72 percent of heart drugs are impacted by genetics, study finds
The evidence for expanded use of pharmacogenetic data to help inform heart medication prescribing just got stronger.
A comprehensive review of the scientific literature on pharmacogenomics and heart medications found that 71.8 percent of the 71 drugs studied had positive evidence for varied response or adverse effects based on genetics. The review encompassed 597 publications and identified 884 unique pairings of a drug and a specific genetic variant (a drug-gene pair).
“Considerable clinically actionable pharmacogenomic information for cardiovascular drugs exists, supporting the idea that consideration of such information when prescribing is warranted,” study authors Kaufman et al write.
After further analysis, 92 of these drug-gene pairs, encompassing 23 drugs, were called out as candidates for clinical summaries that could be used to better inform prescribing decisions. Some medications, such as clopidogrel (Plavix) and warfarin (Coumadin), have existing guidelines and pharmacogenetic information written in to their U.S. Food and Drug Administration (FDA) labeling. Others, like the cholesterol-lowering drug simvastatin, have dosing guidelines produced by the independent Clinical Pharmacogenetics Implementation Consortium (CPIC) but no pharmacogenetic information in their FDA drug labeling.
Here's a table of select drugs-gene pairs the study authors say warrant clinical summaries:
|Drug Name||Associated Gene|
|Warfarin (Coumadin)||CYP2C9 and VKORC1|
|Simvastatin (Zocor)||ABCB1 and SLCO1B1|
With more than 53,000 people sent to the ER per year due to heart-related adverse drug reactions, Kaufman et al. tackled the review project to better inform prescribing decisions for this type of drugs and potentially help lessen this impact. The authors write that there “is a need to better identify therapies that are more likely to be beneficial and less likely to cause harm to individual patients,” especially in the world of cardiac medications.
The authors took special note of the nine most commonly prescribed heart medications in the U.S., a list that simvastatin tops (96.8 million prescriptions were written in 2011). For these nine drugs alone, pharmacogenomic information with a published clinical effect on outcomes has been gathered from studies including more than 83,575 total patients. This information is available to inform potentially 390 million current prescriptions per year, the authors write.
The researchers found that seven of these nine drugs had sufficient literature behind them to support clinical summaries explaining the influence of genetics on drug response and adverse reactions. (Check out this case report about a father and son developing myopathy, or muscle weakness, after taking the same statin.)
“For some drugs, the potential impact could touch millions of patients: simvastatin (and the genetic variant for myopathy risk) is illustrative here as the analysis identified that the evidence base is large (encompassing data from>17,000 patients), but the pool of patients potentially affected by this information is even orders of magnitude larger (as simvastatin is the most commonly prescribed cardiovascular drug),” Kaufman et al write.
Though the field of pharmacogenomics is relatively lacking in large clinical trials, (the gold standard behind the most authoritative clinical guidelines), the authors argue that the sort information they’ve compiled can still prove useful. They conclude that the “implementation of pharmacogenomic evidence can occur even in the absence of a randomized trial if high-quality data standards are met.”
“Given the burden of cardiovascular disease and the potential of personalized medicine, this information merits being made available for clinical implementation in a research context to determine whether it affects physician decision making and patient outcomes,” Kaufman et al. write.
With evidence like this mounting, is it just a matter of time before pharmacogenetic information is incorporated into the standard of care? Only time will tell.
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