| Title: | Assortative mating biases marker-based heritability estimators |
| Journal: | Nature Communications |
| Published: | 3 Feb 2022 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/35115518/ |
| DOI: | https://doi.org/10.1038/s41467-022-28294-9 |
| URL: | https://www.nature.com/articles/s41467-022-28294-9.pdf |
| Citations: | 51 (36 in last 2 years) as of 8 Aug 2024 |
Publication 12568
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Abstract
Many traits are subject to assortative mating, with recent molecular genetic findings confirming longstanding theoretical predictions that assortative mating induces long range dependence across causal variants. However, all marker-based heritability estimators implicitly assume mating is random. We provide mathematical and simulation-based evidence demonstrating that both method-of-moments and likelihood-based estimators are biased in the presence of assortative mating and derive corrected heritability estimators for traits subject to assortment. Finally, we demonstrate that the empirical patterns of estimates across methods and sample sizes for real traits subject to assortative mating are congruent with expected assortative mating-induced biases. For example, marker-based heritability estimates for height are 14% - 23% higher than corrected estimates using UK Biobank data.</p>
16 Keywords
- Algorithms
- Bias
- Computer Simulation
- Female
- Genetics, Population
- Genome-Wide Association Study
- Humans
- Likelihood Functions
- Linkage Disequilibrium
- Male
- Mendelian Randomization Analysis
- Models, Genetic
- Phenotype
- Polymorphism, Single Nucleotide
- Quantitative Trait, Heritable
- Reproduction
8 Authors
- Richard Border
- Sean O'Rourke
- Teresa de Candia
- Michael E. Goddard
- Peter M. Visscher
- Loic Yengo
- Matt Jones
- Matthew C. Keller
1 Application
| Application ID | Title |
|---|---|
| 16651 | Genetic architecture of disease and related anthropometric phenotypes |
Enabling scientific discoveries that improve human health