| Title: | Phenotypic covariance across the entire spectrum of relatedness for 86 billion pairs of individuals |
| Journal: | Nature Communications |
| Published: | 16 Feb 2021 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/33594080/ |
| DOI: | https://doi.org/10.1038/s41467-021-21283-4 |
| URL: | https://www.nature.com/articles/s41467-021-21283-4.pdf |
| Citations: | 27 (11 in last 2 years) as of 8 Aug 2024 |
Publication 12881
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Abstract
Attributing the similarity between individuals to genetic and non-genetic factors is central to genetic analyses. In this paper we use the genomic relationship (π$$\pi$$) among 417,060 individuals to investigate the phenotypic covariance between pairs of individuals for 32 traits across the spectrum of relatedness, from unrelated pairs through to identical twins. We find linear relationships between phenotypic covariance and π$$\pi$$ that agree with the SNP-based heritability (ĥSNP2$$\hat h_{SNP}^2$$) in unrelated pairs (π<0.02$$\pi \, < \, 0.02$$), and with pedigree-estimated heritability in close relatives (π>0.05$$\pi \, > \, 0.05$$). The covariance increases faster than πĥSNP2$$\pi \hat h_{SNP}^2$$ in distant relatives (0.02>π>0.05$$0.02 \, > \, \pi \, > \, 0.05$$), and we attribute this to imperfect linkage disequilibrium between causal variants and the common variants used to construct π$$\pi$$. We also examine the effect of assortative mating on heritability estimates from different experimental designs. We find that full-sib identity-by-descent regression estimates for height (0.66 s.e. 0.07) are consistent with estimates from close relatives (0.82 s.e. 0.04) after accounting for the effect of assortative mating.</p>
17 Keywords
- Adult
- Aged
- Biological Specimen Banks
- Body Mass Index
- Educational Status
- Genome, Human
- Humans
- Inheritance Patterns
- Linkage Disequilibrium
- Middle Aged
- Models, Genetic
- Phenotype
- Phylogeny
- Polymorphism, Single Nucleotide
- Quantitative Trait, Heritable
- Regression Analysis
- United Kingdom
9 Authors
- Kathryn E. Kemper
- Loic Yengo
- Zhili Zheng
- Abdel Abdellaoui
- Matthew C. Keller
- Michael E. Goddard
- Naomi R. Wray
- 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