The role of common genetic variants for predicting the modulation of cardiovascular outcomes

Abstract

Attrition is a major issue in the drug development process with 79% of clinical failures due to safety and efficacy concerns. Genetic research can provide supporting evidence of a clear causal relationship between the drug target and disease or reveal unintended effects through associations with non-relevant phenotypes informing on potential drug safety. However, due to the underlying genetic architecture, it is often unclear which gene or variant in the loci identified through genetic analyses is driving the association. Due to recent advancements in CRISPR-Cas9 gene-editing, it is now possible to relatively easily perform whole gene knock-out studies and single base-edits to validate genetic findings of the most likely causal variant and gene. Utilising a combination of genetic approaches and functional studies can provide supporting evidence of the therapeutic profile and potential effects of drug therapies and improve our overall understanding of biological pathways and disease mechanisms.

The primary aim of this thesis is to provide genetic data to support the ongoing clinical development of hypoxia-inducible factor (HIF)-prolyl hydroxylase inhibitors (PHIs) for treating anaemia of chronic kidney disease (CKD). Genome-wide association studies (GWAS) were used to identify genetic variants lying within or nearby genes encoding the drug target (prolyl hydroxylase [PHD] enzymes). These identified variants were used in Mendelian Randomisation analysis and phenome-wide association studies to genetically mirror the pharmaceutical effects of PHIs and investigate cardiovascular safety. Functional validation studies were employed to functionally validate a genetic variant for use as a proxy and to obtain a better understanding of the downstream causal pathways and biological mechanisms of the drug target.

In summary, this thesis demonstrates how a combination of genetic analyses and functional validation studies is a powerful approach to validate GWAS results and further characterise therapeutic effects. This PhD project identified relevant genetic markers to genetically proxy therapeutic modulation of biomarker levels through PHD inhibition and could potentially inform further research using patient-level clinical data from Phase III trials.