Genomics-driven molecular refinement of the polygenic risk score of coronary heart disease

University of Geneva

Lay summary

Coronary heart disease is a world's number one killer that presents great societal challenges due to the reduction of healthy life years and work productivity. While the attention gained for attaining a healthy lifestyle and the use of preventative therapies have contributed to a decline of mortality rates of the disease, current prevention and risk prediction strategies have not yielded meaningful reduction of its prevalence nor decreased the adverse burden of non-fatal disease manifestations.

This stems mainly from the fact that the current clinically applied risk prediction strategy that relies on the assessment of phenotypic risk factors (e.g., cholesterol and blood pressure levels, smoking duration, concomitant diseases) inherently reflects the measurement of already perturbed molecular pathways. Incorporation of genetic information into risk estimation as means of calculating a polygenic risk score by summing up disease-predisposing genetic variants has been proposed to be circumvent the current limitation. As genetic information does not change over the course of a lifetime, this approach could improve risk assessment far before clinically measured risk factors attain predictive ability. Despite its promising potential, its clinical benefit, as of now, is undermined by lack of understanding the mechanistic context of the disease-associated genetic markers, thereby undermining the personalisation of clinical management and targeted therapy.

Extensive research has revealed that the majority of the disease-associated genetic variants have a regulatory effect on gene expression. Resources that have aimed to determine the links between genetic variants and gene expression levels across different human tissues provide valuable resources for mechanistic interpretation of gene regulation and the genetic basis of disease. Exploitation of these resources allows to determine the mechanistic effect of the variants considered in the polygenic risk score and identify molecular-specific pathways driving the disease onset and progression.

The mechanistic investigation of the genetic variants considered in the polygenic risk score allows to identify the disease trajectories on an individual level and by that facilitate biologically meaningful personalisation of clinical management and tailored therapy. Using large-scale cohort data from the Estonian Biobank and UK Biobank as well as experimentally derived resources of molecular effects of genetic variants on gene expression levels will help in guiding biologically driven improvements that have the potential to transform current clinical management of the disease.