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

Gibran Hemani(National Institute for Health and Care Research), Jie Zheng(National Institute for Health and Care Research), Benjamin Elsworth(National Institute for Health and Care Research), Kaitlin H. Wade(National Institute for Health and Care Research), Valeriia Haberland(National Institute for Health and Care Research), Denis Baird(National Institute for Health and Care Research), Charles Laurin(National Institute for Health and Care Research), Stephen Burgess(University of Cambridge), Jack Bowden(National Institute for Health and Care Research), Ryan Langdon(National Institute for Health and Care Research), Vanessa Y. Tan(National Institute for Health and Care Research), James Yarmolinsky(National Institute for Health and Care Research), Hashem A. Shihab(National Institute for Health and Care Research), Nicholas J. Timpson(National Institute for Health and Care Research), David M. Evans(Translational Research Institute), Caroline L. Relton(National Institute for Health and Care Research), Richard M. Martin(National Institute for Health and Care Research), George Davey Smith(Australian Research Council), Tom R. Gaunt(National Institute for Health and Care Research), Philip Haycock(National Institute for Health and Care Research)
eLife
May 30, 2018
Cited by 8,339Open Access
Full Text

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 (<ext-link ext-link-type="uri" xlink:href="http://www.mrbase.org">http://www.mrbase.org</ext-link>): 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.


Related Papers

No related papers found

Powered by citation graph analysis