Testing and controlling for horizontal pleiotropy with probabilistic Mendelian randomization in transcriptome-wide association studies

Nat Commun. 2020 Jul 31;11(1):3861. doi: 10.1038/s41467-020-17668-6.


Integrating results from genome-wide association studies (GWASs) and gene expression studies through transcriptome-wide association study (TWAS) has the potential to shed light on the causal molecular mechanisms underlying disease etiology. Here, we present a probabilistic Mendelian randomization (MR) method, PMR-Egger, for TWAS applications. PMR-Egger relies on a MR likelihood framework that unifies many existing TWAS and MR methods, accommodates multiple correlated instruments, tests the causal effect of gene on trait in the presence of horizontal pleiotropy, and is scalable to hundreds of thousands of individuals. In simulations, PMR-Egger provides calibrated type I error control for causal effect testing in the presence of horizontal pleiotropic effects, is reasonably robust under various types of model misspecifications, is more powerful than existing TWAS/MR approaches, and can directly test for horizontal pleiotropy. We illustrate the benefits of PMR-Egger in applications to 39 diseases and complex traits obtained from three GWASs including the UK Biobank.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Cardiovascular Diseases / diagnosis
  • Cardiovascular Diseases / genetics
  • Cardiovascular Diseases / pathology
  • Computer Simulation
  • Databases, Factual
  • Gastrointestinal Diseases / diagnosis
  • Gastrointestinal Diseases / genetics
  • Gastrointestinal Diseases / pathology
  • Genetic Pleiotropy*
  • Genetic Predisposition to Disease*
  • Genome-Wide Association Study / statistics & numerical data*
  • Humans
  • Immune System Diseases / diagnosis
  • Immune System Diseases / genetics
  • Immune System Diseases / pathology
  • Likelihood Functions
  • Mendelian Randomization Analysis / statistics & numerical data*
  • Metabolic Diseases / diagnosis
  • Metabolic Diseases / genetics
  • Metabolic Diseases / pathology
  • Models, Genetic*
  • Multifactorial Inheritance
  • Neoplasms / diagnosis
  • Neoplasms / genetics
  • Neoplasms / pathology
  • Neurodegenerative Diseases / diagnosis
  • Neurodegenerative Diseases / genetics
  • Neurodegenerative Diseases / pathology
  • Transcriptome*