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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Vasc Med. Author manuscript; available in PMC 2013 September 4.
Published in final edited form as:
PMCID: PMC3761360

Personalized vascular medicine: Individualizing drug therapy


Personalized medicine refers to the application of an individual’s biological fingerprint – the comprehensive dataset of unique biological information – to optimize medical care. While the principle itself is straightforward, its implementation remains challenging. Advances in pharmacogenomics as well as functional assays of vascular biology now permit improved characterization of an individual’s response to medical therapy for vascular disease. This review describes novel strategies designed to permit tailoring of four major pharmacotherapeutic drug classes within vascular medicine: antiplatelet therapy, antihypertensive therapy, lipid-lowering therapy, and antithrombotic therapy. Translation to routine clinical practice awaits the results of ongoing randomized clinical trials comparing personalized approaches with standard of care management.

Keywords: anticoagulants, antihypertensive agents, aspirin, statins, vascular diseases, warfarin


Give different drugs to different patients, for the sweet ones do not benefit everyone, nor do the astringent ones, nor are all the patients able to drink the same things.1

Hippocrates, circa 400 BC

Personalized medicine refers to the application of an individual’s biological fingerprint – the comprehensive dataset of unique biological information – to optimize preventive and therapeutic management.2 The appealing concept of individualized care is not novel, but rather has stood as a central tenet of medicine since Hippocrates’ seminal works in the 5th century BC.3 Recognizing the “great natural diversities” between persons, he instructed his students to “give different drugs to different patients” to both maximize efficacy and minimize adverse effects.1

Broadly speaking, the critical unmet needs in personalized vascular medicine can be categorized into risk assessment and pharmacotherapeutic management. Current clinical risk stratification schemes, such as the Framingham risk score, suffer from well-documented limitations. In particular, they are designed to estimate risk for populations and fall short when calculating individual risk, especially among women and younger patients.4 Strategies to refine individual risk prediction based on advanced testing, including genetics, biomarkers, and imaging, have been discussed extensively elsewhere.5-7

Administration of pharmacotherapy, the focus of this review, struggles to transcend the ‘one drug fits all’ approach, which may in part explain the observed suboptimal effectiveness, tolerability, and safety. Evidence suggests that most drug therapies not accounting for interindividual differences are either ‘ineffective’ or ‘not completely effective’ in 30–60% of patients.8,9 Even when physicians prescribe effective medications, the usual empiric method of dosing poses an increased risk for adverse drug reactions, with their attendant morbidity, mortality, and economic cost. Adverse drug reactions (ADRs) represent the fourth leading cause of hospitalization in the US, accounting for 100,000 deaths per year and $10 to $150 billion in US healthcare costs annually.9,10 Warfarin provides a clear example of such inefficiency, implicated in numerous ADRs largely attributable to trial-and-error dosing in the face of highly variable response. Personalized medicine seeks to provide patients with ‘the right drug at the right dose at the right time’.11

While the principle itself is straightforward, its implementation remains challenging. Only recently have scientific advancements, including the ‘omics’ sciences of genomics, proteomics, and metabolomics, introduced an unprecedented wealth of individualized data, ushering in a new era of personalized medicine.12 This review describes novel strategies designed to permit tailoring of four major pharmacotherapeutic areas within vascular medicine: anti-platelet therapy, antihypertensive therapy, lipid-lowering therapy, and antithrombotic therapy (Table 1). Translation to routine clinical practice awaits the results of ongoing randomized clinical trials comparing personalized approaches with standard of care management.

Table 1
Overview of approaches to personalize pharmacotherapeutic management in vascular medicine

Antiplatelet therapy

Antiplatelet agents reduce both incident and recurrent atherothrombotic cardiovascular events by as much as 25%.13-16 However, there is considerable variability in responsiveness to platelet inhibition, with as many as 50% and 30% of those with vascular disease demonstrating residual high-platelet reactivity (HPR) on aspirin alone, so-called ‘aspirin resistance’, and dual antiplatelet therapy, respectively.17 Moreover, a number of prospective studies have implicated HPR as a significant risk factor for future cardiovascular events.18-21 The largest outcome trial of HPR to date (n = 802) revealed that among patients undergoing elective percutaneous coronary intervention (PCI), those in the upper two quartiles of adenosine diphosphate (ADP)-stimulated platelet aggregation had a 6.7-fold (95% CI 1.5–29.4) relative risk of composite death, myocardial infarction, or target vessel revascularization.22 Additional studies have similarly demonstrated the prognostic value of HPR in both stable coronary artery disease (CAD) and peripheral artery disease.20,21

Platelet aggregation assays

The incidence of HPR, despite antiplatelet therapy together with its untoward prognostic implications, underscores the need for the identification of individuals at risk and the institution of personalized therapeutic strategies to optimize platelet inhibition. Point-of-care laboratory tests have been developed that detect changes in the optical density of whole blood due to agonist-stimulated platelet aggregation. The VerifyNow® (Accumetrics Inc., San Diego, CA, USA) assay permits the ex vivo assessment of platelet inhibition in the presence of arachidonic acid or ADP, in an effort to identify platelet resistance to aspirin or clopidogrel, respectively. An assay designed to simulate platelet aggregation in the vascular space has also been developed, and operates on the time required for blood to occlude an aperture coated with collagen and a platelet agonist (PFA-100; Dade Behring). These two assays are broadly available and standardized and have shown reproducibility comparable to whole blood aggregometry, the historical gold standard.23,24 Compared with traditional methods, the tests benefit from the ability to be performed at the bedside with whole blood specimens, thereby minimizing post-collection processing. Exposure to Gp IIb/IIIa inhibitors interferes with testing, and therefore testing should occur more than 48 hours or 10 days after exposure to eptifibatide or abciximab, respectively.

Once residual HPR is identified, tailored strategies have been developed in an effort to optimize platelet inhibition with the goal of mitigating cardiovascular risk. These strategies have ranged from simple dose escalation to the initiation of combination antiplatelet therapy. In a prospective study of 504 patients with CAD undergoing PCI, 19% were deemed aspirin low responders based on arachidonic acid-stimulated whole blood aggregation. By increasing aspirin dose, the frequency of low responders was reduced to 5% (325 mg) and 0% (500 mg aspirin) of the study population.25 Similarly, clopidogrel dose escalation incrementally reduces platelet reactivity, and decreases the incidence of HPR across doses ranging from 75 mg to 1200 mg.26

Other strategies to maximize platelet inhibition in low responders involve the use of adjunctive agents that inhibit platelets by alternate intracellular mechanisms. Omega-3 fatty acids have been evaluated as a therapeutic agent in those with a low response to aspirin, presumably by limiting arachidonic acid substrate for cyclooxygenase-1. In patients (n = 30) with stable CAD and residual HPR, introduction of omega-3 fatty acids at 4 g daily significantly reduced the frequency of aspirin resistance by 75%, equivalent to that of increasing aspirin dose from 75 mg to 325 mg daily.27 Similarly, others have added omega-3 fatty acids to dual antiplatelet therapy and demonstrated improved responses to clopidogrel.28 Cilostazol is a phosphodiesterase inhibitor that increases intracellular cyclic adenosine monophosphate and blunts surface expression of glycoprotein IIb/IIIa, an event critical for the stabilization of platelet aggregates. A recent prospective trial was designed to evaluate the effect of cilostazol added to aspirin and clopidogrel therapy in patients undergoing drug-eluting stent implantation. Cilostazol significantly reduced platelet reactivity, and platelet reactivity at discharge was a significant predictor of cardiovascular events. However, cilostazol did not confer a significant reduction in a broad composite cardiovascular outcome that included target vessel revascularization.29

Importantly, though these studies and others30 demonstrate the ability of dose escalation and triple antiplatelet therapy to reduce platelet reactivity in patients with residual HPR, a link between normalizing platelet inhibition and improved clinical outcomes remains elusive. The Gauging Responsiveness With A VerifyNow Assay-Impact On Thrombosis And Safety (GRAVITAS) was a randomized clinical outcomes trial designed to evaluate the effectiveness of a tailored approach to antiplatelet therapy. GRAVITAS enrolled 2214 patients 12–24 hours after PCI who demonstrated residual HPR on standard dose clopidogrel. These patients were randomized to continue standard clopidogrel dosing (75 mg daily) or to receive an additional loading dose and an increased standing daily dose (150 mg daily). Despite a significant reduction in the incidence of HPR at 30 days in the group with dose escalation (−60%), there was no difference in the composite cardiovascular endpoint of death, myocardial infarction or stent thrombosis at 6 months (2.3% versus 2.3%).31 Importantly, in the dose escalation group, 40% of patients demonstrated residual HPR, leaving open the possibility that a more efficacious means of reducing HPR may in fact be clinically beneficial. In addition, the event rate for patients enrolled in GRAVITAS was substantially lower than expected. Evaluation of larger sample sizes or higher risk patients may be needed to demonstrate a significant clinical benefit. The same issue was encountered in the recently halted Testing Platelet Reactivity In Patients Undergoing Elective Stent Placement on Clopidogrel to Guide Alternative Therapy With Prasugrel (TRIGGER-PCI) study.32 Designed to test the effectiveness of prasugrel in reducing composite cardiovascular events in those identified with HPR on clopidogrel therapy, the study was halted after only 20% enrollment due to a low overall event rate. Though the prognostic value of identifying HPR is well demonstrated, GRAVITAS and TRIGGER-PCI call into question the therapeutic value of identifying HPR. A trial of higher risk patients with medically managed acute coronary syndromes (A Comparison of Prasugrel and Clopidogrel in Acute Coronary Syndrome Subjects, TRILOGY-ACS) is underway.33

Genotyping to assess clopidogrel metabolism

Genomic approaches to predict those with HPR on anti-platelet therapy have also recently emerged. Clopidogrel is a pro-drug subject to enzymatic intestinal reflux, hydrolysis by serum esterases, and oxidation by cytochrome P450 (CYP) enzymes, which in sum render approximately 85% of the ingested pro-drug inactive.21 Each of these intermediate steps offers the potential for pharmacokinetic resistance, and polymorphisms in the genes moderating absorption (ABCB1), conversion (CYP2C19) and drug target (P2Y1A1662) have been implicated in HPR on clopidogrel therapy. Moreover, these polymorphisms are more common in those patients with cardiovascular events on therapy compared to those free from events on therapy.34-37 For example, of 2208 patients consecutively admitted for acute myocardial infarction, those with any two CYP2C19 loss-of-function alleles associated with poor clopidogrel biotransformation experienced a twofold (adjusted hazard ratio 2.0; 95% CI 1.1–3.6) increase in composite death, non-fatal stroke, or myocardial infarction at 1 year. Of those that underwent PCI during the index hospitalization, the hazard ratio for composite events among carriers of two CYP2C19 loss-of-function alleles was 3.6 (95% CI 1.7–7.5).34

The CYP2C19 gene encodes the protein responsible for the conversion of the clopidogrel pro-drug to the active form. The metabolite prevents platelet aggregation by irreversibly inhibiting platelet ADP receptors (subtype P2Y12). Loss-of-function alleles (CYP2C19*2, *3, *4, *5) occur at a frequency of up to 30% in the Caucasian population, and are reliably associated with an increased risk of cardiac events, most notably stent thrombosis.38 Indeed, pharmacokinetic studies have demonstrated that patients carrying the loss-of-function CYP2C19 alleles CYP2C19*2 or *4 have roughly 22% less platelet inhibition upon exposure to clopidogrel.39,40 Moreover, a recent study suggested that patients with two loss-of-function CYP2C19 alleles and HPR on therapy were less responsive to dose escalation, and might represent a population that requires non-CYP2C19 dependent P2Y12 inhibition.41,42 Cilostazol has been evaluated in carriers of CYP2C19 polymorphisms, and though a reduced incidence of HPR can be achieved, the clinical relevance of a pharmacogenomics strategy has yet to be determined.43

The paraoxonase 1 (PON1). gene encodes a protein largely responsible for the second step in the transformation of clopidogrel pro-drug to the active metabolite. Individuals with the homozygous variant QQ192 have higher platelet reactivity after clopidogrel and had a hazard ratio of 12.8 (95% CI 4.7–90.9) for stent thrombosis at 18 months compared to controls.44 Moreover, in the only small cohort published to date, PON1 heterogeneity was of greater predictive value than CYP2C19.44 There are no reports regarding the effect of escalating clopidogrel dose on platelet responsiveness in patients with the PON1 QQ192 variant.


Patients with residual HPR on antiplatelet therapy represent a significant proportion of patients with atherosclerotic disease and exhibit a markedly increased risk of future events. These issues highlight the pressing need for further investigation of the significance of resistance to antiplatelet therapy and strategies to optimize platelet inhibition. The emergence of novel potent antiplatelet therapies as well as the growing availability of point-of-care platelet function assays and genetic testing offer an opportunity for a phenotype- and genotype-based individualization of therapy, and the chance to test the concept of personalized vascular medicine. Whether assessing HPR in patients with atherosclerotic disease can yield tailored antiplatelet therapy and improved outcomes remains a pivotal question and the subject of ongoing clinical trials.

Antihypertensive therapy

Hypertension seems an ideal vascular disease for a personalized pharmacotherapeutic approach.45 Beyond its high prevalence and significant associated morbidity and mortality, the arguably unparalleled medical armamentarium, spanning some 10 unique drug classes, provides a broad platform from which to build tailored management strategies.46 To this end, renin profiling represents a promising and mechanistically rational technique to individualize antihypertensive therapy, further supported by recent clinical data. In addition, recent data suggest that haplotype analysis of candidate genes involving the renin-angiotensin-aldosterone and kininogen-kallikrein-bradykinin axes may help identify responders and non-responders to angiotensin-converting enzyme (ACE) inhibitor therapy. Examination of 24-hour ambulatory blood pressure patterns, pulse wave velocity, and central hemodynamics such as aortic pulse pressure may better tailor the use of antihypertensive therapy, as well. These physiologic tests are beyond the scope of the current review.

Renin profiling

The physiologic foundation of renin profiling lies in Hagen-Poiseuille’s Law, formulated in the 1840s, which states that blood pressure equals cardiac output multiplied by total peripheral resistance. In the 1970s, Laragh simplified the equation governing blood pressure by substituting the critical determinants of cardiac output and total peripheral resistance, in particular volume, or preload, and renin as a proxy for angiotensin II.47 Hypertension, then, resulted from an abnormal volume-vasoconstrictor, or salt-renin, product.48 One end of the spectrum, pure renin hypertension, is exemplified by unilateral renovascular disease, which results in very elevated renin levels and a volume-depleted state. Primary hyperaldosteronism provides the contrasting pure salt hypertension characterized by hypervolemia and undetectable renin activity.

Beyond its diagnostic and prognostic implications, Laragh proposed that classification along the volume-vasoconstriction model could be leveraged to tailor antihypertensive therapy to individual patients.49 Patients with a predominant renin-vasoconstrictor factor, identified via a plasma renin activity level greater than 0.65 ng/ml/hour in the presence or absence of antihypertensive drugs, would rationally be treated with renin-inhibiting agents, including beta-blockers, ACE inhibitors, angiotensin receptor blockers, and now direct renin inhibitors. On the other hand, patients with predominant sodium-volume factor, identified with a plasma renin activity level below 0.65 ng/ml/hour in the presence or absence of antihypertensive drugs, would be treated with volume-directed therapy, in particular a diuretic or calcium channel blocker. The threshold plasma renin activity level is based on the understanding that hypertension normally suppresses plasma renin activity levels; therefore, any level above the lowest tertile (0.65 ng/ml/hour) is physiologically inappropriate.49 These guiding principles underlie a detailed protocol, dubbed the Laragh method, for selection of drug therapy for newly diagnosed or untreated hypertensive patients and unsuccessfully treated patients.49 Importantly, the sensitive enzyme kinetic radioimmunoassay used to measure renin activity in the Laragh approach is widely available through commercial laboratories.48

Three recently published studies suggest that this tailored approach using renin profiling may maximize the antihypertensive effect of both single agent and combination therapy. In a crossover clinical trial of 363 men and women aged 65 years and younger with primary hypertension, plasma renin activity predicted systolic and diastolic blood pressure responses to atenolol and hydrochlorothiazide as monotherapy and as add-on therapy.50 Blood pressure was measured twice in the morning and twice in the evening using automatic oscillometric sphygmomanometers. Lower renin activity levels were consistently associated with greater blood pressure reductions with hydrochlorothiazide. As single-agent antihypertensive treatment, hydrochlorothiazide reduced systolic blood pressure by 10–12 mmHg in the lowest renin group and by 6–7 mmHg in the highest renin group. Conversely, higher renin activity levels were reliably associated with greater blood pressure reductions with atenolol. Atenolol as monotherapy reduced systolic blood pressure by 10–12 mmHg in the highest renin group and by only 1–2 mmHg in the lowest renin group. Importantly, the predictive value of renin activity was observed independent of race, sex, age, hypertension duration, smoking status, alcohol intake, height, waist circumference, and pretreatment blood pressure. These data appear to contradict a study of 1031 ambulatory patients which found no incremental benefit of renin profiling above and beyond age and race in predicting blood pressure response to single-drug therapy.51 Importantly, however, this earlier study was restricted to men and the mean age in the older cohort was 66 years, limiting the generalizability of the observed findings.

A second trial similarly reported attenuated blood pressure lowering when antihypertensive therapy proceeded in a manner discordant to patient renin profiles.52 The retrospective analysis evaluated the effect of single-agent therapy with a diuretic, calcium channel blocker, beta-blocker, or ACE inhibitor on blood pressure response measured at the first clinic revisit within 90 days of treatment initiation. Blood pressure was measured by trained nurses using standard mercury sphygmomanometers and recorded as the average of the last two of three readings. Diuretics and calcium channel blockers were associated with a decrease in blood pressure of 16/8 mmHg and 12/7 mmHg in the lowest and highest renin activity tertiles, respectively. In contrast, ACE inhibitors and beta-blockers achieved a decrease in blood pressure of 13/8 mmHg and 6/5 mmHg in the highest and lowest renin activity tertiles, respectively. The goal of systolic blood pressure of 130 mmHg or less was achieved more frequently with single-agent therapy in patients administered diuretics or calcium channel blockers in the lowest tertile (18% vs 5%, p = 0.003), and in patients prescribed beta-blockers or ACE inhibitors in the highest tertile (26% vs 12%, p = 0.002). Interestingly, a ‘paradoxical’ pressor response, defined as a systolic blood pressure increase of at least 10 mmHg, was observed more frequently in the setting of discordant therapy. Among low renin patients, the pressor response was observed in 17% of patients receiving ACE inhibitors or beta-blockers, compared to 6% of those treated with diuretics or calcium channel blockers (p = 0.003). The consistency, mechanism, and clinical significance of this hypertensive response remain uncertain. The authors suggest that perhaps renin, at low levels, suppresses volume-induced hypertension by maintaining adequate glomerular filtration.52

Finally, a prospective, randomized, unblinded clinical trial of 77 uncontrolled hypertensive patients compared the renin-guided approach of Laragh, detailed above, with standard clinical hypertension specialist care.53 To qualify for the study, patients were required to have uncontrolled hypertension, defined as a clinic blood pressure exceeding 130/80 mmHg for those with diabetes or nephropathy and above 140/90 mmHg for all others, despite at least single drug therapy. At baseline, systolic and diastolic blood pressures (157 mmHg vs 153 mmHg, p = 0.27; 87 vs 91 mmHg, p = 0.17) as well as the number of antihypertensive medications (3.1 vs 2.7, p = 0.21) were comparable between the renin-guided cohort and the group receiving standard specialist care. Clinic blood pressures were measured in triplicate using automatic oscillometric sphygmomanometers. Renin profiling was associated with a significantly greater decrease in systolic blood pressure compared to the control group (−29.1 vs −19.2 mmHg, p = 0.03), despite an equivalent number of antihypertensive drugs (3.1 vs 3.0, p = 0.73). Blood pressure control exhibited a non-significant trend to improvement using the renin-guided approach compared to specialist care (74% vs 59%, p = 0.17). Blood pressure targets were defined as below 130/80 mmHg among patients with chronic kidney disease and/or diabetes and 140/90 mmHg in subjects without these comorbidities.

While the more clinically relevant outcome – number of patients at goal – was not improved with renin profiling in the aforementioned proof-of-concept randomized, unblinded study, the magnitude of blood pressure reduction was nonetheless striking in light of the equivalent number of antihypertensive drugs as well as the high-quality comparator group comprised of hypertension specialists. Maintaining the same number of medications suggests a possible downstream benefit in terms of cost and compliance and a reduction in adverse events. Efforts are underway to train additional hypertension specialists to address the limited supply; however, given the prevalence of resistant hypertension, additional strategies readily deployable in the primary care setting would be advantageous. Renin profiling, now standardized and commercially available, may help address the clinical unmet need; importantly, the test does not require any change in baseline medications or diet or any unusual conditions for blood sample collection and processing. Despite initial promising data, additional comparative effectiveness trials are needed to assess the outcomes associated with renin profiling. The therapeutic landscape of resistant hypertension management continues to evolve. The growing use of spironolactone and novel therapies, such as percutaneous renal artery denervation,54 may attenuate any benefit associated with renin profiling.

Haplotype analysis and ACE inhibition

The first large randomized trials of antihypertensive drugs designed to explore the role of common genetic variants were marked by failure to establish a role of genetic polymorphisms in modulating the treatment effect of ACE inhibitors. The Genetics of Hypertension-Associated Treatment (GenHAT) study55 and the Perindopril Protection Against Recurrent Stroke Study (PROGRESS)56 examined cardiovascular outcomes among patients with hypertension and at least one cardiovascular risk factor or a prior history of stroke, respectively. In neither study was a relationship observed between the examined variant and treatment effect; however, the two trials restricted genetic evaluation to the ACE insertion/deletion polymorphism. Investigating interactions between ACE inhibitor (ACEI) therapy and genetic polymorphisms utilizing only one or two variants fails to acknowledge the multiplicity of candidate genes involved in both drug pharmacodynamics and pharmacokinetics. More comprehensive coverage of genetic variation is likely required to elucidate the complex pharmacogenetics of antihypertensive therapy.

The PERindopril GENEtic association study(PERGENE) achieved more comprehensive genetic coverage using haplotype analysis of multiple single nucleotide polymorphism (SNP) clusters inherited together.57 Results suggest that haplotypes involving pathways downstream to ACE inhibition may modulate the treatment effect of perindopril in patients with stable CAD. A substudy of the European Trial on Reduction of Cardiac Events with Perindopril in Stable Coronary Artery Disease (EUROPA) trial, PERGENE evaluated 52 tagging SNPs in 12 candidate genes spanning both the renin-angiotensin-aldosterone and kininogen-kallikrein-bradykinin axes. Pharmacogenetic analysis identified three tag SNPs that significantly modulated the outcomes associated with ACE inhibition after multivariate adjustment: rs12050217 in the bradykinin 1 (BK1) receptor gene and rs275651 and rs5182 in the angiotensin-1 (AT-1) receptor gene (Figure 1).58 The greatest treatment benefit was observed among the 74% of patients with two or fewer unfavorable alleles, who achieved a 3.6% absolute risk reduction in the combined primary endpoint of cardiovascular death, myocardial infarction, or cardiac arrest. Patients with three or more unfavorable alleles, on the other hand, failed to achieve an improvement in outcomes. The structural and functional consequences of the identified polymorphisms in the BK1 receptor and AT-1 receptor genes remain unknown. Interestingly, none of the three haplotypes was associated with the magnitude of systolic or diastolic blood pressure reduction achieved by perindopril therapy, implicating blood pressure-independent pathways mediating the interaction between genetic variants and cardiovascular outcomes. In summary, PERGENE suggests that utilizing a pharmacogenetic profile combining three tag SNPs may better triage stable CAD patients to long-term use of perindopril, decreasing the number needed to treat to avoid one cardiovascular event in ~4 years from 50 to 32 patients.

Figure 1
Tag SNPs modulating perindopril treatment effect in the Perindopril Genetic Association study. 1/1: homozygous common allele; 1/2: heterozygous; 2/2: homozygous common allele. Percentages refer to genotype prevalence.58

Haplotyping across the renin-angiotensin-aldosterone and kininogen-kallikrein-bradykinin axes may help differentiate responders from non-responders to ACE inhibitor therapy. The pharmacogenetic strategy suggested by the PERGENE study may improve resource utilization by limiting lifelong therapy to those who derive the greatest clinical benefit. Perhaps the greatest obstacle to widespread adoption of such an approach is proving the lack of benefit in a subpopulation of high-risk patients. Clinicians appropriately fear the failure of omission more than the failure of commission, particularly when the medication withheld is both safe and well-tolerated. Prospective randomized controlled trials of perindopril and other ACE inhibitors in patients with stable CAD and other clinical states will elucidate the potential role of pharmacogenetic profiling in ACE inhibitor therapy.


As lamented by several hypertension specialists,45,59,60 consensus statements, despite the admonition that “all patients must receive individualized therapy programs”,61 continue to promote “diuretics first for all”62 or the notion that “all drugs are equally effective”.63 Both are conceptually unappealing, incongruous with accepted differences in pharmacodynamic profiles between various antihypertensives and the observed, complex variability in blood pressure response that extends beyond age and race.64 Post hoc analysis of the Quinapril Titration Interval Management Evaluation Trial, for example, demonstrated that interindividual factors other than ethnicity accounted for half of the observed difference in systolic blood pressure response between white and black individuals.65 Carvedilol and metoprolol, two beta-blockers, exert contrasting metabolic changes66,67 and data suggest differing outcomes among patients with heart failure.68,69 Given these findings, it is not only conceivable but probable that completely different antihypertensive drug classes indeed possess unique effects yet to be harnessed in a tailored management strategy. Existing trials supporting a one-size fits all approach70 may well obscure heterogeneity through conventional reporting of blood pressure as means and standard errors.52 Techniques such as renin profiling and haplotyping, coupled with more detailed evaluation of blood pressure response, may reveal methods to personalize approaches to hypertension. ‘Physiologic tailoring’ using renin profiling may be of particular use in the setting of resistant hypertension.71 Given the suboptimal treatment rates of hypertension, with only 44% of hypertensive adults achieving the least stringent target of a blood pressure below 140/90 mmHg,72 the need for novel, effective management strategies remains a pressing public health concern.

Lipid-lowering therapy

The dramatic efficacy and broad therapeutic index of the statin class may at first thought appear to obviate the need for personalizing lipid-lowering therapy. Various statins at differing doses lower low-density lipoprotein (LDL)-cholesterol 30–60% compared to placebo, accompanied by a reduction in cardiovascular events of 20–50% across primary prevention, secondary prevention, acute coronary syndrome, and diabetic cohorts.73-77 Despite these consistent benefits, unmet need remains based on tolerability and efficacy concerns. The often cited 3% incidence of statin-induced myalgias, a figure derived from randomized clinical trials, underestimates the true burden of muscle-related side effects.78 The Prediction of Muscular Risk in Observational Conditions (PRIMO) study, a community cohort study of almost 8000 subjects, observed a real-world prevalence of myalgias of 10% among participants receiving moderate- to high-dose statins for at least 3 months.79 Pharmacogenetic studies may improve the ability to identify patients at risk for muscle-related side effects and may guide selection of particular statin drugs and doses to optimize tolerability and medication adherence. In addition, significant residual risk exists despite statin therapy. Individuals with manifest atherosclerotic disease, or a collection of associated risk factors, continue to endure a high incidence of adverse cardiovascular events despite the use of aggressive medical therapy. The incidence of ‘hard’ cardiovascular events in secondary prevention cohorts approaches 20% after 4–5 years, even in the best-case scenario of intensive treatment and vigilant monitoring.80,81 While mechanistically appealing, combination therapy using statins in conjunction with antidyslipidemic drug classes such as fibrates, niacin, and ezetimibe has yet to demonstrate an incremental clinical outcome benefit above and beyond statin monotherapy in randomized controlled studies.82 Genetic analysis may better identify subpopulations of responders to additional lipid-modifying agents who demonstrate both an improvement in lipid parameters and a consistent reduction in atherothrombotic events.

Genotyping to assess risk of statin myopathy

Minimizing muscle-related side effects to statins involves a thorough review of concomitant medications and a search for comorbidities such as hypothyroidism, renal failure, underlying muscle disease, and arguably, vitamin D deficiency.83 Variants of the gene named solute carrier organic anion transporter family, member 1B1 (SLCO1B1), may be added to this clinical algorithm to better identify patients at risk for myopathy.84 SLCO1B1 encodes the organic aniontransporting polypeptide 1B1 (OATP1B1), an influx transporter expressed on the sinusoidal membrane of hepatocytes that mediates the hepatic uptake of numerous compounds. One variant, designated SLCO1B1*5, is defined by the presence of the C allele of the SNP rs4149056 instead of the wild-type T allele.85 This alteration yields a valine to alanine substitution at amino acid position 174, resulting in a conformational change that interferes with the localization of OATP1B1 to the plasma membrane. Higher systemic statin concentrations have been demonstrated in the presence of SLCO1B1*5, indicating impaired influx transporter capacity.86,87 Simvastatin in particular appeared sensitive to the SLCO1B1*5 variant, with an increase in the plasma concentration time curve of 221% observed among homozygous carriers compared to 145% and 62% for atorvastatin and rosuvastatin, respectively.

Preliminary pharmacokinetic associations have been borne out in clinical studies of statin-induced muscle-related side effects. In the Study of the Effectiveness of Additional Reductions in Cholesterol and Homocysteine (SEARCH) trial, well-defined cases of definite myopathy (muscle symptoms and creatine kinase levels exceeding 10 times the upper limit of normal) and incipient myopathy (creatine kinase levels three times the upper limit of normal and five times the baseline level as well as elevated alanine aminotransferase levels) were used in a genome-wide scan to identify SNPs associated with myopathy.88 The SLCO1B1*5 variant, observed in 15% of study participants, was the only SNP highly associated with myopathy (p = 4 × 10−9), a finding replicated in 20,000 patients examined in the Heart Protection Study.88 The odds ratios among heterozygous and homozygous carriers of SLCO1B1*5 were 4.5 (95% CI 2.6–7.7) and 16.9 (95% CI 4.7–61.1), respectively. Overall, more than 60% of myopathy cases could be attributed to the SLCO1B1*5 variant.

The Statin Response Examined by Genetic Haplotype Markers (STRENGTH) extended these findings to milder muscle-related side effects.89 STRENGTH randomized 509 subjects to high-dose atorvastatin, simvastatin, and pravastatin and followed patients for 8 weeks using the primary composite endpoint of discontinuation for any side effect, myalgia, or creatine kinase exceeding three times the upper limit of normal. The combined adverse event rate was higher among subjects harboring at least one SLCO1B1*5 allele compared to the wild-type group (37% vs 25%, p = 0.03). In multivariate analysis adjusted for race, the SLCO1B1*5 genotype was associated with an odds ratio for adverse events of 1.7 (95% CI 1.04–2.8). There was evidence of a gene–dose effect, with progressively higher adverse event rates observed in those with zero, one, or two alleles (19%, 27%, and 50%, respectively, trend p = 0.01). When stratified by statin use, carriers of SLCO1B1*5 demonstrated the greatest excess risk of muscle-related side effects compared to non-carriers when randomized to simvastatin (p = 0.01) as opposed to atorvastatin or pravastatin.

A differential effect of SLCO1B1*5 on myopathy was also observed in a Dutch study of patients with myopathy, defined as creatine kinase values exceeding 10 times the upper limit of normal.90 Among patients administered simvastatin, SLCO1B1*5 conferred a significant increased risk for myopathy, with an odds ratio of 3.2 (95% CI 0.83–11.96). Carriers of the variant given atorvastatin, on the other hand, exhibited no excess risk of myopathy (odds ratio 1.06, 95% CI 0.22–4.80). These findings are consistent with the pharmacokinetic studies described above.

SLCO1B1 testing may prove useful in the diagnostic approach to CK-negative myalgias in the setting of statin administration or in the selection of drug and dose when faced with the statin-naïve patient. Absence of the SLCO1B1*5 allele, for example, may help exclude a statin-cause of muscle symptoms, particularly when a competing explanation is present.91 That said, a careful history coupled with a trial of statin discontinuation provides the correct diagnosis in most cases; thus, the incremental value of pharmacogenetic data for this purpose remains uncertain. Identification of SLCO1B1*5 may prompt initiation of statin regimens that pose a lower risk of muscle-related adverse events, such as pravastatin or low-dose, pulsed rosuvastatin. This therapeutic decision is not trivial, as these approaches are less potent in reducing LDL-cholesterol and involve longer titration periods or more expensive statins.92 On the other hand, an empiric trial of atorvastatin, available in generic form in late 2011, may prove as effective and more cost-effective than assessing SLCO1B1 status. While SLCO1B1*5 may ultimately prove to be a consistent marker of the risk of muscle-related side effects on statin therapy, formal testing of a pharmacogenetic strategy to minimize statin-associated myalgia and myopathy is required before advocating this approach.

Genotyping to assess efficacy of non-statin lipid-lowering drugs

Genetic testing may also prove useful in tailoring combination lipid-lowering therapy, an exciting though largely hypothetical application at this time. For example, hypertriglyceridemia is currently used as a clinical marker to identify high-risk patients who may benefit from a fibrate in addition to statin therapy. Although no clinical trial of fibrate use has demonstrated an outcome benefit above and beyond statin therapy, the recent Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial demonstrated a trend towards benefit among the subgroup with elevated triglycerides and low high-density lipoprotein (HDL)-cholesterol.82 Patients in the highest tertile of triglycerides (> 204 mg/dl) and lowest tertile of HDL-cholesterol (< 34 mg/dl) demonstrated a 4.9% absolute risk reduction in cardiovascular events that bordered on statistical significance (p = 0.06). Prior fibrate studies similarly demonstrated the greatest benefit among patients with hypertriglyceridemia.93,94

In addition to hypertriglyceridemia, a particular variant in APOA5, the gene encoding apolipoprotein A5, may be associated with a benefit in clinical outcomes. The functional role of apolipoprotein A5, present in plasma at low concentrations, remains unknown; levels appear positively correlated with triglyceride concentrations in most but not all studies.95 Carriers of the APOA5 SNP 56G have been associated with an increased response to fenofibrate therapy. Compared to non-carriers, APOA5 56G carriers demonstrated a more pronounced decrease in fasting triglycerides (−36% vs −28%, p = 0.006) and increase in HDL-cholesterol (+12% vs +7%, p = 0.002) after 3 weeks of fenofibrate therapy.96,97 Following a fat load, a significant decrease in postprandial triglycerides was observed among 56G carriers compared to non-carriers, as well.96,97 The weight of data argues against the use of fibrates to address residual cardiovascular risk in the majority of statin-treated patients. Additional verification is required, but perhaps identifying APOA5 56G may tip the risk–benefit analysis in favor of the addition of a fibrate to background statin therapy.

As with fibrates, no randomized clinical trials have yet definitively established a clinical benefit of ezetimibe when added to statins. The Study of Heart and Renal Protection (SHARP) trial demonstrated a 17% reduction in atherothrombotic events among patients with chronic kidney disease randomized to simvastatin and ezetimibe compared to placebo; however, this trial was not designed to compare ezetimibe plus a statin to statin monotherapy alone.98 While results of ongoing studies are awaited, it is reasonable to postulate that genetic testing may eventually guide ezetimibe use. In particular, absence of the common haplotype of NPC1L1, the gene encoding the intestinal cholesterol transport protein Niemann-Pick C1 Like 1, has been associated with an exaggerated benefit with ezetimibe in terms of LDL-cholesterol response. In one analysis, carriers of uncommon NPC1L1 haplotypes, present in one out of eight study participants, exhibited significantly greater reductions in LDL-cholesterol with ezetimibe compared to those homozygous for the wild-type haplotype 1735C-25342A-27677T (−36% vs −24%, p = 0.0054).99 These findings have yet to be replicated or associated with cardiovascular outcomes. Moreover, any approach to tailoring ezetimibe therapy must first await the results of the Improved Reduction of Outcomes: Vytorin Efficacy International Trial (IMPROVE-IT) study comparing ezetimibe and simvastatin combination therapy to simvastatin alone in stabilized high-risk acute coronary syndrome patients. In the absence of significant safety concerns or efficacy findings from the ongoing randomized trial, perhaps future research will support haplotyping NPC1L1 to identify individuals for whom the benefit of ezetimibe justifies the additional cost or for whom very low-dose ezetimibe, instead of standard dose ezetimibe, may be administered.


Of the genotype-based strategies put forward in this review, genotyping to individualize lipid-lowering therapy is probably the farthest removed from routine clinical use at this time. Although SLCO1B1*5 appears a promising marker for statin-related myopathy, it is not clear that evaluating SLCO1B1 status would confer an advantage over current precautions to minimize statin-related muscle side effects. The frequency of significant adverse outcomes is low, culprit comorbidities such as chronic kidney disease and hypothyroidism have been identified, and a total of seven statins provide an array of therapeutic options. Moreover, the availability of generic atorvastatin later this year provides a cheap, potent alternative to simvastatin, the statin that appears most influenced by SLCO1B1 polymorphisms. Variants in the APOA5 gene may better identify patients for whom the risk–benefit analysis supports fenofibrate therapy above and beyond statin treatment. However, the burden of proof is considerable in light of existing randomized trial data, punctuated by the negative results of ACCORD. Even in high-risk patients, trials of fenofibrate as monotherapy or combination add-on therapy to statins have failed to show a reduction in macrovascular events. Finally, NPC1L1 haplotyping to assess LDL-lowering response to ezetimibe remains premature until results of the ongoing ezetimibe outcomes trial IMPROVE-IT become available.

Antithrombotic therapy

Clinicians must carefully monitor serial international normalized ratios (INRs) in patients treated with warfarin to avoid the risk of bleeding on the one hand and thromboembolic complications on the other. Vigilant titration is particularly critical during drug initiation when patients are most vulnerable.100 Numerous factors such as age, body size, sex, diet, smoking, concomitant medications, and the presence of other comorbidities account for approximately 20% of the variability in an individual patient’s dose requirements.101 Polymorphisms in two genes have demonstrated the predominant impact on variability, explaining as much as 30–40% of warfarin dose variation.102,103 The considerable influence of these genes has led to a number of clinical trials investigating genotype-guided warfarin therapy.

Genotyping to assess warfarin metabolism and to characterize its target enzyme

The cytochrome P450 family 2 subfamily C polypeptide 9 enzyme (CYP2C9) gene exerts its effect on warfarin dose variability through its role in warfarin metabolism. Warfarin consists of a racemic mixture of S- and R-enantiomers.104 CYP2C9 metabolizes S-warfarin, which is three to five times more potent than R-warfarin. Functional variants of the CYP2C9 gene markedly influence the biological effect of warfarin. Over 50 SNPs responsible for the regulation and coding of the CYP2C9 gene have been identified, with the CYP2C9*3 and CYP2C9*2 alleles demonstrating the highest prevalence. These alleles significantly reduce CYP2C9 enzyme activity, leading to slower warfarin metabolism and thus causing carriers of these variants to require lower maintenance and cumulative induction doses.103,105 Patients who possess these alleles are more susceptible to supratherapeutic INRs, as well, increasing their risk of serious or life-threatening bleeding.

Polymorphisms of the vitamin K epoxide reductase complex (VKORC1) gene also contribute to the variance in warfarin sensitivity between individuals. The target enzyme of warfarin, VKORC1 recycles the oxidized form of vitamin K to its reduced form that functions as a cofactor for the gamma-glutamyl carboxylation necessary for the activation of clotting factor proteins II, VII, IX, and X. Warfarin reduces circulating levels of clotting factors by inhibiting the VKORC1 enzyme.102,103 A systematic review and meta-analysis of 19 studies concluded that gene polymorphisms of VKORC1 have a significant impact on individual and interethnic daily warfarin dose requirements and suggested that genotyping before warfarin prescription may reduce the risk of bleeding and enhance drug efficacy. Of note, higher frequencies of the common VKORC1 SNPs 1173TT and 1639AA among Asians compared to Caucasian and African populations may explain the heightened sensitivity to warfarin noted in this ethnic group.106

Although incorporating knowledge of pharmacogenetics in warfarin dosing is stipulated to improve both effectiveness and safety, clinical outcome data currently remain sparse and conflicting. The Medco-Mayo Warfarin Effectiveness Study found that patients who were genotyped early in the course of warfarin treatment experienced 31% fewer all-cause hospitalizations (adjusted hazard ratio 0.69; 95% CI 0.58–0.82) and 28% fewer hospitalizations (adjusted hazard ratio 0.72; 95% CI 0.39–0.83) for bleeding or thromboembolism compared to controls.107 However, these strongly favorable findings for a genotype-based approach were marred by the ‘quasi-experimental’ design and utilization of historical controls, design limitations that may have introduced significant bias into the study results. In addition, a substantial delay (median 32 days, range 11–60 days) occurred between warfarin initiation and delivery of the genotype results to the physician, an interval during which the majority of dosing adjustments would have taken place.

One small-scale prospective randomized controlled study of 161 patients employed a CYP2C9 genotype-adjusted algorithm that suggested a benefit over standard of care. The first therapeutic INR and subsequent stabilization of anticoagulation were achieved 3 and 18 days earlier, respectively, in the study group compared to the control group that did not incorporate genetic information.105 In addition, the time in therapeutic INR range (TTR) was significantly higher (80% vs 63%; p < 0.001) and the incidence of minor episodes of bleeding lower (3% vs 13%; p < 0.02) in the genotype-guided group.105 These results are tempered by differences in baseline characteristics between the two arms of the trial. In particular, despite randomization, the prevalence of CYP2C9 wild-type homozygosity was higher in the genotype-guided cohort (63% vs 53%). CYP2C9*1/*1 carriers are less susceptible to over-anticoagulation, potentially biasing the results in favor of the genotype-guided group. Other randomized studies have yielded equivocal results. The Couma-Gen trial demonstrated no reduction in the primary endpoint of out-of-range INRs with pharmacogenetic-guided dosing, though other modest benefits were observed.108 Compared to standard dosing, dosing based on CYP2C9 genotype resulted in selection of an initial dose more closely predictive of the stable maintenance dose, fewer and smaller dose adjustments, and fewer required INR measurements. A meta-analysis of three randomized trials examined the effect of genotype algorithms on major bleeding events.109 A non-significant trend towards a reduction in this adverse outcome was observed with a genotype-guided approach (adjusted risk ratio 0.68; 95% CI 0.22–2.06).

Not surprisingly, results of cost-effectiveness analyses are similarly divided. On the one hand, a preliminary study calculated that pharmacogenetic guidance of warfarin dosing may avert as many as 85,000 hemorrhages and 17,000 strokes, providing attributable health care savings of between $100 million to $2 billion.110 A more conservative outlook incorporating the cost of genetic testing, taken to be $400, estimated only a modest 10% chance that genotype-guided dosing would prove cost-effective.


Warfarin has significantly contributed to the prevention of morbidity and mortality associated with thromboembolism for the past 60 years. Despite its established role and widespread use, warfarin therapy is accompanied by a high incidence of adverse events due to a narrow therapeutic range and interindividual differences in response to the drug, with as much as a 30-fold variance in maintenance dose requirements between patients.111 Inhibitors of direct thrombin and factor Xa may overcome these dosing concerns,112 an accepted limitation of warfarin; however, the low cost and availability of warfarin coupled with its longer-term data for conditions ranging from venous thromboembolism to mechanical valves will undoubtedly assure the ongoing need for warfarin and improved dosing strategies.

Pharmacogenetic studies to date suggest a role for CKYP2C9 and VKORC1 variants in safely and effectively initiating warfarin therapy, though definitive clinical outcome data regarding both thromboembolic events and bleeding complications are still wanting. In light of ongoing controversies regarding the incremental benefit of genetic testing in anticoagulation, it is perhaps a bit surprising that in 2007 the US Food and Drug Administration incorporated consideration of genotyping in warfarin labeling.113 Contrary to this approach, the 2008 American College of Chest Physicians’ guidelines recommended against the use of pharmacogenetic-based initial dosing to individualize warfarin dosing.114

Large randomized clinical trials are underway to further characterize the clinical utility of pharmacogenetic warfarin dosing. The Clarification of Optimal Anticoagulation through Genetics (COAG) trial is investigating the effect of CYP2C9 and VKORC1 genotype-guided dosing compared to the usual clinical approach on the percentage of time warfarin-treated patients achieve an INR within the therapeutic range.115 The Genetics Informatics Trial of Warfarin to Prevent Deep Venous Thrombosis (GIFT) will assess the effect on postoperative patients of genotype-guided warfarin dosing on venous thromboembolic and bleeding events.116 Care must be taken in interpreting and generalizing results based on design considerations, as exemplified by the Medco-Mayo study. Of note, randomized trials performed primarily in academic tertiary care centers may underestimate real-world benefit, given the increased frequency of INR monitoring observed among academic-based compared to community-based practices. Ongoing studies will better determine whether genotype-guided warfarin therapy may confer safer and more effective anticoagulation.


Advances in pharmacogenomics as well as functional assays of vascular biology now permit improved characterization of an individual’s response to medical therapy for vascular disease. Novel strategies have been proposed to tailor anti-platelet, antihypertensive, lipid-lowering, and antithrombotic therapies. Whether or not these emerging strategies to achieve personalized vascular medicine ultimately yield improvements in clinical outcomes – reductions in either drug-related adverse effects or atherothrombotic events – and pass cost-effectiveness thresholds remains to be seen.



The salaries of Dr deGoma, Dr Usman, and Dr Mohler are partially funded via NIH National Heart, Lung, and Blood Institute grant K12 HL083772-01.


Conflicts of interest

None declared.


1. Hippocrates. Diseases III. Cambridge: Loeb Classic Library; 1988.
2. Lesko LJ. Personalized medicine: elusive dream or imminent reality? Clin Pharmacol Ther. 2007;81:807–816. [PubMed]
3. Sykiotis GP, Kalliolias GD, Papavassiliou AG. Pharmacogenetic principles in the Hippocratic writings. J Clin Pharmacol. 2005;45:1218–1220. [PubMed]
4. Schlendorf KH, Nasir K, Blumenthal RS. Limitations of the Framingham risk score are now much clearer. Prev Med. 2009;48:115–116. [PubMed]
5. Greenland P, Alpert JS, Beller GA, et al. 2010 ACCF/AHA guideline for assessment of cardiovascular risk in asymptomatic adults: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. Circulation. 2010;122:e584–636. [PubMed]
6. Kathiresan S, Melander O, Anevski D, et al. Polymorphisms associated with cholesterol and risk of cardiovascular events. N Engl J Med. 2008;358:1240–1249. [PubMed]
7. Ridker PM, Buring JE, Rifai N, Cook NR. Development and validation of improved algorithms for the assessment of global cardiovascular risk in women: the Reynolds Risk Score. JAMA. 2007;297:611–619. [PubMed]
8. Aspinall MG, Hamermesh RG. Realizing the promise of personalized medicine. Harv Bus Rev. 2007;85:108–117. 165. [PubMed]
9. Piquette-Miller M, Grant DM. The art and science of personalized medicine. Clin Pharmacol Ther. 2007;81:311–315. [PubMed]
10. Lunshof JE, Pirmohamed M, Gurwitz D. Personalized medicine: decades away? Pharmacogenomics. 2006;7:237–241. [PubMed]
11. Hamburg MA, Collins FS. The path to personalized medicine. N Engl J Med. 2010;363:301–304. [PubMed]
12. Woodcock J. The prospects for ‘personalized medicine’ in drug development and drug therapy. Clin Pharmacol Ther. 2007;81:164–169. [PubMed]
13. Antithrombotic Trialists’ Collaboration. Collaborative meta-analysis of randomised trials of antiplatelet therapy for prevention of death, myocardial infarction, and stroke in high risk patients. BMJ. 2002;324:71–86. [PMC free article] [PubMed]
14. Yusuf S, Mehta SR, Zhao F, et al. Early and late effects of clopidogrel in patients with acute coronary syndromes. Circulation. 2003;107:966–972. [PubMed]
15. Mehta SR, Yusuf S, Peters RJ, et al. Effects of pretreatment with clopidogrel and aspirin followed by long-term therapy in patients undergoing percutaneous coronary intervention: the PCI-CURE study. Lancet. 2001;358:527–533. [PubMed]
16. Chen ZM, Jiang LX, Chen YP, et al. Addition of clopidogrel to aspirin in 45,852 patients with acute myocardial infarction: randomised placebo-controlled trial. Lancet. 2005;366:1607–1621. [PubMed]
17. Mehta JL, Mohandas B. Aspirin resistance: fact or fiction? A point of view. World J Cardiol. 2010;2:280–288. [PMC free article] [PubMed]
18. Migliorini A, Valenti R, Marcucci R, et al. High residual platelet reactivity after clopidogrel loading and long-term clinical outcome after drug-eluting stenting for unprotected left main coronary disease. Circulation. 2009;120:2214–2221. [PubMed]
19. Krasopoulos G, Brister SJ, Beattie WS, Buchanan MR. Aspirin ‘resistance’ and risk of cardiovascular morbidity: systematic review and meta-analysis. BMJ. 2008;336:195–198. [PMC free article] [PubMed]
20. Geisler T, Langer H, Wydymus M, et al. Low response to clopidogrel is associated with cardiovascular outcome after coronary stent implantation. Eur Heart J. 2006;27:2420–2425. [PubMed]
21. Angiolillo DJ, Fernandez-Ortiz A, Bernardo E, et al. Variability in individual responsiveness to clopidogrel: clinical implications, management, and future perspectives. J Am Coll Cardiol. 2007;49:1505–1516. [PubMed]
22. Hochholzer W, Trenk D, Bestehorn HP, et al. Impact of the degree of peri-interventional platelet inhibition after loading with clopidogrel on early clinical outcome of elective coronary stent placement. J Am Coll Cardiol. 2006;48:1742–1750. [PubMed]
23. Gasparyan AY, Watson T, Lip GY. The role of aspirin in cardiovascular prevention: implications of aspirin resistance. J Am Coll Cardiol. 2008;51:1829–1843. [PubMed]
24. Nielsen HL, Kristensen SD, Thygesen SS, et al. Aspirin response evaluated by the VerifyNow Aspirin System and light transmission aggregometry. Thromb Res. 2008;123:267–273. [PubMed]
25. Neubauer H, Kaiser AF, Endres HG, et al. Tailored antiplatelet therapy can overcome clopidogrel and aspirin resistance – The BOchum CLopidogrel and Aspirin Plan (BOCLA-Plan) to improve antiplatelet therapy. BMC Med. 2011;9:3. [PMC free article] [PubMed]
26. Gladding P, Webster M, Zeng I, et al. The pharmacogenetics and pharmacodynamics of clopidogrel response: an analysis from the PRINC (Plavix Response in Coronary Intervention) trial. JACC Cardiovasc Interv. 2008;1:620–627. [PubMed]
27. Lev EI, Solodky A, Harel N, et al. Treatment of aspirin-resistant patients with omega-3 fatty acids versus aspirin dose escalation. J Am Coll Cardiol. 2010;55:114–121. [PubMed]
28. Gajos G, Rostoff P, Undas A, Piwowarska W. Effects of polyunsaturated omega-3 fatty acids on responsiveness to dual antiplatelet therapy in patients undergoing percutaneous coronary intervention: the OMEGA-PCI (OMEGA-3 fatty acids after pci to modify responsiveness to dual antiplatelet therapy) study. J Am Coll Cardiol. 2010;55:1671–1678. [PubMed]
29. Suh JW, Lee SP, Park KW, et al. Multicenter randomized trial evaluating the efficacy of cilostazol on ischemic vascular complications after drug-eluting stent implantation for coronary heart disease: results of the CILON-T (influence of CILostazol-based triple antiplatelet therapy ON ischemic complication after drug-eluting stenT implantation) trial. J Am Coll Cardiol. 2011;57:280–289. [PubMed]
30. Jeong YH, Lee SW, Choi BR, et al. Randomized comparison of adjunctive cilostazol versus high maintenance dose clopidogrel in patients with high post-treatment platelet reactivity: results of the ACCEL-RESISTANCE (Adjunctive Cilostazol Versus High Maintenance Dose Clopidogrel in Patients With Clopidogrel Resistance) randomized study. J Am Coll Cardiol. 2009;53:1101–1109. [PubMed]
31. Price MJ, Berger PB, Teirstein PS, et al. GRAVITAS Investigators Standard- vs high-dose clopidogrel based on platelet function testing after percutaneous coronary intervention: the GRAVITAS randomized trial. JAMA. 2011;305:1097–1105. [PubMed]
32. [April 2011];HeartWire, ‘TRIGGER-PCI Halted’ 2011
33. Chin CT, Roe MT, Fox KA, et al. TRILOGY ACS Steering Committee. Study design and rationale of a comparison of prasugrel and clopidogrel in medically managed patients with unstable angina/non-ST-segment elevation myocardial infarction: the Targeted platelet Inhibition to cLarify the Optimal strateGy to medicallY manage Acute Coronary Syndromes (TRILOGY ACS) trial. Am Heart J. 2010;160:16–22. [PubMed]
34. Simon T, Verstuyft C, Mary-Krause M, et al. Genetic determinants of response to clopidogrel and cardiovascular events. N Engl J Med. 2009;360:363–375. [PubMed]
35. Kim KA, Park PW, Hong SJ, Park JY. The effect of CYP2C19 polymorphism on the pharmacokinetics and pharmacodynamics of clopidogrel: a possible mechanism for clopidogrel resistance. Clin Pharmacol Ther. 2008;84:236–242. [PubMed]
36. Mega JL, Close SL, Wiviott SD, et al. Genetic variants in ABCB1 and CYP2C19 and cardiovascular outcomes after treatment with clopidogrel and prasugrel in the TRITON-TIMI 38 trial: a pharmacogenetic analysis. Lancet. 2010;376:1312–1319. [PMC free article] [PubMed]
37. Trenk D, Hochholzer W, Fromm MF, et al. Cytochrome P450 2C19 681G>A polymorphism and high on-clopidogrel platelet reactivity associated with adverse 1-year clinical outcome of elective percutaneous coronary intervention with drug-eluting or bare-metal stents. J Am Coll Cardiol. 2008;51:1925–1934. [PubMed]
38. Harmsze AM, van Werkum JW, Ten Berg JM, et al. CYP2C19*2 and CYP2C9*3 alleles are associated with stent thrombosis: a case–control study. Eur Heart J. 2010;31:3046–3053. [PubMed]
39. Varenhorst C, James S, Erlinge D, et al. Assessment of P2Y(12) inhibition with the point-of-care device VerifyNow P2Y12 in patients treated with prasugrel or clopidogrel coad-ministered with aspirin. Am Heart J. 2009;157:562 e1–9. [PubMed]
40. Hulot JS, Bura A, Villard E, et al. Cytochrome P450 2C19 loss-of-function polymorphism is a major determinant of clopidogrel responsiveness in healthy subjects. Blood. 2006;108:2244–2247. [PubMed]
41. Gladding P, Webster M, Zeng I, et al. The antiplatelet effect of higher loading and maintenance dose regimens of clopidogrel: the PRINC (Plavix Response in Coronary Intervention) trial. JACC Cardiovasc Interv. 2008;1:612–619. [PubMed]
42. Barker CM, Murray SS, Teirstein PS, Kandzari DE, Topol EJ, Price MJ. Pilot study of the antiplatelet effect of increased clopidogrel maintenance dosing and its relationship to CYP2C19 genotype in patients with high on-treatment reactivity. JACC Cardiovasc Interv. 2010;3:1001–1007. [PubMed]
43. Kim IS, Jeong YH, Park Y, et al. Platelet inhibition by adjunctive cilostazol versus high maintenance-dose clopidogrel in patients with acute myocardial infarction according to cytochrome P450 2C19 genotype. JACC Cardiovasc Interv. 2011;4:381–391. [PubMed]
44. Bouman HJ, Schomig E, van Werkum JW, et al. Paraoxonase-1 is a major determinant of clopidogrel efficacy. Nat Med. 2011;17:110–116. [PubMed]
45. Turner ST, Schwartz GL, Boerwinkle E. Personalized medicine for high blood pressure. Hypertension. 2007;50:1–5. [PMC free article] [PubMed]
46. Izzo JL, Jr, Sica DA, Black HR. American Heart Association Hypertension Primer. 4. New York: Lippincott Williams & Wilkins; 2007.
47. Laragh JH, Baer L, Brunner HR, Buhler FR, Sealey JE, Vaughan ED., Jr Renin, angiotensin and aldosterone system in pathogenesis and management of hypertensive vascular disease. Am J Med. 1972;52:633–652. [PubMed]
48. Laragh J. Laragh’s lessons in pathophysiology and clinical pearls for treating hypertension. Am J Hypertens. 2001;14:307–310. [PubMed]
49. Laragh J. Laragh’s lessons in pathophysiology and clinical pearls for treating hypertension. Am J Hypertens. 2001;14:491–503. [PubMed]
50. Turner ST, Schwartz GL, Chapman AB, et al. Plasma renin activity predicts blood pressure responses to beta-blocker and thiazide diuretic as monotherapy and add-on therapy for hypertension. Am J Hypertens. 2010;23:1014–1022. [PMC free article] [PubMed]
51. Preston RA, Materson BJ, Reda DJ, et al. Age-race subgroup compared with renin profile as predictors of blood pressure response to antihypertensive therapy. Department of Veterans Affairs Cooperative Study Group on Antihypertensive Agents. JAMA. 1998;280:1168–1172. [PubMed]
52. Alderman MH, Cohen HW, Sealey JE, Laragh JH. Pressor responses to antihypertensive drug types. Am J Hypertens. 2010;23:1031–1037. [PubMed]
53. Egan BM, Basile JN, Rehman SU, et al. Plasma renin test-guided drug treatment algorithm for correcting patients with treated but uncontrolled hypertension: a randomized controlled trial. Am J Hypertens. 2009;22:792–801. [PubMed]
54. Esler MD, Krum H, Sobotka PA, Schlaich MP, Schmieder RE, Bohm M. Renal sympathetic denervation in patients with treatment-resistant hypertension (The Symplicity HTN-2 Trial): a randomised controlled trial. Lancet. 2010;376:1903–1909. [PubMed]
55. Arnett DK, Davis BR, Ford CE, et al. Pharmacogenetic association of the angiotensin-converting enzyme insertion/deletion polymorphism on blood pressure and cardiovascular risk in relation to antihypertensive treatment: the Genetics of Hypertension-Associated Treatment (GenHAT) study. Circulation. 2005;111:3374–3383. [PubMed]
56. Harrap SB, Tzourio C, Cambien F, et al. The ACE gene I/D polymorphism is not associated with the blood pressure and cardiovascular benefits of ACE inhibition. Hypertension. 2003;42:297–303. [PubMed]
57. Brugts JJ, Isaacs A, Boersma E, et al. Genetic determinants of treatment benefit of the angiotensin-converting enzyme-inhibitor perindopril in patients with stable coronary artery disease. Eur Heart J. 2010;31:1854–1864. [PubMed]
58. Brugts JJ, Boersma E, Simoons ML. Tailored therapy of ACE inhibitors in stable coronary artery disease: pharmaco-genetic profiling of treatment benefit. Pharmacogenomics. 2010;11:1115–1126. [PubMed]
59. Furberg CD. Renin-guided treatment of hypertension: time for action. Am J Hypertens. 2010;23:929–930. [PubMed]
60. Brown MJ. Heterogeneity of blood pressure response to therapy. Am J Hypertens. 2010;23:926–928. [PubMed]
61. Report of the Joint National Committee on Detection, Evaluation, and Treatment of High Blood Pressure. A cooperative study. JAMA. 1977;237:255–261. [PubMed]
62. Chobanian AV, Bakris GL, Black HR, et al. Seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure. Hypertension. 2003;42:1206–1252. [PubMed]
63. Mancia G, Laurent S, Agabiti-Rosei E, et al. Reappraisal of European guidelines on hypertension management: a European Society of Hypertension Task Force document. J Hypertens. 2009;27:2121–2158. [PubMed]
64. Sehgal AR. Overlap between whites and blacks in response to antihypertensive drugs. Hypertension. 2004;43:566–572. [PubMed]
65. Mokwe E, Ohmit SE, Nasser SA, et al. Determinants of blood pressure response to quinapril in black and white hypertensive patients: the Quinapril Titration Interval Management Evaluation trial. Hypertension. 2004;43:1202–1207. [PubMed]
66. Fonseca V, Bakris GL, Bell DS, et al. Differential effect of beta-blocker therapy on insulin resistance as a function of insulin sensitizer use: results from GEMINI. Diabet Med. 2007;24:759–763. [PubMed]
67. Torp-Pedersen C, Metra M, Charlesworth A, et al. Effects of metoprolol and carvedilol on pre-existing and new onset diabetes in patients with chronic heart failure: data from the Carvedilol Or Metoprolol European Trial (COMET) Heart. 2007;93:968–973. [PMC free article] [PubMed]
68. Poole-Wilson PA, Swedberg K, Cleland JG, et al. Comparison of carvedilol and metoprolol on clinical outcomes in patients with chronic heart failure in the Carvedilol Or Metoprolol European Trial (COMET): randomised controlled trial. Lancet. 2003;362:7–13. [PubMed]
69. Remme WJ, Torp-Pedersen C, Cleland JG, et al. Carvedilol protects better against vascular events than metoprolol in heart failure: results from COMET. J Am Coll Cardiol. 2007;49:963–971. [PubMed]
70. Wald DS, Law M, Morris JK, Bestwick JP, Wald NJ. Combination therapy versus monotherapy in reducing blood pressure: meta-analysis on 11,000 participants from 42 trials. Am J Med. 2009;122:290–300. [PubMed]
71. Spence JD. Physiologic tailoring of therapy for resistant hypertension: 20 years’ experience with stimulated renin profiling. Am J Hypertens. 1999;12:1077–1083. [PubMed]
72. Ostchega Y, Yoon SS, Hughes J, Louis T. Hypertension awareness, treatment, and control – continued disparities in adults: United States, 2005–2006. NCHS Data Brief. 2008 Jan;(3):1–8. [PubMed]
73. Randomised trial of cholesterol lowering in 4444 patients with coronary heart disease: the Scandinavian Simvastatin Survival Study (4S) Lancet. 1994;344:1383–1389. [PubMed]
74. Heart Protection Study Collaborative Group. Heart Protection Study of cholesterol lowering with simvastatin in 20,536 high-risk individuals: a randomised placebo-controlled trial. Lancet. 2002;360:7–22. [PubMed]
75. Ridker PM, Danielson E, Fonseca FA, et al. Rosuvastatin to prevent vascular events in men and women with elevated C-reactive protein. N Engl J Med. 2008;359:2195–2207. [PubMed]
76. Sever PS, Dahlof B, Poulter NR, et al. Prevention of coronary and stroke events with atorvastatin in hypertensive patients who have average or lower-than-average cholesterol concentrations, in the Anglo-Scandinavian Cardiac Outcomes Trial—Lipid Lowering Arm (ASCOT-LLA): a multicentre randomised controlled trial. Lancet. 2003;361:1149–1158. [PubMed]
77. Shepherd J, Cobbe SM, Ford I, et al. Prevention of coronary heart disease with pravastatin in men with hypercholesterolemia. West of Scotland Coronary Prevention Study Group. N Engl J Med. 1995;333:1301–1307. [PubMed]
78. Kashani A, Phillips CO, Foody JM, et al. Risks associated with statin therapy: a systematic overview of randomized clinical trials. Circulation. 2006;114:2788–2797. [PubMed]
79. Bruckert E, Hayem G, Dejager S, Yau C, Begaud B. Mild to moderate muscular symptoms with high-dosage statin therapy in hyperlipidemic patients—the PRIMO study. Cardiovasc Drugs Ther. 2005;19:403–414. [PubMed]
80. Boden WE, O’Rourke RA, Teo KK, et al. Optimal medical therapy with or without PCI for stable coronary disease. N Engl J Med. 2007;356:1503–1516. [PubMed]
81. Frye RL, August P, Brooks MM, et al. A randomized trial of therapies for type 2 diabetes and coronary artery disease. N Engl J Med. 2009;360:2503–2515. [PMC free article] [PubMed]
82. ACCORD Study Group. Ginsberg HN, Elam MB, Lovato LC, et al. Effects of combination lipid therapy in type 2 diabetes mellitus. N Engl J Med. 2010;362:1563–1574. [PMC free article] [PubMed]
83. Gupta A, Thompson PD. The relationship of vitamin D deficiency to statin myopathy. Atherosclerosis. 2011;215:23–29. [PubMed]
84. Ghatak A, Faheem O, Thompson PD. The genetics of statin-induced myopathy. Atherosclerosis. 2010;210:337–343. [PubMed]
85. Kameyama Y, Yamashita K, Kobayashi K, Hosokawa M, Chiba K. Functional characterization of SLCO1B1 (OATP-C) variants, SLCO1B1*5, SLCO1B1*15 and SLCO1B1*15+C1007G, by using transient expression systems of HeLa and HEK293 cells. Pharmacogenet Genomics. 2005;15:513–522. [PubMed]
86. Pasanen MK, Fredrikson H, Neuvonen PJ, Niemi M. Different effects of SLCO1B1 polymorphism on the pharmacokinetics of atorvastatin and rosuvastatin. Clin Pharmacol Ther. 2007;82:726–733. [PubMed]
87. Pasanen MK, Neuvonen M, Neuvonen PJ, Niemi M. SLCO1B1 polymorphism markedly affects the pharmacokinetics of simvastatin acid. Pharmacogenet Genomics. 2006;16:873–879. [PubMed]
88. Link E, Parish S, Armitage J, et al. SLCO1B1 variants and statin-induced myopathy—a genomewide study. N Engl J Med. 2008;359:789–799. [PubMed]
89. Voora D, Shah SH, Spasojevic I, et al. The SLCO1B1*5 genetic variant is associated with statin-induced side effects. J Am Coll Cardiol. 2009;54:1609–1616. [PMC free article] [PubMed]
90. Brunham LR, Lansberg PJ, Zhang L, et al. Differential effect of the rs4149056 variant in SLCO1B1 on myopathy associated with simvastatin and atorvastatin. Pharmacogenomics J. 2011 Jan 18; Epub ahead of print. [PubMed]
91. Voora D, Ginsburg GS. Pharmacogenetics of the response to statins. Curr Cardiovasc Risk Rep. 2009;3:434–440.
92. Glueck CJ, Aregawi D, Agloria M, et al. Rosuvastatin 5 and 10 mg/d: a pilot study of the effects in hypercholesterolemic adults unable to tolerate other statins and reach LDL cholesterol goals with nonstatin lipid-lowering therapies. Clin Ther. 2006;28:933–942. [PubMed]
93. Manninen V, Tenkanen L, Koskinen P, et al. Joint effects of serum triglyceride and LDL cholesterol and HDL cholesterol concentrations on coronary heart disease risk in the Helsinki Heart Study. Implications for treatment. Circulation. 1992;85:37–45. [PubMed]
94. Secondary prevention by raising HDL cholesterol and reducing triglycerides in patients with coronary artery disease: the Bezafibrate Infarction Prevention (BIP) study. Circulation. 2000;102:21–27. [PubMed]
95. Tai ES, Ordovas JM. Clinical significance of apolipoprotein A5. Curr Opin Lipidol. 2008;19:349–354. [PMC free article] [PubMed]
96. Lai CQ, Arnett DK, Corella D, et al. Fenofibrate effect on triglyceride and postprandial response of apolipoprotein A5 variants: the GOLDN study. Arterioscler Thromb Vasc Biol. 2007;27:1417–1425. [PubMed]
97. Hegele RA, Pollex RL. Apolipoprotein A-V genetic variation and plasma lipoprotein response to fibrates. Arterioscler Thromb Vasc Biol. 2007;27:1224–1227. [PubMed]
98. Sharp Collaborative Group. Study of Heart and Renal Protection (SHARP): randomized trial to assess the effects of lowering low-density lipoprotein cholesterol among 9,438 patients with chronic kidney disease. Am Heart J. 2010;160:785–794.e10. [PubMed]
99. Hegele RA, Guy J, Ban MR, Wang J. NPC1L1 haplotype is associated with inter-individual variation in plasma low-density lipoprotein response to ezetimibe. Lipids Health Dis. 2005;4:16. [PMC free article] [PubMed]
100. Gage BF, Eby C, Johnson JA, et al. Use of pharmacogenetic and clinical factors to predict the therapeutic dose of warfarin. Clin Pharmacol Ther. 2008;84:326–331. [PMC free article] [PubMed]
101. Glurich I, Burmester JK, Caldwell MD. Understanding the pharmacogenetic approach to warfarin dosing. Heart Fail Rev. 2010;15:239–248. [PubMed]
102. Flockhart DA, O’Kane D, Williams MS, et al. Pharmacogenetic testing of CYP2C9 and VKORC1 alleles for warfarin. Genet Med. 2008;10:139–150. [PubMed]
103. Tan GM, Wu E, Lam YY, Yan BP. Role of warfarin pharmacogenetic testing in clinical practice. Pharmacogenomics. 2010;11:439–448. [PubMed]
104. Wadelius M, Pirmohamed M. Pharmacogenetics of warfarin: current status and future challenges. Pharmacogenomics J. 2007;7:99–111. [PubMed]
105. Caraco Y, Blotnick S, Muszkat M. CYP2C9 genotype-guided warfarin prescribing enhances the efficacy and safety of anticoagulation: a prospective randomized controlled study. Clin Pharmacol Ther. 2008;83:460–470. [PubMed]
106. Yang L, Ge W, Yu F, Zhu H. Impact of VKORC1 gene polymorphism on interindividual and interethnic warfarin dosage requirement—a systematic review and meta analysis. Thromb Res. 2010;125:e159–166. [PubMed]
107. Epstein RS, Moyer TP, Aubert RE, et al. Warfarin genotyping reduces hospitalization rates results from the MM-WES (Medco-Mayo Warfarin Effectiveness study) J Am Coll Cardiol. 2010;55:2804–2812. [PubMed]
108. Anderson JL, Horne BD, Stevens SM, et al. Randomized trial of genotype-guided versus standard warfarin dosing in patients initiating oral anticoagulation. Circulation. 2007;116:2563–2570. [PubMed]
109. Eckman MH, Rosand J, Greenberg SM, Gage BF. Cost-effectiveness of using pharmacogenetic information in warfarin dosing for patients with nonvalvular atrial fibrillation. Ann Intern Med. 2009;150:73–83. [PubMed]
110. McWilliam A, Lutter R, Nardinelli C. Healthcare impact of personalized medicine using genetic testing: an exploratory analysis for warfarin. Per Med. 2008;5:279–284.
111. Kim MJ, Huang SM, Meyer UA, Rahman A, Lesko LJ. A regulatory science perspective on warfarin therapy: a pharmacogenetic opportunity. J Clin Pharmacol. 2009;49:138–146. [PubMed]
112. Wrigley BJ, Lip GY, Shantsila E. Novel oral anticoagulants: the potential relegation of vitamin K antagonists in clinical practice. Int J Clin Pract. 2010;64:835–838. [PubMed]
113. Rosove MH, Grody WW. Should we be applying warfarin pharmacogenetics to clinical practice? No, not now. Ann Intern Med. 2009;151:270–273. W95. [PubMed]
114. Ansell J, Hirsh J, Hylek E, Jacobson A, Crowther M, Palareti G. Pharmacology and management of the vitamin K antagonists: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines (8th Edition) Chest. 2008;133:160S–198S. [PubMed]
115. French B, Joo J, Geller NL, et al. COAG (Clarification of Optimal Anticoagulation through Genetics) Investigators. Statistical design of personalized medicine interventions: the Clarification of Optimal Anticoagulation through Genetics (COAG) trial. Trials. 2010;11:108. [PMC free article] [PubMed]
116. Do EJ, Lenzini P, Eby CS, et al. Genetics informatics trial (GIFT) of warfarin to prevent deep vein thrombosis (DVT): rationale and study design. Pharmacogenomics J. 2011;1:1–8. [PMC free article] [PubMed]