Serially Measured Cytokines and Cytokine Receptors in Relation to Clinical Outcome in Patients With Stable Heart Failure

Between October 2011 and June 2013, a total of 263 patients were prospectively enrolled at 2 tertiary medical centres in the Biomarker Measurements and New Echocardiographic Techniques in Chronic Heart Failure Patients Result in Tailored Prediction of Prognosis (Bio-SHiFT) study. Stable HF patients were recruited during their regular outpatient clinic visit, as described previously.^, In the current investigation, only the 250 patients with HF with a reduced ejection fraction were evaluated. Ambulatory patients were recruited during their regular outpatient clinic visit, and these patients were stable as defined by the fact that they had not been hospitalized for HF in the past 3 months. The study was approved by the responsible medical ethics committees and conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all patients. The trial is registered in ClinicalTrials.gov (NCT01851538; https://clinicaltrials.gov/ct2/show/NCT01851538).

An extended version of the Methods section with additional information is given in the Supplementary Material. We performed blood sampling and medical evaluation at baseline and this was repeated at each study follow-up visit. These visits were predefined and scheduled every 3 months (±1 month) with a maximum of 10 study follow-up visits. For the current investigation, follow-up lasted until November 2015. The primary end point (PE) was a composite of cardiac death, heart transplantation, left ventricular assist device implantation, and hospitalization for management of acute or worsened HF, whichever occurred first. We collected 1984 ethylenediaminetetraacetic acid (EDTA) plasma samples before occurrence of the PE or censoring (9 [25th-75th percentile, 5-10] blood samples per patient) during this first inclusion round of the Bio-SHiFT study. For reasons of efficiency, for the current investigation, we selected all samples drawn at baseline, the last sample available in patients in whom the PE did not occur during follow-up, and the 2 samples available before the PE (which, by design, were 3 months apart; Supplemental Fig. S1). This selection was on the basis of previous investigations in this cohort, which showed that levels of several biomarkers change in months before the incident adverse event, whereas event-free patients show stable biomarker levels. Altogether, this resulted in 530 samples.

A total of 17 cytokines and cytokine receptors were measured using the Cardiovascular panel III of Olink Proteomics AB, Uppsala, Sweden, in a batch-wise analysis of the samples. Biomarkers were delivered in normalized protein expression (NPX) units, which are relative units expressed on a log2 scale in which 1 unit higher NPX thus represents a doubling of the measured protein concentrations.

We used linear mixed effect models to plot the average temporal pattern of the biomarkers for patients with and without a PE during follow-up, and freedom from composite end point was assessed using Kaplan–Meier analysis. To estimate the associations between patient-specific repeated biomarker measurements and the PE, we applied joint modelling (JM) analyses. JM combines linear mixed effect models for temporal evolution of the repeated measurements with relative risk models for the time-to-event data. We studied the repeatedly measured biomarker levels (including baseline and follow-up), as well as their rates of change (ie, the slopes, which corresponds to the first derivative of the longitudinal biomarker trajectories). First, all JM analyses were performed univariably. Subsequently, we performed multivariable analyses to adjust for potential confounders. We applied a “clinical model,” which was adjusted for age, sex, diabetes mellitus, atrial fibrillation, New York Heart Association class, use of diuretics, and systolic blood pressure, and a “cardiac biomarker model,” which was adjusted for baseline NT-proBNP, high-sensitivity troponin T, and CRP. Adjustments were made in the relative risk and linear mixed effect model parts. For all JM analyses, we used the Z-score (ie, the standardized form) of the NPX values to allow for direct comparisons of different biomarkers. Results are given as hazard ratios (HRs) and 95% confidence intervals (CIs) per 1 SD difference of the repeatedly measured biomarker level and per 0.1 SD per year difference of the slope at any point in time during follow-up.

We used the conventional P < 0.05 threshold to conclude significance for the relation between patient characteristics and the occurrence of the PE during follow-up (Table 1). For the other analyses, we corrected for multiple testing using the Bonferroni correction (n = 17), which resulted in a significance level of P < 0.0029.

Temporal patterns of several cytokines and cytokine receptors were associated with adverse events in 250 stable patients with HF, even after adjustment for clinical factors. Proinflammatory cytokines are known for their important roles in the disease process of HF. In a recent meta-analysis, concentrations of tumour necrosis factor-α, IL-6, IL-1β, and CRP were significantly higher in chronic HF patients than in control participants, and serum IL-6 predicted mortality. Recently, a study suggested that IL-32 is a novel predictor of adverse cardiac events in HF patients after myocardial infarction. Nevertheless, clinical trials targeting different immune components have not resulted in improved clinical outcomes; some interventions even resulted in worsening of HF. Previous studies in chronic HF patients have mostly described the value of single measurements of inflammatory markers (eg, at admission) for prognosis. To the best of our knowledge, the temporal patterns of cytokine-related biomarkers in patients with stable HF and their associations with clinical outcome have not yet been investigated in detail. Repeated measurements could provide more information on changes in marker levels over time and the association between these changes and adverse clinical events. Apart from the potential value for personalized risk assessment, when investigated in more detail, these temporal patterns might contribute to elucidation of aspects of immune activation that contribute to the progression of HF.

Some limitations of our study warrant consideration. Because of efficiency reasons, as described previously, we used a subset of all available plasma samples. However, our previous investigations using all samples showed that most of the examined biomarkers’ levels change before the incident adverse event. Thus, we believe that with our approach we retain the most informative measurements while enhancing efficiency. Furthermore, the current investigation focused on HF with reduced ejection fraction patients only.

In conclusion, we showed that temporal patterns of several cytokines and cytokine receptors are independently associated with clinical adverse events in patients with stable HF. These results suggest that repeated measurements of these biomarkers, in addition to traditional cardiac biomarkers, might contribute to personalized risk assessment and better identify high-risk patients. Additionally, these findings might open new avenues for druggable targets. Further studies that measure absolute biomarker concentrations repeatedly in larger cohorts are needed to confirm and extend these findings.

This work was supported by the Jaap Schouten Foundation and the Noordwest Academie.

The authors have no conflicts of interest to disclose.