MR-PheWAS: Hypothesis prioritization among potential causal effects of body mass index on many outcomes, using Mendelian randomization
Louise A C Millard,Neil M Davies,Nicholas J. Timpson,Kate Tilling,Peter A. Flach,George Davey Smith +5 more
TLDR
This work demonstrates a novel extension to the phenome-wide association study approach, using automated screening with genotypic instruments to screen for causal associations amongst any number of phenotypic outcomes, and finds novel evidence of effects of BMI on a global self-worth score.Abstract:
Observational cohort studies can provide rich datasets with a diverse range of phenotypic variables. However, hypothesis-driven epidemiological analyses by definition only test particular hypotheses chosen by researchers. Furthermore, observational analyses may not provide robust evidence of causality, as they are susceptible to confounding, reverse causation and measurement error. Using body mass index (BMI) as an exemplar, we demonstrate a novel extension to the phenome-wide association study (pheWAS) approach, using automated screening with genotypic instruments to screen for causal associations amongst any number of phenotypic outcomes. We used a sample of 8,121 children from the ALSPAC dataset, and tested the linear association of a BMI-associated allele score with 172 phenotypic outcomes (with variable sample sizes). We also performed an instrumental variable analysis to estimate the causal effect of BMI on each phenotype. We found 21 of the 172 outcomes were associated with the allele score at an unadjusted p < 0.05 threshold, and use Bonferroni corrections, permutation testing and estimates of the false discovery rate to consider the strength of results given the number of tests performed. The most strongly associated outcomes included leptin, lipid profile, and blood pressure. We also found novel evidence of effects of BMI on a global self-worth score.read more
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The MR-Base platform supports systematic causal inference across the human phenome
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,David M. Evans,Caroline L Relton,Richard M. Martin,George Davey Smith,Tom R. Gaunt,Philip C Haycock +20 more
TL;DR: MR-Base is 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, and includes several sensitivity analyses for assessing the impact of horizontal pleiotropy and other violations of assumptions.
Journal ArticleDOI
Guidelines for performing Mendelian randomization investigations.
Stephen Burgess,George Davey Smith,Neil M Davies,Frank Dudbridge,Dipender Gill,M. Maria Glymour,Fernando Pires Hartwig,Fernando Pires Hartwig,Michael V. Holmes,Michael V. Holmes,Cosetta Minelli,Caroline L Relton,Evropi Theodoratou,Evropi Theodoratou +13 more
TL;DR: The guidelines are divided into nine sections: motivation and scope, data sources, choice of genetic variants, variant harmonization, primary analysis, supplementary and sensitivity analyses, data presentation, and interpretation.
Journal ArticleDOI
Recent Developments in Mendelian Randomization Studies
Jie Zheng,Denis Baird,Maria Carolina Borges,Jack Bowden,Gibran Hemani,Philip C Haycock,David M. Evans,David M. Evans,George Davey Smith +8 more
TL;DR: In conjunction with the growing availability of large-scale genomic databases, higher level of automation and increased robustness of the methods, MR promises to be a valuable strategy to examine causality in complex biological/omics networks, inform drug development and prioritize intervention targets for disease prevention in the future.
Journal ArticleDOI
Genetics of obesity: what genetic association studies have taught us about the biology of obesity and its complications
TL;DR: Gene by environment and lifestyle interaction analyses have revealed that the authors' increasingly obesogenic environment might be amplifying genetic risk for obesity, yet those at highest risk could mitigate this risk by increasing physical activity and possibly by avoiding specific dietary components.
Journal ArticleDOI
Mendelian Randomization as an Approach to Assess Causality Using Observational Data
TL;DR: Special issues in nephrology are discussed, such as inverse risk factor associations in advanced disease, and opportunities to design Mendelian randomization studies around kidney function and disease are outlined.
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Timothy M. Frayling,Nicholas J. Timpson,Michael N. Weedon,Eleftheria Zeggini,Eleftheria Zeggini,Eleftheria Zeggini,Rachel M. Freathy,Cecilia M. Lindgren,John R. B. Perry,Katherine S. Elliott,Katherine S. Elliott,Hana Lango,Nigel W. Rayner,Nigel W. Rayner,Nigel W. Rayner,Beverley M. Shields,Lorna W. Harries,Jeffrey C. Barrett,Jeffrey C. Barrett,Sian Ellard,Christopher J. Groves,Christopher J. Groves,Bridget A. Knight,Ann-Marie Patch,Andy R Ness,Shah Ebrahim,Debbie A Lawlor,Susan M. Ring,Yoav Ben-Shlomo,Marjo-Riitta Järvelin,Marjo-Riitta Järvelin,Ulla Sovio,Ulla Sovio,Amanda J. Bennett,Amanda J. Bennett,David Melzer,Luigi Ferrucci,Ruth J. F. Loos,Inês Barroso,Nicholas J. Wareham,Fredrik Karpe,Fredrik Karpe,Katharine R. Owen,Katharine R. Owen,Lon R. Cardon,Mark Walker,Graham A. Hitman,Graham A. Hitman,Colin N. A. Palmer,Colin N. A. Palmer,Alex S. F. Doney,Alex S. F. Doney,Andrew D. Morris,George Davey Smith,Andrew T. Hattersley,Mark I. McCarthy +55 more
TL;DR: A genome-wide search for type 2 diabetes–susceptibility genes identified a common variant in the FTO (fat mass and obesity associated) gene that predisposes to diabetes through an effect on body mass index (BMI).
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