Genetic drug target validation using Mendelian randomisation
Heidelberg University · University Hospital Heidelberg · +8 more institutions
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…
Citation impact
- FWCI
- 32.07
- Percentile
- 100%
- References
- 83
Authors
11- AFAmand F. SchmidtCorresponding
Heidelberg University, University Hospital Heidelberg, University Medical Center Utrecht, UCL Biomedical Research Centre, University College London
- CFChris Finan
UCL Biomedical Research Centre, University College London
- MGMaría Gordillo‐Marañón
University College London
- FWFolkert W. Asselbergs
Heidelberg University, University Hospital Heidelberg, University Medical Center Utrecht, Health Data Research UK, University College London
- DFDaniel F. Freitag
Bayer (Germany)
Topics & keywords
- Mendelian randomization
- Pleiotropy
- Computational biology
- Inference
- Robustness (evolution)
- Mendelian inheritance
- Disease
- Computer science
Funding
- WTWellcome TrustAwards: FC001002, MR/N013867/1
- EFEuropean Federation of Pharmaceutical Industries and AssociationsAward: 116074
- NINational Institute for Health and Care Research
- BHBritish Heart FoundationAwards: FS/17/70/33482, AA/18/6/34223, FS/14/76/30933, Accelerator AA/18/6/34223, PG/18/5033837
- UCUniversity College London
- RTRosetrees Trust
- NRNorthwest Regional Development Agency
- MRMedical Research CouncilAwards: MR/N013867/1, FC001002