Background In patients with heart failure (HF), imbalance between the activity of the sympathetic and parasympathetic nervous systems is well recognized. The Poincaré plot index (SD1/SD2), a marker of heart rate variability, reflects the balance of the cardiac autonomic nervous system. However, the molecular pathomechanisms underlying aberrant levels of SD1/SD2 relevant for the development and progression of HF are not well understood.

Methods Data from the MyoVasc study, (N=3,289; NCT04064450) a prospective cohort study on HF with highly standardized biannual deep (sub)clinical phenotyping and biobanking, were analyzed. Participants received 24-hour Holter ECG recordings and venous blood was drawn at baseline and at each follow-up visit. Clinical outcome information was obtained through structured follow-up visits with subsequent validation and independent adjudication of endpoints. RR intervals were extracted from Holter ECG to evaluate the Poincaré plot index. A total of 358 proteins were quantified in EDTA plasma using a targeted immuno-qPCR-based proteomics assay (Olink Proteomics, Uppsala, Sweden) at two timepoints (i.e. baseline and 2-year follow-up). Elastic net linear regression models were used to identify proteins associated with Poincaré plot index at baseline (cross-sectional score), and to identify proteins related to a change in Poincaré plot index over time, i.e., after 2 years of follow-up (longitudinal score), independently of age, sex, cardiovascular risk factors (CVRF), comorbidities and medication. Protein scores based on the selected proteins for both cross-sectional and longitudinal analysis of the Poincaré plot index were generated in an unsupervised manner using the first component of principal component analyses. To evaluate the relationship with clinical HF outcome, both protein scores were analysed in Cox regression models. Pathway and enrichment analyses were subsequently performed using Metascape.

Results Holter ECG recordings and protein biomarkers were available for analysis in 974 study participants (mean age 64.5±10.5 years; female sex: 35.4%). A total of 45 proteins (10-fold cross-validated [CV] R² = 0.18) and 30 proteins (Leave-One-Out CV R² = 0.32; [n=228, intra-individual subsample]) were selected for the Poincaré plot index at baseline and for its change over time, respectively. In multivariable Cox regression analyses performed in the total sample of the cohort, both the cross-sectional (hazard ratio per standard deviation (HR_SD) 1.50, [95% confidence interval (CI) 1.33, 1.70], p<0.0001) and the longitudinal (HR_SD 1.66 [95%CI 1.49, 1.84], p<0.0001) protein scores for SD1/SD2 were strong predictors of worsening of HF during a follow-up time of 6 years, independent of age, sex, CVRF, comorbidities and medication. Enrichment analyses revealed that the protein signatures are involved in cardiovascular disease development and progression via inflammatory pathways, interleukin signalling, lipid metabolism, and extracellular matrix remodeling of the vasculature.
Conclusions Using a targeted proteomics approach, this study identified molecular mechanisms associated with measures of autonomic dysfunction in individuals with HF. New pathomechanistic insights for the role of autonomic dysfunction in HF were revealed and further support the relevance of autonomic dysfunction for the development and progression of HF.