Unknown

Dataset Information

0

Distinguishing genetic correlation from causation across 52 diseases and complex traits.


ABSTRACT: Mendelian randomization, a method to infer causal relationships, is confounded by genetic correlations reflecting shared etiology. We developed a model in which a latent causal variable mediates the genetic correlation; trait 1 is partially genetically causal for trait 2 if it is strongly genetically correlated with the latent causal variable, quantified using the genetic causality proportion. We fit this model using mixed fourth moments [Formula: see text] and [Formula: see text] of marginal effect sizes for each trait; if trait 1 is causal for trait 2, then SNPs affecting trait 1 (large [Formula: see text]) will have correlated effects on trait 2 (large ?1?2), but not vice versa. In simulations, our method avoided false positives due to genetic correlations, unlike Mendelian randomization. Across 52 traits (average n?=?331,000), we identified 30 causal relationships with high genetic causality proportion estimates. Novel findings included a causal effect of low-density lipoprotein on bone mineral density, consistent with clinical trials of statins in osteoporosis.

SUBMITTER: O'Connor LJ 

PROVIDER: S-EPMC6684375 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

altmetric image

Publications

Distinguishing genetic correlation from causation across 52 diseases and complex traits.

O'Connor Luke J LJ   Price Alkes L AL  

Nature genetics 20181029 12


Mendelian randomization, a method to infer causal relationships, is confounded by genetic correlations reflecting shared etiology. We developed a model in which a latent causal variable mediates the genetic correlation; trait 1 is partially genetically causal for trait 2 if it is strongly genetically correlated with the latent causal variable, quantified using the genetic causality proportion. We fit this model using mixed fourth moments [Formula: see text] and [Formula: see text] of marginal ef  ...[more]

Similar Datasets

| S-EPMC3809096 | biostudies-literature
| S-EPMC7217279 | biostudies-literature
| S-EPMC5673668 | biostudies-literature
| S-EPMC8220172 | biostudies-literature
| S-EPMC8422619 | biostudies-literature
| S-EPMC11256968 | biostudies-literature
| S-EPMC6547727 | biostudies-literature
| S-EPMC8425307 | biostudies-literature
| S-EPMC5368911 | biostudies-literature
| S-EPMC5880536 | biostudies-other