| Title: | Genetic evidence of assortative mating in humans |
| Journal: | Nature Human Behaviour |
| Published: | 9 Jan 2017 |
| DOI: | https://doi.org/10.1038/s41562-016-0016 |
| Citations: | 268 (58 in last 2 years) as of 8 Aug 2024 |
Publication 1823
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Abstract
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.</p>
20 Authors
- Matthew R. Robinson
- Aaron Kleinman
- Mariaelisa Graff
- Anna A. E. Vinkhuyzen
- David Couper
- Michael B. Miller
- Wouter J. Peyrot
- Abdel Abdellaoui
- Brendan P. Zietsch
- Ilja M. Nolte
- Jana V. van Vliet-Ostaptchouk
- Harold Snieder
- Sarah E. Medland
- Nicholas G. Martin
- Patrik K. E. Magnusson
- William G. Iacono
- Matt McGue
- Kari E. North
- Jian Yang
- Peter M. Visscher
1 Application
| Application ID | Title |
|---|---|
| 12514 | The limits of predicting complex traits and diseases from genetic data |
Enabling scientific discoveries that improve human health