N-terminal pro–B-type natriuretic peptide (NT–pro-BNP) is a commonly measured cardiovascular biomarker in ambulatory and hospital settings. Nonetheless, there are limited data regarding “normal” ranges for NT–pro-BNP in healthy subjects, despite the importance of such information for interpreting natriuretic peptide measurements. In this study, a healthy reference sample free of cardiovascular disease from the Framingham Heart Study Generation 3 cohort was examined; there were 2,285 subjects (mean age 38 years, 56% women). Plasma NT–pro-BNP levels were measured using the Roche Diagnostics Elecsys 2010 assay, and reference values (2.5th, 50th, and 97.5th quantiles) were determined using empiric and quantile regression methods. Gender, age, blood pressure, and body mass index accounted for approximately 33% of the interindividual variability in NT–pro-BNP in the reference sample. NT–pro-BNP values were substantially higher in women compared to men at every age, and levels increased with increasing age for both genders. Using quantile regression, the upper reference values (97.5th quantile) for NT–pro-BNP were 42.5 to 106.4 pg/ml in men (depending on age) and 111.0 to 215.9 pg/ml in women. Intraindividual variability was assessed in an additional 12 healthy subjects, who had serial NT–pro-BNP measurements over 1 month. Intraclass correlation was 0.85, indicating that most of the variability in NT–pro-BNP concentrations was among rather than within subjects. However, the reference change value was 100%, suggesting that small proportional differences in NT–pro-BNP could be attributable to analytic variability. In conclusion, the reference limits obtained from this large, healthy, community-based sample may aid in the evaluation of NT–pro-BNP concentrations measured for clinical and research purposes.
The objectives of the present study were threefold. First, we sought to establish reference limits for N-terminal pro–B-type natriuretic peptide (NT–pro-BNP) using a widely available commercial assay and a large, well-characterized community-based sample. Second, we examined the clinical correlates of NT–pro-BNP in this reference sample and assessed the influence of age and gender on the normal ranges. Last, we set out to determine the intraindividual variability of NT–pro-BNP concentrations over serial measurements.
Methods
The design and selection criteria of the Framingham Heart Study Generation 3 cohort have been previously described. The Generation 3 cohort began in 2002 with the recruitment of 4,095 men and women who were the grandchildren of the original Framingham Heart Study participants. Participants who attended the first examination cycle (from 2002 to 2005) were eligible for this investigation. Subjects were excluded for the following reasons, in a hierarchical manner: prevalent cardiovascular disease, including history of myocardial infarction, angina pectoris, coronary insufficiency, heart failure, stroke, transient ischemic attack, or intermittent claudication (n = 45); history of atrial fibrillation (n = 16); diabetes (n = 112); hypertension (systolic blood pressure ≥140 mm Hg or diastolic blood pressure ≥90 mm Hg or the use of antihypertensive medications; n = 595); obesity (body mass index ≥30 kg/m 2 ; n = 591); valvular heart disease (grade 3/6 systolic murmur or any diastolic murmur on examination; n = 24); renal insufficiency (estimated glomerular filtration rate ≤60 ml/min using the Modification of Diet in Renal Disease [MDRD] formula; n = 8); history of pulmonary disease (n = 304); history of thyroid disease (n = 99); age <20 or >59 years (n = 12); and missing NT–pro-BNP values (n = 4). The final reference sample comprised 2,285 subjects (56% of participants, 1,013 men and 1,272 women) after these exclusions.
A separate group of men and women aged 18 to 75 years (not part of the Framingham Heart Study) was enrolled at Massachusetts General Hospital for intraindividual variability analyses. Exclusion criteria included a history of congestive heart failure or myocardial infarction, previous coronary angioplasty or stent implantation, history of coronary artery bypass graft surgery, history of stable or unstable angina, history of peripheral vascular surgery or procedure, hypertension or the use of antihypertensive medications, use of nitrates or phosphodiesterase inhibitors, body mass index ≥27 kg/m 2 (calculated on the basis of reported height and weight), diabetes, renal failure, and pregnancy. After applying these exclusions, a sample of 12 healthy subjects (aged 26 to 53 years) were included in the analysis. The institutional review boards of Boston University and Massachusetts General Hospital approved these studies. All participants provided informed consent before their involvement.
At the Framingham examination, a detailed medical history was obtained to determine cardiovascular disease risk factors. Participants underwent routine physical examinations, venipuncture with collection of fasting blood samples, anthropometry, and 12-lead electrocardiography. Systolic and diastolic blood pressures were measured in the left arm with the participant seated for 5 minutes using a standard mercury column sphygmomanometer. The examining physician recorded values to the nearest even number, and the mean of 2 separate readings was used for study analysis.
In the intraindividual variability study at Massachusetts General Hospital, participants were examined up to 4 times over a 1-month period. Absence of intercurrent illness or use of new medications was confirmed by a nurse-administered questionnaire. Blood pressure was checked at each visit, following the protocol described previously.
Blood samples were obtained from fasting participants in the morning, typically between 8 and 9 am . Subjects were in the supine position, and blood was obtained from the antecubital vein. Samples were immediately transferred to prechilled tubes containing ethylenediaminetetraacetic acid and then stored at −70°C for future analysis. Plasma NT–pro-BNP was measured with an electrochemiluminesence assay (Elecsys 2010; Roche Diagnostics, Indianapolis, Indiana) using established methods. The lower limit of detection was 4 pg/ml. The mean coefficient of variation for these samples was 2.7%.
In the healthy Framingham sample, we estimated reference limits for NT–pro-BNP using 2 statistical approaches: empiric and quantile regression. To develop empiric reference limits, the sample was divided into subgroups on the basis of gender and 5-year age bins; estimates of the 2.5th, 50th, and 97.5th quantiles were made within each subgroup. With moderate subgroup sizes, empiric estimates tend to vary substantially. Therefore, we also used linear quantile regression (PROC QUANTREG) to estimate conditional quantile functions for log NT–pro-BNP. Gender-specific regressions were used with age as the predictor. The regression coefficients were estimated at the 2.5th, 50th, and 97.5th quantiles; reference limits were estimated at 5-year age increments for men and women separately. In addition, multivariate linear regression analyses were performed to assess the clinical correlates of log NT–pro-BNP, regressing log NT–pro-BNP on gender, age, body mass index, systolic blood pressure, and diastolic blood pressure. Continuous predictor variables were standardized (SD = 1) to facilitate comparison of effect sizes. We tested for a gender interaction and repeated the analyses separately in men and women.
To assess intraindividual variability from the Massachusetts General Hospital sample, we calculated the mean intraindividual variance and the intraclass correlation (ICC) for the group. The ICC varies from 0 to 1 and corresponds to the proportion of total variability in the analyte attributable to among-subject rather than within-subject variability. Additionally, we determined the reference change value for the group using a Z value of 1.96, as described previously. All analyses were done using SAS version 9.1.3 (SAS Institute Inc., Cary, North Carolina).
Results
Characteristics of the subjects included in the reference sample are listed in Table 1 . The mean age was 38 years, and 56% were women. Using empiric and quantile regression approaches, we estimated NT–pro-BNP reference limits in men and women aged 20 to 59 years. Upper (97.5th quantile), median (50th quantile), and lower (2.5th quantile) reference limits are presented by 5-year age intervals separately for men and women in Table 2 and Figure 1 .
| Variable | Men | Women |
|---|---|---|
| (n = 1,013) | (n = 1,272) | |
| Age (years) | 39 (20, 59) | 38 (20, 59) |
| Body mass index (kg/m 2 ) | 25.6 ± 2.6 | 23.4 ± 2.9 |
| Systolic blood pressure (mm Hg) | 116 ± 9 | 109 ± 10 |
| Diastolic blood pressure (mm Hg) | 75 ± 8 | 70 ± 8 |
| Creatinine (mg/dl) | 0.91 ± 0.12 | 0.70 ± 0.10 |
| NT–pro-BNP (pg/ml) | 16.5 (4.0, 225.5) | 44.0 (4.0, 510.3) |
| Age Group (Years) (Men/Women) | NT–pro-BNP (pg/ml) | |||||
|---|---|---|---|---|---|---|
| Men | Women | |||||
| 2.5th Quantile | 50th Quantile | 97.5th Quantile | 2.5th Quantile | 50th Quantile | 97.5th Quantile | |
| Empiric reference limits | ||||||
| 20–24 (68/90) | 4 | 9.6 | 41.8 | 4 | 29 | 103.5 |
| 25–29 (82/100) | 4 | 13.5 | 51.6 | 10.3 | 39.4 | 153.7 |
| 30–34 (164/215) | 4 | 14.7 | 53.1 | 9.5 | 42.7 | 134.1 |
| 35–39 (230/297) | 4 | 14.6 | 69.2 | 9.7 | 43.2 | 154.2 |
| 40–44 (197/280) | 4 | 18.5 | 59.8 | 8.9 | 44.1 | 161.5 |
| 45–49 (175/167) | 4 | 18.7 | 84.7 | 11 | 53.5 | 185.7 |
| 50–54 (81/93) | 4 | 27.7 | 103.5 | 11.5 | 51 | 201 |
| 55–59 (16/30) | 4 | 22.1 | 131.2 | 19.8 | 57.8 | 223.8 |
| Quantile regression reference limits | ||||||
| 20–24 | 4 | 10.5 | 42.5 | 4.1 | 34.2 | 111 |
| 25–29 | 4 | 11.8 | 48.5 | 4.9 | 36.8 | 122.1 |
| 30–34 | 4 | 13.3 | 55.3 | 5.8 | 39.7 | 134.3 |
| 35–39 | 4 | 15 | 63 | 7 | 42.8 | 147.6 |
| 40–44 | 4 | 16.8 | 71.8 | 8.4 | 46.1 | 162.4 |
| 45–49 | 4 | 18.9 | 81.9 | 10 | 49.7 | 178.5 |
| 50–54 | 4 | 21.3 | 93.3 | 12 | 53.6 | 196.3 |
| 55–59 | 4 | 24 | 106.4 | 14.4 | 57.7 | 215.9 |
For men, the lower (2.5th quantile) reference limit was equal to the assay lower limit of detection (4.0 pg/ml) across all age groups, regardless of the statistical approach used. The overall percentages of men and women with values at the detection limit were 14% and 1%, respectively. The median and upper reference limits for men increased with age for both genders. NT–pro-BNP values were substantially higher in women compared to men at every age.
Clinical correlates of NT–pro-BNP in the reference sample are listed in Table 3 . Age, gender, BMI, and blood pressure accounted for 33% of the variability in NT–pro-BNP concentrations. Most of this variation was attributable to gender, which accounted for 29% of the variability in NT–pro-BNP. Using modeled data, the percentage reduction in NT–pro-BNP concentrations per 10 kg change in body weight at different heights for men and women is shown in Figure 2 .
| Covariate Included in the Model ⁎ | Regression Coefficient | SE | Percentage Difference † | p Value |
|---|---|---|---|---|
| Whole sample | ||||
| Female gender | 0.908 | 0.036 | +148% | <0.0001 |
| Age (per 8.4 years) | 0.180 | 0.016 | +20 | <0.0001 |
| Body mass index (per 3.0 kg/m 2 ) | −0.077 | 0.018 | −7% | <0.0001 |
| Diastolic blood pressure (per 8 mm Hg) | −0.105 | 0.022 | −10% | <0.0001 |
| Systolic blood pressure (per 11 mm Hg) | 0.012 | 0.022 | +1% | 0.60 |
| Men | ||||
| Age (per 8.4 years) | 0.228 | 0.026 | +26% | <0.0001 |
| Body mass index (per 3.0 kg/m 2 ) | −0.075 | 0.030 | −7% | 0.01 |
| Diastolic blood pressure (per 8 mm Hg) | −0.105 | 0.034 | −10% | 0.002 |
| Systolic blood pressure (per 11 mm Hg) | −0.007 | 0.036 | −1% | 0.83 |
| Women | ||||
| Age (per 8.4 years) | 0.138 | 0.021 | +15% | <0.0001 |
| Body mass index (per 3.0 kg/m 2 ) | −0.083 | 0.022 | −8% | 0.0001 |
| Diastolic blood pressure (per 8 mm Hg) | −0.116 | 0.029 | −11% | <0.0001 |
| Systolic blood pressure (per 11 mm Hg) | 0.038 | 0.029 | +4% | 0.18 |
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