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Circulation. Author manuscript; available in PMC Sep 23, 2009.
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PMCID: PMC2730023

Ethnic Differences in Cardiovascular Drug Response: Potential Contribution of Pharmacogenetics


In the early 1980's clinical differences in response to the blood pressure lowering effects of β-blockers, and to a lesser extent, diuretics between ethnic groups were noted. The most convincing evidence at that time came from a VA Cooperative Trial,1 which along with other smaller studies, suggested that whites (those of European ancestry) had a better antihypertensive response to β-blockers than blacks (those of African ancestry), while blacks had a slight better response to diuretics than whites. Shortly after the first ACE inhibitor was approved in the mid-1980's, it was also recognized that whites responded more favorably to ACE inhibitors than did blacks. Over time these differences in response became well accepted, such that ethnicity began to be used in helping to guide selection of antihypertensive drug therapy.2, 3 While the ethnic differences in response between β-blockers and ACE inhibitors in hypertension are perhaps the mostly widely recognized examples of ethnic differences in response to cardiovascular drugs, there are others.

Pharmacogenetics is a field that seeks to unravel the genetic underpinnings of variable drug responses.4 Given the recognized ethnic differences in drug responses, and the fact that many genetic polymorphisms differ in frequency based on ethnicity/ancestry, questions about whether pharmacogenetics may also lead to an understanding of the ethnic differences in drug response are not surprising. This review will summarize the most widely recognized examples of cardiovascular drugs with differential response by ethnicity, and the evidence that pharmacogenetics data may aid in our understanding of these differences. Given that there are many examples in the literature of genetic associations that are not replicated, the pharmacogenetic examples discussed herein will come from those for which there is some evidence of replication, or for which there have been multiple negative findings.

Given the socially charged issues surrounding race and genetics, we will typically refer to groups either as ethnic groups (meaning groups who may have similar ancestral origins, and who share certain social or cultural practices) or will refer to continental ancestry, referring to the three major continental populations from which the human population mainly derives (namely European, African and Asian, ancestry).

Ethnic differences in response to warfarin therapy

Ethnic differences in the warfarin dose required for an international normalized ratio (INR) between 2-3 are well documented in the literature, but do not appear to be widely appreciated by clinicians. For example, the anticoagulation consensus guidelines that relate specifically to warfarin do not mention the influence of ethnicity on the typical maintenance dose,5 a fact that may result from trials conducted predominantly in white populations. Figure 1 depicts average warfarin dose requirements for Asians, Hispanics, whites and blacks to maintain an INR of 2-3.6 While these data were derived from a relatively small sample, average daily doses of 3.4 mg in Asians, 5.1 mg in whites and 6.1 mg in blacks are representative of the literature for these ethnic groups. Given that most dosing algorithms recommend initiating therapy at 5 mg daily, it is apparent from Figure 1 that this is a reasonable estimate of the starting dose in whites, but likely an excessive dose in Asians and an inadequate dose in blacks. The lower dose requirements in Asians was sufficiently recognized to warrant special notation in FDA approved labeling for warfarin, which indicates requirements for a lower dose in Asians.7 While some would argue that initiating therapy with an inappropriate dose will be quickly corrected based on close monitoring of INR, data clearly suggest the risk of bleeding is highest in the first 30 days of therapy, when the appropriate dose is typically still being determined.8 This would suggest that more accurate initial dosing may have the potential to reduce the early risk of bleeding.

Figure 1
Average warfarin dose requirements, by ethnicity, to maintain a therapeutic INR (2-3). Reproduced from Dang et al6, with permission

In addition to differences in dose, there are questions about whether risks of warfarin therapy also differ by ethnicity. The large trials that established an INR range of 2-3 to balance the benefits (reduced thromboembolic events) with the risks (bleeding) of warfarin therapy were conducted almost exclusively in whites. Thus, it is not clear is this is the most appropriate INR range across ethnic groups, although some data suggest it may not be in Asians. For example, in a study of 563 Taiwanese patients with mechanical valve replacements (where the usual INR range is 2.5-3.5), investigators found the risks of thromboembolism were not different for those with an INR > 2 versus <2.9 In a study of 491 Chinese patients treated with warfarin, the INR associated with the lowest hemorrhagic and thromboembolic rate was 1.8 to 2.4.10 These data suggest Asians may have greater thromboembolic protection at lower INRs than whites. Finally in a study of 667 Japanese, nonvalvular atrial fibrillation patients studied for one year, INR ≥ 2.27 was associated with an odds ratio (95% confidence interval) of 4.33 (1.30-14.39) for major bleeding. Further, despite low-dose warfarin therapy (target INR 1.6-2.6) the rate of major bleeding and intracranial hemorrhage was similar to the rate observed in Western populations with full dose anticoagulation (target INR 2-3) and approximately double the rate observed in Western populations for low-intensity warfarin therapy.11 Combined, these data suggest that Asians might require a lower INR for protection from thromboembolism, and be at increased risk of bleeding at lower INRs.

Warfarin pharmacogenetics

Among cardiovascular drugs, warfarin has the strongest pharmacogenetics data, which may also help explain ethnic differences in dose requirements for a stable INR. Two genes have been clearly associated with variable warfarin dose, those encoding the major enzyme responsible for warfarin's metabolism (cytochrome P450 2C9, CYP2C9), and the protein upon which warfarin exerts its pharmacological effect (vitamin K epoxide reductase, VKORC1). The first report of genetic association with warfarin dose and CYP2C9 genotype was in 1999,12 and numerous studies since that time have documented this association, across a variety of ethnic populations (see reviews13, 14). Specifically, there are two polymorphisms, commonly called CYP2C9*2 and CYP2C9*3, both of which reduce the normal metabolic activity of the enzyme, although the *3 polymorphism does so to a greater extent than the *2 polymorphism. In a 2005 meta-analysis, which included 2,775 patients and eight different studies relating the polymorphisms to warfarin dose, the analysis suggested that carriers of at least one variant copy of the *2 allele required 0.85 mg less of warfarin daily (95% CI: -1.11 mg to -0.60 mg), and those carrying at least one copy of the *3 allele required 1.92 mg less of warfarin daily (95% CI: -2.47 mg to -1.37 mg).14 Several studies have also documented that individuals with CYP2C9 variant alleles require a longer period of time to achieve a stable dose, and are at increased bleeding risk, particularly during the period of therapy initiation (i.e. first 1-3 months).12, 14-16 Data on the influence of CYP2C9 variants are available from multiple populations in the U.S., Europe and Asia and all consistently show a genetic association with CYP2C9 polymorphisms. What differs however is the frequency of the polymorphisms, and thus their overall impact in that ethnic population. Table 1 depicts allele frequencies for the CYP2C9 variant alleles and shows there are clear differences by ethnicity. Specifically, variant alleles for CYP2C9 are much more common in whites than other groups, thus at a population level, the impact of CYP2C9 variants on warfarin dose is greater in whites. This may help to explain the slightly lower doses in whites versus blacks, but does not explain the very low doses typically required by Asians.

Table 1
Ethnic differences in variant allele frequencies (as %) for genes important to variable warfarin dose/response (CYP2C9 and VKORC1)

Differing warfarin sensitivities by ethnicity are perhaps better explained by variant alleles in VKORC1. A number of different polymorphisms have been studied in this gene, and evidence currently points to a promoter polymorphism (referred to in the literature at 3673 G>A or -1639 G>A) as the most likely candidate for the functional polymorphism.17, 18 Importantly, many different polymorphisms have been studied, and due to a high degree of linkage disequilbrium (inheritance of SNPs together) between these SNPs in whites and Asians, the various SNPs tested all gave similar genetic associations. However, like with many other genes, the degree of linkage disequilibrium in VKORC1 is lower in blacks than other groups. In analyses in our laboratory of a variety of VKORC1 SNPs, only 3673 and 6484 were significantly associated with warfarin dose in blacks, while numerous SNPs were associated with dose in whites. This is explained by high levels of linkage disequilibrium across numerous SNPs in whites, but only these two SNPs in blacks. This emphasizes the importance of studying the functional polymorphism, since reliance on linkage disequilibrium between SNPs can be problematic across different ancestral populations. Table 1 also provides a comparison by ethnicity for the presumed functional VKORC1 polymorphism, and reveals striking differences, such that the “variant” (i.e. less common allele) in whites and blacks, (with approximate frequencies of 45% and 10%, respectively) is the major allele in Asians, with a frequency of 90-95%.19

To date, there have been at > 30 studies published on the genetic association between VKORC1 SNPs and warfarin dose, and all have shown a significant association, with the variant allele being associated with a lower warfarin dose.13, 17, 18, 20-25 These studies have included numerous white populations from the U.S., Europe and Israel, along with Japanese, Chinese, Indians, and Malays. In whites, across a variety of studies, the average dose for GG homozygotes (using -1639 as the reference) was 6.1 mg daily, those with a GA genotype required 4.5 mg daily and AA homozygotes required 3.0 mg daily. Among Asians, doses for GG and GA have often not been reported separately (due to low G allele frequency) but across studies AA homozygotes required 2.8 mg daily, similar to the dose required by whites with the AA genotype. In the one study with a reasonably sized black cohort, daily dose requirements for GG, GA, and AA genotypes were 5.7 mg, 4.5 mg and 3.1 mg, respectively, nearly identical to that in whites.20 Given that most blacks have the GG genotype, and most Asians the AA genotype, these data suggest genetics may contribute substantially to the ethnic differences in dose.

Taken together, there is little doubt that genetic variability helps explain differences in warfarin dose requirements, particularly the VKORC1 polymorphisms. Numerous different investigative groups have attempted to determine the amount of variability in warfarin dose that can be explained by genetic, demographic and clinical factors. These studies suggest that between 30 and 60% of warfarin dose variability can be explained, with genetic factors responsible about explaining about two-thirds of that variability. Clinical/demographic factors that have also consistently been associated with warfarin dose variability are age (reduced dose with increasing age), body size (increased dose with increased body size, assessed as body surface area, body mass index or weight), and in most studies smoking status and interacting drugs. Given the well-known effect of high content vitamin K foods on warfarin dose requirements, it is also possible that dietary differences between the ethnic groups contributes to differences in warfarin sensitivity. It is also possible, although not tested to date, that there may be significant gene-diet interaction, particularly with VKORC1 or other genes in the vitamin K pathway, that may also contribute to variability and might differ by ethnicity. Thus, in addition to genotype, there are also a variety of other demographic, clinical and environmental factors that may also contribute to ethnic differences in warfarin dose requirements.

In order to advance the clinical translation of these findings, several groups have suggested warfarin dosing equations that incorporate genetic and nongenetic factors, some of which have been tested prospectively in small cohorts.21, 26-29 Two studies have tested prospectively a genotype-guided versus usual dosing control group, with one study considering only CYP2C930, and the other considering both CYP2C9 and VKORC1.31 Both studies were relatively small (about 200 subjects each), and had mixed results regarding significant differences in specified outcomes between genotype-guided versus usual care approaches. However, these studies and others clearly support the need for an adequately powered randomized clinical trial.

One of the challenges regarding clinical use of warfarin pharmacogenetic information is the lack of availability of a dosing algorithm/equation that has relevance across various geographic and ethnic groups. Based on this and other issues, investigative teams with warfarin pharmacogenetics data have shared their data in a common database, with the primary goal of defining a warfarin pharmacogenetics dosing equation with validity across the globe. It is anticipated that this dosing equation will incorporate information not only on VKORC1 and CYP2C9 genotypes but also various clinical and demographic factors that influence warfarin dose requirements. The group, called the International Warfarin Pharmacogenetics Consortium (IWPC) is comprised of 21 research groups from 11 countries and four continents, and combined they have contributed warfarin genotype and phenotype data on nearly 6,000 individuals, with all three major ethnic groups well-represented. Following publication of the first paper from this group, all data will be made publicly available at www.pharmgkb.org. An additional aim of the IWPC is to test questions relating to genetic associations and ethnicity, given that the combined group will have greater power than single site studies to test a variety of hypotheses relating to ethnicity and warfarin pharmacogenetics.

Utilization of genetic information for warfarin dosing made headlines in both the medical and lay press in the summer of 2007 when the FDA product labeling (package insert) for warfarin was changed to include suggestions on (but not require) using genetic information to guide early warfarin dosing. There is great controversy about whether these data are to the point that such clinical utilization is appropriate, since there have been only two small randomized prospective studies testing the prospective use of genetic information to guide warfarin dosing.30, 31 These questions will be addressed more comprehensively by a study from the National Heart Lung and Blood Institute, which will conduct a prospective clinical trial that tests genotype-guided warfarin dosing against usual dose initiation approaches. The study is intended to launch in late 2008, and last approximately 18 months. This trial will not be powered to test (as a primary endpoint) for reductions in bleeds or prevention of thromboembolic events with the randomized dosing strategies. That CYP2C9 genotype is associated with bleeding risk seems clear, but it is not known whether prospective use of genetic information will reduce bleeding events. To the extent that some clinicians will judge reduced risk for bleeding to be the only meaningful endpoint for prospective warfarin pharmacogenetic testing, this may represent a longterm limitation of the data. Other clinicians will judge other endpoints to also be clinically meaningful (e.g. time to stable INR, time to INR > 4, etc), and these should be well-addressed by the planned trial. In the meantime clinicians will be faced with deciding whether and how to use genetic information with warfarin in the clinical setting. In the absence of genetic information, it seems clear that ethnicity should be considered as a factor when selecting initial warfarin doses.

Ethnic Differences in Responses to Antihypertensive Therapies

As described above, antihypertensive drugs were the first cardiovascular therapies for which there was wide recognition of clinical differences in response based on ethnicity. The Fourth Report of the Joint National Committee (JNC-IV) on the Detection, Evaluation and Treatment of High Blood Pressure, published in 1988, was the first to recommend consideration of race/ethnicity in selection of antihypertensive therapy,32 and the three subsequent sets of JNC guidelines have contained similar recommendations. The most notable differences are in response to β-blockers, ACE inhibitors and angiotensin receptor blockers (ARBs). The widespread clinical recognition of such differences followed the 1982 VA Cooperative Study Group finding that 62% of whites and 54% of blacks achieved blood pressure goal with propranolol, while such goal was attained with hydrochlorothiazide (HCTZ) in 55% of whites and 71% of blacks.1 Another VA cooperative study a decade later similarly found that, particularly in older blacks, atenolol and captopril were less effective at blood pressure lowering than HCTZ and diltiazem.33, 34 A meta-analysis, published in 2004, evaluated 15 clinical trials published between 1984 and 1998 that reported differences in antihypertensive response between blacks and whites, and met other specified criteria.35 Their analysis is summarized in Table 2, and highlights that blacks generally respond more favorably to diuretics or calcium channel blockers, while whites tend to respond similarly to all the drug classes. In comparisons between groups, blacks respond slightly better than whites to diuretics and CCBs, while whites respond slightly better than blacks to ACE inhibitors and β-blockers. More recent data on lisinopril, quinapril and losartan support the differences with ACE inhibitors and ARBs suggested by the meta-analysis.36-38

Table 2
Pooled estimates of decrement in blood pressure with antihypertensive drug treatments

Thus, the literature suggests there are consistent, although perhaps small, differences in responses between blacks and whites, particularly for ACE inhibitors, ARBs and β-blockers. However, an important point from the meta-analysis and several other papers is that while a mean difference in response between groups exists, there is also a large degree of overlap in responses between the two groups, as depicted in Figure 2.39 Viewed in this way, it makes therapy decisions based on ethnicity seem less reasonable.

Figure 2
Representative decrement in blood pressure among whites and blacks afar administration of antihypertensive drug. Shaded area represents white and blacks who have similar responses. Differential responses are represented of those observed with ACE inhibitors, ...

Perhaps the more important question is whether these arguably small differences in BP response translate into differences in outcomes. Only a few trials have addressed this question, the largest being ALLHAT.36 In the case of amlodipine versus chlorthalidone (the reference therapy), there were no difference in outcomes between blacks and non-blacks. However, for lisinopril there were some outcomes for which there were significantly different treatment effects by ethnicity. Specifically, lisinopril (versus chlorthalidone) was associated with a significantly increased risk of stroke in blacks (RR 1.40), but no such effect was observed in whites (RR 1.00). There were also significant differences between blacks and nonblacks in the risk of combined cardiovascular disease (RR 1.19 in blacks, versus 1.06 in nonblacks). Many have suggested that some of these differences were likely explained by the differences in BP achieved by blacks and non-blacks, although the ALLHAT analysis which controlled for BP did not suggest this to be the primary explanation.36 In the INVEST trial, which randomized patients to a calcium channel blocker or β-blocker strategy, there were no differences in outcomes (composite of death, myocardial infarction or stroke) by drug strategy for blacks, whites or Hispanics.40 In the LIFE trial, losartan was superior to atenolol in nonblacks (HR 0.83; 95% CI: 0.73-0.94) while it was associated with increased risk in blacks (HR 1.67; 95% CI: 1.04-2.66).41 The African American Study of Kidney Disease and Hypertension (AASK) found that outcomes were better or not different with ACE inhibitor versus beta-blocker or calcium channel blocker therapy in blacks.42, 43 While this study did not provide comparisons between ethnic groups, it does suggest a lack of difference in outcomes by drug therapy in blacks. Most of the large, outcomes-driven hypertension trials do not provide insight into therapy-related differences in outcomes, either because they do not include sufficient numbers of non-whites, or because they do report such differences in a meaningful way in the manuscript As such, one must conclude that based on the available evidence there are not clear differences in outcomes between blacks and whites with various antihypertensive regimens, thus treatment decisions, as it relates to outcomes, should not be based on ethnicity.

Pharmacogenetics and ethnic differences in antihypertensive drug responses

Overall, the literature suggests ethnic differences in the blood pressure lowering response to antihypertensive drugs, with less evidence for differences in outcomes. The question is whether these differences can be explained by genetic polymorphisms. The hypothesis is that a “responsive” genotype might differ in its frequency in different ethnic populations, leading to differences in response, such as is depicted in Figure 2. The more clinically relevant issue is that at present, many clinicians use ethnicity to guide selection of drug therapy. As suggested in Figure 2, a certain portion of blacks and whites will respond well to the therapy. Even if, as suggested in Figure 2, whites are over-represented in the “good responders”, and blacks are over-represented in the “poor responders”, it is clear that ethnicity does not sufficiently separate those for whom a given therapy will be effective versus ineffective. The potential promise of pharmacogenetics is that it may present a more effective way of identifying responders and non-responders, allowing clinicians to begin to move away from use of ethnicity as a method for selecting therapy. While it seems that genetic differences are an important potential explanation for differences in response, ethnic or cultural differences can also influence response to antihypertensive medications. For example, some antihypertensive drugs are more or less effective in the presence of a high salt diet, and dietary differences by ethnicity or geographic region are well documented. Thus, in the future it will likely be a cadre of genetic information, along with demographic and other information (e.g. dietary information) considered together that might be most effective at targeting therapy, as is evident with warfarin. Whether ethnicity will be an appropriate surrogate for the cultural or dietary components, or whether more refined tools to capture such information will be needed remains to be seen.

ACE inhibitors and ARBs

The literature does not provide much insight regarding genetic polymorphisms and response. Despite the fact that there have been many studies evaluating the associations of numerous candidate genes with ACE inhibitor or ARB response, none have been consistently associated. Most studied is the ACE gene, and most of the studies with this gene have focused on an insertion/deletion (I/D) polymorphism, with equivocal data. The most convincing study in this area is the pharmacogenetic substudy of ALLHAT, called GenHAT. This study tested the association of various outcomes in ALLHAT with the I/D polymorphism in 37,939 patients. They found no association between this polymorphism and BP lowering (with lisinopril or any other study drugs), nor with any of the study outcomes, when considered combined or stratified by drug therapy.44 As discussed with warfarin, ethnic differences in linkage disequilibrium between blacks and whites may be diminishing the ability to document associations with this gene, since the I/D is not believed to be the functional polymorphism. While this gene remains one of interest, any polymorphism that influences the ACE inhibitor or ARB response remains to be identified.

Another gene that has been widely studied relative to the ACE inhibitor and ARB response is the gene for the angiotensin type 1 receptor, AGTR1. Similar to ACE there have been no consistent findings with this gene, and we recently reported no association with blood pressure response to trandolapril in whites, blacks or Hispanics.45

There are also clear ethnic differences in the risk for angioedema from ACE inhibitors, with blacks being at greater risk,36 but there are no pharmacogenetic studies to provide insight into these differences.


Unlike ACE inhibitors and ARBs, the β-blocker pharmacogenetics literature may provide some insights into ethnic differences in response. There are at least 6 papers in the literature reporting the association between BP lowering with beta-blockers and one of two genetic polymorphisms in the β1-adrenergic receptor gene (ADRB1); Ser49Gly and Arg389Gly. All but one of the papers reported significantly greater BP lowering in the Arg389Arg individuals, with the other showing differences that did not achieve statistical significance.46 Studies have generally reported that alone, the Ser49Gly polymorphism does not importantly influence response, but when considered in combination with the Arg389Gly polymorphism, may be more informative than Arg389Gly alone.47, 48 Regarding the Arg389Gly polymorphism there is concordance of this association in the literature. Additionally, since these have been documented as functional polymorphisms, the challenges of studying a nonfunctional polymorphism and ancestral differences in linkage disequilibrium are not believed to be an issue. Whether these polymorphisms help explain differences in β-blocker response between ethnic populations was only addressed in one paper, since the others were comprised of mostly or all one ethnic group.47 In multiple regression analysis of the determinants of the blood pressure response to metoprolol, ADRB1 genotypes, but not ethnicity, were significant determinants of response. Figure 3 depicts blood pressure responses to metoprolol when considering the Ser49Gly and Arg389Gly polymorphisms, in a US-based study that included blacks and whites, and a study in Chinese. As is evident from this figure, the two most responsive diplotypes (genotype combinations for the two polymorphisms) are consistent across the two studies. Of interest is that the frequency of these two most responsive diplotyes varies by ethnicity. Specifically, 54% of Chinese, 44% of whites but only 23% of blacks carry one of the two most responsive diplotypes shown in Figure 3. This is not direct evidence that this gene helps explain ethnic differences in beta-blocker response, but does provide preliminary evidence in support of such a hypothesis. The Pharmacogenomic Evaluation of Antihypertensive Responses (PEAR) Study is an ongoing NIH-funded pharmacogenetic study of beta-blocker and thiazide diuretic that is accruing a large cohort of black and white hypertensives, and should be able to address this question more directly.

Figure 3Figure 3
Antihypertensive responses to metoprolol among various ADRB1 diplotype groups (genotype combination for Ser49Gly and Arg389Gly), among whites and blacks (A) and Chinese (B). S=Ser49, R=Arg389, G=Gly49 (when the first of 2 letters) or Gly389 (when the ...

Thiazide diuretics

There are limited examples in the literature of replicated associations with the response to thiazide diuretics. The strongest example, which may also provide insight into ethnic differences in response, is a functional SNP in G protein β3 subunit gene (GNB3), which has been shown in at least two studies to be associated with the antihypertensive response. While one study was conducted only in whites,49 the other included blacks and whites.50 In this latter study, ethnicity was a significant predictor of diuretic response in univariate analysis, but when genotype was included in a multivariate analysis, genotype remained a significant predictor, while ethnicity did not. Thus, similar to the β-blocker data, these data suggest that genotype may be a better predictor of response than ethnicity. The contribution of dietary sodium intake and its potential ethnic differences was not addressed in this study. As with the β-blockers, these findings do not provide direct evidence that pharmacogenetics may help explain differences in response, but they are suggestive. As with the beta-blockers, the PEAR study should provide more specific evidence in this regard. Nonetheless, the studies with beta-blockers and diuretics studies provide the conceptual framework that genetics may represent a significant (albeit not the only) factor in ethnic differences in response, and more importantly, may be superior to ethnicity in separating responders from nonresponders.

Ethnic Differences in Responses to Heart Failure Therapies

Heart failure therapies have been among the most controversial regarding ethnic differences in response. This is largely due to the African American Heart Failure Trial (A-HeFT), which enrolled only self-declared African Americans to test the efficacy of isosorbide dinitrate-hydralazine (I-H) versus placebo,(A-HeFT) and led to the eventual FDA approval of I-H for treatment of African Americans with heart failure. This represents the only FDA-approved therapy with explicit labeling for a single race/ethnicity group, and caused great controversy about the appropriateness of clinical trials conducted exclusively in one race/ethnicity group and/or FDA labeling of drugs in a single group.


The A-HeFT trial was stimulated by data from the V-HeFT I and V-HeFT II trials, which suggested that blacks derived greater benefit from I-H than whites.51 Specifically, in V-HEFT I, I-H significantly reduced mortality compared to placebo in blacks, but not whites (Table 3), although there were no statistical differences in response by ethnicity. In V-HeFT II, again there were no significant ethnicity*treatment interactions, although enalapril provided significant benefit over I-H in whites but not in blacks. Further, mortality rates with I-H were numerically higher in whites than blacks.51 This led the investigators to conduct the A-HeFT trial, enrolling only African Americans because the previous data suggested this group might obtain the greatest benefit.

Table 3
Ethnic differences in mortality rates from the V-HeFT trials*

ACE inhibitors

Ethnic differences in response to ACE inhibitors were also suggested by the investigators reporting differences in response by ethnicity from the V-HeFT trials (Table 3).51 However, it is not clear the data support this contention. Specifically the manuscript does not report statistical comparisons of mortality in enalapril-treated blacks and whites, and while mortality was numerically lower in whites than blacks, it seems unlikely this difference was statistically significant.(Table 3) In a matched cohort analysis of blacks and whites from the Studies of Left Ventricular Dysfunction (SOLVD) Prevention and Treatment trials, investigators found that enalapril was associated with a significant 49% adjusted risk reduction in heart failure hospitalization in whites, and a nonsignificant 14% adjusted risk reduction in blacks, for a significant treatment*ethnicity interaction (p=0.005).52 They did not however observe differences in mortality reduction between ethnic groups. In both the V-HeFT II and SOLVD analyses, whites had greater BP reduction with enalapril than blacks, which may have contributed to the observed differences in outcomes. A subsequent analysis that only involved the SOLVD Prevention Trial, did not observe any differences between blacks and whites in the risk reduction associated with enalapril in progression to symptomatic heart failure.53 Finally, a meta-analysis did not suggest any differences in ACE inhibitor efficacy in reducing adverse cardiovascular outcomes in heart failure between blacks and non-blacks in heart failure.54


Over a period of a couple years, the efficacy of bisoprolol, metoprolol CR/XL, and carvedilol in heart failure were all documented.55-57 Thus it came as a surprise when the large clinical trial with bucindolol (called BEST) failed to achieve the primary endpoint.58 There were two hypotheses put forward by the authors to explain why bucindolol failed to reduce mortality in heart failure, when other drugs had shown such benefit. Specifically, they hypothesized it might be due to differences in the patient populations for the various trials, or there were ancillary pharmacological properties of bucindolol that reduced its efficacy. Regarding the differences in study populations, the most notable difference was that BEST enrolled substantially more blacks than any other trial (i.e. 23% in the bucindolol trial, < 1% in the bisoprolol trial, and 5% in the metoprolol CR/XL and carvedilol trials).59 Further, in the BEST subgroup analysis there was no benefit evident in blacks (HR 1.17, 95% CI: 0.89-1.53) whereas there was a significant mortality reduction in nonblacks (HR 0.82; 95% CI: 0.70-0.96). This prompted a variety of subsequent analyses to evaluate whether there was lower efficacy with β-blockers in blacks in the treatment of heart failure. A reanalysis of the carvedilol data by ethnicity suggested no differences in outcomes, with blacks having similar estimates of risk reduction to whites.60 Nonetheless, there were only 217 black participants in the trial and a lack of, or reduced efficacy in blacks cannot be ruled out by these analyses. Subgroup analyses of the metoprolol CR/XL data were not as convincing regarding the lack of a difference by ethnicity.61 While all hazard ratios in blacks were < 1.0, for total mortality the hazard ratio point estimate was 0.79 in blacks (not significant) and 0.67 in whites (significant). Similarly, for mortality plus heart failure hospitalization, the point estimate was approximately 0.98 in blacks and 0.70 in whites.54, 61 Thus, although the authors concluded no differences between blacks and whites, it is not apparent this is the case. Whether the study was simply underpowered to test for ethnic differences or no such differences exist is unknown. Interestingly, the FDA package labeling for metoprolol CR/XL indicates that among the U.S.-based participants in the metoprolol CR/XL clinical trial (MERIT-HF), no benefit was evident. Given that nearly all the blacks in MERIT-HF came from the US,61 it is possible that reduced efficacy in this population led to the failure to observe a benefit among the US population for this trial. Thus, while there is reasonable evidence for a lack of ethnic difference in response to carvedilol, it is less clear for metoprolol CR/XL. There was also a meta-analysis, which included two carvedilol trials, the metoprolol CR/XL trial and BEST.54 A suggested by the previous analyses, point estimates for blacks and non-blacks were similar, except for bucindolol. In the meta-analysis that included BEST, there was significantly less relative risk reduction in blacks than whites, while in the meta-analysis that excluded BEST data, there was no significant difference in the relative risk reduction. However, in this meta-analysis and in three of the four trials, the risk reduction ratio (blacks/whites) was greater than 1.0 suggesting less risk reduction in blacks (albeit nonsignificant except in BEST). Given that even when combined, the other three trials included 82 fewer blacks than BEST, it is difficult to exclude a reduced efficacy with β-blockers in blacks. Finally, the BEST investigators conducted an analysis where they created a subgroup in BEST that closely matched the demographics of the other trials.59 In the BEST comparison subgroup they showed a significant reduction in mortality (HR 0.77; 95% CI: 0.65-0.92), making the findings similar to the trials with the other drugs. This comparison subgroup included no blacks, supporting their initial hypothesis that differences in their study population, particularly a larger black population, may have influenced the inability to show a significant reduction in mortality with bucindolol.

Pharmacogenetics and ethnic differences in responses to heart failure therapies


If one accepts that I-H is more efficacious in blacks than whites, a potential explanation for such a finding is that there might be a “responsive” genotype that occurs exclusively or more commonly in blacks. Work is ongoing in the A-HeFT genetic substudy to address this question. However, equally likely to a genetic or ethnic explanation for the I-H findings is that response differences highlight differences in two different heart failure phenotypes, which happen to differ by ethnicity. Specifically, blacks are significantly more likely to have hypertensive heart failure, whereas the underlying cause is more likely to be ischemic heart disease in whites. Thus, it is possible that blacks and whites with hypertensive heart failure would respond equally well to I-H, and that ethnicity per se is not the source of response differences. It is unlikely that there will be future studies that sufficiently dissect the role of genetics versus differences in phenotype in the response differences to I-H. However, whichever of these might be the explanation, either would highlight that a portion of whites would be expected to benefit from I-H, and a portion of blacks would be expected to not benefit.


As described, there appears to be reasonable evidence for differences in response to bucindolol between blacks and whites, and while the studies with the other β-blockers did not provide convincing evidence for differences in response, the number of blacks included was small, and such a difference cannot be excluded. As with the antihypertensive response, the pharmacogenetics data with β-blockers may be considered consistent with a potential mechanistic explanation for such differences in response. For example, studies have shown that the ADRB1 Arg389Gly polymorphism is significantly associated with improvement in left ventricular ejection fraction (LVEF) associated with carvedilol,62 metoprolol CR/XL,63 and bisoprolol.64 Specifically, in all these studies the Arg389Arg genotype group had the greatest improvement in LVEF, and given that improvement in LVEF is considered a good surrogate for improvement in survival, such differences may have clinical relevance. The first two studies were conducted in the U.S., while the latter was conducted in China, which also suggests these associations are consistent across ethnic groups.

Consistent with the associations between genotype and improvement in LVEF are data from BEST, which showed that Arg389Arg homozygotes had a significant mortality reduction with bucindolol compared to placebo, but such a benefit was not evident in the Gly389 carriers.65 Of importance is that the frequency of the Arg389Arg genotype is lower in blacks than whites, which is consistent with the potential ethnic differences in response. Specifically, among whites approximately 55% of the population has the Arg389Arg genotype, compared to approximately 30-35% of blacks. This would not appear to explain the literature suggesting a lack of difference by ethnicity for carvedilol, and a more dramatic difference with bucindolol. However, studies of Liggett and colleagues on the effects of genotype on ex vivo ventricular contractile responses may be insightful. They found that in precontracted ventricular trabeculae, bucindolol behaved as an inverse agonist in the Arg389Arg hearts only, while carvedilol was a neutral antagonist in Arg389Arg and Gly389 carriers.65 These data suggest that ancillary properties of the drugs might also vary by genotype, and thus may influence variable efficacy between drugs and across ethnic groups.

Another ancillary property of bucindolol that may have influenced its failure to reduce mortality in the overall population is its sympatholytic properties. Specifically, it was shown that a portion of the bucindolol-treated population had dramatic reductions in norepinephrine, due to its sympatholytic effects, and those with the greatest decline in norepinephrine were at increased mortality risk.66 Of interest is that the sympatholytic effects of bucindolol may be associated with the amino acid 322-325 insertion/deletion (Ins/Del) polymorphism in the alpha2C-adrenergic receptor (ADRA2C), with Del carriers having greater norepinephrine reductions with bucindolol.67 Additionally, in BEST, ADRA2C Del carriers had no benefit from bucindolol relative to placebo, whereas Ins/Ins homozygotes had a significant benefit from bucindolol therapy. And the group with the greatest benefit was those with both ADRA2C Ins/Ins and ADRB1 Arg389Arg genotypes. As with the Arg389Gly polymorphism, there are significant ethnic differences in the ADRA2C 322-325 Ins/Del polymorphism. Specifically, in BEST, 66% of blacks were Del carriers, versus 8% of whites. Thus, two genes have been associated with different outcomes for bucindolol and in both cases, blacks are less likely than whites to have the favorable response genotype.

Of interest is that among the β-blockers used in heart failure, the sympatholytic effects appear to be confined to bucindolol, so these findings would not translate to the other β-blockers. It may help explain why bucindolol appears to be most extreme regarding the ethnic differences in response. For example, we found that ADRA2C Del carriers had significantly greater improvements in LVEF with metoprolol than Ins/Ins homozygotes.68 Additionally, when considered with the ADRB1Arg389Gly polymorphism, it appeared that the LVEF improvement in Arg389Arg homozygotes/Del carriers was synergistic relative to those carrying just one of the favorable genotypes. This finding is also consistent with the known functional effects of the ADRA2C polymorphism, where the Del carriers have impairment in the normal autoinhibitory function of the receptor, leading to enhanced norepinephrine release.69 In the absence of sympatholytic effects of the drug, Del carriers would be expected to have a greater response to β-blocker therapy. Considering data from the two drugs together, they suggest that the most favorable genotype combination for bucindolol (Arg389Arg + Ins/Ins) is different than the most favorable combination for metoprolol (Arg389Arg + Del carrier). Blacks are more likely to have the latter rather than the former genotype combination, consistent with the data suggesting a more minimal difference in response to metoprolol CR/XL between blacks and whites than with bucindolol. Data considering both genes are not available for carvedilol so it is not possible to know what the most favorable genotype combination might be for this drug.

The pharmacogenetics data for β-blockers in heart failure suggest several things. First, it appears the observed ethnic differences in response in clinical trials might be explained to some degree by pharmacogenetics. The data also suggest that it might be possible to more precisely select β-blocker therapy based on genotype, and that such an approach would appear to be superior to selecting therapy based on a patient's ethnicity. Specifically, while one might conclude from the literature that bucindolol would be a suboptimal therapy in blacks, certain blacks will carry the genotype combination for which it might be an effective therapy. A small pharmaceutical company has purchased the rights to bucindolol, and will be filing a new drug application to the FDA, with the drug being most strongly recommended for Arg389Arg + Ins/Ins genotype patients. Thus, use of genetic information to guide β-blocker selection in heart failure may soon be a clinical reality, and would be expected to be a more reliable predictor of response than reliance on data regarding differences or similarities in response by ethnic group.

Challenges to defining the role of pharmacogenetics in ethnic differences in drug response

Ethnic differences in responses to cardiovascular drugs have been recognized for several decades, and in some cases ethnicity is used in drug therapy decision-making. It is intuitively attractive to speculate that pharmacogenetics may contribute to our understanding of ethnic differences in drugs response, and some of the examples cited herein support that pharmacogenetics may contribute to such differences. However, there are certain challenges to defining the role of pharmacogenetics in ethnic differences in drug response that must be recognized. First, the heritable contribution to drug response variability is rarely defined experimentally, but if one assumes that it is approximately the same as the heritable contribution to the diseases the drug treats, then on average, this would represent 30-60% of variability that has a genetic basis, with the remaining being environmental or demographic. Additionally, it is expected that for most drug responses, the genetic underpinnings will be explained by a variety of genes, thus making any calculation of the role of pharmacogenetics in ethnic differences in response more challenging. It is possible that the examples provided herein are ones for which the genetic contribution from a single gene is larger than normal, thus making the potential contribution of that gene to ethnic differences in response more evident. Additionally, as genetic studies move toward a tag SNP approach, where the functional polymorphism is unknown, differences in linkage disequilibrium between ancestral popluations will add to the challenge of defining an association across different ethnic groups, and defining the role of that polymorphism in ethnic differences in response. This has been clearly evident with warfarin and the VKORC1 SNPs. The contribution of environmental factors to drug response, particularly diet for many of the cardiovascular drugs, and how this may confound the search for the genetic underpinnings of ethnic differences in response remains to be clarified. Finally, there are the challenges associated with translation of any finding or technology to practice. This includes accumulating sufficient data that the genetic (and probably other) information is predictive enough to be useful clinically, followed by the education required of clinicians for adoption to practice.

Despite the many challenges, it appears that in at least some cases pharmacogenetic findings may help to explain ethnic differences in response. As the goals of personalized medicine begin to be realized, it is possible that use of genetic and other patient-specific information, including environmental factors, will be superior to use of ethnic information and will help guide drug-therapy decisions for certain drugs.


The helpful comments of Dr. Amber Beitelshees are gratefully acknowledged.

Funding sources: This work was supported in part by NIH grants GM074492, HL074730; and HL68834.


Confluct of Interest Disclosure statement: Dr. Johnson served as a one-time consultant for Third Wave Technology (< $5000).


1. Comparison of propranolol and hydrochlorothiazide for the initial treatment of hypertension. II. Results of long-term therapy. Veterans Administration Cooperative Study Group on Antihypertensive Agents. Jama. 1982;248(16):2004–2011. [PubMed]
2. Messerli FH, Ventura HO. Cardiovascular pathophysiology of essential hypertension: a clue to therapy. Drugs. 1985;30 1:25–34. [PubMed]
3. Zing W, Ferguson RK, Vlasses PH. Calcium antagonists in elderly and black hypertensive patients. Therapeutic controversies. Arch Intern Med. 1991;151(11):2154–2162. [PubMed]
4. Roden DM, Altman RB, Benowitz NL, Flockhart DA, Giacomini KM, Johnson JA, Krauss RM, McLeod HL, Ratain MJ, Relling MV, Ring HZ, Shuldiner AR, Weinshilboum RM, Weiss ST. Pharmacogenomics: challenges and opportunities. Ann Intern Med. 2006;145(10):749–757. [PubMed]
5. Ansell J, Hirsh J, Poller L, Bussey H, Jacobson A, Hylek E. The pharmacology and management of the vitamin K antagonists: the Seventh ACCP Conference on Antithrombotic and Thrombolytic Therapy. Chest. 2004;126(3 Suppl):204S–233S. [PubMed]
6. Dang MT, Hambleton J, Kayser SR. The influence of ethnicity on warfarin dosage requirement. Ann Pharmacother. 2005;39(6):1008–1012. [PubMed]
8. White RH, Beyth RJ, Zhou H, Romano PS. Major bleeding after hospitalization for deep-venous thrombosis. Am J Med. 1999;107(5):414–424. [PubMed]
9. Yu HY, Liu CH, Chen YS, Wang SS, Chu SH, Lin FY. Relationship of international normalized ratio to bleeding and thromboembolism rates in Taiwanese patients receiving vitamin K antagonist after mechanical valve replacement. J Formos Med Assoc. 2005;104(4):236–243. [PubMed]
10. You JH, Chan FW, Wong RS, Cheng G. Is INR between 2.0 and 3.0 the optimal level for Chinese patients on warfarin therapy for moderate-intensity anticoagulation? Br J Clin Pharmacol. 2005;59(5):582–587. [PMC free article] [PubMed]
11. Suzuki S, Yamashita T, Kato T, Fujino T, Sagara K, Sawada H, Aizawa T, Fu LT. Incidence of major bleeding complication of warfarin therapy in Japanese patients with atrial fibrillation. Circ J. 2007;71(5):761–765. [PubMed]
12. Aithal GP, Day CP, Kesteven PJ, Daly AK. Association of polymorphisms in the cytochrome P450 CYP2C9 with warfarin dose requirement and risk of bleeding complications. Lancet. 1999;353(9154):717–719. [PubMed]
13. Wadelius M, Pirmohamed M. Pharmacogenetics of warfarin: current status and future challenges. Pharmacogenomics J. 2007;7(2):99–111. [PubMed]
14. Sanderson S, Emery J, Higgins J. CYP2C9 gene variants, drug dose, and bleeding risk in warfarin-treated patients: a HuGEnet systematic review and meta-analysis. Genet Med. 2005;7(2):97–104. [PubMed]
15. Higashi MK, Veenstra DL, Kondo LM, Wittkowsky AK, Srinouanprachanh SL, Farin FM, Rettie AE. Association between CYP2C9 genetic variants and anticoagulation-related outcomes during warfarin therapy. Jama. 2002;287(13):1690–1698. [PubMed]
16. Limdi NA, McGwin G, Goldstein JA, Beasley TM, Arnett DK, Adler BK, Baird MF, Acton RT. Influence of CYP2C9 and VKORC1 1173C/T genotype on the risk of hemorrhagic complications in African-American and European-American patients on warfarin. Clin Pharmacol Ther. 2008;83(2):312–321. [PMC free article] [PubMed]
17. Yuan HY, Chen JJ, Lee MT, Wung JC, Chen YF, Charng MJ, Lu MJ, Hung CR, Wei CY, Chen CH, Wu JY, Chen YT. A novel functional VKORC1 promoter polymorphism is associated with inter-individual and inter-ethnic differences in warfarin sensitivity. Hum Mol Genet. 2005;14(13):1745–1751. [PubMed]
18. Rieder MJ, Reiner AP, Gage BF, Nickerson DA, Eby CS, McLeod HL, Blough DK, Thummel KE, Veenstra DL, Rettie AE. Effect of VKORC1 haplotypes on transcriptional regulation and warfarin dose. N Engl J Med. 2005;352(22):2285–2293. [PubMed]
19. Takahashi H, Wilkinson GR, Nutescu EA, Morita T, Ritchie MD, Scordo MG, Pengo V, Barban M, Padrini R, Ieiri I, Otsubo K, Kashima T, Kimura S, Kijima S, Echizen H. Different contributions of polymorphisms in VKORC1 and CYP2C9 to intra- and inter-population differences in maintenance dose of warfarin in Japanese, Caucasians and African-Americans. Pharmacogenet Genomics. 2006;16(2):101–110. [PubMed]
20. Schelleman H, Chen Z, Kealey C, Whitehead AS, Christie J, Price M, Brensinger CM, Newcomb CW, Thorn CF, Samaha FF, Kimmel SE. Warfarin response and vitamin K epoxide reductase complex 1 in African Americans and Caucasians. Clin Pharmacol Ther. 2007;81(5):742–747. [PubMed]
21. Caldwell MD, Berg RL, Zhang KQ, Glurich I, Schmelzer JR, Yale SH, Vidaillet HJ, Burmester JK. Evaluation of genetic factors for warfarin dose prediction. Clin Med Res. 2007;5(1):8–16. [PMC free article] [PubMed]
22. Schalekamp T, Brasse BP, Roijers JF, Chahid Y, van Geest-Daalderop JH, de Vries-Goldschmeding H, van Wijk EM, Egberts AC, de Boer A. VKORC1 and CYP2C9 genotypes and acenocoumarol anticoagulation status: interaction between both genotypes affects overanticoagulation. Clin Pharmacol Ther. 2006;80(1):13–22. [PubMed]
23. Lee SC, Ng SS, Oldenburg J, Chong PY, Rost S, Guo JY, Yap HL, Rankin SC, Khor HB, Yeo TC, Ng KS, Soong R, Goh BC. Interethnic variability of warfarin maintenance requirement is explained by VKORC1 genotype in an Asian population. Clin Pharmacol Ther. 2006;79(3):197–205. [PubMed]
24. Aquilante CL, Langaee TY, Lopez LM, Yarandi HN, Tromberg JS, Mohuczy D, Gaston KL, Waddell CD, Chirico MJ, Johnson JA. Influence of coagulation factor, vitamin K epoxide reductase complex subunit 1, and cytochrome P450 2C9 gene polymorphisms on warfarin dose requirements. Clin Pharmacol Ther. 2006;79(4):291–302. [PubMed]
25. D'Andrea G, D'Ambrosio RL, Di Perna P, Chetta M, Santacroce R, Brancaccio V, Grandone E, Margaglione M. A polymorphism in the VKORC1 gene is associated with an interindividual variability in the dose-anticoagulant effect of warfarin. Blood. 2005;105(2):645–649. [PubMed]
26. Tham LS, Goh BC, Nafziger A, Guo JY, Wang LZ, Soong R, Lee SC. A warfarin-dosing model in Asians that uses single-nucleotide polymorphisms in vitamin K epoxide reductase complex and cytochrome P450 2C9. Clin Pharmacol Ther. 2006;80(4):346–355. [PubMed]
27. Sconce EA, Khan TI, Wynne HA, Avery P, Monkhouse L, King BP, Wood P, Kesteven P, Daly AK, Kamali F. The impact of CYP2C9 and VKORC1 genetic polymorphism and patient characteristics upon warfarin dose requirements: proposal for a new dosing regimen. Blood. 2005;106(7):2329–2333. [PubMed]
28. Millican EA, Lenzini PA, Milligan PE, Grosso L, Eby C, Deych E, Grice G, Clohisy JC, Barrack RL, Burnett RS, Voora D, Gatchel S, Tiemeier A, Gage BF. Genetic-based dosing in orthopedic patients beginning warfarin therapy. Blood. 2007;110(5):1511–1515. [PMC free article] [PubMed]
29. Voora D, Eby C, Linder MW, Milligan PE, Bukaveckas BL, McLeod HL, Maloney W, Clohisy J, Burnett RS, Grosso L, Gatchel SK, Gage BF. Prospective dosing of warfarin based on cytochrome P-450 2C9 genotype. Thromb Haemost. 2005;93(4):700–705. [PubMed]
30. 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. 2007 [PubMed]
31. Anderson JL, Horne BD, Stevens SM, Grove AS, Barton S, Nicholas ZP, Kahn SF, May HT, Samuelson KM, Muhlestein JB, Carlquist JF. Randomized trial of genotype-guided versus standard warfarin dosing in patients initiating oral anticoagulation. Circulation. 2007;116(22):2563–2570. [PubMed]
32. The 1988 report of the Joint National Committee on Detection, Evaluation, and Treatment of High Blood Pressure. Arch Intern Med. 1988;148(5):1023–1038. [PubMed]
33. Materson BJ, Reda DJ, Cushman WC, Massie BM, Freis ED, Kochar MS, Hamburger RJ, Fye C, Lakshman R, Gottdiener J, et al. Single-drug therapy for hypertension in men. A comparison of six antihypertensive agents with placebo. The Department of Veterans Affairs Cooperative Study Group on Antihypertensive Agents. N Engl J Med. 1993;328(13):914–921. [PubMed]
34. Preston RA, Materson BJ, Reda DJ, Williams DW, Hamburger RJ, Cushman WC, Anderson RJ. 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(13):1168–1172. [PubMed]
35. Brewster LM, van Montfrans GA, Kleijnen J. Systematic review: antihypertensive drug therapy in black patients. Ann Intern Med. 2004;141(8):614–627. [PubMed]
36. Wright JT, Jr, Dunn JK, Cutler JA, Davis BR, Cushman WC, Ford CE, Haywood LJ, Leenen FH, Margolis KL, Papademetriou V, Probstfield JL, Whelton PK, Habib GB. Outcomes in hypertensive black and nonblack patients treated with chlorthalidone, amlodipine, and lisinopril. Jama. 2005;293(13):1595–1608. [PubMed]
37. Mokwe E, Ohmit SE, Nasser SA, Shafi T, Saunders E, Crook E, Dudley A, Flack JM. Determinants of Blood Pressure Response to Quinapril in Black and White Hypertensive Patients. The Quinapril Titration Interval Management Evaluation Trial. Hypertension. 2004 01.HYP.0000127924.0000167353.0000127986. [PubMed]
38. Flack JM, Oparil S, Pratt JH, Roniker B, Garthwaite S, Kleiman JH, Yang Y, Krause SL, Workman D, Saunders E. Efficacy and tolerability of eplerenone and losartan in hypertensive black and white patients. J Am Coll Cardiol. 2003;41(7):1148–1155. [PubMed]
39. Sehgal AR. Overlap between whites and blacks in response to antihypertensive drugs. Hypertension. 2004;43(3):566–572. [PubMed]
40. Pepine CJ, Handberg EM, Cooper-DeHoff RM, Marks RG, Kowey P, Messerli FH, Mancia G, Cangiano JL, Garcia-Barreto D, Keltai M, Erdine S, Bristol HA, Kolb HR, Bakris GL, Cohen JD, Parmley WW. A calcium antagonist vs a non-calcium antagonist hypertension treatment strategy for patients with coronary artery disease. The International Verapamil-Trandolapril Study (INVEST): a randomized controlled trial. Jama. 2003;290(21):2805–2816. [PubMed]
41. Julius S, Alderman MH, Beevers G, Dahlof B, Devereux RB, Douglas JG, Edelman JM, Harris KE, Kjeldsen SE, Nesbitt S, Randall OS, Wright JT., Jr Cardiovascular risk reduction in hypertensive black patients with left ventricular hypertrophy: the LIFE study. J Am Coll Cardiol. 2004;43(6):1047–1055. [PubMed]
42. Wright JT, Jr, Bakris G, Greene T, Agodoa LY, Appel LJ, Charleston J, Cheek D, Douglas-Baltimore JG, Gassman J, Glassock R, Hebert L, Jamerson K, Lewis J, Phillips RA, Toto RD, Middleton JP, Rostand SG. Effect of blood pressure lowering and antihypertensive drug class on progression of hypertensive kidney disease: results from the AASK trial. Jama. 2002;288(19):2421–2431. [PubMed]
43. Norris K, Bourgoigne J, Gassman J, Hebert L, Middleton J, Phillips RA, Randall O, Rostand S, Sherer S, Toto RD, Wright JT, Jr, Wang X, Greene T, Appel LJ, Lewis J. Cardiovascular outcomes in the African American Study of Kidney Disease and Hypertension (AASK) Trial. Am J Kidney Dis. 2006;48(5):739–751. [PubMed]
44. Arnett DK, Davis BR, Ford CE, Boerwinkle E, Leiendecker-Foster C, Miller MB, Black H, Eckfeldt JH. 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(25):3374–3383. [PubMed]
45. Brunner M, Cooper-DeHoff RM, Gong Y, Karnes JH, Langaee TY, Pepine CJ, Johnson JA. Factors influencing blood pressure response to trandolapril add-on therapy in patients taking verapamil SR (from the International Verapamil SR/Trandolapril [INVEST] Study) Am J Cardiol. 2007;99(11):1549–1554. [PMC free article] [PubMed]
46. Shin J, Johnson JA. Pharmacogenetics of beta-blockers. Pharmacotherapy. 2007;27(6):874–887. [PMC free article] [PubMed]
47. Johnson JA, Zineh I, Puckett BJ, McGorray SP, Yarandi HN, Pauly DF. Beta 1-adrenergic receptor polymorphisms and antihypertensive response to metoprolol. Clin Pharmacol Ther. 2003;74(1):44–52. [PubMed]
48. Liu J, Liu ZQ, Yu BN, Xu FH, Mo W, Zhou G, Liu YZ, Li Q, Zhou HH. beta1-Adrenergic receptor polymorphisms influence the response to metoprolol monotherapy in patients with essential hypertension. Clin Pharmacol Ther. 2006;80(1):23–32. [PubMed]
49. Schelleman H, Stricker BH, Verschuren WM, de Boer A, Kroon AA, de Leeuw PW, Kromhout D, Klungel OH. Interactions between five candidate genes and antihypertensive drug therapy on blood pressure. Pharmacogenomics J. 2006;6(1):22–26. [PubMed]
50. Turner ST, Schwartz GL, Chapman AB, Boerwinkle E. C825T polymorphism of the G protein beta(3)-subunit and antihypertensive response to a thiazide diuretic. Hypertension. 2001;37(2 Part 2):739–743. [PubMed]
51. Carson P, Ziesche S, Johnson G, Cohn JN. Racial differences in response to therapy for heart failure: analysis of the vasodilator-heart failure trials. Vasodilator-Heart Failure Trial Study Group. J Card Fail. 1999;5(3):178–187. [PubMed]
52. Exner DV, Dries DL, Domanski MJ, Cohn JN. Lesser Response to Angiotensin-Converting-Enzyme Inhibitor Therapy in Black as Compared with White Patients with Left Ventricular Dysfunction. N Engl J Med. 2001;344(18):1351–1357. [PubMed]
53. Dries DL, Strong MH, Cooper RS, Drazner MH. Efficacy of angiotensin-converting enzyme inhibition in reducing progression from asymptomatic left ventricular dysfunction to symptomatic heart failure in black and white patients. J Am Coll Cardiol. 2002;40(2):311–317. [PubMed]
54. Shekelle PG, Rich MW, Morton SC, Atkinson CS, Tu W, Maglione M, Rhodes S, Barrett M, Fonarow GC, Greenberg B, Heidenreich PA, Knabel T, Konstam MA, Steimle A, Warner Stevenson L. Efficacy of angiotensin-converting enzyme inhibitors and beta-blockers in the management of left ventricular systolic dysfunction according to race, gender, and diabetic status: a meta-analysis of major clinical trials. J Am Coll Cardiol. 2003;41(9):1529–1538. [PubMed]
55. The Cardiac Insufficiency Bisoprolol Study II (CIBIS-II): a randomised trial. Lancet. 1999;353(9146):9–13. see comments. [PubMed]
56. Effect of metoprolol CR/XL in chronic heart failure: Metoprolol CR/XL Randomised Intervention Trial in Congestive Heart Failure (MERIT-HF) Lancet. 1999;353(9169):2001–2007. see comments. [PubMed]
57. Packer M, Bristow MR, Cohn JN, Colucci WS, Fowler MB, Gilbert EM, Shusterman NH. The effect of carvedilol on morbidity and mortality in patients with chronic heart failure. U.S. Carvedilol Heart Failure Study Group. N Engl J Med. 1996;334(21):1349–1355. see comments. [PubMed]
58. The Beta-Blocker Evaluation of Survival Trial Investigators. A Trial of the Beta-Blocker Bucindolol in Patients with Advanced Chronic Heart Failure. N Engl J Med. 2001;344(22):1659–1667. [PubMed]
59. Domanski MJ, Krause-Steinrauf H, Massie BM, Deedwania P, Follmann D, Kovar D, Murray D, Oren R, Rosenberg Y, Young J, Zile M, Eichhorn E. A comparative analysis of the results from 4 trials of beta-blocker therapy for heart failure: BEST, CIBIS-II, MERIT-HF, and COPERNICUS. J Card Fail. 2003;9(5):354–363. [PubMed]
60. Yancy CW, Fowler MB, Colucci WS, Gilbert EM, Bristow MR, Cohn JN, Lukas MA, Young ST, Packer M. U.S. Carvedilol Heart Failure Study Group. Race and the Response to Adrenergic Blockade with Carvedilol in Patients with Chronic Heart Failure. N Engl J Med. 2001;344(18):1358–1365. [PubMed]
61. Wikstrand J, Wedel H, Ghali J, Deedwania P, Fagerberg B, Goldstein S, Gottlieb S, Hjalmarson A, Kjekshus J, Waagstein F. How should subgroup analyses affect clinical practice? Insights from the Metoprolol Succinate Controlled-Release/Extended-Release Randomized Intervention Trial in Heart Failure (MERIT-HF) Card Electrophysiol Rev. 2003;7(3):264–275. [PubMed]
62. Mialet Perez J, Rathz DA, Petrashevskaya NN, Hahn HS, Wagoner LE, Schwartz A, Dorn GW, Liggett SB. Beta 1-adrenergic receptor polymorphisms confer differential function and predisposition to heart failure. Nat Med. 2003;9(10):1300–1305. [PubMed]
63. Terra SG, Hamilton KK, Pauly DF, Lee CR, Patterson JH, Adams KF, Schofield RS, Belgado BS, Hill JA, Aranda JM, Yarandi HN, Johnson JA. Beta1-adrenergic receptor polymorphisms and left ventricular remodeling changes in response to beta-blocker therapy. Pharmacogenet Genomics. 2005;15(4):227–234. [PubMed]
64. Yu WP, Lou M, Deng B, Song HM, Wang HB. Beta1-adrenergic receptor (Arg389Gly) polymorphism and response to bisoprolol in patients with chronic heart failure. Zhonghua Xin Xue Guan Bing Za Zhi. 2006;34(9):776–780. [PubMed]
65. Liggett SB, Mialet-Perez J, Thaneemit-Chen S, Weber SA, Greene SM, Hodne D, Nelson B, Morrison J, Domanski MJ, Wagoner LE, Abraham WT, Anderson JL, Carlquist JF, Krause-Steinrauf HJ, Lazzeroni LC, Port JD, Lavori PW, Bristow MR. A polymorphism within a conserved beta(1)-adrenergic receptor motif alters cardiac function and beta-blocker response in human heart failure. Proc Natl Acad Sci U S A. 2006;103(30):11288–11293. [PMC free article] [PubMed]
66. Bristow MR, Krause-Steinrauf H, Nuzzo R, Liang CS, Lindenfeld J, Lowes BD, Hattler B, Abraham WT, Olson L, Krueger S, Thaneemit-Chen S, Hare JM, Loeb HS, Domanski MJ, Eichhorn EJ, Zelis R, Lavori P. Effect of baseline or changes in adrenergic activity on clinical outcomes in the beta-blocker evaluation of survival trial. Circulation. 2004;110(11):1437–1442. [PubMed]
67. Bristow MR, Robertson AD, Lavori P, Thaneemit-Chen S, Liggett SB. Alpha2c-adrenergic receptor 322-325 DEL polymorphism enhanced the sympatholytic effect of bucindolol, and adversely affected clinical outcomes in the BEST trial (Abstract) Circulation. 2005;112:II–351.
68. Lobmeyer MT, Gong Y, Terra SG, Beitelshees AL, Langaee TY, Pauly DF, Schofield RS, Hamilton KK, Herbert Patterson J, Adams KF, Jr, Hill JA, Aranda JM, Jr, Johnson JA. Synergistic polymorphisms of beta1 and alpha2C-adrenergic receptors and the influence on left ventricular ejection fraction response to beta-blocker therapy in heart failure. Pharmacogenet Genomics. 2007;17(4):277–282. [PubMed]
69. Neumeister A, Charney DS, Belfer I, Geraci M, Holmes C, Sharabi Y, Alim T, Bonne O, Luckenbaugh DA, Manji H, Goldman D, Goldstein DS. Sympathoneural and adrenomedullary functional effects of alpha2C-adrenoreceptor gene polymorphism in healthy humans. Pharmacogenet Genomics. 2005;15(3):143–149. [PubMed]
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