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MR-Base: a platform for systematic causal inference across the phenome using billions of genetic associations

Gibran Hemani, Jie Zheng, Kaitlin H Wade, Charles Laurin, Benjamin Elsworth, Stephen Burgess, Jack Bowden, Ryan Langdon, Vanessa Tan, James Yarmolinsky, Hashem A. Shihab, Nicholas Timpson, David M Evans, Caroline Relton, Richard M Martin, George Davey Smith, Tom R Gaunt, Philip C Haycock
doi: https://doi.org/10.1101/078972
Gibran Hemani
1Medical Research Council (MRC) Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, United Kingdom
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Jie Zheng
1Medical Research Council (MRC) Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, United Kingdom
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Kaitlin H Wade
1Medical Research Council (MRC) Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, United Kingdom
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Charles Laurin
1Medical Research Council (MRC) Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, United Kingdom
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Benjamin Elsworth
1Medical Research Council (MRC) Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, United Kingdom
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Stephen Burgess
2Department of Public Health and Primary Care, University of Cambridge, United Kingdom
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Jack Bowden
1Medical Research Council (MRC) Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, United Kingdom
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Ryan Langdon
1Medical Research Council (MRC) Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, United Kingdom
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Vanessa Tan
1Medical Research Council (MRC) Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, United Kingdom
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James Yarmolinsky
1Medical Research Council (MRC) Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, United Kingdom
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Hashem A. Shihab
1Medical Research Council (MRC) Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, United Kingdom
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Nicholas Timpson
1Medical Research Council (MRC) Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, United Kingdom
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David M Evans
1Medical Research Council (MRC) Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, United Kingdom
3University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Queensland, Australia
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Caroline Relton
1Medical Research Council (MRC) Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, United Kingdom
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Richard M Martin
1Medical Research Council (MRC) Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, United Kingdom
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George Davey Smith
1Medical Research Council (MRC) Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, United Kingdom
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Tom R Gaunt
1Medical Research Council (MRC) Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, United Kingdom
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Philip C Haycock
1Medical Research Council (MRC) Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, United Kingdom
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Nicole Soranzo
4Human Genetics, Wellcome Trust Sanger Institute, Genome Campus, Hinxton Cambridge, United Kingdom
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David A van Heel
5Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
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Yukinori Okada
6Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan
7Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
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Clara S. Tang
8Department of Surgery, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong
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Merce Garcia-Barcelo
8Department of Surgery, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong
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Paul KH Tam
8Department of Surgery, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong
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Kaya Kvarme Jacobsen
9Department of Biomedicine and Center for Medical Genetics and Molecular Medicine, University of Bergen and Haukeland University Hospital
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Gregory T Jones
10Surgery Department, University of Otago, Dunedin, New Zealand
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Matthew J Bown
11The Department of Cardiovascular Sciences and the NIHR Leicester Cardiovascular Biomedical Research Unit, University of Leicester, Leicester, United Kingdom
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Omar Albagha
12Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
13Qatar Biomedical Research Institute, Hamad Bin Khalifa University, Doha, Qatar
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Stuart H. Ralston
14Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
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Andre Franke
15Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
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Annegret Fischer
16Institute of Clinical Molecular Biology, Kiel University and University Hospital Schleswig-Holstein, Kiel, Germany
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David Ellinghaus
15Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
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Asta Försti
17Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
18Center for Primary Health Care Research, Clinical Research Center, Lund University, Malmö, Sweden
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Hauke Thomsen
17Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
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Stefano Landi
19Department of Biology, University of Pisa, Pisa, Italy
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Heather Cordell
20Institute of Genetic Medicine, Newcastle University, International Centre for Life, Central Parkway, Newcastle upon Tyne, United Kingdom
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Ani W Manichaikul
21Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA USA
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R Graham Barr
22Department of Medicine and Department of Epidemiology, Columbia University Medical Center, New York, NY 10032, USA
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Jeffrey E Lee
23Department of Surgical Oncology, The University of Texas, MD Anderson Cancer Center, Houston, Texas
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  • Abstract
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Abstract

Published genetic associations can be used to infer causal relationships between phenotypes, bypassing the need for individual-level genotype or phenotype data. We have curated complete summary data from 1094 genome-wide association studies (GWAS) on diseases and other complex traits into a centralised database, and developed an analytical platform that uses these data to perform Mendelian randomization (MR) tests and sensitivity analyses (MR-Base, http://www.mrbase.org). Combined with curated data of published GWAS hits for phenomic measures, the MR-Base platform enables millions of potential causal relationships to be evaluated. We use the platform to predict the impact of lipid lowering on human health. While our analysis provides evidence that reducing LDL-cholesterol, lipoprotein(a) or triglyceride levels reduce coronary disease risk, it also suggests causal effects on a number of other non-vascular outcomes, indicating potential for adverse-effects or drug repositioning of lipid-lowering therapies.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted December 16, 2016.
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MR-Base: a platform for systematic causal inference across the phenome using billions of genetic associations
Gibran Hemani, Jie Zheng, Kaitlin H Wade, Charles Laurin, Benjamin Elsworth, Stephen Burgess, Jack Bowden, Ryan Langdon, Vanessa Tan, James Yarmolinsky, Hashem A. Shihab, Nicholas Timpson, David M Evans, Caroline Relton, Richard M Martin, George Davey Smith, Tom R Gaunt, Philip C Haycock
bioRxiv 078972; doi: https://doi.org/10.1101/078972
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MR-Base: a platform for systematic causal inference across the phenome using billions of genetic associations
Gibran Hemani, Jie Zheng, Kaitlin H Wade, Charles Laurin, Benjamin Elsworth, Stephen Burgess, Jack Bowden, Ryan Langdon, Vanessa Tan, James Yarmolinsky, Hashem A. Shihab, Nicholas Timpson, David M Evans, Caroline Relton, Richard M Martin, George Davey Smith, Tom R Gaunt, Philip C Haycock
bioRxiv 078972; doi: https://doi.org/10.1101/078972

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