| Title: | Cross-trait assortative mating is widespread and inflates genetic correlation estimates |
| Journal: | Science |
| Published: | 17 Nov 2022 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/36395242/ |
| DOI: | https://doi.org/10.1126/science.abo2059 |
| URL: | https://escholarship.org/content/qt8ph6d7gn/qt8ph6d7gn.pdf |
| Citations: | 82 (77 in last 2 years) as of 8 Aug 2024 |
Publication 10698
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
Abstract
The observation of genetic correlations between disparate human traits has been interpreted as evidence of widespread pleiotropy. Here, we introduce cross-trait assortative mating (xAM) as an alternative explanation. We observe that xAM affects many phenotypes and that phenotypic cross-mate correlation estimates are strongly associated with genetic correlation estimates (R2=74%). We demonstrate that existing xAM plausibly accounts for substantial fractions of genetic correlation estimates and that previously reported genetic correlation estimates between some pairs of psychiatric disorders are congruent with xAM alone. Finally, we provide evidence for a history of xAM at the genetic level using cross-trait even/odd chromosome polygenic score correlations. Together, our results demonstrate that previous reports have likely overestimated the true genetic similarity between many phenotypes.</p>
5 Keywords
- Cell Communication
- Genome-Wide Association Study
- Humans
- Multifactorial Inheritance
- Phenotype
12 Authors
- Richard Border
- Georgios Athanasiadis
- Alfonso Buil
- Andrew J Schork
- Na Cai
- Alexander I Young
- Thomas Werge
- Jonathan Flint
- Kenneth S Kendler
- Sriram Sankararaman
- Andy W Dahl
- Noah A Zaitlen
1 Application
| Application ID | Title |
|---|---|
| 33127 | Methods for large-scale medical and population genetic data |
Enabling scientific discoveries that improve human health