ScienceGeneticsPeer-reviewed journal article
Cross-trait assortative mating is widespread and inflates genetic correlation estimates
Richard BorderiD, Georgios I. AthanasiadisiD, Alfonso BuiliD, Andrew Joseph SchorkiD, Na CaiiD, Alexander I. YoungiD, Thomas Mears WergeiD, Jonathan Flint CiD, Kenneth S. KendleriD, Sriram SankararamaniD, Andy W. DahliD, Noah ZaitleniD
Abstract
The observation of genetic correlations between disparate traits has been interpreted as evidence of widespread pleiotropy, altered theories of human genetic architecture, and spurred considerable research activity across the natural and social sciences. Here, we introduce cross-trait assortative mating (xAM) as an alternative explanation for observed genetic correlations. We observe that xAM is common across a broad array of phenotypes and that phenotypic cross-mate correlation estimates are strongly associated with genetic correlation estimates (R2 = 76%). Then, we present theoretical and simulation-based results demonstrating that, under xAM, genetic correlation estimators yield significant estimates even for traits with entirely distinct genetic bases. We demonstrate that existing xAM plausibly accounts for substantial fractions of genetic correlation estimates in two large samples (N = 827,960). For example, previously reported genetic correlation estimates between many pairs of psychiatric disorders are fully consistent with xAM alone. Finally, we provide evidence for a history of xAM at the genetic level using a novel approach based on 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.
- organism: human
- assay: GWAS summary statistics
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 144
- FWCI
- 17.81
- Field percentile
- top 1%
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