In human populations, assortative mating is almost universally positive, with similarities between partners for quantitative phenotypes1–6, common disease risk1,3,7–10, behaviour6,11, social factors12–14 and personality4,5,11. The causes and genetic consequences of assortative mating remain unresolved because partner similarity can arise from different mechanisms: phenotypic assortment based on mate choice15,16, partner interaction and convergence in phenotype over time14,17, or social homogamy where individuals pair according to social or environmental background. Here, we present theory and an analytical approach to test for genetic evidence of assortative mating and find a correlation in genetic value among partners for a range of phenotypes. Across three independent samples of 24,662 spousal pairs in total, we infer a correlation at trait-associated loci between partners for height (0.200, 0.004 standard error, SE) that matched the phenotypic correlation (0.201, 0.004 SE), and a correlation at trait-associated loci for BMI (0.143, 0.007 SE) that was significantly lower than the phenotypic value (0.228, 0.004 SE). We extend our analysis to the UK Biobank study (7,780 pairs), finding evidence of a correlation at trait-associated loci for waist-to-hip ratio (0.101, 0.041 SE), systolic blood pressure (0.138, 0.064 SE) and educational attainment (0.654, 0.014 SE). Our results imply that mate choice, combined with widespread pleiotropy among traits, affects the genomic architecture of traits in humans.
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Zietsch, B. P., Verweij, K. J. H., Heath, A. C. & Martin, N. G. Variation in human mate choice: simultaneously investigating heritability, parental influence, sexual imprinting, and assortative mating. Am. Nat. 177, 605–616 (2011).
Silventoinen, K., Kaprio, J., Lahelma, E., Viken, R. J. & Rose, R. J. Assortative mating by body height and BMI: Finnish twins and their spouses. Am. J. Hum. Biol. 15, 620–627 (2003).
Maes, H., Neale, M. & Eaves, L. Genetic and environmental factors in relative body weight and human adiposity. Behav. Genet. 27, 325–351 (1997).
Keller, M. C. et al. The genetic correlation between height and IQ: Shared genes or assortative mating? PLoS Genet. 9, e1003451 (2013).
Eaves, L. J. Assortative mating and intelligence: An analysis of pedigree data. Heredity (Edinb.) 30, 199–210 (1973).
Eaves, L. J. & Heath, A. C. Detection of the effects of asymmetric assortative mating. Nature 289, 205–206 (1981).
Vandenberg, S. G. Assortative mating, or who marries whom? Behav. Genet. 2, 127–157 (1972).
Hippisley-Cox, J. Married couples’ risk of same disease: Cross sectional study. Br. Med. J. 325, 636 (2002).
Willemsen, G. Assortative mating may explain spouses’ risk of same disease. Br. Med. J. 326, 396a–396 (2003).
Ajslev, T. A. et al. Assortative marriages by body mass index have increased simultaneously with the obesity epidemic. Front. Genet. 3, 125 (2012).
Eaves, L. et al. Comparing the biological and cultural inheritance of personality and social attitudes in the Virginia 30,000 study of twins and their relatives. Twin Res. 2, 62–80 (1999).
Heath, A. C. et al. No decline in assortative mating for educational level. Behav. Genet. 15, 349–369 (1985).
Heath, A. C. & Eaves, L. J. Resolving the effects of phenotype and social background on mate selection. Behav. Genet. 15, 15–30 (1985).
Heath, A. C., Eaves, L. J., Nance, W. E. & Corey, L. A. Social inequality and assortative mating: Cause or consequence? Behav. Genet. 17, 9–17 (1987).
Falconer, D. & Mackay, T. F. C. Introduction to Quantitative Genetics (Pearson Prentice Hall, 1996).
Fisher, R. A. The correlation between relatives on the supposition of Mendelian inheritance. Trans. R. Soc. Edinb. 52, 399–433 (1918).
Nance, W. E., Corey, L. A., Rose, R. J. & Eaves, L. J. Relevance of the marriages of twins to the causal analysis of nonrandom mating. Prog. Clin. Biol. Res. 69 (Pt B), 61–71 (1981).
Crow, J. F. & Kimura, M. An Introduction to Population Genetics Theory (Harper and Row, 1970).
Wilson, S. R. The correlation between relatives under the multifactorial model with assortative mating. Ann. Hum. Genet. 37, 189–204 (1973).
Wright, S. Systems of mating. III. Assortative mating based on somatic resemblance. Genetics 6, 144–161 (1921).
Eaves, L. J., Last, K., Martin, N. G. & Jinks, J. L. A progressive approach to non-additivity and genotype-environmental covariance in the analysis of human differences. Br. J. Math. Stat. Psychol. 30, 1–42 (1977).
Pearson, K. & Lee, A. On the laws of inheritance in man I. Inheritance of physical characters. Biometrika 2, 357–462 (1903).
Galton, F. Measurement of character. Fortn. Rev. 36, 179–185 (1884).
Falconer, D. S. Introduction to Quantitative Genetics (Ronald, 1960).
Zou, J. Y. et al. Genetic and socioeconomic study of mate choice in Latinos reveals novel assortment patterns. Proc. Natl Acad. Sci. USA 112, 13621–13626 (2015).
Guo, G., Wang, L., Liu, H. & Randall, T. Genomic assortative mating in marriages in the United States. PLoS One 9, e112322 (2014).
Domingue, B. W., Fletcher, J., Conley, D. & Boardman, J. D. Genetic and educational assortative mating among US adults. Proc. Natl Acad. Sci. USA 111, 7996–8000 (2014).
Abdellaoui, A., Verweij, K. J. H. & Zietsch, B. P. No evidence for genetic assortative mating beyond that due to population stratification. Proc. Natl Acad. Sci. USA 111, E4137 (2014).
Abdellaoui, A. et al. Association between autozygosity and major depression: stratification due to religious assortment. Behav. Genet. 43, 455–467 (2013).
Abdellaoui, A. et al. Educational attainment influences levels of homozygosity through migration and assortative mating. PLoS One 10, e0118935 (2015).
Sebro, R., Hoffman, T. J., Lange, C., Rogus, J. J. & Risch, N. J. Testing for non-random mating: Evidence for ancestry-related assortative mating in the Framingham heart study. Genet. Epidemiol. 34, 674–679 (2010).
Tenesa, A., Rawlik, K., Navarro, P. & Canela-Xandri, O. Genetic determination of height-mediated mate choice. Genome Biol. 16, 269 (2016).
Wood, A. R. et al. Defining the role of common variation in the genomic and biological architecture of adult human height. Nat. Genet. 46, 1173–1186 (2014).
Locke, A. E. et al. Genetic studies of body mass index yield new insights for obesity biology. Nature 518, 197–206 (2015).
de Los Campos, G., Vazquez, A. I., Fernando, R., Klimentidis, Y. C. & Sorensen, D. Prediction of complex human traits using the genomic best linear unbiased predictor. PLoS Genet. 9, e1003608 (2013).
Goddard, M. E., Wray, N. R., Verbyla, K. & Visscher, P. M. Estimating effects and making predictions from genome-wide marker data. Stat. Sci. 24, 517–529 (2009).
Price, A. L. et al. Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 38, 904–909 (2006).
Zheng, H.-F. et al. Whole-genome sequencing identifies EN1 as a determinant of bone density and fracture. Nature 526, 112–117 (2015).
International Consortium for Blood Pressure Genome-Wide Association Studies et al. Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk. Nature 478, 103–109 (2011).
Heid, I. M. et al. Meta-analysis identifies 13 new loci associated with waist–hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution. Nat. Genet. 42, 949–960 (2010).
Okbay, A. et al. Genome-wide association study identifies 74 loci associated with educational attainment. Nature 533, 539–542 (2016).
Vattikuti, S., Guo, J. & Chow, C. C. Heritability and genetic correlations explained by common SNPs for metabolic syndrome traits. PLoS Genet. 8, e1002637 (2012).
Rietveld, C. A. et al. GWAS of 126,559 individuals identifies genetic variants associated with educational attainment. Science 340, 1467–1471 (2013).
Yang, J. et al. Genetic variance estimation with imputed variants finds negligible missing heritability for human height and body mass index. Nat. Genet. 47, 1114–1120 (2015).
Lynch, M. & Walsh, B. Genetics and Analysis of Quantitative Traits. (Sinauer, 1998).
Yang, J. et al. Genomic inflation factors under polygenic inheritance. Eur. J. Hum. Genet. 19, 807–812 (2011).
Eriksson, N. et al. Web-based, participant-driven studies yield novel genetic associations for common traits. PLoS Genet. 6, e1000993 (2010).
Tung, J. Y. et al. Efficient replication of over 180 genetic associations with self-reported medical data. PLoS One 6, e23473 (2011).
Yang, J. et al. Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits. Nat. Genet. 44, 369–375 (2012).
Yang, J., Lee, S. H., Goddard, M. E. & Visscher, P. M. GCTA: a tool for genome-wide complex trait analysis. Am. J. Hum. Genet. 88, 76–82 (2011).
Haseman, J. K. & Elston, R. C. The investigation of linkage between a quantitative trait and a marker locus. Behav. Genet. 2, 3–19 (1972).
Visscher, P. M. et al. Statistical power to detect genetic (co)variance of complex traits using SNP data in unrelated samples. PLoS Genet. 10, e1004269 (2014).
Yang, J., Zaitlen, N. A., Goddard, M. E., Visscher, P. M. & Price, A. L. Advantages and pitfalls in the application of mixed-model association methods. Nat. Genet. 46, 100–106 (2014).
Silventoinen, K., Kaprio, J. & Lahelma, E. Genetic and environmental contributions to the association between body height and educational attainment: A study of adult Finnish twins. Behav. Genet. 30, 477–485 (2000).
Lin, D.-Y. & Sullivan, P. F. Meta-analysis of genome-wide association studies with overlapping subjects. Am. J. Hum. Genet. 85, 862–872 (2009).
The University of Queensland group is supported by the Australian National Health and Medical Research Council (NHMRC grants 1078037, 1048853 and 1050218), the Australian Research Council (Discovery Project 160103860) and the National Institute of Health (NIH grants R21ESO25052-01, R01AG042568 and PO1GMO99568). J.Y. is supported by a Charles and Sylvia Viertel Senior Medical Research Fellowship. We thank the participants of the cohort studies, as well as C. Haley and our colleagues at the Program in Complex Trait Genomics, for comments and suggestions. 23andMe cohort thank the research participants and employees of 23andMe. This work was supported by the National Human Genome Research Institute of the NIH (grant number R44HG006981). The UK Biobank research was conducted using the UK Biobank Resource under project 12514. TWINGENE was supported by the Swedish Research Council (M-2005-1112), GenomEUtwin (EU/QLRT-2001-01254; QLG2-CT-2002-01254), NIH DK U01-066134, the Swedish Foundation for Strategic Research, and the Heart and Lung Foundation grant no. 20070481. The Atherosclerosis Risk in Communities Study (ARIC) is a collaborative study supported by National Heart, Lung, and Blood Institute contracts (HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, and HHSN268201100012C). K.E.N and M.G. are supported by NIDDK R01 DK089256. We thank the staff and participants of the ARIC study for their contributions. Generation and management of GWAS genotype data for the LifeLines Cohort Study is supported by the Netherlands Organization of Scientific Research (grant 175.010.2007.006), the Economic Structure Enhancing Fund of the Dutch government, the Ministry of Economic Affairs, the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the Northern Netherlands Collaboration of Provinces, the Province of Groningen, University Medical Center Groningen, the University of Groningen, Dutch Kidney Foundation and Dutch Diabetes Research Foundation. The authors acknowledge the services of the LifeLines Cohort Study, the contributing research centres delivering data to LifeLines, and all the study participants. Minnesota Center for Twin and Family Research (MCTFR) is funded by US Public Health Service grants from the National Institute on Alcohol Abuse and Alcoholism (AA09367, AA11886), National Institute on Drug Abuse (DA05147, DA13240, DA024417, DA036216) and National Institute of Mental Health (MH066140). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
The authors declare no competing interests.
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Robinson, M., Kleinman, A., Graff, M. et al. Genetic evidence of assortative mating in humans. Nat Hum Behav 1, 0016 (2017). https://doi.org/10.1038/s41562-016-0016
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