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

Nat Genet
Authors
Keywords
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 αα), 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.

Year of Publication
2018
Journal
Nat Genet
Volume
50
Issue
12
Pages
1728-1734
Date Published
2018 Dec
ISSN
1546-1718
DOI
10.1038/s41588-018-0255-0
PubMed ID
30374074
PubMed Central ID
PMC6684375
Links
Grant list
U01 CA194393 / CA / NCI NIH HHS / United States
U01 CA194393 / NH / NIH HHS / United States
R01 MH101244 / NH / NIH HHS / United States
T32 HG002295 / HG / NHGRI NIH HHS / United States
R01 MH107649 / MH / NIMH NIH HHS / United States
R01 MH101244 / MH / NIMH NIH HHS / United States