AF associated with different CV risk marker profiles in HFpEF and HFrEF
Comparing biomarker profiles of patients with heart failure: atrial fibrillation vs. sinus rhythm and reduced vs. preserved ejection fraction
Literature - Santema BT, Kloosterman M, Van Gelder IC et al. - Eur Heart J 2018; published online ahead of printIntroduction and methods
Heart failure with reduced ejection fraction (HFrEF) and heart failure with preserved ejection fraction (HFpEF) are known to have different pathophysiological backgrounds, and therefore, atrial fibrillation (AF) may have different effects on these two HF phenotypes [1-3]. Biomarkers may contribute to the understanding of these differences. Therefore, this post hoc analysis of the BIOlogy Study to TAilored Treatment in Chronic Heart Failure (BIOSTAT-CHF) [4,5] evaluated the biomarker profiles of patients with HFrEF and HFpEF, with and without AF.
BIOSTAT-CHF is an observational study that included patients with new-onset or worsening signs and/or symptoms of HF, documented either by left ventricular ejection fraction (LVEF) of ≤40%, or plasma concentrations of NTproBNP >2000 pg/mL, who were categorized into two groups based on transthoracic echocardiography: HFrEF (LVEF <40%) and HFpEF (LVEF ≥50%). Patients with unknown LVEF and those with LVEF of 40%-49% were excluded from this analysis. Biomarker profiles were created based on the Olink Cardiovascular III panel, which includes 92 CVD-related biomarkers. The primary outcome was time to all-cause mortality.
Main results
- Out of 2,676 HF patients, 2,152 patients had HFrEF, of whom 1,419 were in sinus rhythm (SR) and 733 had AF, while 524 patients had HFpEF, of whom 286 were in SR and 238 had AF. The median follow-up duration was 21 months (IQR: 11–32 months).
- In HFrEF patients, the relative CV risk marker levels (77 of 92 [84%]) were higher in those with AF compared with those in SR, which resulted in a homogeneous risk marker pattern.
- In HFpEF patients, the risk marker profile of patients with AF vs. SR was much more scattered, since 51 (55%) risk markers were higher in patients in SR and 36 (39%) in patients with AF.
- When the biomarker interactions between rhythm group and HF phenotype were tested using a univariable and a multivariable model, a significant interaction was observed for 44 biomarkers, of which 26 (59%) remained significant in the multivariable model.
- An overlap in top five biomarkers with the largest difference between AF and SR was observed, when comparing HFrEF (MMP2, NOTCH3, NTproBNP, SPON1 and ST2) and HFpEF (IGFBP1, NTproBNP, PDGFSUBUNITA, SPON1 and ST2).
- AF was associated with increased all-cause mortality risk in the total cohort (HR: 1.44; 95%CI: 1.25–1.66; P<0.001), as well as in the HFrEF group (HR: 1.41; 95%CI: 1.19–1.68; P<0.001), and in the HFpEF group (HR: 1.39; 95%CI: 1.05–1.83; P=0.022).
- After multivariable adjustment, the association of AF and all-cause death remained significant in the total cohort (HR: 1.27; 95%CI: 1.09–1.48; P= 0.002) and in the HFrEF group (HR: 1.28, 95%CI: 1.07-1.53, P=0.007), but not in the HFpEF group (HR: 1.10, 95%CI: 0.81-1.49, P=0.550). No significant interaction was observed between heart rhythm and the relationship of HF phenotype and outcome (P=0.71).
Conclusion
In this observational study AF was associated with a homogeneously elevated CV risk marker profile in HFrEF patients, whereas in HFpEF, the presence of AF was associated with a more scattered risk marker profile. These findings suggest that there might be differences in underlying pathophysiological mechanisms of AF in these two HF phenotypes.
Editorial comment
In their editorial article, Nishimura and Maisel [6] note that in the study of Santema et al., risk markers were not increased in patients with AF and HFpEF, a finding that is not in accordance with existing data, and emphasize that despite that, the mortality was higher in the total cohort of HF with AF, which leaves a question open in regard to the clinical implications of the various biomarker profiles. Moreover, they point at a weakness in the inclusion criteria, which allow the inclusion of only those HFpEF patients who had increased NT-proBNP levels, who probably represent the ‘sickest’ HFpEF patients. Next, the authors discuss the importance of clinical context in interpretation of biomarkers. Current national guidelines rely heavily on cardiac biomarkers for the diagnosis and management of conditions such as HF. However, while these biomarkers can be extremely valuable, various underlying conditions, such as the presence of HFpEF vs. HFrEF and AF vs. normal SR, can drastically change the expressed biomarkers as seen in this study. They conclude: ‘Elevation of biomarkers can be reflective of a number of competing mechanisms, and interpretation must be done with caution. The ability to use and interpret these biomarkers appropriately is integral to the care of cardiac patients.’
References
1. Borlaug BA, Paulus WJ. Heart failure with preserved ejection fraction: pathophysiology, diagnosis, and treatment. Eur Heart J 2011;32:670–679.
2. Ling L, Kistler PM, Kalman JM, Schilling RJ, Hunter RJ. Comorbidity of atrial fibrillation and heart failure. Nat Rev Cardiol 2016;13:131.
3. Paulus WJ, Tschope C. A novel paradigm for heart failure with preserved ejection fraction: comorbidities drive myocardial dysfunction and remodeling through coronary microvascular endothelial inflammation. J Am Coll Cardiol 2013;62:263–271.
4. Voors AA, Anker SD, Cleland JG, et al. A systems BIOlogy Study to Tailored Treatment in Chronic Heart Failure: rationale, design, and baseline characteristics of BIOSTAT-CHF. Eur J Heart Fail 2016;18:716–726.
5. Ouwerkerk W, Voors AA, Anker SD, et al. Determinants and clinical outcome of uptitration of ACE-inhibitor and beta-blocker in patients with heart failure: a prospective European study. Eur Heart J 2017;38:1883–1890.
6. Nishimura M and Maisel AS. Biomarkers: a window into the pathophysiology of atrial fibrillation in heart failure with reduced vs. preserved ejection fraction. European Heart Journal (2018) 39, 3876–3878.
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