The MR-Base Platform Supports Systematic Causal Inference Across the Human Phenome

Overview

Journal Elife

Specialty Biology

Date 2018 May 31

PMID 29846171

Citations 3120

Authors

Gibran Hemani

Jie Zheng

Benjamin Elsworth

Kaitlin H Wade

Valeriia Haberland

Denis Baird

Charles Laurin

Stephen Burgess

Jack Bowden

Ryan Langdon

Vanessa Y Tan

James Yarmolinsky

Hashem A Shihab

Nicholas J Timpson

David M Evans

Caroline Relton

Richard M Martin

George Davey Smith

Tom R Gaunt

Philip C Haycock

Affiliations

Soon will be listed here.

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.

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