Phenotypic correlations among partners for traits such as longevity or late-onset disease have been found to be comparable to phenotypic correlations in first-degree relatives. How these correlations arise in late life is poorly understood. Here we introduce a novel paradigm to establish the presence of indirect assortment on factors correlated across generations, by examining correlations between parents of couples, i.e., in-laws. Using correlations in additive genetic values we further corroborate the presence of indirect assortment on heritable factors. Specifically, using couples from the UK Biobank cohort, we show that longevity and disease history of the parents of White British couples are correlated, with correlations of up to 0.09. The correlations in parental longevity are replicated in the FamiLinx cohort, a larger and geographically more diverse historical ancestry dataset spanning a broader time frame. These correlations in parental longevity significantly (pval < 0.0093 for all pairs of parents) exceed what would be expected due to variations in lifespan based on year and location of birth. For cardiovascular diseases, in particular hypertension, we find significant correlations (r = 0.028, pval = 0.005) in genetic values among partners, supporting a model where partners assort for risk factors to some extent genetically correlated with cardiovascular disease. Partitioning the relative importance of indirect assortative mating and shared common environment will require large, well-characterized longitudinal cohorts aimed at understanding phenotypic correlations among none-blood relatives. Identifying the factors that mediate indirect assortment on longevity and human disease risk will help to unravel factors affecting human disease and ultimately longevity.
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Required data can be accessed through the UK Biobank (http://www.ukbiobank.ac.uk/) and the FamiLinx website (http://www.familinx.org/), respectively. For analyses involving genotypes, we used the individuals genotyped in phase 1 of the UK Biobank genotyping project, which were released by the UK Biobank in June 2015. The genotype data were downloaded on 5 June 2015. The DISSECT software used to perform the analysis based on genetic values is freely available from http://www.dissect.ed.ac.uk/.
Anonymous (1903) Assortative mating in man: a cooperative study. Biometrika 2:481–498
Begier MH, Hamdan MA (1971) Correlation in a bivariate normal distribution with truncation in both variables. Aust J Stat 13:77–82
Belsky DW, Domingue BW, Wedow R et al. (2018) Genetic analysis of social-class mobility in five longitudinal studies. Proc Natl Acad Sci USA 115:E7275-E7284
Bulik-Sullivan, B, Finucane HK, Anttila V et al. (2015) An atlas of genetic correlations across human diseases and traits. Nat Genet 47:1236–1241
Canela-Xandri O, Law A, Gray A et al. (2015) A new tool called DISSECT for analysing large genomic data sets using a Big Data approach Nat Commun 6:10162
Canela-Xandri O, Rawlik K, Tenesa A (2018) An atlas of genetic associations in UK Biobank. Nat Genet 50:1593–1599
Canela-Xandri O, Rawlik K, Woolliams JA et al. (2016) Improved genetic profiling of anthropometric traits using a Big Data approach PLoS ONE 11:e0166755
Conley D, Laidley T, Belsky DW et al. (2016) Assortative mating and differential fertility by phenotype and genotype across the 20th century. Proc Natl Acad Sci USA 113: 6647–6652
Cover TM, Thomas JA (2012) Elements of information theory. John Wiley & Sons, Hoboken, New Jersey, USA
Drasgow F (1986) Polychoric and polyserial correlations. In: Kotz S and Johnson N (eds) The Encyclopedia of Statistics. John Wiley and Sons, Inc. Hoboken, New Jersey, USA
Falconer DS, Mackay TFC (1996) Introduction to quantitative genetics. Prentice Hall, Pearson
Fox J (2010) polycor: Polychoric and polyserial correlations. https://CRAN.R-project.org/package=polycor
Gianola D (1982) Assortative mating and the genetic correlation. Theor Appl Genet 62:225–231
Herskind AM, McGue M, Holm NV et al. (1996) The heritability of human longevity: a population-based study of 2872 Danish twin pairs born 1870–1900. Human Genet 97:319–323
Hippisley-Cox J, Coupland C, Pringle M et al. (2002) Married couples’ risk of same disease: cross sectional study BMJ 325:636
Hugh-Jones D, Verweij KJ, Pourcain BS et al. (2016) Assortative mating on educational attainment leads to genetic spousal resemblance for polygenic scores Intelligence 59:103–108
Joshi PK, Fischer K, Schraut KE et al. (2016) Variants near CHRNA3/5 and APOE have age-and sex-related effects on human lifespan. Nat Commun 7:11174
Kaplanis J, Gordon A, Shor T et al. (2018) Quantitative analysis of population-scale family trees with millions of relatives. Science 360:171–175
Kong A, Thorleifsson G, Frigge ML et al. (2018) The nature of nurture: effects of parental genotypes. Science 359:424–428
Lee SH, Naomi RW, Goddard ME et al. (2011) Estimating missing heritability for disease from genome-wide association studies Am J Human Genet 88:294–305
Muñoz M, Pong-Wong R, Canela-Xandri O et al. (2016) Evaluating the contribution of genetics and familial shared environment to common disease using the UK Biobank. Nat Genet 48:980–983
Nordsletten AE, Larsson H, Crowley JJ et al. (2016) Patterns of nonrandom mating within and across 11 major psychiatric disorders. JAMA Psychiatry 73:354–361
Peyrot WJ, Robinson MR, Penninx BW et al. (2016) Exploring boundaries for the genetic consequences of assortative mating for psychiatric traits JAMA Psychiatry 73:1189–1195
Philippe P (1978) Familial correlations of longevity: an isolate-based study. Am J Med Genet 2:121–129
Robinson MR, Kleinman A, Graff M et al. (2017) Genetic evidence of assortative mating in humans. Nat Hum Behav 1:0016
Schulze R (2004) Meta-analysis-a comparison of approaches. Hogrefe & Huber, Ashland, Ohio, USA
Silventoinen K, Kaprio J, Lahelma E et al. (2003) Assortative mating by body height and BMI: Finnish twins and their spouses Am J Human Biol 15:620–627
Stulp G, Simons MJ, Grasman S et al. (2017) Assortative mating for human height: a meta‐analysis. Am J Hum Biol 29
Tenesa A, Rawlik K, Navarro P et al. (2015) Genetic determination of height-mediated mate choice Genome Biol 16:1–8
Xia C, Amador C, Huffman J et al. (2016) Pedigree- and SNP-associated genetics and recent environment are the major contributors to anthropometric and cardiometabolic trait variation. PLoS Genet 12:e1005804
Zietsch BP, Verweij KJ, Heath AC et al. (2011) Variation in human mate choice: simultaneously investigating heritability, parental influence, sexual imprinting, and assortative mating Am Nat 177:605–616
This work was mainly supported by The Roslin Institute Strategic Grant funding from the BBSRC. AT also acknowledges funding from the Medical Research Council Human Genetics Unit. This work used the ARCHER UK National Supercomputing Service (http://www.archer.ac.uk) and the Edinburgh Compute and Data Facility (ECDF) (http://www.ecdf.ed.ac.uk/). This research has been conducted using the UK Biobank Resource under project 6684.
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Rawlik, K., Canela-Xandri, O. & Tenesa, A. Indirect assortative mating for human disease and longevity. Heredity 123, 106–116 (2019). https://doi.org/10.1038/s41437-019-0185-3
Journal of Risk and Uncertainty (2019)
Nature Communications (2019)
SSRN Electronic Journal (2019)