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

Gibran Hemani, Jie Zheng, Benjamin Elsworth, Kaitlin Wade, Valeriia Haberland, Denis Baird, Charles Laurin, Stephen Burgess, Jack Bowden, Ryan Langdon, Vanessa Tan, James Yarmolinsky, Hashem Shihab, Nicholas Timpson, David Evans, Caroline Relton, Richard Martin, George Davey Smith, Tom Gaunt, Philip Haycock

Research output: Contribution to journalArticle (Academic Journal)peer-review

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Summary data from genome-wide association studies (GWAS) can be used to infer causal relationships between phenotypes, using an analytical strategy known as 2-sample Mendelian randomization (2SMR), bypassing the need for individual-level data. However, 2SMR methods are evolving rapidly and can be difficult to implement, while GWAS summary data required for 2SMR are often not systematically curated, undermining efficient implementation of the approach. To address these challenges, we developed MR-Base ( a platform that integrates a curated database of GWAS summary data for thousands of traits obtained from UK Biobank and trait-specific GWAS studies, with R packages and a web app that automates several analytical strategies for causal inference through 2SMR. The software includes many sensitivity analyses for assessing analytical assumptions. The database curates 24 billion SNP-trait associations from 1693 GWAS studies. Integrating data with software ensures more rigorous application of hypothesis-driven analyses, whilst enabling millions of potential causal relationships to be systematically and efficiently evaluated in phenome-wide association studies (PheWAS).
Original languageEnglish
Article numbere34408
Number of pages29
Publication statusPublished - 30 May 2018

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