La génétique humaine pour l'étude de cibles pharmacologiques

Using population-level data, it is possible to identify genetic polymorphisms that confer natural protection against disease. If the molecular mechanism underlying this protection can be understood, for example by linking variants to the disruption of a particular protein, it may be possible to develop drugs that act on the same biological target. This link between drugs and variants is a central premise of genetic drug target validation.  In this work, a genetic model is used to predict the beneficial and adverse effects of ivabradine, a drug used to lower heart rate. Ivabradine is an inhibitor of the ion channel potassium/sodium hyperpolarization-activated cyclic nucleotide-gated channel 4, encoded by the HCN4 gene, with heterogeneous benefits in different patient populations. This drug is effective in the treatment of angina and heart failure but it is ineffective in patients with stable coronary artery disease without systolic dysfunction. Characterization of the effect of ivabradine has occurred over a 6-year period and three large phase III trials have been conducted. We will investigate whether this process could have been streamlined using genetic models and contrast the ivabradine-specific effect with the general effect of heart rate reduction using a Mendelian Randomization approach.  Second, a genetic approach is used to study the effect of inhibiting cholesteryl ester tranfer protein (CETP), an enzyme responsible for the transfer of cholestery esters and triglycerides between different lipoproteins and a widely studied drug target for the treatment of coronary artery disease. Genetic studies predict a benefit of CETP inhibition, but randomized trials yielded heterogeneous and disappointing results. We will use a genetic model of CETP inhibition to identify variables that may modulate the effect of CETP inhibition on biomarkers and ischemic disease. The biomarkers we considered included low- and high-density lipoprotein cholesterol levels but also the plasma cholesterol efflux capacity, an important and understudied functional measure of high density lipoproteins. Sex and body mass index strongly modulated the effect of a genetically predicted lower CETP concentration on the lipid profile. Our model predicts a greater benefit of CETP inhibition in women and individuals with normal body mass index on the lipid profile, but these observations did not translate to changes in the effect on cardiovascular outcomes. This study remains methodologically important because it demonstrates the possibility of using genetic models of drug targets to predict heterogeneity in drug response, a shortcoming of conventional randomized trials.  Finally, we adopted a gene-centric approach to characterize the effect of 19,114 human protein-coding genes on 1,210 UK Biobank phenotypes. The results of this study are publicly available (https://exphewas.statgen.org/) and provide a valuable resource to rapidly screen the phenotypic consequences associated with a gene. In the context of drug target validation, this platform can help quickly identify potential safety issues or discover drug repurposing opportunities. An example of the use of this platform is presented where we identify the myotilin gene as a potential atrial fibrillation gene.

Keyphrases: PheWAS, Ivabradine, CETP, Drug target, Mendelian randomization, Atrial fibrillation, Human genetics, Coronary artery disease