Introduction:
Autonomic dysfunction underlies a variety of chronic diseases including heart failure (HF). Acceleration and deceleration capacity of heart rate represent activity of the cardiac sympathetic and parasympathetic nervous systems, respectively. The molecular pathomechanisms underlying aberrant acceleration capacity (AC) and deceleration capacity (DC) relevant for the progression and development of HF are yet unknown.
Methods:
Data from the MyoVasc study (N=3,289; NCT04064450), a prospective cohort study on chronic HF with highly standardized phenotyping and biobanking, were analyzed. Study participants underwent 24-hour Holter ECG recording upon visit to the study center, as well as venous blood sampling. Clinical outcome information was obtained from structured follow-up with subsequent validation through source data and independent assessment of clinical endpoints. RR intervals were extracted from Holter ECG recording to evaluate AC and DC via phase-rectified signal averaging. A total of 358 proteins was quantified in EDTA plasma using a targeted immuno-qPCR-based proteomics assay (Olink Proteomics, Uppsala, Sweden). Elastic net linear regression models were performed to identify proteins associated with AC and DC, adjusting for age, sex, cardiovascular risk factors (CVRF), comorbidities, and medication. Selected proteins were subsequently subjected to protein-protein interaction network (PPIN) analyses to aid interpretation of their involvement in pathways and functional groups, using the STRING database (https://string-db.org). Protein scores based on the selected proteins for AC and DC were generated for the total sample in an unsupervised manner using the first component of principal component analyses. To evaluate the relationship with clinical outcome of individuals with HF, the proteomic scores were analyzed in Cox regression models to predict worsening of HF and all-cause mortality.
Results:
Holter ECG recordings and protein biomarkers were both available for analysis in 974 study participants (mean age 64.5±10.5 years; female sex: 35.4%). A total of 43 proteins (10-fold cross-validated R2 = 0.18) and 24 proteins (10-fold cross-validated R2 = 0.19) were selected for AC and DC, respectively. PPIN analyses revealed that the selected proteins are involved in cardiovascular disease development and progression via inflammatory and metabolic pathways, myocardial remodeling, and coagulation and complement system. In multivariable Cox regression analyses performed in the total sample of the cohort (N=3,289), the protein scores of the selected proteins for AC (hazard ratio per SD (HRSD) 1.50, [95% confidence interval (CI) 1.34, 1.67], p<0.0001), and DC (HRSD 1.49 [95%CI 1.33, 1.66], p<0.0001) were strong predictors of worsening of HF, independent of age, sex, CVRF, comorbidities and medication. In addition, both protein scores were also predictive of all-cause death independent of age, sex, CVRF, comorbidities and medication: AC-related protein score: HRSD 1.65 [95%CI 1.45, 1.87], p<0.0001; DC-related protein score: HRSD 1.78 [95%CI 1.58, 2.02], p<0.0001.
Conclusions:
This study identified molecular mechanisms associated with AC and DC in the context of HF using a targeted proteomics approach. These data provide novel pathomechanistic insights for the role of autonomous dysfunction in patients with HF. The clinical relevance is further substantiated by the strong relationship of the identified proteins with clinical outcome.