How Pharmacogenomics Might Be Used Clinically

Pharmacological management of cardiovascular diseases is largely based on evidence from clinical trials and guidelines from expert consensus panels. For example, current consensus guidelines recommend the institution of angiotensin-converting enzyme (ACE) inhibitors and ^-blockers and consideration of spironolactone in all patients with severe heart failure, based on evidence that these drugs reduced morbidity and mortality in several large clinical trials (1). However, not all participants enrolled in heart failure studies with ACE inhibitors, ^-blockers, and spironolactone derived clinical benefits from these drugs, and some study participants experienced serious adverse drug reactions requiring study discontinuation. For instance, in the Studies of Left Ventricular Dysfunc

Patients with same diagnosis

Predicted increased toxicity risk Decrease dose or use different drug

Predicted good response to tested drug

Predicted poor or nonresponse Use different drug

Fig. 1. Clinical potential of pharmacogenetics. Patients with the same empirical diagnosis (e.g., hypertension, leukemia, etc.) are typically treated in the same manner, although their responses to drug therapy will not be the same. Pharmacogenetics has the potential to provide a tool for predicting those patients who are likely to have the desired response to the drug, those who are likely to have little or no benefit, and those at risk for toxicity. This would allow tailored therapy that should reduce adverse reactions to drugs, and increase efficacy rates. (Reproduced with permission from ref. 64.)

Predicted increased toxicity risk Decrease dose or use different drug

Predicted good response to tested drug

Predicted poor or nonresponse Use different drug

Fig. 1. Clinical potential of pharmacogenetics. Patients with the same empirical diagnosis (e.g., hypertension, leukemia, etc.) are typically treated in the same manner, although their responses to drug therapy will not be the same. Pharmacogenetics has the potential to provide a tool for predicting those patients who are likely to have the desired response to the drug, those who are likely to have little or no benefit, and those at risk for toxicity. This would allow tailored therapy that should reduce adverse reactions to drugs, and increase efficacy rates. (Reproduced with permission from ref. 64.)

tion (SOLVD), one of the first trials to demonstrate the benefits of ACE inhibitor therapy in heart failure, approx 5% of participants discontinued ACE inhibitor treatment because of worsening disease (2). An additional 8% of participants discontinued treatment because of adverse drug effects. Thus, one cannot assume that a given patient will have a favorable response to a particular drug, despite benefits observed in the overall population of a clinical trial.

Pharmacogenomics might enable clinicians to individualize cardiovascular drug therapy based on a person's genotype, as shown in Fig. 1. This approach to cardiovascular disease management has the potential to streamline the management of diseases such as heart failure. Rather than starting all heart failure patients on the same therapy, drug regimens might be tailored according to each individual's genetic predisposition for obtaining benefit or experiencing harm from a particular drug. For instance, patients with heart failure would be genotyped for drug response at the time of heart failure diagnosis. Then, the drug or drugs expected to produce the greatest clinical response for a particular patient with regard to reductions in morbidity and mortality would be started and titrated to maximally tolerated doses. This approach would be particularly beneficial for patients with inadequate blood pressure to safely take recommended doses of both ACE inhibitors and P-blockers. Patients with a genetic predisposition to serious adverse drug effects, such as angioedema from ACE inhibitors, could be started on alternative therapy. Not only would this approach to heart failure management potentially improve clinical outcomes in the heart failure population as a whole, but it might also reduce healthcare costs associated with the management of adverse drug reactions and with unnecessary polypharmacy.

Pharmacogenomics also has the potential to eliminate the trial-and-error approach to the management of diseases such as hypertension. Patients with hypertension are currently started on one or two drugs to lower their blood pressure. Therapy is then continued as initially prescribed if an adequate response is obtained, or, more commonly, therapy is adjusted until there is sufficient blood pressure reduction. Often, initial drug therapy is abandoned because of a lack of response or intolerable adverse effects, and alternative agents are instituted. For example, in the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT), 15-20% of participants discontinued initial antihypertensive therapy, usually as a result of adverse drug events or therapeutic failure (3). With pharmacogenomics, clinicians might be able to predict a patient's response to various antihypertensive medications prior to drug initiation and then prescribe the drug expected to produce the greatest blood pressure response with the least potential for harm. Such an approach to hypertension management may shorten the duration until blood pressure control is achieved and thus the length of time the patient is at risk for hypertension-related end-organ damage. Additionally, this approach would reduce the number of office visits required to find the best therapy, minimize exposure to agents that will not provide benefit but could still cause adverse effects, and avoid costs for ineffective agents and the adverse events they might cause.

Blood Pressure Health

Blood Pressure Health

Your heart pumps blood throughout your body using a network of tubing called arteries and capillaries which return the blood back to your heart via your veins. Blood pressure is the force of the blood pushing against the walls of your arteries as your heart beats.Learn more...

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