153–1157 (2005).

  41. 41.

    et al. Natural selection on genes that underlie human disease susceptibility. Curr. Biol. 18, 883–889 (2008).

  42. 42.

    , , , & Natural selection has driven population differentiation in modern humans. Nat. Genet. 40, 340–345 (2008).

  43. 43.

    et al. Population history and natural selection shape patterns of genetic variation in 132 genes. PLoS Biol. 2, e286 (2004).

  44. 44.

    & From evolutionary genetics to human immunology: how selection shapes host defence genes. Nat. Rev. Genet. 11, 17–30 (2010).

  45. 45.

    & The impact of natural selection on health and disease: uses of the population genetics approach in humans. Evol. Appl. 6, 596–607 (2013).

  46. 46.

    , & Y chromosome diversity, human expansion, drift, and cultural evolution. Proc. Natl. Acad. Sci. USA 106, 20174–20179 (2009).

  47. 47.

    , , , & A new method to uncover signatures of divergent and stabilizing selection in quantitative traits. Genetics 189, 621–632 (2011).

  48. 48.

    Diverse Populations Collaborative Group. Weight-height relationships and body mass index: some observations from the Diverse Populations Collaboration. Am. J. Phys. Anthropol. 128, 220–229 (2005).

  49. 49.

    Genetic variation and phenotypic evolution during allopatric speciation. Am. Nat. 116, 463–479 (1980).

  50. 50.

    et al. Genetic characterization of northeastern Italian population isolates in the context of broader European genetic diversity. Eur. J. Hum. Genet. 21, 659–665 (2013).

  51. 51.

    & Estimating F-statistics. Annu. Rev. Genet. 36, 721–750 (2002).

  52. 52.

    & Estimating F-statistics for the analysis of population structure. Evolution 38, 1358–1370 (1984).

  53. 53.

    & Correlations, descent measures: drift with migration and mutation. Proc. Natl. Acad. Sci. USA 84, 8512–8514 (1987).

  54. 54.

    , , , & Phasing of many thousands of genotyped samples. Am. J. Hum. Genet. 91, 238–251 (2012).

  55. 55.

    , & Genotype imputation with thousands of genomes. G3 (Bethesda) 1, 457–470 (2011).

  56. 56.

    1000 Genomes Project Consortium. An integrated map of genetic variation from 1,092 human genomes. Nature 491, 56–65 (2012).

  57. 57.

    , & A linear complexity phasing method for thousands of genomes. Nat. Methods 9, 179–181 (2012).

  58. 58.

    MCMC methods for multi-response generalized linear mixed models: the MCMCglmm R package.

Download references


We thank the reviewers for their very helpful and insightful comments that greatly improved the manuscript. We also thank B. Hill and O. Ovaskainen for useful discussions. The University of Queensland group is supported by the Australian National Health and Medical Research Council (NHMRC; grants 1078037, 1048853 and 1050218). J.E.P. is supported by Australian Research Council grant DE130100691. J.Y. is supported by a Charles and Sylvia Viertel Senior Medical Research Fellowship and by NHMRC grant 1052684. We thank our colleagues at the Centre for Neurogenetics and Statistical Genomics for comments and suggestions. We are grateful to the twins and their families for their generous participation in the full-sibling family data set, which includes data from many cohorts and received support from many funding bodies. TWINGENE was supported by the Swedish Research Council (M-2005-1112), GenomEUtwin (EU/QLRT-2001-01254 and QLG2-CT-2002-01254), US National Institutes of Health (NIH) grant DK U01-066134, the Swedish Foundation for Strategic Research (SSF), and the Heart and Lung Foundation (20070481). For the Netherlands Twin Register (NTR), funding was obtained from the Netherlands Organization for Scientific Research (NWO; MagW/ZonMW grants 904-61-090, 985-10-002, 904-61-193, 480-04-004, 400-05-717, Addiction-31160008, Middelgroot-11-09-032 and Spinozapremie 56-464-14192), the Center for Medical Systems Biology (CSMB; NWO Genomics), NBIC/BioAssist/RK(2008.024), Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL; 184.021.007), the VU University's Institute for Health and Care Research (EMGO+) and Neuroscience Campus Amsterdam (NCA), the European Science Foundation (ESF; EU/QLRT-2001-01254), the European Community's Seventh Framework Programme (FP7/2007-2013) under the ENGAGE project grant agreement (HEALTH-F4-2007-201413), the European Research Council (ERC Advanced; 230374), the Rutgers University Cell and DNA Repository (National Institute for Mental Health (NIMH), U24-MH068457-06), the Avera Institute (Sioux Falls, South Dakota, USA) and the US NIH (R01-D0042157-01A, Grand Opportunity grants 1RC2-MH089951-01 and 1RC2-MH089995-01). Part of the genotyping and analyses were funded by the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health. The TwinsUK study was funded by the Wellcome Trust and the European Community's Seventh Framework Programme (FP7/2007-2013) under the ENGAGE project grant agreement (HEALTH-F4-2007-201413). TwinsUK also receives support from the UK Department of Health via the National Institute for Health Research (NIHR) comprehensive Biomedical Research Centre award to Guy's and St Thomas' National Health Service (NHS) Foundation Trust in partnership with King's College London. T.D.S. is the holder of an ERC Advanced Principal Investigator award. Genotyping for the TwinsUK study was performed by the Wellcome Trust Sanger Institute, with the support of the National Eye Institute via a US NIH/Center for Inherited Disease Research (CIDR) genotyping project. The Framingham Heart Study is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with Boston University (contract N01-HC-25195). This manuscript was not prepared in collaboration with investigators of the Framingham Heart Study and does not necessarily reflect the opinions or views of the Framingham Heart Study, Boston University or NHLBI. Funding for SHARe Affymetrix genotyping was provided by NHLBI contract N02-HL-64278. Funding for SHARe Illumina genotyping was provided under an agreement between Illumina and Boston University. The QIMR researchers acknowledge funding from the Australian NHMRC (grants 241944, 389875, 389891, 389892, 389938, 442915, 442981, 496739, 496688 and 552485) and the US NIH (grants AA07535, AA10248, AA014041, AA13320, AA13321, AA13326 and DA12854). We are grateful to M. Gill (Trinity College Dublin) and K. Nicodemus (University of Edinburgh) for access to the ISC–Trinity College Dublin cohort, which was supported by the Wellcome Trust and the Health Research Board, Ireland. Access to the Bulgarian cohort data was kindly facilitated by G. Kirov and V. Excott-Price. For the Danish cohort, the Danish Scientific Committees and the Danish Data Protection Agency approved the study and all the patients gave written informed consent before inclusion in the project. The National Institute on Aging (NIA) provided funding for the Health and Retirement Study (HRS; U01-AG09740). The HRS is performed at the Institute for Social Research at the University of Michigan. This manuscript was not prepared in collaboration with investigators of the HRS and does not necessarily reflect the opinions or views of the HRS, University of Michigan or NIA. The Netherlands genotype samples were part of Project MinE, which was supported by the ALS Foundation Netherlands. Research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013).

Author information


  1. Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia.

    • Matthew R Robinson
    • , Gibran Hemani
    • , Konstantin Shakhbazov
    • , Joseph E Powell
    • , Anna Vinkhuyzen
    • , Jian Yang
    •  & Peter M Visscher
  2. Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands.

    • Carolina Medina-Gomez
    •  & Fernando Rivadeneira
  3. Institute for Maternal and Child Health, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) 'Burlo Garofolo', Trieste, Italy.

    • Massimo Mezzavilla
    •  & Paolo Gasparini
  4. Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK.

    • Massimo Mezzavilla
    •  & Paolo Gasparini
  5. Estonian Genome Center, University of Tartu, Tartu, Estonia.

    • Tonu Esko
    • , Andres Metspalu
    •  & Joel N Hirschhorn
  6. Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, Massachusetts, USA.

    • Tonu Esko
    • , Tune H Pers
    • , Sailaja Vedantam
    •  & Joel N Hirschhorn
  7. Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.

    • Tonu Esko
    • , Tune H Pers
    • , Sailaja Vedantam
    •  & Joel N Hirschhorn
  8. Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA.

    • Tonu Esko
    • , Tune H Pers
    • , Daniel I Chasman
    •  & Joel N Hirschhorn
  9. University of Queensland Diamantina Institute, University of Queensland, Translational Research Institute, Brisbane, Queensland, Australia.

    • Joseph E Powell
    • , Jian Yang
    •  & Peter M Visscher
  10. Division of Cancer Epidemiology and Genetics, National Cancer Institute, US National Institutes of Health, Bethesda, Maryland, USA.

    • Sonja I Berndt
  11. Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden.

    • Stefan Gustafsson
    •  & Erik Ingelsson
  12. Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.

    • Anne E Justice
  13. Division of Gastroenterology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA.

    • Bratati Kahali
    •  & Kari E North
  14. Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA.

    • Bratati Kahali
    •  & Kari E North
  15. Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.

    • Adam E Locke
    • , Goncalo R Abecasis
    •  & Elizabeth K Speliotes
  16. Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark.

    • Tune H Pers
  17. Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, UK.

    • Andrew R Wood
    •  & Timothy M Frayling
  18. Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands.

    • Wouter van Rheenen
    • , Leonard H van den Berg
    •  & Jan H Veldink
  19. Norwegian Centre for Mental Disorders Research (NORMENT), KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.

    • Ole A Andreassen
  20. Institute of Biological Psychiatry, MHC Sct. Hans, Mental Health Devices Copenhagen, Roskilde, Denmark.

    • Thomas M Werge
  21. Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.

    • Thomas M Werge
  22. Lundbeck Foundation Initiative for Integrative Psychiatric Research, (iPSYCH), Aarhus, Denmark.

    • Thomas M Werge
  23. Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands.

    • Dorret I Boomsma
    • , Eco J C de Geus
    •  & Jouke Jan Hottenga
  24. EMGO+ Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands.

    • Dorret I Boomsma
    • , Eco J C de Geus
    •  & Jouke Jan Hottenga
  25. Department of Biological Psychology, VU University Amsterdam, Amsterdam, the Netherlands.

    • Dorret I Boomsma
    • , Eco J C de Geus
    •  & Jouke Jan Hottenga
  26. Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.

    • Daniel I Chasman
  27. Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.

    • Erik Ingelsson
  28. Medical Research Council (MRC) Epidemiology Unit, University of Cambridge, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK.

    • Ruth J F Loos
  29. Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

    • Ruth J F Loos
  30. Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

    • Ruth J F Loos
  31. Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

    • Ruth J F Loos
  32. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

    • Patrik K E Magnusson
    •  & Nancy L Pedersen
  33. QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.

    • Nicholas G Martin
    •  & Grant W Montgomery
  34. Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.

    • Kari E North
  35. Department of Twin Research and Genetic Epidemiology, King's College London, St. Thomas' Hospital, London, UK.

    • Timothy D Spector
  36. Biosciences Research Division, Department of Primary Industries, Melbourne, Victoria, Australia.

    • Michael E Goddard
  37. Department of Food and Agricultural Systems, University of Melbourne, Melbourne, Victoria, Australia.

    • Michael E Goddard


  1. Search for Matthew R Robinson in:

  2. Search for Gibran Hemani in:

  3. Search for Carolina Medina-Gomez in:

  4. Search for Massimo Mezzavilla in:

  5. Search for Tonu Esko in:

  6. Search for Konstantin Shakhbazov in:

  7. Search for Joseph E Powell in:

  8. Search for Anna Vinkhuyzen in:

  9. Search for Sonja I Berndt in:

  10. Search for Stefan Gustafsson in:

  11. Search for Anne E Justice in:

  12. Search for Bratati Kahali in:

  13. Search for Adam E Locke in:

  14. Search for Tune H Pers in:

  15. Search for Sailaja Vedantam in:

  16. Search for Andrew R Wood in:

  17. Search for Wouter van Rheenen in:

  18. Search for Ole A Andreassen in:

  19. Search for Paolo Gasparini in:

  20. Search for Andres Metspalu in:

  21. Search for Leonard H van den Berg in:

  22. Search for Jan H Veldink in:

  23. Search for Fernando Rivadeneira in:

  24. Search for Thomas M Werge in:

  25. Search for Goncalo R Abecasis in:

  26. Search for Dorret I Boomsma in:

  27. Search for Daniel I Chasman in:

  28. Search for Eco J C de Geus in:

  29. Search for Timothy M Frayling in:

  30. Search for Joel N Hirschhorn in:

  31. Search for Jouke Jan Hottenga in:

  32. Search for Erik Ingelsson in:

  33. Search for Ruth J F Loos in:

  34. Search for Patrik K E Magnusson in:

  35. Search for Nicholas G Martin in:

  36. Search for Grant W Montgomery in:

  37. Search for Kari E North in:

  38. Search for Nancy L Pedersen in:

  39. Search for Timothy D Spector in:

  40. Search for Elizabeth K Speliotes in:

  41. Search for Michael E Goddard in:

  42. Search for Jian Yang in:

  43. Search for Peter M Visscher in:


Conception and design of the study: M.R.R., M.E.G., J.Y. and P.M.V. Data analysis: M.R.R., with additional contributions from G.H., C.M.-G., M.M., K.S., T.E., J.E.P., A.V., S.I.B., S.G., A.E.J., B.K., A.E.L., T.H.P., S.V., A.R.W. and W.v.R. Study oversight, sample collection and management: J.H.V., L.H.v.d.B., O.A.A., P.G., A.M., F.R., T.M.W., G.R.A., D.I.B., D.I.C., E.J.C.d.G., T.M.F., J.N.H., J.J.H., E.I., R.J.F.L., P.K.E.M., N.G.M., G.W.M., K.E.N., N.L.P., T.D.S. and E.K.S. Manuscript writing: M.R.R. and P.M.V., with contributions from all authors on the final version.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Matthew R Robinson or Peter M Visscher.

Integrated supplementary information

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–15, Supplementary Tables 1 and 2, and Supplementary Note.

About this article

Publication history






Further reading