Literature DB >> 25515070

Mendelian randomisation applied to drug development in cardiovascular disease: a review.

Lauren E Mokry1, Omar Ahmad2, Vincenzo Forgetta3, George Thanassoulis4, J Brent Richards5.   

Abstract

Despite increased expenditure, productivity of the pharmaceutical industry has decreased and currently 90% of developed molecules entering phase II and phase III clinical trials fail to gain regulatory approval. Most of these failures are due to lack of therapeutic efficacy rather than lack of safety, suggesting that drug development failures may often be due to poor drug target validation. Currently, drug targets are largely validated using in vitro assays and animal models which may not translate well to human disease. Emerging methods from human genetics, such as Mendelian randomisation (MR), can enable the validation of putative biomarker drug targets in humans prior to the initiation of clinical trials. MR studies can provide evidence as to whether genetically determined levels of a biomarker influence disease aetiology, enabling investigators to infer whether the biomarker is causal. We review the extent to which MR techniques may be helpful in biomarker validation by assessing the concordance between the results from MR studies and phase III clinical trials for lipid therapy in cardiovascular disease. Our findings show that concordance is highest when MR provides evidence suggesting that a biomarker is not causal. In contrast, there are many examples of clinical trials that still failed despite targeting confirmed causal biomarkers. We discuss why such trials may not succeed, despite evidence for causality in MR studies, and outline important limitations when using MR for biomarker validation in drug development. Nonetheless, given the current inefficiencies in drug development, MR methods have potential to improve the success rate of drug development and ultimately the delivery of new molecules to clinical care. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Entities:  

Keywords:  Cardiovascular disease; Drug development; Genetic epidemiology; Mendelian randomization

Mesh:

Year:  2014        PMID: 25515070     DOI: 10.1136/jmedgenet-2014-102438

Source DB:  PubMed          Journal:  J Med Genet        ISSN: 0022-2593            Impact factor:   6.318


  19 in total

Review 1.  Mendelian Randomization as an Approach to Assess Causality Using Observational Data.

Authors:  Peggy Sekula; Fabiola Del Greco M; Cristian Pattaro; Anna Köttgen
Journal:  J Am Soc Nephrol       Date:  2016-08-02       Impact factor: 10.121

2.  Genome-wide DNA methylation study identifies genes associated with the cardiovascular biomarker GDF-15.

Authors:  Weronica E Ek; Åsa K Hedman; Stefan Enroth; Andrew P Morris; Cecilia M Lindgren; Anubha Mahajan; Stefan Gustafsson; Ulf Gyllensten; Lars Lind; Åsa Johansson
Journal:  Hum Mol Genet       Date:  2015-12-17       Impact factor: 6.150

Review 3.  Transformational Applications of Human Cardiac Organoids in Cardiovascular Diseases.

Authors:  Wanling Xuan; Srinivas M Tipparaju; Muhammad Ashraf
Journal:  Front Cell Dev Biol       Date:  2022-06-09

Review 4.  IMI - Myopia Genetics Report.

Authors:  Milly S Tedja; Annechien E G Haarman; Magda A Meester-Smoor; Jaakko Kaprio; David A Mackey; Jeremy A Guggenheim; Christopher J Hammond; Virginie J M Verhoeven; Caroline C W Klaver
Journal:  Invest Ophthalmol Vis Sci       Date:  2019-02-28       Impact factor: 4.799

Review 5.  Causal Inference in Cancer Epidemiology: What Is the Role of Mendelian Randomization?

Authors:  James Yarmolinsky; Kaitlin H Wade; Rebecca C Richmond; Ryan J Langdon; Caroline J Bull; Kate M Tilling; Caroline L Relton; Sarah J Lewis; George Davey Smith; Richard M Martin
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2018-06-25       Impact factor: 4.254

6.  A Mendelian randomization study of the effect of type-2 diabetes on coronary heart disease.

Authors:  Omar S Ahmad; John A Morris; Muhammad Mujammami; Vincenzo Forgetta; Aaron Leong; Rui Li; Maxime Turgeon; Celia M T Greenwood; George Thanassoulis; James B Meigs; Robert Sladek; J Brent Richards
Journal:  Nat Commun       Date:  2015-05-28       Impact factor: 14.919

7.  A pooling-based approach to mapping genetic variants associated with DNA methylation.

Authors:  Irene M Kaplow; Julia L MacIsaac; Sarah M Mah; Lisa M McEwen; Michael S Kobor; Hunter B Fraser
Journal:  Genome Res       Date:  2015-04-24       Impact factor: 9.043

8.  Vitamin D and Risk of Multiple Sclerosis: A Mendelian Randomization Study.

Authors:  Lauren E Mokry; Stephanie Ross; Omar S Ahmad; Vincenzo Forgetta; George Davey Smith; David Goltzman; Aaron Leong; Celia M T Greenwood; George Thanassoulis; J Brent Richards
Journal:  PLoS Med       Date:  2015-08-25       Impact factor: 11.069

9.  A Mendelian Randomization Study of Plasma Homocysteine and Multiple Myeloma.

Authors:  Yang Xuan; Xiao-Hong Li; Zhong-Qian Hu; Zhi-Mei Teng; Dao-Jun Hu
Journal:  Sci Rep       Date:  2016-04-29       Impact factor: 4.379

Review 10.  Genetic epidemiology and Mendelian randomization for informing disease therapeutics: Conceptual and methodological challenges.

Authors:  Lavinia Paternoster; Kate Tilling; George Davey Smith
Journal:  PLoS Genet       Date:  2017-10-05       Impact factor: 5.917

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