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Original Contribution |

β2-Adrenergic Receptor Genotype and Survival Among Patients Receiving β-Blocker Therapy After an Acute Coronary Syndrome FREE

David E. Lanfear, MD; Philip G. Jones, MS; Sharon Marsh, PhD; Sharon Cresci, MD; Howard L. McLeod, PharmD; John A. Spertus, MD, MPH
[+] Author Affiliations

Author Affiliations: Departments of Medicine (Drs Lanfear, Marsh, Cresci, and McLeod), Genetics (Dr McLeod), and Molecular Biology and Pharmacology (Dr McLeod), Washington University School of Medicine, St Louis, Mo; Mid America Heart Institute, St Luke’s Hospital, Kansas City, Mo (Mr Jones and Dr Spertus); and the Department of Medicine, University of Missouri, Kansas City (Dr Spertus). Dr Lanfear is now with the Department of Medicine, Henry Ford Hospital, Detroit, Mich.

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JAMA. 2005;294(12):1526-1533. doi:10.1001/jama.294.12.1526.
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Context Previous data support an association between polymorphisms of the β1- and β2-adrenergic receptors (ADRB1 and ADRB2) and surrogate end points of response to β-adrenergic blocker therapy. However, no associations between these polymorphisms and mortality have been demonstrated.

Objective To evaluate the effect of ADRB1 Arg389Gly (1165 CG), Ser49Gly (145 AG), and ADRB2 Gly16Arg (46 GA), Gln27Glu (79 CG) genotypes on survival among patients discharged with prescribed β-blockers after an acute coronary syndrome (ACS).

Design, Setting, and Patients Prospective cohort study of 735 ACS patients admitted to 2 Kansas City, Mo, medical centers between March 2001 and October 2002; 597 patients were discharged with β-blocker therapy.

Main Outcome Measure Multivariable-adjusted time to all-cause 3-year mortality.

Results There were 84 deaths during follow-up. There was a significant association between ADRB2 genotype and 3-year mortality among patients prescribed β-blocker therapy. For the 79 CG polymorphism, Kaplan-Meier 3-year mortality rates were 16% (35 deaths), 11% (27 deaths), and 6% (4 deaths) for the CC, CG, and GG genotypes, respectively (P = .03; adjusted hazard ratios [AHRs], 0.51 [95% confidence interval {CI}, 0.30-0.87] for CG vs CC and 0.24 (95% CI, 0.09-0.68) for GG vs CC, P = .004). For the ADRB2 46 GA polymorphism, 3-year Kaplan-Meier mortality estimates were 10% (17 deaths), 10% (28 deaths), and 20% (20 deaths) for the GG, GA, and AA genotypes, respectively (P = .005; AHRs, 0.48 [95% CI, 0.27-0.86] for GA vs AA and 0.44 [95% CI, 0.22-0.85] for GG vs AA, P = .02). No mortality difference between genotypes was found among patients not discharged with β-blocker therapy for either the 79 CG or 46 GA polymorphisms (P = .98 and P = .49, respectively). The ADRB2 diplotype and compound genotypes were predictive of survival in patients treated with β-blockers (P = .04 and P = .002; AHRs, 5.36 [95% CI, 1.83-15.69] and 2.41 [95% CI, 0.86-6.74] for 46 A homozygous and composite heterozygous vs 79 G homozygous, respectively). No association of the ADRB1 variants with mortality was observed in either the β-blocker or no β-blocker groups.

Conclusions Patients prescribed β-blocker therapy after an ACS have differential survival associated with their ADRB2 genotypes. Further assessment of the benefits of β-blocker therapy in high-risk genotype groups may be warranted.

Figures in this Article

Cardiovascular disease, including acute coronary syndromes (ACS), is the major cause of morbidity and mortality in the Western world.1 Acute and long-term therapy with β-adrenergic antagonists (β-blockers) has become a standard of post-ACS care.2,3 Therapy with β-blockers has been shown to reduce infarct size4 and mortality5,6 among myocardial infarction (MI) patients, most likely by decreasing cardiac energy requirements7 and modifying arrhythmic risk.5,8 Based on multiple clinical trials and guidelines, it has also been used as an important marker of health care quality.9,10 Yet clinical trials report the benefits for groups of patients, and it is quite possible that an ”average” benefit may result from some subgroups of patients deriving substantial benefit, while others derive little benefit from therapy.

One intriguing patient characteristic that may influence response to pharmacotherapy is genetic variation.11 Seminal works by Liggett, Johnson, Woods, and others have demonstrated that specific sequence variants in the β-adrenergic receptor genes alter receptor physiology1214 and pharmacology.1517 Specifically, there are 4 common, nonsynonymous coding variants in the β1-adrenergic receptor (ADRB1) and β2-adrenergic receptor (ADRB2) genes. The ADRB1 variants Ser49Gly (145 AG) and Arg389Gly (1165 CG) have both been associated with altered receptor activation or G protein coupling,12,18 while the ADRB2 variants, Gln27Glu (79 CG) and Gly16Arg (46 GA), have been linked primarily to altered receptor trafficking and down-regulation.19

Underscoring the importance of these polymorphisms is recent data showing that several variants mediate differential therapeutic end points of β-blocker treatment such as blood pressure response in hypertensive patients16,20 and improvement of ejection fraction among heart failure patients.15,21 For example, ADRB2 gene Gln27Glu (79 CG) G allele carriers with heart failure were significantly more likely to demonstrate an improved ejection fraction with carvedilol therapy than were patients homozygous for the C allele.21

Despite the potential importance of these observed associations of β-adrenergic receptor sequence variants with surrogate end points, no relationship between these variants and the survival of patients receiving β-blocker therapy has been reported. Identifying such an association could provide an important opportunity to further individualize therapy and target it to those patients with the greatest opportunity to benefit. As an initial step, we conducted pharmacogenetic analyses of a prospective registry of ACS patients by examining the association of all-cause mortality, stratified by discharge β-blocker status, with genotypes of 4 common functional polymorphisms in ADRB1 and ADBR2 (ADRB1 1165 CG, 145 AG and ADRB2 46 GA, 79 GC).

Patients

Patients were prospectively enrolled into an ACS registry at 2 Kansas City hospitals, the Mid America Heart Institute and Truman Medical Center. All 10 911 consecutive patients admitted between March 1, 2001, and October 31, 2002, who had a troponin blood test ordered were prospectively screened for a possible ACS. Standard definitions were used to diagnose ACS patients with either MI22 or unstable angina.23 Myocardial infarction patients were defined by an elevated troponin value in the setting of symptoms or electrocardiographic changes (both ST-segment elevation and non–ST-segment elevation changes) consistent with an MI. Unstable angina was diagnosed if the patient had a negative troponin blood test and any one of the following: new-onset angina (<2 months) of at least class III of the Canadian Cardiovascular Society Classification, prolonged (>20 minutes) rest angina, recent (<2 months) worsening of angina, or angina that occurred within 2 weeks of an MI.23 All potential unstable angina patients who were found to have a diagnostic study that excluded obstructive coronary disease (ie, coronary angiography, nuclear or echocardiographic stress testing) or who had an additional diagnostic study confirming an alternative explanation for the patient’s presentation (eg, esophago-gastro-duodenoscopy) were subsequently excluded. Three physicians reviewed the charts of all patients for whom diagnostic uncertainty remained and attained consensus on the final diagnosis.

Each participating patient was prospectively interviewed as early as possible during their admission to ascertain sociodemographic, economic, and health status (symptoms, function, and quality of life) characteristics. Patient race was abstracted from hospital admission records. To examine the potential for misclassification of race, we conducted a prospective study of 410 acute MI patients in which a data collector abstracted the patient’s race from the chart and compared this with the patient’s self-reported racial designation. Using patient designation as the gold standard, only 3 (0.7%) patients were misclassified (1 patient who classified himself as black was considered white by chart abstraction and 2 patients who considered themselves to be white were classified as black). Since the same data collectors and hospitals were used for both studies, race classification in this study was considered accurate. Detailed chart abstractions were performed to ascertain patients’ medical history, laboratory results, disease severity, and the processes of inpatient care (including β-blocker administration).

Approval from the institutional review boards of both institutions was obtained prior to the conduct of the study, and written informed consent to participate in the interviews and chart abstractions was signed by each participant. A separate written consent form for the acquisition of blood for genetic analysis was signed by each patient. Although there were no differences in sex (93.2% of men vs 92.2% of women), whites were less likely to consent to DNA testing (91.5% vs 98.3%, P<.001) as were older patients (mean [SD] age for those consenting, 61 [13] years vs 65 [13] years, P = .004). A total of 742 patients were enrolled in the genetic studies of this registry; of these, 735 had discharge medication status known, constituting the cohort for the current analyses.

Mortality Assessment

The Social Security Administration Death Master File was queried to determine patients’ vital status as of March 1, 2005 (http://www.ntis.gov/products/ssa-dmf.asp).

Genotyping

Genomic DNA was isolated using an extraction kit (Gentra, Minneapolis, Minn). Genotyping was carried out using genotyping assays (Applied Biosystems, Foster City, Calif). For ADRB1 145AG and 1165GC, Assays-on-Demand was used (assay No. C_8898508_10 and No. C_8898494_10, respectively). For ADRB2 46 GA and 79 CG, Assays-by-Design was used with the primer and probe sequences listed in Table 1. Pairwise linkage (D’) and haplotype analysis was carried out using the Polymorphism and Haplotype Analysis Suite (http://ilya.wustl.edu/~pgrn/programs.html)24 among African Americans and whites separately.

Table Graphic Jump LocationTable 1. Primers and Probes for ADRB2 Genotype Analysis

The 4 variants analyzed were chosen due to their frequency and the strength of evidence linking them to cardiovascular phenotypes, particularly β-blocker response phenotypes. There are 2 other, uncommon, nonsynonymous coding variants in ADRB2 (Val34Met and Ile164Thr) that were not included due to very small sizes of specific genotype groups that would greatly limit our analyses (both have frequency of heterozygosity <5%). This study was approved by the Washington University Human Studies Committee. These data have been deposited in the Pharmacogenetics and Pharmacogenomics Knowledge Base (accession No. PS205292).

Statistical Analysis

Baseline and follow-up characteristics were compared by genotype. Categorical data are reported as frequencies, and differences between groups were compared with χ2 or Fisher exact tests if expected cell frequencies were less than 5. Continuous data are reported as the mean (SD), and differences between groups were tested using 1-way analysis of variance. Hardy-Weinberg equilibrium was assessed using χ2 tests.

Kaplan-Meier estimates and Cox proportional hazards models were used to describe the association of genotype with patients’ survival. Proportional hazards assumptions were confirmed using Schoenfeld residuals. Follow-up began at the time of discharge from the index hospitalization. To estimate the effect of each polymorphism within β-blocker exposure groups, the population was stratified into those who did or did not receive β-blocker therapy at discharge. To estimate the independent contribution of genotype after adjusting for potential confounders and other clinical predictors, covariates were identified that were either thought to be clinically important or differed significantly by genotype. These included age, race, sex, type of ACS, hypertension, diabetes, heart failure, chronic obstructive pulmonary disease, coronary angiography, and coronary revascularization. Patients’ compound genotypes and inferred diplotypes were analyzed using the same survival models.

As an exploratory analysis, we examined the therapeutic efficacy of β-blocker treatment by genotype. These analyses were considered exploratory because it was anticipated that the study was underpowered to detect mortality differences by genotype within patients not receiving β-blockers or to detect β-blocker-by-genotype interactions. First, a comparison of demographic, clinical, and treatment characteristics by β-blocker therapy was performed (Table 2). Then a nonparsimonious logistic regression model of the propensity to be discharged with β-blockers was created using the variables listed in Table 2 and Table 3. All variables were included as main effects in the model, and second-order terms were included using stepwise selection with P value criteria of <.20. The c statistic of the final model was 0.74. There was sufficient overlap across quintiles of propensity score to permit stratification, and all variables in Table 3 were comparable between β-blocker and no β-blocker patients within quintile of propensity score. The quintile of propensity for β-blocker use was then included in the Cox proportional hazards models along with genotype, β-blocker use, and a genotype-by-β-blocker interaction term. The latter was used to establish differences in β-blocker efficacy by genotype.

Table Graphic Jump LocationTable 2. Baseline Characteristics by Discharge β-Blocker Status*
Table Graphic Jump LocationTable 3. Baseline Characteristics by Genotype*

For all analyses, P values <.05 were considered statistically significant. Analyses were performed with SAS version 9.1 (SAS Institute Inc, Cary, NC) and R version 2.1.0.25

A total of 735 patients made up our study cohort; during 3 years of follow-up, 84 patients died. Baseline characteristics of patients by genotype are listed in Table 3. Mean (SD) age was 60 (12.5) years, 64% (n = 467) of all patients were male, and 77% (n = 567) were identified as white. No significant differences in mortality were observed between races (white vs African American vs other), either by univariable analysis (P = .59) or after adjustment for clinical variables (P = .66). Genotypes were obtained in 86% to 93% of patients (not all variants were successfully genotyped in all patients). None of the variants deviated significantly from Hardy-Weinberg equilibrium within racial groups. The allele frequencies obtained were roughly similar to that reported for the general population26 and did not vary by sex (P>.08 for all). Other classes of discharge medications (aspirin, angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers, statins, nitrates, and diuretics) did not differ significantly between genotype groups (all P>.08), except for aspirin across the ADRB1 145 GA genotypes only (P = .02). At discharge, 597 (81.2%) of patients were treated with β-blockers and 138 (18.8%) were not.

79 CG Genotype and Mortality

Among patients treated with β-blockers, the ADRB2 79 CG genotype was significantly associated with survival (Figure 1). Patients homozygous for the C allele had the worst survival, followed by patients heterozygous for the C allele, with the best survival in patients homozygous for the G allele (3-year Kaplan-Meier mortality rates = 16%, 11%, and 6%, respectively; P = .03). This association remained statistically significant even after adjustment for age, race, sex, ACS type, hypertension, diabetes, heart failure, chronic obstructive pulmonary disease, prior coronary artery bypass graft surgery, renal failure, smoking history, coronary angiography, and coronary revascularization (adjusted hazard ratios [AHRs], 0.51 [95% confidence interval {CI}, 0.30-0.87] for CG vs CC and 0.24 [95% CI, 0.09-0.68] for GG vs CC, P = .004). No association was identified between genotype and mortality among the patients not discharged with β-blocker therapy (3-year Kaplan-Meier mortality rates: CC, 9%; CG, 10%; GG, 7%, P = .98 [unadjusted], P = .61 [adjusted]; AHRs, 0.41 [95% CI, 0.07-2.44] for CG vs CC and 0.49 [95% CI, 0.04-6.92] for GG vs CC).

Figure 1. Mortality of Patients Receiving β-Blocker Therapy by ADRB2 79 C to G Genotype
Graphic Jump Location

P = .03 (unadjusted), P = .004 (adjusted).

46 GA Genotype and Mortality

Among patients treated with β-blockers, the ADRB2 46 GA genotype was significantly associated with survival (Figure 2). The 3-year Kaplan-Meier mortality rates were 20% for AA vs 10% in the GA and GG patients (P = .005). This remained significant after multivariable adjustment (AHRs, 0.48 [95% CI, 0.27-0.86] for GA vs AA and 0.44 [95% CI, 0.22-0.85] for GG vs AA, P = .02). No significant association was observed between genotype and mortality among the patients not discharged with β-blocker therapy (3-year Kaplan-Meier mortality rates : AA, 16%; GA, 8%; GG, 8%, P = .49 [unadjusted], P = .63 [adjusted]; AHRs, 0.40 [95% CI, 0.06-2.57] for GA vs AA and 0.47 [95% CI, 0.06-4.05] for GG vs AA).

Figure 2. Mortality of Patients Receiving β-Blocker Therapy by ADRB2 46 G to A Genotype
Graphic Jump Location

P = .002 (unadjusted), P = .005 (adjusted).

Genotypes and Mortality

No significant association of the ADRB1 1165 CG variant with mortality was observed in either patients discharged with β-blocker therapy (3-year Kaplan-Meier mortality rates: CC, 13%; CG, 10%; GG, 17%, P = .39; AHRs, 0.80 [95% CI, 0.45-1.42] for CG vs CC and 0.91 [95% CI, 0.43-1.91] for GG vs CC, P = .75] or without β-blocker therapy (3-year Kaplan-Meier mortality rates: CC, 10%; CG, 9%; GG, 0%, P = .68; AHRs, 0.95 [95% CI, 0.18-4.97] for CG vs CC, 0 [95% CI, 0-∞] for GG vs CC, P = .99). Similarly, the ADRB1 145 AG variant did not show a significant association with mortality in either the patients discharged with β-blocker therapy (3-year Kaplan-Meier mortality rates : AA, 12%; AG, 12%, GG, 14%, P = .99; AHRs, 0.99 [95% CI, 0.55-1.79] for AG vs AA and 0.47 [95% CI, 0.07-3.13] for GG vs AA, P = .73) or those without β-blocker therapy (3-year Kaplan-Meier mortality rates: AA, 7%; AG, 14%; GG, 0%, P = .38; AHRs, 2.65 [95% CI, 0.54-13.15] for AG vs AA, 0 [95% CI, 0-∞] for GG vs AA, P = .49).

Haplotypes and Compound Genotypes

To better assess the impact of both of the ADRB2 polymorphisms together we performed haplotype and compound genotype analyses. The 2 ADRB2 variants studied were in linkage disequilibrium (D’ = −1, for both African American and whites, both P<.001). Three ADRB2 haplotypes (AC, GC, and GG) were observed, accounting for 42% (562 haplotypes), 21% (283 haplotypes), and 37% (503 haplotypes) of the total, respectively. The ADRB2 diplotype was significantly associated with 3-year mortality among those prescribed β-blocker therapy (P = .04). This divided the β-blocker group into 6 subgroups with 3-year Kaplan-Meier mortality rates ranging from 6% to 20%. To simplify this classification, a composite genotype approach was taken (Table 4). Grouping patients by whether they were homozygous for the 79 G allele (group A), homozygous for the 46 A allele (group C), or neither (composite “heterozygotes,” group B), resulted in low-, high-, and intermediate-risk groups (Figure 3, P = .003). Specifically, group C patients were a high-risk subset with a 3-year Kaplan-Meier mortality rate of 20%. Those in group A were at low risk having a 3-year Kaplan-Meier mortality rate of only 6%, while the remaining patients showed an intermediate Kaplan-Meier mortality rate of 11%. This association remained significant after multivariable adjustment (P = .002; AHRs, 5.36 [95% CI, 1.83-15.69] for group C vs group A and 2.41 [95% CI, 0.86-6.74] for group B vs group A). In the no β-blocker group, no significant association of these composite genotypes with survival was observed (3-year Kaplan-Meier mortality rates = 7%, 8%, 16% for groups A, B, and C, respectively, P = .51 [unadjusted], P = .59 [adjusted]; AHRs, 2.29 [95% CI, 0.13-40.48] for group C vs group A and 0.83 [95% CI, 0.07-10.03] for group B vs group A).

Figure 3. Mortality of Patients Receiving β-Blocker Therapy by ADRB2 Composite Genotype
Graphic Jump Location

A, B, and C refer to composite genotype groups in Table 4. P = .003 (unadjusted), P = .002 (adjusted).

Exploratory Analysis of β-Blocker Efficacy by

As an exploratory analysis, we examined the efficacy of β-blocker therapy within ADRB2 genotypes. Baseline characteristics among those with and without discharge β-blocker therapy are shown in Table 2. Due to small numbers of patients within each genotype who were not treated with β-blockers, no significant interaction was observed for either the 79 CG or 46 GA polymorphisms with β-blocker therapy in terms of mortality (P = .66 and .99, respectively).

In a prospective pharmacogenetic cohort study of patients with ACS, we observed a significant association of ADRB2 genotypes with 3-year survival among those discharged with β-blocker therapy. The 79 C allele was associated with higher mortality in a gene-dose manner. The ADRB2 46 A allele homozygotes were also observed to have higher mortality. Risk stratification was maximized when both genotypes were taken into account, with mortality ranging from 6% in the 46 GG/79 GG group to 20% in the 46 AA/79 CC group. This association remained highly significant after controlling for clinical variables and was only seen in the patients prescribed β-blocker therapy.

This initial description of an association of ADRB2 genotype with survival among patients receiving β-blocker therapy has potentially important implications. The ADRB2 79 CG polymorphism has been previously associated with β-blocker efficacy in heart failure patients,21 with which our results are consistent. It has not, to our knowledge, been examined in the setting of ACS or shown to predict mortality. A decreased risk of incident coronary events was previously noted among elderly G allele carriers,27 consistent in direction with our results, but no effect on overall mortality was identified. The 46 GA variant has been associated with response to β-agonists,28,29 but has not been previously demonstrated to predict surrogate response to β-blocker therapy or mortality.

The ADRB2 79 G allele has been associated with impaired agonist-mediated down-regulation relative to the C allele.30 Mechanistic data regarding the 46 GA polymorphism is somewhat conflicting, with some investigators demonstrating impaired agonist-mediated down-regulation associated with the A allele,30 while others have reported relatively enhanced agonist-mediated desensitization.14,31 It is intriguing to consider that impaired desensitization of the β2-adrenergic receptor may allow for a better response to β-blocker therapy since there would theoretically be both greater adrenergic responsiveness and more receptor sites for antagonist binding. Thus, β-blocker treatment may be especially beneficial among patients carrying the 79 G or 46 G alleles. Conversely, the relatively enhanced agonist mediated desensitization of the 79 C and 46 A alleles may represent “physiologic β-blockade” and enhanced adaptation to the state of adrenergic activation, thus mitigating the beneficial effects of receptor antagonism.

The lack of association between the ADRB1 1165 CG genotype and the mortality of patients treated with β-blockers is also noteworthy. Several studies have suggested that this variant is indicative of β-blocker response among heart failure patients.15,32 It could be that we simply had insufficient power to detect a subtle, but real relationship. It is also possible that this variant is indeed associated with survival among heart failure patients treated with β-blocker therapy, but does not have the same prognostic value among ACS patients. Alternatively, this variant may affect ejection fraction recovery in heart failure, yet not influence mortality. This latter hypothesis is consistent with a substudy of 600 patients from the Metoprolol Extended-Release Randomized Intervention Trial in Heart Failure (MERIT-HF) trial where no mortality difference by ADRB1 1165 CG genotype was found.33

Our study has several important limitations. First, it is an observational cohort study from 2 centers, and therefore cannot account for all sources of variability and confounding. Despite this, our study population is typical in their demographic makeup, overall postevent survival, and rates of drug treatment. An additional potential limitation is that we did not have access to adjudicated causes of death. Although cardiovascular causes are likely to predominate, we cannot make direct inferences about the clinical mechanism of the observed effect. Another concern is that not all patients consented to the genetic portion of this registry. While this could introduce bias, it seems unlikely that patients’ genotypes would be associated with their refusal to participate. In addition, we did not have information on continuous medication use throughout the study period. Although we and others have observed that 70% to 90% of patients continue taking their discharge medications long term,34 we cannot rule out crossover events in terms of β-blocker therapy, although these should bias our results to the null hypothesis.

Most importantly, the number of patients in the no β-blocker group, particularly with minor genotypes, was small. This limited our ability to examine the significance of the association of genotype with mortality in the no β-blocker patients, or to assess the efficacy of β-blocker therapy within genotypes. To definitively address this, a larger cohort of patients not receiving β-blocker therapy is required, or a clinical trial of β-blocker therapy among ADRB2 79 C homozygotes might be considered. Thus, these results provide evidence of a new genetic marker for post-MI risk stratification among patients treated with β-blockers but do not clarify the benefits of β-blocker therapy within specific genotypes.

Among ACS patients discharged with β-blocker therapy, we have identified a genetic association with survival that can assist in the risk stratification of patients. Specifically, the 79 CC and 46 AA groups (39% and 16%, respectively, of our population) are at high risk for long-term mortality and may need additional treatments to optimize their prognosis. Further studies of the efficacy of β-blocker treatment in these patients is warranted to be sure that we are not institutionalizing therapy through the adoption of health care quality performance measures that may offer little benefit, or even potential harm, to these patient subgroups. We strongly encourage further replication of our findings in distinct patient cohorts so that the potential benefit or harm of β-blocker therapy within specific ADRB2 genotype groups can be definitively demonstrated. With further validation, pharmacogenetic targeting of β-blocker therapy may be an opportunity to further improve ACS care and outcomes.

Corresponding Author: Howard L. McLeod, PharmD, Washington University School of Medicine, 660 S Euclid Ave, Campus Box 8069, St Louis, MO 63110 (hmcleod@im.wustl.edu).

Author Contributions: Drs Lanfear, McLeod, and Spertus had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Lanfear, Marsh, Cresci, McLeod, Spertus.

Acquisition of data: Lanfear, McLeod, Spertus.

Analysis and interpretation of data: Lanfear, Jones, Marsh, Cresci, McLeod, Spertus.

Drafting of the manuscript: Lanfear, Marsh, McLeod, Spertus.

Critical revision of the manuscript for important intellectual content: Lanfear, Jones, Marsh, Cresci, McLeod, Spertus.

Statistical analysis: Lanfear, Jones, Spertus.

Obtained funding: McLeod, Spertus.

Administrative, technical, or material support: Lanfear, Marsh, McLeod, Spertus.

Study supervision: Marsh, McLeod, Spertus.

Financial Disclosures: None reported.

Funding/Support: This work was supported in part by grant R01 HS11282-01 from the Agency for Healthcare Research and Quality, grant U01 GM63340 from the NIH Pharmacogenetics research network, an HFSA Research Fellowship Grant, and grant P50 HL077113 from the Specialized Centers of Clinically Oriented Research (SCCOR) program of the National Heart, Lung, and Blood Institute.

Role of the Sponsors: The funding sources had no role in the design, analysis, or interpretation of the manuscript.

Acknowledgment: We thank Adam Garsa, BA, Department of Medicine, Washington University School of Medicine, for genotyping assistance vital to this work. The data have been submitted to www.PharmGKB.org; PS205292.

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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;74:44-52
PubMed   |  Link to Article
Hoit BD, Suresh DP, Craft L, Walsh RA, Liggett SB. Beta2-adrenergic receptor polymorphisms at amino acid 16 differentially influence agonist-stimulated blood pressure and peripheral blood flow in normal individuals.  Am Heart J. 2000;139:537-542
PubMed
Levin MC, Marullo S, Muntaner O, Andersson B, Magnusson Y. The myocardium-protective Gly-49 variant of the beta 1-adrenergic receptor exhibits constitutive activity and increased desensitization and down-regulation.  J Biol Chem. 2002;277:30429-30435
PubMed   |  Link to Article
Liggett SB. Beta(2)-adrenergic receptor pharmacogenetics.  Am J Respir Crit Care Med. 2000;161:S197-S201
PubMed   |  Link to Article
Liu J, Liu ZQ, Tan ZR.  et al.  Gly389Arg polymorphism of beta1-adrenergic receptor is associated with the cardiovascular response to metoprolol.  Clin Pharmacol Ther. 2003;74:372-379
PubMed   |  Link to Article
Kaye DM, Smirk B, Williams C, Jennings G, Esler M, Holst D. Beta-adrenoceptor genotype influences the response to carvedilol in patients with congestive heart failure.  Pharmacogenetics. 2003;13:379-382
PubMed   |  Link to Article
Alpert JS, Thygesen K, Antman E, Bassand JP. Myocardial infarction redefined—a consensus document of the Joint European Society of Cardiology/American College of Cardiology Committee for the redefinition of myocardial infarction.  J Am Coll Cardiol. 2000;36:959-969
PubMed   |  Link to Article
Braunwald E. Unstable angina: a classification.  Circulation. 1989;80:410-414
PubMed   |  Link to Article
Schaid DJ, Rowland CM, Tines DE, Jacobson RM, Poland GA. Score tests for association between traits and haplotypes when linkage phase is ambiguous.  Am J Hum Genet. 2002;70:425-434
PubMed   |  Link to Article
R Development Core Team.  R: A Language and Environment for Statistical ComputingVienna, Austria: R Foundation for Statistical Computing; 2005
Belfer I, Buzas B, Evans C.  et al.  Haplotype structure of the beta-adrenergic receptor genes in US Caucasians and African Americans.  Eur J Hum Genet. 2005;13:341-351
PubMed   |  Link to Article
Heckbert SR, Hindorff LA, Edwards KL.  et al.  Beta2-adrenergic receptor polymorphisms and risk of incident cardiovascular events in the elderly.  Circulation. 2003;107:2021-2024
PubMed   |  Link to Article
Israel E, Drazen JM, Liggett SB.  et al.  Effect of polymorphism of the beta(2)-adrenergic receptor on response to regular use of albuterol in asthma.  Int Arch Allergy Immunol. 2001;124:183-186
PubMed   |  Link to Article
Israel E, Chinchilli VM, Ford JG.  et al.  Use of regularly scheduled albuterol treatment in asthma: genotype-stratified, randomised, placebo-controlled cross-over trial.  Lancet. 2004;364:1505-1512
PubMed   |  Link to Article
Green SA, Turki J, Innis M, Liggett SB. Amino-terminal polymorphisms of the human beta 2-adrenergic receptor impart distinct agonist-promoted regulatory properties.  Biochemistry. 1994;33:9414-9419
PubMed   |  Link to Article
Chong LK, Chowdry J, Ghahramani P, Peachell PT. Influence of genetic polymorphisms in the beta2-adrenoceptor on desensitization in human lung mast cells.  Pharmacogenetics. 2000;10:153-162
PubMed   |  Link to Article
Terra SG, Hamilton KK, Pauly DF.  et al.  Beta-1 adrenergic receptor polymorphisms and left ventricular remodeling changes in response to beta-blocker therapy.  Pharmacogenet Genomics. 2005;15:227-234
PubMed   |  Link to Article
White HL, de Boer RA, Maqbool A.  et al.  An evaluation of the beta-1 adrenergic receptor Arg389Gly polymorphism in individuals with heart failure: a MERIT-HF sub-study.  Eur J Heart Fail. 2003;5:463-468
PubMed   |  Link to Article
Muhlestein JB, Horne BD, Bair TL.  et al.  Usefulness of in-hospital prescription of statin agents after angiographic diagnosis of coronary artery disease in improving continued compliance and reduced mortality.  Am J Cardiol. 2001;87:257-261
PubMed   |  Link to Article

Figures

Figure 1. Mortality of Patients Receiving β-Blocker Therapy by ADRB2 79 C to G Genotype
Graphic Jump Location

P = .03 (unadjusted), P = .004 (adjusted).

Figure 2. Mortality of Patients Receiving β-Blocker Therapy by ADRB2 46 G to A Genotype
Graphic Jump Location

P = .002 (unadjusted), P = .005 (adjusted).

Figure 3. Mortality of Patients Receiving β-Blocker Therapy by ADRB2 Composite Genotype
Graphic Jump Location

A, B, and C refer to composite genotype groups in Table 4. P = .003 (unadjusted), P = .002 (adjusted).

Tables

Table Graphic Jump LocationTable 1. Primers and Probes for ADRB2 Genotype Analysis
Table Graphic Jump LocationTable 2. Baseline Characteristics by Discharge β-Blocker Status*
Table Graphic Jump LocationTable 3. Baseline Characteristics by Genotype*

References

American Heart Association.  Heart Disease and Stroke Statistics-2005 Update. American Heart Association. Available at: http://www.americanheart.org/presenter.jhtml?identifier=1928; 2004. Accessibility verified August 17, 2005
Hennekens CH, Braunwald E. Clinical Trials in Cardiovascular Disease: A Companion to Braunwald's Heart DiseasePhiladelphia, Pa: WB Saunders; 1999
Spertus JA, Radford MJ, Every NR, Ellerbeck EF, Peterson ED, Krumholz HM. Challenges and opportunities in quantifying the quality of care for acute myocardial infarction: summary from the Acute Myocardial Infarction Working Group of the American Heart Association/American College of Cardiology First Scientific Forum on Quality of Care and Outcomes Research in Cardiovascular Disease and Stroke.  Circulation. 2003;107:1681-1691
PubMed   |  Link to Article
Herlitz J, Waldenstrom J, Hjalmarson A. Infarct size limitation after early intervention with metoprolol in the MIAMI Trial.  Cardiology. 1988;75:117-122
PubMed   |  Link to Article
β-Blocker Heart Attack Trial Research Group.  A randomized trial of propranolol in patients with acute myocardial infarction, I: mortality results.  JAMA. 1982;247:1707-1714
PubMed   |  Link to Article
First International Study of Infarct Survival Collaborative Group.  Randomised trial of intravenous atenolol among 16 027 cases of suspected acute myocardial infarction: ISIS-1.  Lancet. 1986;2:57-66
PubMed
Ohte N, Kurokawa K, Iida A.  et al.  Myocardial oxidative metabolism in remote normal regions in the left ventricles with remodeling after myocardial infarction: effect of beta-adrenoceptor blockers.  J Nucl Med. 2002;43:780-785
PubMed
Evrengul H, Dursunoglu D, Kayikcioglu M.  et al.  Effects of a beta-blocker on ventricular late potentials in patients with acute anterior myocardial infarction receiving successful thrombolytic therapy.  Jpn Heart J. 2004;45:11-21
PubMed   |  Link to Article
Marciniak TA, Ellerbeck EF, Radford MJ.  et al.  Improving the quality of care for Medicare patients with acute myocardial infarction: results from the Cooperative Cardiovascular Project.  JAMA. 1998;279:1351-1357
PubMed   |  Link to Article
Jencks SF, Cuerdon T, Burwen DR.  et al.  Quality of medical care delivered to Medicare beneficiaries: a profile at state and national levels.  JAMA. 2000;284:1670-1676
PubMed   |  Link to Article
Evans WE, McLeod HL. Pharmacogenomics—drug disposition, drug targets, and side effects.  N Engl J Med. 2003;348:538-549
PubMed   |  Link to Article
Mason DA, Moore JD, Green SA, Liggett SB. A gain-of-function polymorphism in a G-protein coupling domain of the human beta1-adrenergic receptor.  J Biol Chem. 1999;274:12670-12674
PubMed   |  Link to Article
Drysdale CM, McGraw DW, Stack CB.  et al.  Complex promoter and coding region beta 2-adrenergic receptor haplotypes alter receptor expression and predict in vivo responsiveness.  Proc Natl Acad Sci U S A. 2000;97:10483-10488
PubMed   |  Link to Article
Dishy V, Sofowora GG, Xie HG.  et al.  The effect of common polymorphisms of the beta2-adrenergic receptor on agonist-mediated vascular desensitization.  N Engl J Med. 2001;345:1030-1035
PubMed   |  Link to Article
Mialet Perez J, Rathz DA, Petrashevskaya NN.  et al.  Beta(1)-adrenergic receptor polymorphisms confer differential function and predisposition to heart failure.  Nat Med. 2003;9:1300-1305
PubMed   |  Link to Article
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;74:44-52
PubMed   |  Link to Article
Hoit BD, Suresh DP, Craft L, Walsh RA, Liggett SB. Beta2-adrenergic receptor polymorphisms at amino acid 16 differentially influence agonist-stimulated blood pressure and peripheral blood flow in normal individuals.  Am Heart J. 2000;139:537-542
PubMed
Levin MC, Marullo S, Muntaner O, Andersson B, Magnusson Y. The myocardium-protective Gly-49 variant of the beta 1-adrenergic receptor exhibits constitutive activity and increased desensitization and down-regulation.  J Biol Chem. 2002;277:30429-30435
PubMed   |  Link to Article
Liggett SB. Beta(2)-adrenergic receptor pharmacogenetics.  Am J Respir Crit Care Med. 2000;161:S197-S201
PubMed   |  Link to Article
Liu J, Liu ZQ, Tan ZR.  et al.  Gly389Arg polymorphism of beta1-adrenergic receptor is associated with the cardiovascular response to metoprolol.  Clin Pharmacol Ther. 2003;74:372-379
PubMed   |  Link to Article
Kaye DM, Smirk B, Williams C, Jennings G, Esler M, Holst D. Beta-adrenoceptor genotype influences the response to carvedilol in patients with congestive heart failure.  Pharmacogenetics. 2003;13:379-382
PubMed   |  Link to Article
Alpert JS, Thygesen K, Antman E, Bassand JP. Myocardial infarction redefined—a consensus document of the Joint European Society of Cardiology/American College of Cardiology Committee for the redefinition of myocardial infarction.  J Am Coll Cardiol. 2000;36:959-969
PubMed   |  Link to Article
Braunwald E. Unstable angina: a classification.  Circulation. 1989;80:410-414
PubMed   |  Link to Article
Schaid DJ, Rowland CM, Tines DE, Jacobson RM, Poland GA. Score tests for association between traits and haplotypes when linkage phase is ambiguous.  Am J Hum Genet. 2002;70:425-434
PubMed   |  Link to Article
R Development Core Team.  R: A Language and Environment for Statistical ComputingVienna, Austria: R Foundation for Statistical Computing; 2005
Belfer I, Buzas B, Evans C.  et al.  Haplotype structure of the beta-adrenergic receptor genes in US Caucasians and African Americans.  Eur J Hum Genet. 2005;13:341-351
PubMed   |  Link to Article
Heckbert SR, Hindorff LA, Edwards KL.  et al.  Beta2-adrenergic receptor polymorphisms and risk of incident cardiovascular events in the elderly.  Circulation. 2003;107:2021-2024
PubMed   |  Link to Article
Israel E, Drazen JM, Liggett SB.  et al.  Effect of polymorphism of the beta(2)-adrenergic receptor on response to regular use of albuterol in asthma.  Int Arch Allergy Immunol. 2001;124:183-186
PubMed   |  Link to Article
Israel E, Chinchilli VM, Ford JG.  et al.  Use of regularly scheduled albuterol treatment in asthma: genotype-stratified, randomised, placebo-controlled cross-over trial.  Lancet. 2004;364:1505-1512
PubMed   |  Link to Article
Green SA, Turki J, Innis M, Liggett SB. Amino-terminal polymorphisms of the human beta 2-adrenergic receptor impart distinct agonist-promoted regulatory properties.  Biochemistry. 1994;33:9414-9419
PubMed   |  Link to Article
Chong LK, Chowdry J, Ghahramani P, Peachell PT. Influence of genetic polymorphisms in the beta2-adrenoceptor on desensitization in human lung mast cells.  Pharmacogenetics. 2000;10:153-162
PubMed   |  Link to Article
Terra SG, Hamilton KK, Pauly DF.  et al.  Beta-1 adrenergic receptor polymorphisms and left ventricular remodeling changes in response to beta-blocker therapy.  Pharmacogenet Genomics. 2005;15:227-234
PubMed   |  Link to Article
White HL, de Boer RA, Maqbool A.  et al.  An evaluation of the beta-1 adrenergic receptor Arg389Gly polymorphism in individuals with heart failure: a MERIT-HF sub-study.  Eur J Heart Fail. 2003;5:463-468
PubMed   |  Link to Article
Muhlestein JB, Horne BD, Bair TL.  et al.  Usefulness of in-hospital prescription of statin agents after angiographic diagnosis of coronary artery disease in improving continued compliance and reduced mortality.  Am J Cardiol. 2001;87:257-261
PubMed   |  Link to Article

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