“Distinguishing Genetic Correlation from Causation across 52 Diseases and Complex Traits”, 2018-10-29 (; backlinks; similar):
Mendelian Randomization (MR), a method to infer causal relationships, is confounded by genetic correlations reflecting shared etiology.
We developed a model in which a latent causal variable (LCV) mediates the genetic correlation; trait 1 is partially genetically causal for trait 2 if it is strongly genetically correlated with the LCV, quantified using the genetic causality proportion (gcp).
We fit this model using mixed fourth moments E(α12α1α2) and E(α22α1α2) of marginal effect sizes for each trait; if trait 1 is causal for trait 2, then SNPs affecting trait 1 (large α12) will have correlated effects on trait 2 (large α1α2), but not vice versa. In simulations, our method avoided false positives due to genetic correlations, unlike MR.
Across 52 traits (average n = 331k), we identified 30 causal relationships with high gcp estimates. Novel findings included a causal effect of LDL on bone mineral density, consistent with clinical trials of statins in osteoporosis.