Validation of therapeutic targets in cardiometabolic disease using Mendelian randomisation.
Doctoral thesis, UCL (University College London).
Complex diseases such as coronary heart disease (CHD) are a major and growing burden on public and individual health worldwide. As an increasing number of risk factors for CHD are identified, more questions arise over the pathogenesis of the disease, and potential new therapeutic and preventive strategies. Mendelian randomisation (MR) offers a means of addressing these questions, using common genetic variants as proxies for a putative risk factor. By exploiting the innate properties of the genotype of an individual, MR overcomes many limitations of traditional observational epidemiology. The lifelong and largely immutable influence of genetic variation on pathogenic mechanisms and risk of disease avoid confounding and reverse causation, and allow robust causal inference in the context of observational population studies. The validity of such a MR experiment is dependent on the choice of genetic instrument and considerations of specificity and phenotypic effect size are important in selecting the most appropriate instrument for different applications of MR. The considerations involved in optimising the selection of genetic instruments for MR were explored in the context of CHD. Using variants in a gene encoding a protein that may be a target for pharmacological intervention, the MR paradigm can be applied to the validation of potential therapeutic targets. The practical considerations, limitations, and utility of this approach were demonstrated in a proof-of-principle study of the widely prescribed and well characterised 3-hydroxy-3-methylglutaryl-CoA (HMG-CoA) reductase inhibitors (statins) and variants in the gene encoding their target (HMGCR). Associations of variants in HMGCR in a large collaborative sample of population studies were compared to the effects of statin treatment reported in randomised trials in order to investigate the strengths and limitations of the MR approach to drug target validation. Moreover, this investigation allowed the mechanism-based actions of statin therapy to be distinguished from those likely to be off-target. A causal role for inflammatory pathways is suggested in atherosclerosis, and higher circulating concentrations of inflammatory markers such as interleukin-6 (IL-6) are strongly associated in observational studies with higher risk of CHD. Two other inflammatory markers, C-reactive protein (CRP) and fibrinogen, have been shown using MR methods to be unlikely to play a causal role in atherogenesis, but interest in the role of IL-6 and potential for modulation of its actions as a preventive strategy in CHD remains. A iii monoclonal antibody, tocilizumab, licensed for the treatment of rheumatoid arthritis (RA), specifically inhibits the IL-6 receptor (IL-6R). In a large, collaborative general population sample, associations of common variants in the gene encoding the IL-6R (IL6R) with a range of biomarkers relevant to cardiovascular disease (CVD), and with risk of CVD events, were estimated. These estimates were compared with the effects of tocilizumab therapy on similar biomarkers in order to validate the IL-6R as a potential therapeutic target in CHD. Evidence from this large-scale genetic analysis and existing clinical trials of tocilizumab suggest inhibition of IL-6 signalling may be a valuable new therapeutic strategy for prevention of CHD. The work presented here makes a case for the wider use of the MR principle for improving efficiency in drug discovery. By exploiting findings from genome-wide association (GWA) studies, MR may be used to validated and prioritise drug targets earlier in development, and help to reduce rates of late-stage failure.
|Title:||Validation of therapeutic targets in cardiometabolic disease using Mendelian randomisation|
|Additional information:||Authorisation for digitisation not received|
|UCL classification:||UCL > School of Life and Medical Sciences
UCL > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science
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