Background
Knowledge about atrial fibrillation (AF) has been steadily increasing over the last two decades together with the awareness that this arrhythmia is an important health problem [
1]. Clinical and bio-humoral markers associated with AF increase our understanding of its mechanisms and may help in predicting the risk of recurrence of AF [
2,
3]. Previous data from GISSI-AF trial and also from other authors showed that circulating biomarkers are associated to AF but are not strong predictors for AF recurrence in patients in sinus rhythm with a recent history of paroxysmal or persistent AF [
4‐
6].
N-terminal pro-B type natriuretic peptide (NT-proBNP) has been regularly reported to be a strong—possibly the strongest—predictor of recurrent AF among several novel circulating biomarkers, as recently pointed out in the Framingham Heart Study [
7]; however, its predictive power is still modest.
NT-proBNP and BNP are produced in equimolar amounts in cardiomyocytes in response to increased wall stretch, volume overload and ischemia (6–8); BNP but not NT-proBNP has physiological activity. There are nine known O-glycosylation sites on proBNP and NT-proBNP. On average, 7.4% of circulating NT-proBNP in HF patients is glycosylated in the central region of the molecule [
11]. Commercial NT-proBNP ELISA contains antibodies directed to epitopes in the central region of NT-proBNP and detects non-glycosylated forms. Thus the assay underestimates the circulating concentrations of NT-proBNP when these sites are glycosylated [
12,
13], and this may have different impacts on NT-proBNP’s performance as a biomarker in different pathologies [
11].
The subgroup of patients in the bio-humoral substudy of GISSI-AF [
14,
15] was deemed adequate to test independently two features of an exploratory panel of nine circulating biomarkers, deglycosylated total NT-proBNP and NT-proBNP in AF: (1) the association of a biomarker with AF, when a blood sample is taken at the 6- or 12-month visit while AF is present in the electrocardiogram (ECG), and (2) the predictive power of the same biomarker at baseline, when the patient is in sinus rhythm, for recurrence of AF or incident hospitalization for CV reasons. We focused on total NT-proBNP to assess whether glycosylation influences its prognostic accuracy.
Methods
The GISSI-AF trial
(Clinical Trials.gov identifier: NCT00376272; EudraCT Number: 2004-003036-53) was a double-blind randomized placebo-controlled multicenter trial in 114 cardiology divisions between November 2004–January 2007 that enrolled, 1442 patients in sinus rhythm with a history of AF (two or more episodes of symptomatic ECG-documented AF in the previous 6 months) or successful cardioversion, electrical or pharmacologic, between 14 days and 48 h before randomization). A routine clinical examination, including ECG and laboratory testing, was done at each study visit (baseline, weeks 2, 4, 8, 24 and 52). To increase the likelihood of detecting AF, all patients were given a trans-telephonic monitoring device (see Additional file
1: Appendix 1). Each AF episode during the trial was adjudicated blindly by a central reader and verified by an ad-hoc validation committee. The rationale, design, and results of the trial have already been published [
14,
15]
. Patients from 36 centers participated in a sub-study with serial bio-humoral tests at baseline, 6 and 12 months.
Ongoing AF is defined as the presence of AF rhythm in a 12- lead electrocardiogram recorded during the scheduled 6 or 12- month follow-up visit, during which a blood sample was drawn to assess circulating biomarkers. AF recurrence is defined as an episode of AF detected by telemonitoring or during the scheduled follow-up visits. In the first this case the patient was asked to come for an office visit to confirm the arrhythmia by a 12-lead ECG (see also Additional file
1: Appendix 1 Detection of recurrent AF during follow-up).
Assays of circulating biomarkers and detection of AF recurrence
The following biomarkers were included in the analyses: total N-terminal pro-B type natriuretic peptide (total NT proBNP), N-terminal pro-B type natriuretic peptide (NT-proBNP), angiopoietin 2 (Ang2), bone morphogenic protein-10 (BMP10), Dickkopf-related protein-3 (DKK3), endothelial cell specific molecule-1 (ESM1), fatty acid-binding protein 3 (FABP3), fibroblast growth factor 23 (FGF23), growth differentiation factor-15 (GDF15), insulin-like growth factor-binding protein-7 (IGFBP7), and myosin binding protein C3 (MYPBC3). The characteristics of the biomarkers (e.g. an exploratory analysis of nine circulating biomarkers, total NT-proBNP and NT-proBNP), are described in Additional file
1: Appendix 2 Assays of circulating biomarkers and detection of recurrent AF during follow-up, and detectability in Table
1.Table 1
Biomarker concentrations at each study visit and lower limit of quantification and detection
Total NT proBNP * pg/mL | BL | 376 | 1727 | 1712 | 1230 | 667 | 2011 | 75 | 12,700 | 8.3 pg/mL | 6.52 pg/mL |
6 M | 321 | 1494 | 1611 | 985 | 507 | 1959 | 34 | 12,626 |
12 M | 323 | 1672 | 1825 | 1008 | 564 | 2112 | 62 | 11,992 |
NT-proBNP (pg/mL) | BL | 382 | 344.6 | 496.3 | 191.0 | 95.0 | 367.0 | 5.0 | 4347 | 50 pg/mL# | 10 pg/mL## |
6 M | 325 | 278.6 | 414.5 | 136.0 | 66.0 | 324.0 | 5.0 | 3906 |
12 M | 331 | 328.0 | 555.9 | 149.0 | 63.0 | 350.0 | 5.0 | 6345 |
Ang2 * ng/mL | BL | 379 | 3.44 | 1.95 | 2.91 | 2.21 | 3.99 | 0.73 | 15.04 | 0.058 ng/mL | 0.028 ng/mL |
6 M | 324 | 2.85 | 1.34 | 2.49 | 2.01 | 3.19 | 1.01 | 10.14 |
12 M | 329 | 2.88 | 1.31 | 2.56 | 2.02 | 3.28 | 1.16 | 10.09 |
BMP10 * ng/mL | BL | 375 | 2.09 | 0.52 | 2.02 | 1.75 | 2.33 | 1.14 | 5.04 | 0.009 ng/mL | 0.003 ng/mL |
6 M | 321 | 2.05 | 0.47 | 2.01 | 1.75 | 2.28 | 1.16 | 4.76 |
12 M | 327 | 2.09 | 0.50 | 2.00 | 1.74 | 2.34 | 1.15 | 4.54 |
DKK3 * ng/mL | BL | 377 | 59.87 | 15.37 | 57.5 | 49.3 | 68.7 | 27.1 | 142.6 | 0.025 ng/mL | 0.003 ng/mL |
6 M | 321 | 57.83 | 14.42 | 55.8 | 48.2 | 64.0 | 28.7 | 118.7 |
12 M | 324 | 59.51 | 16.47 | 57.5 | 48.6 | 66.2 | 26.8 | 136.9 |
ESM1 * ng/mL | BL | 377 | 2.23 | 1.01 | 2.02 | 1.65 | 2.55 | 0.87 | 9.17 | < 0.003 ng/mL | 0.001 ng/mL |
6 M | 321 | 2.04 | 0.65 | 1.94 | 1.62 | 2.33 | 0.97 | 5.65 |
12 M | 324 | 2.13 | 0.70 | 1.99 | 1.64 | 2.47 | 0.85 | 5.68 |
FABP3 * ng/mL | BL | 375 | 30.98 | 10.96 | 29.2 | 24.2 | 35.3 | 12.1 | 105.3 | 1.0 ng/mL | n.a |
6 M | 321 | 33.17 | 11.17 | 31.2 | 25.7 | 38.8 | 11.6 | 86.7 |
12 M | 327 | 34.80 | 12.13 | 33.1 | 26.2 | 40.1 | 15.0 | 91.4 |
FGF23 * pg/mL | BL | 374 | 0.14 | 0.10 | 0.11 | 0.09 | 0.15 | 0.01 | 0.87 | 0.004 ng/mL | n.a |
6 M | 321 | 0.14 | 0.09 | 0.11 | 0.09 | 0.15 | 0.01 | 0.92 |
12 M | 322 | 0.14 | 0.10 | 0.12 | 0.09 | 0.15 | 0.03 | 0.94 |
GDF15 pg/mL | BL | 375 | 1272 | 793 | 1053 | 745 | 1523 | 235 | 7059 | ≤ 400 pg/mL | ≤ 400 pg/mL |
6 M | 321 | 1344 | 1136 | 1080 | 794 | 1518 | 317 | 12,471 |
12 M | 327 | 1355 | 965 | 1140 | 808 | 1555 | 369 | 9783 |
IGFBP7 * ng/mL | BL | 379 | 178 | 44 | 172 | 152 | 194 | 97 | 685 | 0.4 ng/mL | 0.01 ng/mL |
6 M | 324 | 179 | 48 | 170 | 154 | 191 | 80 | 705 |
12 M | 329 | 184 | 49 | 174 | 157 | 199 | 91 | 701 |
MYBPC3 * ng/mL | BL | 373 | 5.63 | 6.33 | 3.69 | 2.29 | 6.35 | 0.34 | 48.48 | 2.1 pg/mL | 0.458 pg/mL |
6 M | 321 | 4.86 | 6.31 | 3.18 | 1.98 | 5.42 | 0.29 | 66.73 |
12 M | 327 | 4.98 | 5.91 | 3.10 | 1.91 | 5.95 | 0 | 47.05 |
Per protocol, for handling and processing the samples were left in the local lab for up to 1 h before freezing at − 70 °C. Samples stored locally were transferred to the core lab every year.
Biomarkers were assayed under blind conditions in a laboratory at Roche Diagnostics, Penzberg, Germany. Total NT-proBNP (Roche Diagnostics GmbH, Mannheim) was measured on a Cobas Elecsys Immunoanalyzer with a prototype sandwich immunoassay for use in exploratory research. This detects any NT-proBNP that is not O-glycosylated (position S44). The lower limit of detection is 6.5 pg/mL; within-run and between-run precisions are ≤ 1.2% and ≤ 2.5%.
Statistical methods
Primary objective of this study is to evaluate whether deglycosylated total NT-proBNP, NT-proBNP and other nine circulating biomarkers are associated to AF, both ongoing or recurrent; the secondary endpoint is the relationship with first hospitalization for cardiovascular reasons. Continuous variables are expressed as mean ± SD if normally distributed or median and interquartile range [IQR] if not normally distributed; categorical variables were reported as absolute numbers and percentages. Differences between groups of patients with and without ongoing or recurrent AF were assessed with one-way ANOVA, Kruskal–Wallis test or χ2 test, as appropriate. The correlations between circulating biomarkers were analyzed with Spearman's rank correlation coefficient.
The association of each biomarker with ongoing AF at the follow-up visit was assessed on the basis of the area under the curve (AUC) of ROC analysis, followed by logistic regression analysis adjusted for variables significantly associated with AF in univariate analysis: heart failure, LVEF < 40% or both, history of hypertension, AF episode with LA dilatation, and oral anticoagulant use. Biomarkers which had an AUC < 70% and were not independently associated with ongoing atrial fibrillation were then excluded from further analyses except BMP10. This biomarker was carried included in the analyses after an authoritative study on its mechanistic involvement in the pathophysiology of AF and its specific production by atrial tissue [
16]
Kaplan–Meier curves and log-rank tests were used to assess differences in the AF recurrence-free survival according to biomarker baseline values above or below the median. Biomarkers were modelled as continuous variables (expressed as 1 SD increment) as linearity was tested by restricted cubic splines. Cox proportional univariable and adjusted hazard models were constructed to assess the prediction of AF recurrence. Cardiovascular hospitalization was predicted similarly. Cox analyses were adjusted for covariates selected on the basis of univariate analysis; for AF recurrence, sex and two or more episodes of AF in the six months before inclusion in GISSI-AF. For cardiovascular hospitalization, systolic blood pressure, history of hypertension, peripheral artery disease and smoking. The c-index derived from the multivariable models was used to assess the improvement in the prognostic model including either Total NT-proBNP or NT-proBNP in the adjusted model. Comparisons between the areas under the ROC curves were performed with the use of U-statistics [
17]. All probability values are two-tailed and p-values were corrected for multiple testing by means of the False Discovery Rate (FDR-correction). A p < 0.05 was considered significant. Data were analyzed using SPSS Version 25 (IBM SPSS, Armonk, NY) and SAS Version 9.4.
Discussion
This study in patients in sinus rhythm but at risk of AF shows for the first time that the relationship of ongoing AF and the risk of first AF recurrence and first hospitalization for CV reasons with the novel biomarker total NT-proBNP is as strong as that of NT-proBNP. From the panel of biomarkers studied, also BMP10, a marker of cardiomyocyte growth in the myocardium of the right atrium and ventricle, and Ang2, involved in inflammation and coagulation, were associated with AF.
While the association of a biomarker with AF may give useful mechanistic insights on the disease, a biomarker that can tell the doctor in advance what is the risk of a patient having new episodes of AF, is clinically important. That is why we assessed, for the first time, the association and the predictive power for AF of the plasma concentrations of total NT-proBNP in a cohort of patients with a history of AF, in sinus rhythm, at high risk of AF recurrence.
We hypothesized that the accuracy and prognostic value of NT-proBNP would improve using a biomarker to identify the glycosylated NT-proBNP. This task by itself is challenging, given the repeatedly reported superiority of NT-proBNP [
7]. In fact, we did see that both total NT-proBNP and NT-proBNP gave significant and similar results for predicting AF. The median total NT-proBNP plasma concentration was 6.6, 7.2 and 6.8 times higher than NT-proBNP at baseline and at six- and 12-months follow-up (Table
1 and
2). The wide inter-individual variability in the ratio (e.g. 0.57 to 42.05) justifies the search for associations of total NT-proBNP and AF or clinical events. This indicated that in patients in sinus rhythm with a recent history of AF, NT-proBNP is extensively glycosylated and the extent of glycosylation does not change over time. In patients with acute dyspnea, and using deglycosylation enzymes to identify total NT-proBNP, Røsjø et al. [
18] reported nearly double the levels of total NT-proBNP than NT-proBNP in HF and non-HF patients. At a median of 816 days, both natriuretic peptides were associated with all-cause mortality risk in HF patients; for the deglycosylated total NT-proBNP concentration the HR [95%CI] was 1.42 [1.24–1.63], p < 0.001, and for NT-proBNP 1.29 [1.13–1.46], p < 0.001. In the present study only 42 patients had clinically diagnosed HF or LVEF < 40% (11%); this small number does not permit analysis of AF stratified by HF, although the incidence of AF recurrence was no different in patients with HF (12.3%) and those without (9.5%, p = 0.38). Nonetheless, circulating biomarkers were significantly higher in patients with HF, independently of AF. The only exception was BMP10, apparently independent of HF (Additional file
1: Table 6 Concentrations of circulating biomarkers in patients with and without clinical HF or LVEF<40% ).
Ang2 showed a strong association with AF, confirming the pathogenic role of inflammatory activation in AF [
19]; however, Ang2 had no predictive power for recurrent AF. In the GISSI-AF sub-study, similar results were reported for two other inflammatory markers, IL6 and hsCRP [
6]. Like for Ang2 these two biomarkers were not independent predictors of AF recurrence.
In relation to AF, another marker closely involved in inflammations—GDF15—performed poorly in the present study. However, the ARISTOTLE large-scale trial reported GDF15 as a risk factor for major bleeding, mortality, and stroke in patients with permanent AF [
20].
Very recently, in 359 patients after catheter ablation, BMP10 was an independent predictor of AF recurrence while NT-proBNP was not [
16]. However, those patients were more severely ill than those in the present study (47% had HF and 12% a history of stroke; NT-proBNP approximately double), and absolute concentrations of BMP10 were only slightly higher.
Recently natriuretic peptides, particularly NT-proBNP, have been reported to be associated with inflammation [
21]. This suggests a common pathophysiological mechanism for the biomarkers assessed in this study that were associated with AF.
Strengths and limitations of the study
The main strengths of this study are: (a) it was a multicenter randomized clinical trial with concomitant serial echocardiography and circulating biomarkers analyzed centrally; and (b) trans-telephonic electrocardiographic monitoring enabled us to record and identify AF recurrence efficiently during the 12-month follow-up. Another strength is the simultaneous analysis of total NT-proBNP with other biomarkers involved in different pathophysiological mechanisms, some of them assessed for the first time for AF diagnosis or as predictors of AF recurrence (Ang2, BMP10). The potential added value of total NT-proBNP to the benchmark biomarker NT-proBNP was assessed from different dimensions of performance, as recently proposed for the evaluation of new biomarkers [
20].
Our results cannot apply to all patients with AF since at baseline the GISSI-AF patients were in sinus rhythm and had a lower rate of co-morbidities than patients with AF in real life or in other cohorts with a higher frequency of persistent or permanent AF [
1,
2,
18]. This was due to compliance with the strict eligibility criteria of the trial. The mean CHADS2 modified score was indeed very low, averaging 1.41 ± 0.84 in the whole population, compatible with the low morbidity rate of the patients selected [
22]. The low frequency of deaths after 12 months (only one) and thromboembolic events (three) in the GISSI-AF sub-study could not be considered for the outcome analysis. The small number of patients with ongoing AF at a follow-up visit is a limitation for the association of the biomarkers with the diagnosis of AF.
Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit
http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (
http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.