@article{d49e3fed4dab4a6692ccdad720ab7ee7,
title = "Genetic drug target validation using Mendelian randomisation",
abstract = "Mendelian randomisation (MR) analysis is an important tool to elucidate the causal relevance of environmental and biological risk factors for disease. However, causal inference is undermined if genetic variants used to instrument a risk factor also influence alternative disease-pathways (horizontal pleiotropy). Here we report how the 'no horizontal pleiotropy assumption' is strengthened when proteins are the risk factors of interest. Proteins are typically the proximal effectors of biological processes encoded in the genome. Moreover, proteins are the targets of most medicines, so MR studies of drug targets are becoming a fundamental tool in drug development. To enable such studies, we introduce a mathematical framework that contrasts MR analysis of proteins with that of risk factors located more distally in the causal chain from gene to disease. We illustrate key model decisions and introduce an analytical framework for maximising power and evaluating the robustness of analyses.",
keywords = "Confidence Intervals, Coronary Disease/genetics, Drug Delivery Systems, Genes, Genome, Human, Humans, Linkage Disequilibrium/genetics, Lipids/chemistry, Mendelian Randomization Analysis, Models, Genetic, Odds Ratio, Phenomics, Polymorphism, Single Nucleotide/genetics, Proteins/genetics, Quantitative Trait Loci/genetics, Reproducibility of Results",
author = "Schmidt, {Amand F} and Chris Finan and Maria Gordillo-Mara{\~n}{\'o}n and Asselbergs, {Folkert W} and Freitag, {Daniel F} and Patel, {Riyaz S} and Beno{\^i}t Tyl and Sandesh Chopade and Rupert Faraway and Magdalena Zwierzyna and Hingorani, {Aroon D}",
note = "Funding Information: AFS is supported by BHF grant PG/18/5033837 and the UCL BHF Research Accelerator AA/18/6/34223. CF and AFS received additional support from the National Institute for Health Research University College London Hospitals Biomedical Research Centre. MGM is supported by a BHF Fellowship FS/17/70/33482. RF is supported by UK Medical Research Council (FC001002, MR/N013867/1). MZ contributed to this work as part of her PhD, which was funded by BenevolentAI, where she was an employee. ADH is an NIHR Senior Investigator. We further acknowledge support from the Rosetrees and Stoneygate Trusts. FWA is supported by UCL Hospitals NIHR Biomedical Research Centre. RSP is supported by a BHF Fellowship FS/14/76/30933. This work has received support from the EU/EFPIA Innovative Medicines Initiative [2] Joint Undertaking BigData@Heart grant n° 116074. This research has been conducted using the UK Bio-bank Resource under Application Number 12113. The authors are grateful to UK Bio-bank participants. UK Biobank was established by the Wellcome Trust medical charity, Medical Research Council, Department of Health, Scottish Government, and the Northwest Regional Development Agency. Publisher Copyright: {\textcopyright} 2020, The Author(s). Copyright: Copyright 2020 Elsevier B.V., All rights reserved.",
year = "2020",
month = jun,
day = "26",
doi = "10.1038/s41467-020-16969-0",
language = "English",
volume = "11",
pages = "1--12",
journal = "Nature Communications",
issn = "2041-1723",
publisher = "Nature Publishing Group",
number = "1",
}