A slow, steady heart rate (HR) is necessary for optimal image quality during coronary computed tomographic angiography. Beta blockers are often used, but the goal HR is not achieved in some patients. The aim of this study was to examine the influence of single-nucleotide polymorphisms (SNPs) of the β 1 (codons 49 and 389) and β 2 (codons 16, 27, and 164) adrenergic receptor (AR) genes on HR response to metoprolol in 200 adults (mean age 56 ± 11 years) referred for coronary computed tomographic angiography (using a 64-slice scanner). Oral and intravenous (IV) metoprolol was given to achieve a goal HR of <60 beats/min. Overall, 37 patients (18.5%) did not reach the goal HR despite the administration of oral (181 ± 116 mg) and IV (4.2 ± 9.4 mg) metoprolol. Patients with the β 1 -AR Ser49Gly or Gly49Gly genotype (n = 49) more often failed to reach an optimal HR compared to those with the Ser49Ser genotype (n = 151) (29% vs 15%, p = 0.04), despite receiving higher doses of oral (210 ± 115 vs 172 ± 115 mg, p = 0.048) and IV (7 ± 13 vs 3 ± 8 mg, p = 0.02) metoprolol. Similarly, patients with the β 1 -AR Gly389Gly genotype (n = 11) more often failed to reach an optimal HR compared to those with the Arg389Arg and Arg389Gly genotypes (n = 189) (45% vs 17%, p = 0.02), despite receiving higher doses of IV (13 ± 15 vs 4 ± 9 mg, p = 0.002) but not oral (162 ± 105 vs 182 ± 117 mg, p = 0.50) metoprolol. Multivariate analysis identified β 1 -AR SNPs at codons 49 and 389 and β 2 -AR SNP at codon 27 as independent predictors of suboptimal HR response. In conclusion, these data indicate that the selected SNPs of β 1 -AR and β 2 -AR genes influence HR response to metoprolol in patients who undergo coronary computed tomographic angiography.
Noninvasive coronary computed tomographic angiography (CCTA), using multidetector (≥64 channels) technology, is an established technique for diagnosis and risk stratification of coronary artery disease (CAD). However, image quality and diagnostic accuracy of the current-generation scanners and radiation dose reduction algorithms are dependent on the heart rate (HR) and the regularity of cardiac rhythm. A slow (<60 beats/min) and steady HR is thus recommended for optimal image quality. An “optimal” HR, however, is frequently not observed on patient presentation and is often not achieved despite the administration of β-adrenergic receptor (AR) blockers, predominantly metoprolol. Suboptimal HR control in this setting has been attributed to high baseline HR (partially mediated through anxiety) or inadequate doses of β blockers in the absence of a widely adopted protocol. Genetic factors are recognized as major determinants of rest HR and individual response to β blockers, but their effect on HR control before CCTA is unknown. Therefore, we aimed to prospectively examine the impact of β-AR gene functional single-nucleotide polymorphisms (SNPs) on HR response to metoprolol before CCTA.
Methods
From May 2008 to November 2009, 201 adults scheduled for clinically indicated CCTA were prospectively enrolled. Patients fulfilled the following inclusion criteria: age >18 years, in sinus rhythm, no contraindication to β blockers, and ability to provide written consent. Genotyping could not be performed on 1 sample, and thus 1 patient was excluded. The study was approved by the institutional research review board.
Venous blood was obtained peripherally before CCTA and was stored in the Genomic Core Laboratory. Deoxyribonucleic acid was extracted from ethylenediaminetetraacetic acid–anticoagulated whole blood using the MagAttract DNA Blood Midi M48 Kit and BioRobot M48 Workstation (Qiagen, Valencia, California). Genotyping was performed on a 7500 real-time polymerase chain reaction system (Applied Biosystems, Foster City, California) using assay reagents for β 1 -AR and β 2 -AR SNPs obtained from Applied Biosystems (β 1 -AR: rs1801252, assay ID C_8898508_10; rs1801253, assay ID C_8898494_10; β 2 -AR: rs1800888, assay ID C_8950503_20; rs1042713, assay ID C_2084764_20; rs1042714, assay ID C_2084765_20). The components for each genotyping reaction were as follows: 10 ng of deoxyribonucleic acid, 5 μl of TaqMan Genotyping Master Mix (Applied Biosystems), 0.25 μl of assay mix (40×), and water up to a total volume of 10 μl. The thermal cycler conditions for real-time polymerase chain reaction were 50°C for 2 minutes, 95°C for 10 minutes, 40 cycles of 95°C for 15 seconds, and 60°C for 60 seconds and a 1-minute post–polymerase chain reaction read at 60°C. The reaction was analyzed with the Applied Biosystems 7500 Sequence Detection Software.
A steady goal HR of <60 beats/min defined the “responders.” All patients with baseline HRs >50 beats/min received ≥1 dose of oral metoprolol (50 mg). Additional oral (50- to 100-mg doses) and intravenous (IV) (5-mg doses) metoprolol was given as needed to achieve the goal HR in those with HRs ≥60 beats/min after the initial dose. Oral lorazepam (0.5 to 1.0 mg) was given to 9 patients in whom anxiety seemed to have contributed to poor HR control.
A standard coronary computed tomographic angiographic imaging protocol was followed as described previously using a 64-slice scanner (GE LightSpeed VCT; GE Healthcare, Milwaukee, Wisconsin).
On the basis of reported allele frequencies in Caucasians and the Hardy-Weinberg equilibrium, we expected the following genotype frequencies: 50% Arg-Arg, 40% Arg-Gly, and 10% Gly-Gly for codon 389 and 60% Ser-Ser, 35% Ser-Gly, and 5% Gly-Gly for codon 49 of the β 1 -AR gene. Because of small number of expected homozygotes for the minor allele, sample size was calculated to detect significant differences between homozygotes for the more frequent allele and carriers of the minor allele. A sample size of 200 patients was required to detect a 20% absolute difference in percentage of patients who would reach goal HR <60 beats/min between Arg389 homozygotes (Arg389Arg) and Gly389 carriers (Arg389Gly + Gly389Gly) and a 17% absolute difference between Ser49 homozygotes (Ser49Ser) and Gly49 carriers (Ser49Gly + Gly49Gly). The calculated sample size had 80% power at prespecified 2-tailed α level of 0.05.
Results are presented as range (mean ± SD) or as number (percentage). Discrete variables were compared using chi-square analysis or Fisher’s exact test, and continuous variables were compared using Student’s t test. Conformity of the genotype distributions to the Hardy-Weinberg equilibrium was assessed using the chi-square test. Analysis of variance was used to compare >2 groups. A nominal 2-sided p value <0.05 defined statistical significance. Multivariate logistic regression was performed to determine independent predictors of suboptimal response to metoprolol by entering all predictors with p values <0.10 in univariate analysis into a forward stepwise model.
Results
Demographic and clinical characteristics of the 200 adults are listed in Table 1 . The patient population served by the Geisinger Health System is predominantly (>95%) of European descent, and therefore only Caucasians were enrolled. Hypertension was defined as blood pressure >140/90 mm Hg or the use of antihypertensive medications, hypercholesterolemia was defined as total serum cholesterol >200 mg/dl or the use of lipid-lowering drugs, and CAD was defined as at least moderate (>25%) luminal narrowing in ≥1 major epicardial coronary artery by CCTA.
| Variable | Value |
|---|---|
| Age (yrs) | 24–85 (56 ± 11) |
| Men/women | 107 (53.5%)/93 (46.5%) |
| White | 200 (100%) |
| Height (cm) | 74–193 (169 ± 13) |
| Weight (kg) | 50–175 (91 ± 22) |
| Body mass index (kg/m 2 ) | 18–51 (31 ± 7) |
| Hypertension | 80 (40%) |
| Diabetes mellitus | 26 (13%) |
| Hypercholesterolemia | 158 (79%) |
| Coronary artery disease | 119 (59.5%) |
| Left ventricular ejection fraction (%) | 23–87 (63 ± 10) |
| Baseline medications | |
| β-blocking agents | 87 (43.5%) |
| Calcium channel blockers | 7 (3.5%) |
| Flecainide | 2 (1%) |
| Sotalol | 2 (1%) |
| Digoxin | 1 (0.5%) |
The allele frequencies for the β 1 -AR SNPs were comparable to those in previous reports in Caucasians: 0.88 Ser/0.12 Gly at codon 49 and 0.75 Arg/0.25 Gly at codon 389. Genotype frequencies were also in agreement with other studies ( Table 2 ) and included relatively few homozygotes for the minor alleles (11 Gly389Gly and 4 Gly49Gly). Minor allele frequencies of the β 2 -AR SNPs at codons 16 and 27 were also comparable to those in previous reports.
| Codon | Genotype | Frequency |
|---|---|---|
| β 1 -AR gene | ||
| 49 | Ser/Ser | 151 (76%) |
| Ser/Gly | 45 (22%) | |
| Gly/Gly | 4 (2%) | |
| 389 | Arg/Arg | 108 (54%) |
| Arg/Gly | 81 (41%) | |
| Gly/Gly | 11 (5%) | |
| β 2 -AR gene | ||
| 16 | Arg/Arg | 32 (16%) |
| Arg/Gly | 83 (42%) | |
| Gly/Gly | 83 (42%) | |
| 27 | Gln/Gln | 64 (32%) |
| Gln/Glu | 93 (47%) | |
| Glu/Glu | 42 (21%) | |
| 164 | Thr/Thr | 196 (98%) |
| Thr/Ile | 4 (2%) |
The mean HR on presentation was 74 beats/min (range 46 to 122). Metoprolol dosage varied among subjects depending on the baseline HR and response to initial dose of metoprolol. Thus, 8 patients with baseline HRs ≤50 beats/min received no metoprolol, while 192 (96%) with baseline HRs >50 beats/min received ≥50 mg of oral metoprolol (range 50 to 500, mean 181 ± 116). In addition, 48 patients (24%) received IV metoprolol (range 5 to 25 mg, mean 4.2 ± 9.0). Lorazepam (0.5 to 1.0 mg) was administered to 9 patients (4.5%) in addition to metoprolol.
Overall, 37 subjects (18.5%) did not reach a HR of <60 beats/min (nonresponders). Compared to 163 responders, nonresponders had lower left ventricular ejection fractions (59 ± 13% vs 64 ± 9%, p = 0.03) and higher baseline HRs (81 ± 13 vs 73 ± 12 beats/min, p = 0.002). Equal proportions of patients in the 2 groups were receiving β blockers at baseline. Nonresponders, however, received significantly higher doses of oral (252 ± 109 vs 165 ± 112 mg, p = 0.001) and IV (18 ± 14 vs 1 ± 3 mg, p = 0.001) metoprolol before CCTA ( Table 3 ). In addition, a higher percentage of the nonresponders required IV metoprolol (20 [12%] vs 28 [75%], p = 0.001). A higher proportion of nonresponders carried the Gly allele at codon 49 (Ser49Gly and Gly49Gly genotypes) and were homozygote for the Gly allele at codon 389 (Gly389Gly genotype) ( Table 3 ). No significant difference existed in β 2 -AR genotype frequencies between responders and nonresponders.
| Variable | HR (beats/min) | p Value | |
|---|---|---|---|
| <60 (n = 163) | ≥60 (n = 37) | ||
| Age (yrs) | 56 ± 11 | 52 ± 13 | 0.07 |
| Men/women | 87 (53%)/76 (47%) | 20 (54%)/17 (46%) | NS |
| Hypertension | 64 (39%) | 16 (43%) | NS |
| Diabetes mellitus | 18 (11%) | 8 (22%) | 0.08 |
| Coronary artery disease | 92 (56%) | 27 (73%) | 0.06 |
| Left ventricular ejection fraction (%) | 64 ± 9 | 59 ± 13 | 0.03 |
| Taking a β blocker at baseline | 71 (44%) | 16 (43%) | NS |
| Baseline heart rate (beats/min) | 73 ± 12 | 81 ± 13 | 0.002 |
| β blocker received before CCTA | |||
| Oral metoprolol (mg) | 165 ± 112 | 252 ± 109 | 0.001 |
| Any IV metoprolol | 20 (12%) | 28 (75%) | 0.001 |
| Dosage (mg) | 1 ± 3 | 18 ± 14 | 0.001 |
| Genotypes | |||
| β 1 -AR | |||
| Codon 49 | |||
| Ser/Ser | 128 (79%) | 23 (62%) | 0.037 |
| Ser/Gly + Gly/Gly | 35 (21%) | 14 (38%) | |
| Codon 389 | |||
| Arg/Arg + Arg/Gly | 157 (96%) | 32 (87%) | 0.02 |
| Gly/Gly | 6 (4%) | 5 (13%) | |
| β 2 -AR | |||
| Codon 16 | |||
| Arg/Arg + Arg/Gly | 97 (59%) | 19 (51%) | 0.80 |
| Gly/Gly | 66 (41%) | 18 (49%) | |
| Codon 27 | |||
| Gln/Gln + Gln/Glu | 132 (81%) | 25 (68%) | 0.10 |
| Glu/Glu | 31 (19%) | 12 (32%) | |
| Codon 164 | |||
| Thr/Thr | 159 (98%) | 37 (100%) | 0.80 |
| Thr/Ile | 4 (2%) | 0 | |
Table 4 lists the nonresponse rates and oral and IV metoprolol doses for various β 1 -AR and β 2 -AR genotypes. Gly49 carriers had a higher nonresponse rate than Ser49 homozygotes (29% vs 15%, p = 0.04) despite receiving higher doses of oral and IV metoprolol. Similarly, Gly389 homozygotes had a higher nonresponse rate than Arg389 carriers (45% vs 17%, p = 0.02) despite receiving higher doses of IV metoprolol. Thus, Ser49 homozygotes and Arg389 carriers (sensitive genotypes) were better responders to metoprolol than Gly49 carriers and Gly389 homozygotes (resistant genotypes). Therefore, we also evaluated the HR response to metoprolol in various diplotypes of the codons 49 and 389 of the β 1 -AR gene. The most sensitive diplotypes were the Arg389Arg/Ser49Ser and Arg389Gly/Ser49Ser (nonresponse rate 12.9%), followed by an intermediate response group including Arg389Arg/Ser49Gly, Arg389Arg/Gly49Gly, and Arg389Gly/Ser49Gly (nonresponse rate 28.6%) and a resistant diplotype (Gly389Gly/Ser49Ser, nonresponse rate 45.5%) ( Table 5 ). No patient had any of the 2 diplotypes that could theoretically have the highest nonresponse rates to metoprolol (Gly389Gly/Ser49Gly or Gly383Gly/Gly49Gly).
| Genotype | Nonresponse Rate | Oral Metoprolol (mg) | IV Metoprolol (mg) |
|---|---|---|---|
| β 1 -AR | |||
| Codon 49 | |||
| Ser/Ser | 23/151 (15%) | 172 ± 115 | 3.3 ± 7.9 |
| Ser/Gly + Gly/Gly | 14/49 (29%) (p = 0.04) | 210 ± 115 (p = 0.048) | 7 ± 12.8 (p = 0.02) |
| Codon 389 | |||
| Arg/Arg + Arg/Gly | 32/189 (17%) | 182 ± 117 | 3.7 ± 8.8 |
| Gly/Gly | 5/11 (45%) (p = 0.02) | 163 ± 105 (p = 0.50) | 12.7 ± 15.4 (p = 0.002) |
| β 2 -AR | |||
| Codon 16 | |||
| Arg/Arg + Arg/Gly | 19/115 (16.5%) | 187 ± 121 | 4.1 ± 9 |
| Gly/Gly | 17/83 (20.5%) (p = 0.50) | 174 ± 109 (p = 0.40) | 4.1 ± 10.1 (p = 0.90) |
| Codon 27 | |||
| Gln/Gln + Gln/Glu | 25/157 (16%) | 180 ± 118 | 3.9 ± 8.7 |
| Glu/Glu | 12/42 (29%) (p = 0.06) | 184 ± 111 (p = 0.80) | 5.1 ± 11.8 (p = 0.50) |
| Codon 164 | |||
| Thr/Thr | 37/196 (19%) | 181 ± 117 | 4.2 ± 9.5 |
| Thr/Ile | 0/4 (0%) (p = 0.90) | 175 ± 50 (p = 0.80) | 1.2 ± 2.5 (p = 0.50) |
| Variable | Sensitivity of HR to Metoprolol | p Value | ||
|---|---|---|---|---|
| High ∗ (n = 140) | Intermediate † (n = 49) | Low ‡ (n = 11) | ||
| Nonresponse rate (HR >60 beats/min) | 12.9% | 28.6% | 45.5% | 0.003 |
| Oral metoprolol (mg) | 173 ± 105 | 163 ± 105 | 207 ± 115 | 0.1 |
| IV metoprolol (mg) | 2.5 ± 6.5 | 7 ± 13 | 13 ± 15 | 0.001 |
| Lowest HR (beats/min) | 52 ± 6 | 54 ± 7 | 58 ± 8 | 0.004 |
| Age (yrs) | 56 ± 10 | 53 ± 13 | 54 ± 13 | NS |
| Men | 54% | 51% | 64% | NS |
| Ejection fraction | 64 ± 10 | 63 ± 12 | 60 ± 12 | NS |
| Hypertension | 41% | 39% | 36% | NS |
| Diabetes mellitus | 11% | 16% | 27% | NS |
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