Review

Genetic polymorphisms as predictive markers for statin therapy: a route to improved cardiovascular patient outcomes?

B. Kansu

Received:

19 Feb 2017

Accepted:

31 Jul 2017

Published:

11 Sept 2017

Volume:

10

Issue:

1

Keywords:

statins, cardiovascular, genetics, pharmacogenetics, pharmacogenomics, biomarkers

Abstract:

Cardiovascular disease (CVD) is a leading cause of morbidity and mortality worldwide. A significant risk factor for developing CVD is the presence of high plasma levels of low-density lipoprotein (LDL) cholesterol. With regard to pharmacological intervention, ‘fat busting’ statins are seen as the wonder drugs for lipid lowering and reducing the risk of myocardial infraction and stroke. However, there is wide inter-patient variability in measureable responses to these HMG-CoA reductase inhibitors, with individual patient genotypes being increasingly recognized as important contributors to this phenomenon. In recent years there have been great advances in our understanding of how personal genetics plays a role in controlling responses to drug therapies. Nevertheless, to date, there is no clinical application of identifying genetic markers that may predict responses to statins and subsequently modify cardiovascular outcomes. This review discusses the current literature regarding the potential roles of individual genetic polymorphisms in influencing responses to statins, and whether this can translate into clinical benefits for patients. While the significance of individual single nucleotide polymorphisms is yet to be established, it is suggested from genome-wide association studies that combinations of polymorphisms could be of greater clinical relevance. Further studies investigating the long-term influence of personal genetics on responses to statins and hard clinical outcomes are essential. As technology advances and the cost of genome sequencing falls, it will become increasingly easier to use individual genetic profiles to predict drug responses, tailor treatments and provide clinical benefit across populations.

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