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Genetic epidemiology and Mendelian randomization for informing disease therapeutics: Conceptual and methodological challenges
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Abstract
The past decade has been proclaimed as a hugely successful era of gene discovery through the high yields of many genome-wide association studies (GWAS).However, much of the perceived benefit of such discoveries lies in the promise that the identification of genes that influence disease would directly translate into the identification of potential therapeutic targets, but this has yet to be realized at a level reflecting expectation.One reason for this, we suggest, is that GWAS, to date, have generally not focused on phenotypes that directly relate to the progression of disease and thus speak to disease treatment.A valuable proposed outcome of the GWAS era is the identification of novel therapeutic targets [1-4].As of 3 April 2017, the GWAS Catalog contained 2,854 publications and 33,674 unique SNP-trait associations [5].The large majority of these studies investigate genetic variation related to the presence (or occurrence) of disease.Such variants, though they may be informative for the prevention of disease, have unclear utility in informing disease treatment.If variants implicate etiological mechanisms of import for disease onset but sometimes of little relevance to disease progression, then the use of case/control GWAS as evidence to inform disease treatment-related drug discovery could be misleading.As an obvious example, consider GWAS of lung cancer.The lead variants identified in such GWAS tag a locus related to the heaviness of cigarette smoking [6], supporting the overwhelming evidence that smoking causes lung cancer.However, the cessation of smoking is hardly an efficacious treatment strategy after the onset of disease, although not smoking is a highly effective means of very substantially reducing the risk of developing lung cancer in the first place.Examples of factors causing both disease incidence and disease progression exist-for example, low-density lipoprotein (LDL) cholesterol levels clearly influence the risk of initial coronary events, and lowering LDL cholesterol reduces the risk of subsequent events.However, it is not necessarily the case that risk factors will influence both disease onset and disease progression-for example, a recent GWAS of Crohn disease observed independent genetic variants for the risk of onset and progression [7] and reported a negative genetic correlation (estimated through linkage disequilibrium [LD]
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Metadata
- Authors
- Paternoster, L., Tilling, K., & Davey Smith, G.
- Affiliations
- University of Bristol (GB)
- Corresponding author
- Paternoster, Lavinia
- Tilling, Kate
- Venue
- PLOS Genetics
- Publisher
- Public Library of Science (PLoS)
- Published
- 2017-10-05
- Volume
- 13
- Issue
- 10
- Pages
- e1006944
- ISSN
- 1553-7390 (ISSN-L)
- 1553-7404
- PMC
- PMC5628782
- OpenAlex
- W2951286101
- Cited by
- 271
- References
- 38
- Citations by year
- 2026: 10 · 2025: 16 · 2024: 37 · 2023: 37 · 2022: 38 · 2021: 47 · 2020: 36 · 2019: 23 · 2018: 21 · 2017: 6
- FWCI
- 3.08
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS Genetics (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Explore Bristol Research (submittedVersion, cc-by)
- Funders
- Medical Research Council (MC_UU_12013, MCUU12013/1)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Physical Performance
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
- Keywords
- drug target identification, disease progression, genetic epidemiology, Mendelian randomization, genome-wide association study, drug discovery, genetic correlation, Crohn's disease, LDL cholesterol, smoking and lung cancer
- MeSH terms
- Coronary Disease, Humans, Phenotype, Risk Factors, Disease Progression, Genetic Predisposition to Disease, Genetic Diseases, Inborn, Genome-Wide Association Study, Mendelian Randomization Analysis
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