| Title: | Decomposing heritability and genetic covariance by direct and indirect effect paths |
| Journal: | PLOS Genetics |
| Published: | 23 Jan 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/36689559/ |
| DOI: | https://doi.org/10.1371/journal.pgen.1010620 |
| URL: | https://journals.plos.org/plosgenetics/article/file?id=10.1371/journal.pgen.1010620&type=printable |
Publication 7977
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Abstract
Estimation of heritability and genetic covariance is crucial for quantifying and understanding complex trait genetic architecture and is employed in almost all recent genome-wide association studies (GWAS). However, many existing approaches for heritability estimation and almost all methods for estimating genetic correlation ignore the presence of indirect genetic effects, i.e., genotype-phenotype associations confounded by the parental genome and family environment, and may thus lead to incorrect interpretation especially for human sociobehavioral phenotypes. In this work, we introduce a statistical framework to decompose heritability and genetic covariance into multiple components representing direct and indirect effect paths. Applied to five traits in UK Biobank, we found substantial involvement of indirect genetic components in shared genetic architecture across traits. These results demonstrate the effectiveness of our approach and highlight the importance of accounting for indirect effects in variance component analysis of complex traits.7 Authors
- Jie Song
- Yiqing Zou
- Yuchang Wu
- Jiacheng Miao
- Ze Yu
- Jason M. Fletcher
- Qiongshi Lu
2 Applications
| Application ID | Title |
|---|---|
| 42148 | Dissect the genetic architecture of various sociological traits through integrative analysis of GWAS and functional annotations |
| 57284 | Understanding Environmental and Intergenerational Effects on Genetic Measures and Longer Term Social, Economic, and Health Outcomes |
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