Researchers at the University of Dundee have found that genetic factors can predict the risk of unwanted side-effects of statins, allowing doctors to take a personalised prescribing approach to improve patient outcomes.
Statins are a commonly used medication for heart disease, but many individuals experience side-effects such as muscle pain. This often leads to individuals opting to discontinue the drug, significantly increasing their chance of heart disease. By identifying individuals with a higher likelihood of developing side effects, the choice of statin medications and dosage can be tailored to potentially improve treatment outcomes.
At present, testing for genetic factors that predict statin intolerance in the clinical setting is limited. This is partly because the existing genetic test does not fully predict who will develop intolerance to statins or how soon.
The new research improves on current genetic testing by developing a gene-risk score for the protein that transports statins in the body. This approach allowed researchers to develop a more robust tool for assessing an individual's risk of experiencing muscle symptoms.
By minimising the occurrence of uncomfortable muscle symptoms, it is hoped patient adherence will increase and, in turn, help prevent heart problems.
Dr Margherita Bigossi, a PhD student affiliated with Dundee’s School of Medicine and the Catholic University of the Sacred Heart in Rome, explained, “In our research, we considered genetic variants to identify individuals who are at a higher risk of developing side effects.
“Moreover, we found that people with this genetic risk were likely to experience muscle symptoms earlier than those without the genetic risk, particularly on higher doses of statin treatment.
“While previous studies focused mainly on a well-known genetic variant or factor, we aimed to investigate the potential effects of other variants in the same gene that had not been as extensively studied. We investigated how combining all these genetic variants into a single genetic test would yield a more effective tool compared to relying on a single variant.
“The long-term significance of this research lies in the potential to improve patient outcomes and increase adherence to statin therapy. Ultimately, this can lead to better management of cholesterol levels, lower rates of cardiovascular events, and improved overall patient well-being.”
Dr Moneeza Siddiqui, who led the research, added, “Our goal was to build on and compare to the existing standard of genetic testing. This increases the likelihood of the test being used clinically and that individuals who are starting therapy or require higher doses of the medication might benefit sooner.
“This study is unique in investigating the long-term risk of side-effects to statins and how genetics can predict how soon after commencing statin therapy a person can start to develop intolerance to the medication.”
Statins work by blocking an enzyme in the liver that produces cholesterol, preventing its accumulation in arteries. To be effective, statins need to be transported from the bloodstream into the liver, and this is where a specific protein called OATP1B1 comes into play.
Our genetic makeup can influence how well proteins, including OATP1B1, function. Certain genetic variations or factors in the gene that produces this protein can affect its activity, leading to differences in the concentration of statins in the bloodstream. These differences can impact the likelihood of experiencing muscle symptoms, such as pain or cramps.
Genetic testing needs to be more widely implemented in primary care settings for it to routinely inform tailored patient care. Further clinical studies are also needed to confirm the efficacy of the gene-risk score across diverse patient populations before it can be successfully integrated into clinical practice.
The research is published today in European Heart Journal – Cardiovascular Pharmacotherapy. The Dundee study was funded by a University of Dundee Baxter Fellowship for Dr Siddiqui and an Italian Government PhD Studentship for Dr Bigossi, and featured patients from the NHS Tayside and NHS Fife areas.