The MR-Base platform supports systematic causal inference across the human phenome

TLDR

Results from GWAS can be used to infer causal relationships between phenotypes via 2‑sample Mendelian randomization, but rapidly evolving methods and insufficiently curated GWAS data hinder efficient implementation. We therefore developed MR‑Base, a platform that integrates a curated database of complete GWAS results with an API, web app, and R packages to automate 2SMR. The software includes several sensitivity analyses for assessing horizontal pleiotropy and other assumption violations. The database contains 11 billion SNP‑trait associations from 1,673 GWAS and is regularly updated; integrating data with software enables rigorous hypothesis‑driven analyses and allows millions of potential causal relationships to be efficiently evaluated in phenome‑wide association studies.

Abstract

Results from genome-wide association studies (GWAS) can be used to infer causal relationships between phenotypes, using a strategy known as 2-sample Mendelian randomization (2SMR) and bypassing the need for individual-level data. However, 2SMR methods are evolving rapidly and GWAS results are often insufficiently curated, undermining efficient implementation of the approach. We therefore developed MR-Base ( http://www.mrbase.org ): a platform that integrates a curated database of complete GWAS results (no restrictions according to statistical significance) with an application programming interface, web app and R packages that automate 2SMR. The software includes several sensitivity analyses for assessing the impact of horizontal pleiotropy and other violations of assumptions. The database currently comprises 11 billion single nucleotide polymorphism-trait associations from 1673 GWAS and is updated on a regular basis. Integrating data with software ensures more rigorous application of hypothesis-driven analyses and allows millions of potential causal relationships to be efficiently evaluated in phenome-wide association studies.